Color, Proximate Composition, Bioactive Compounds and Antinutrient Profiling of Rose

Color, Proximate Composition, Bioactive Compounds and Antinutrient Profiling of Rose | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Color, Proximate Composition, Bioactive Compounds and Antinutrient Profiling of Rose Sharmila Rani Mallick, Jahidul Hassan, Md. Azizul Hoque, Hasina Sultana, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3873110/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted 5 You are reading this latest preprint version Abstract Rose ( Rosa sp. ) is one of the most important ornamentals which is commercialize for its aesthetic values, essential oils, cosmetic, perfume, pharmaceuticals and food industries in the world. It has wide range of variations that is mostly distinguished by petal color differences which is interlinked with the phytochemicals, secondary metabolites and antinutrient properties. Here, we explored the color, bioactive compounds and antinutritional profiling and their association to sort out the most promising rose genotypes. For this purpose, we employed both quantitative and qualitative evaluation by colorimetric, spectrophotometric and visual analyses following standard protocols. The experiment was laid out in randomized complete block design (RCBD) with three replications where ten rose accessions labelled R1, R2, R3, R4, R5, R6, R7, R8, R9 and R10 were used as plant materials. Results revealed in quantitative assessment, the maximum L*, a* and b* value was recorded from rose accessions R4, R6 and R10, respectively which is further confirmed with the visually observed color of the respective rose petals. Proximate composition analyses showed that the highest amount of carotenoid and β-carotene was found in R10 rose accession, anthocyanin and betacyanin in R7. Among the bioactive compounds, maximum tocopherol, phenolic and flavonoid content was recorded in R8, R6 and R3 while R1 showed the highest free radical scavenging potentiality with the lowest IC 50 (82.60 µg/ mL FW) compared to the others. Meanwhile, the enormous variation was observed among the studied rose genotypes regarding the antinutrient contents of tannin, alkaloid, saponin and phytate whereas some other antinutrient like steroids, coumarines, quinones, anthraquinone and phlobatanin were also figured out with their presence or absence following qualitative visualization strategies. Furthermore, according to the Principal Component Analysis (PCA), correlation matrix and heatmap dendogram and cluster analysis, the ten rose accessions were grouped into three clusters where, cluster-I composed of R3, R4, R5, R8, cluster-II: R9, R10 and cluster-III: R1, R2, R6, R7 where the rose accessions under cluster III and cluster II were mostly contributed in the total variations by the studied variables. Therefore, the rose accessions R9, R10 and R1, R2, R6, R7 might be potential valuable resources of bioactive compounds for utilization in cosmetics, food coloration, and drugs synthesis which have considerable health impact. Biological sciences/Plant sciences Biological sciences/Ecology/Biodiversity antioxidants antinutrient bioactive compounds color molar ratio rose petal secondary metabolites variability Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Rose is a highly significant decorative plant in the commercial floriculture business, with great economic, cultural, and symbolic value. Rose flowers are vital in the floriculture sector of Bangladesh, serving as cut flowers for various festivals and religious events, as well as being used for potted plants and garden plants. Rose blossoms possess not only aesthetic qualities but also serve as a fundamental component in the production of industrial goods. Rose water, rose oil, rose concrete, dried petals, dried buds, and rose absolute are the primary derivatives of roses. These products find applications in various industries such as cosmetics, perfume manufacturing, food production, and pharmaceuticals for drug development on a global scale [ 1 ]. The rose flower is rich in antioxidant substances such as polyphenols, flavonoids, and phenolic acid, which have the capacity to capture free radicals [ 2 ]. In Bangladesh, there is a variety of rose called Rosa kordesii . The petals of this rose contain high levels of antioxidants such as terpenoids, flavonoids, saponins, tannins, and phenolic compounds, which are effective in scavenging free radicals [ 3 ]. Furthermore, rose petals possess antibacterial properties that prevent bacterial infection in the bladder. Additionally, rose petal tea, which is devoid of caffeine, can alleviate moderate sore throat due to its high antioxidant content [ 4 ]. The rose blossom can serve as an excellent resource for preparing functional food that promotes blood circulation, making it beneficial for individuals with high blood pressure. Moreover, rose petals are rich in vitamins, and when taken in an edible form, particularly vitamin C, they enhance the production of red blood cells [ 5 ]. Plants create and store a significant quantity of natural bio-active chemicals and secondary metabolites, such as anthocyanins, flavonoids, phenolic acids, and carotenoids, possess significant economic and commercial value. They contribute to the smells in flowers, provide color, and serve as key components in pharmaceutical products [ 6 ]. Among the secondary metabolites, antioxidants have diverse and important impacts on health-related matters. During normal oxygen metabolism in the human body, reactive oxygen species (ROS) such as superoxide (O 2− ) and nitric oxide (NO) are naturally created as byproducts, along with highly reactive free radicals. Imbalance between the production and scavenging of reactive oxygen species (ROS) and free radicals can result in the presence of redox-active transition metal ions, such as iron (II) or copper. This imbalance leads to significant oxidative stress, causing the oxidation of cellular biomolecules such as DNA, lipids, and proteins. This process is associated with the development of chronic diseases including hyperlipidemia, hypertension, and cancer [ 1 ]. In addition, the rose flower includes antioxidant components such as polyphenols, flavonoids, and phenolic acid, which are capable of capturing free radicals [ 7 ]. The antioxidant activities of rose hips [ 8 , 9 ] and rose petals [ 10 , 11 ] are known to be linked to their chemical makeup and phenolic compounds. The focus lies on utilizing bioactive compounds derived from nature to eliminate these free radicals. Within this particular context, the rose flower possesses the potential to serve as a valuable biological resource for enhancing nutritional attributes, in addition to its elevated levels of antioxidants. The genus Rosa has a wide range of decorative plants, consisting of about 200 species and around 18,000 distinct cultivars of roses. These roses can be found in Asia, Europe, the Middle East, and North America [ 12, 13]. The history of rose evolution reveals key characteristics of rose variation resulting from interspecific hybridization and polyploidization. The rose, belonging to the genus Rosa , is a highly significant flower known for its exceptional fragrance, captivating colors, and rich nutritional characteristics. Roses exhibit a diverse range of biochemical activities due to their high levels of phenolic compounds, phenolic acid, flavonoids, carotenoids, and anthocyanins. These substances are the outcomes of several physiological processes in roses [ 14 ]. The wide variety of bioactive chemicals found in roses makes every component of the plant an essential ingredient in the creation of medications. The presence of these secondary metabolites in roses contributes to their therapeutic effects in treating various illnesses. Rose possesses antibacterial, antispasmodic, anti-inflammatory, astringent, analgesic, antidepressant, and diuretic effects [ 1 ]. Moreover, these biochemical qualities render roses valuable as raw materials for several sectors, cosmetics formulation, perfume production, and food coloring agents. In Bangladesh, around 10,000–12,000 hectares of land are dedicated to flower cultivation, with roses being the dominant variety. This plays a crucial part in the economic growth of the flourishing floriculture industry in Bangladesh [ 15 ]. However, there is a lack of official statistics regarding the production of rose flowers in our country. These bioactive chemicals, which are abundant in rose flowers, are exclusively utilized as fresh flowers for events and are not employed in industrial processing. Conversely, Bangladesh imports a variety of processed rose products annually. Golden Rose is a highly sought-after brand in our country that offers a range of processed rose products, including cosmetics and perfumes. Consumers of these processed products utilize them without being aware of their chemical composition. Scientists worldwide have conducted research on the chemical composition of diverse species within the genus Rosa . There is evidence that the bioactive secondary metabolites differ among different species of the Rosa genus. Rosa kordesii is a rose cultivar that is found in Bangladesh. The petals of this rose contain high levels of antioxidants such as terpenoids, flavonoids, saponins, tannins, and phenolic compounds, which are effective in scavenging free radicals [ 3 ]. There is a limited amount of information on the heterogeneity of secondary metabolites in roses in Bangladesh due to the large number of rose cultivars present. This provides a significant opportunity to categorize the rose genotypes according to the diversity of secondary metabolites. Thus, it has been postulated that the rose genotypes may exhibit diversity in their response to the color, secondary metabolites, nutritional and antinutritional profiling. The purpose of this study was to sort out the variations in color, antinutrients, and secondary metabolites among several rose accessions. Additionally, to find the most promising rose accession that is rich in important secondary metabolites to use as a resource for commercial products and as a substitute for artificial food coloring. Materials and Methods Chemicals The chemical and reagents used in this study such as hydrochloric acid (37%), sulphuric acid (95–98%), sodium tungstate, manganese sulphate, sodium carbonate (99.5%), calcium nitrate (≥ 95%), potaddium iodide, folin-ciocalteu reagent, gallic acid (98.0%) acetone (99.0%), hexane, quercetin hydrate (≥ 95%), ammonium hydroxide, diethyl ether (99.5%), ethanol, methanol, ferric chloride (97%), ferric sulphate (399.88 anhydrous basis), phosphomolybdic acid (47.5%), aluminium chloride, chloroform (99.5%), 2,2-bipyridyl (99.5%), ammonium thiocyanate, tannic acid, dl-α-tocopherol acetate, potassium permanganate, DPPH (2,2-diphenyl-1-picrylhydrazyl), ascorbic acid, sodium acetate, acetic acid, n-butanol, sodium hydroxide of trace grade were purchased from Sigma Aldrich (St Louis, USA) and used to prepare working solutions as well as for laboratory analysis. Experimental Design The experiment was conducted at the Laboratory of Horticulture, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Bangladesh using ten (10) rose accessions viz. R1, R2, R3, R4, R5, R6, R7, R8, R9 and R10 as plant materials (Supplementary Figure. 1). The flowers at full-bloom stage were collected from the rose garden of BSMRAU at early morning and brought to the laboratory as soon as possible. After that, the outermost, innermost and basal part of petals from each flower of an accession were discarded and only the middle portion of petals from each flower were used as study sample those were divided into two parts [ 16 ]. One part of the selected petals was rapidly frozen and stored at − 40 ◦ C until the extraction and analysis. While the rest part of fresh flowers was used to perform colorimetric analysis, pH measurement and drying purposes. For drying, the petals were spread on plastic net bags and shade dried for 1 week at 25 ± 2 ◦ C. Then these shade dried petals were subjected for oven drying at 80 ◦ C for 48 h until reaching a constant weight which were used for relative moisture content determination. Then dried petals were pulverized and preserved at − 40 ◦ C for further analysis. The study was designed following randomized complete block design (RCBD) with three replications. The petals were collected from the six flowers of each accession and used in extraction preparation for qualitative and quantitative analyses of color, bioactive compounds and antinutrient properties. All analyses were conducted on the data of the three biological repeats, each with three technical repeats. Quantitative analysis of proximate composition and secondary metabolites Color The colors of the studied rose flowers were measured using a bench-top spectrophotometer (CR-5; Konica Minolta). Nine petals from three flowers per accession were randomly selected, with care taken not to include petals from the outermost and innermost layers. The selected petals were then measured at their mid-point of the adaxial surface. The color change was determined as L* indicates the darkness and lightness of color and ranges from 0 to 100 (L*=0 means black and L*=100 means white). Color parameters a* and b* extend from − 60 to + 60 [− a* = green and + a* = red; − b* = blue and + b* = yellow]. A white standard plate was used to calibrate the spectrometer before use to ensure the accuracy of the data. The hue angle (h°) is expressed in degrees from 0° to 360° (0° = red, 90° = yellow, 180° = green, and 360° = blue) [ 11 ]. The hue angle and Chroma (C) were calculated by following equations [ 17 ]. $$h=\text{a}\text{r}\text{c}\text{t}\text{a}\text{n}\left(\frac{b*}{a*}\right)\dots \dots \dots \dots \dots \dots \left(1\right)$$ $$C=\sqrt{\left( {a}^{*2}+ {b}^{*2}\right)}\dots \dots \dots \dots \dots .\left(2\right)$$ pH pH was determined by a digital pH meter (Digital Hanna pH Meter, Hand-Held, Pocket type pH Meter). To do so, petal extract was prepared by macerating the 0.5 g of petals in 5 mL of double distilled water and stirring for 2 h. The resulting aliquots were used for pH estimation and this quantification was repeated for three times for each accession [ 11]. Total soluble solids (TSS) (°Brix) Total soluble solids (TSS) of fresh rose petals were measured by hand refractometer (Model: Atago N1, Japan). Firstly, it was calibrated by placing one drop of distilled water on the prism and looking on the scale as it is showing the horizontal line between blue and white color in 0 level. Then, a drop of juice generated after squeezing 1 g of sample was placed on the prism of hand refractometer and the soluble solids content was recorded as degree Brix (°Brix) by observing the scale [ 18 ]. Total carotenoids Content (mg/100g) The total carotenoid content of the rose petals was determined according to the method described by [ 19 ]. Rose petals of each accession (100 mg) was extracted overnight with 5 ml of 80% acetone and stored at 4°C in the dark for 24 h in the air tight test tube. After that, 1 mL supernatant was taken into 1 mL glass cuvette and absorbance was read in the spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan) at 663, 646, 470 nm corresponding to Chl a, Chl b and carotenoids, respectively where, the 80% acetone was used as blank. For quantification of total carotenoids, the following equations was applied [ 20 ]. $$\text{C}\text{h}\text{l} \text{a} \left({\mu }\text{g}/\text{m}\text{L}\right)=12.21 \left({A}_{663}\right)– 2.81 \left({A}_{646}\right)\dots \dots \dots \dots \dots \dots \dots \left(3\right)$$ $$Chl b \left({\mu }\text{g}/\text{m}\text{L}\right)=20.13 \left({A}_{646}\right)– 5.03 \left({A}_{663}\right)\dots \dots \dots \dots \dots \dots \dots \left(4\right)$$ $$Carotenoid \left({\mu }\text{g}/\text{m}\text{L}\right)=\frac{1000 \left(A470\right)-3.27 \left(Chl a\right)-104 \left(Chl b\right)}{229}\dots \dots .\left(5\right)$$ For expressing the value in mg/100g the formula was used \(\frac{{\mu }\text{g}}{\text{m}\text{L}}\times \frac{V\times 100}{1000\times W}\) ; Where, V = Volume of acetone used (mL); and W = Weight of petal sample (g). β-carotene (mg/100g) For analysis β-Carotene, 1 g fresh sample was blended thoroughly by mortar pestle and mixed with 10 ml acetone: hexane (4:6) solution. This sample was centrifuged at 6000 rpm for 15 min and the filtered with Whatman no. 1 filter paper. Then the optical density of the supernatant was measured at 663 nm, 645 nm, 505 nm and 453 nm by using a spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan) and β-Carotene was estimated by using following formula [ 21 ]. $${\beta }-\text{c}\text{a}\text{r}\text{o}\text{t}\text{e}\text{n}\text{e} \left(\frac{\text{m}\text{g}}{100\text{g}}\right)=0.216\left({OD}_{663}\right)+ 0.452\left({OD}_{453}\right)– 1.22\left({OD}_{645}\right)– 0.304\left({OD}_{505}\right)\dots \dots \left(6\right)$$ Where, the bold figure indicates optical density; 0.216; 0.452; 1.22; 0.304 = Absorbance coefficient of the respective absorbance. Total anthocyanin content (AOA) (mg/100g) The total anthocyanin content was analyzed by following the methods [ 22 ] with some modifications. Briefly, 1 g of fresh rose flower petals were collected and grinded. For anthocyanin extraction this petal pastes were transferred to a 5 mL extraction solution comprising methanol, 6M hydrochloric acid and water mixture (70:7:23 v/v). After that, the extract solution was incubated at 4 ◦ C in dark for 24 h. Thereafter, 2 mL of the extracted solution was taken in centrifuge tube where 2 mL water and 2 mL chloroform were added in each of the tube and centrifuged at 5000 rpm for 15min. Then 3 mL supernatant was carried to a glass cuvette, and absorbance was measured at optical density (OD) of 530 nm by using a spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan). The total anthocyanin content was measurement by using the following formula- $${Q}_{At}={A}_{530}\times {M}^{-1}\times 100\dots \dots \dots \dots \dots \dots \left(7\right)$$ Where, Q At = Amount of total Anthocyanin A 530 = Absorbances at 530 nm M = Fresh weight of the material used for extraction (g) Total betacyanin content (TBC) (mg/100g DW) Betacyanin content was determined using methanolic extract following the procedure of [ 23 ] with some modification. To do so, the petals of ten rose genotypes were sun dried and then powered through grinding machine. After that, 2 g of dried petal powder was taken in the ten separate test tubes where 15 ml methanol was added and kept in room temperature for 24 hours with intermittent shaking. Then filtered through Whatman No. 1 filter paper and the filtrated extraction sample was used for total betacyanin content (TBC) estimation. For TBC estimation, firstly 15 mL filtered extract was taken in the falcon tube and centrifuged at 6000 rpm for 15min. Then 2 mL of aliquot was diluted with 8 mL distilled water and absorbance reading was taken at 538 nm using spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD-303 UV, PD 33-3-OMS-101 b, Japan). Betacyanin content (TBC) was calculated by using the following formula- $$\text{B}\text{e}\text{t}\text{a}\text{c}\text{y}\text{a}\text{n}\text{i}\text{n}\text{s} \text{c}\text{o}\text{n}\text{t}\text{e}\text{n}\text{t} \left(\frac{\text{m}\text{g}}{100}\text{g} \text{o}\text{f} \text{D}\text{r}\text{y} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t}\right)=\frac{A\times MW\times V\times DF\times 100}{L\times W\times \text{€}}\dots \dots \dots \dots \dots \left(8\right)$$ Where, A = Absorbance at 538 nm (lmax), MW = Molecular weight of betanin (550g/mol) DF = Dilution factor (1), V = Volume of extract (mL) L (path length) = 1.0 cm W = Sample weight (g) For betanin, € (mean molar absorptivity) = \(6.5 \text{x} 104\) L/mol cm in H 2 O Tocopherol (VitE) (mg α-tocopherol/100 g DW) Tocopherol content of the rose petals was analyzed by following the methods described by [ 24 ]. 1 g of the sample was macerated in 20 ml of ethanol and filtered in a test tube. Thereafter, 1 ml of 0.2% ferric chloride ethanolic solution and 1 ml of 0.5% α -dipyridyl solution were added to 1 ml of the filtrate in a new test tube. The solution was further diluted with distilled water to 5 ml, and the absorbance was measured at 520 nm. To prepare the ∝-tocopherol standard, 100 mg/100 mL ∝-tocopherol was taken in absolute ethanol and four concentration 0.2, 0.4, 0.6, 0.8 and 1.0 mg/mL was made. After that, the standard curve was drawn and the concentration of Tocopherol content (Vit. E) equivalent (mg d-alpha-tocopherol/100 g) was calculated by using the following standard curve gradient: $$Y = 1.9283\text{x} – 6.2896\dots \dots \dots \dots \left(9\right) {R}^{2} = 0.9661.$$ Where, y = Absorbance of samples x = Tocopherol content (VitE) Total antioxidant activity (IC 50 ) (µg/ mL FW) The bioactive properties of rose like total antioxidant activity (TAA), total phenolic content (TPC) and total flavonoid content (TFC) were determined from methanolic extract of rose petals. For determination of these properties of roses the methanolic extract was prepared. Initially, 1 g of fresh rose petals sample were weighed with electronic precision balanced (Digiscales, Germany) and immersed in methanol (25 ml) in the test tube. Then, test tube was placed in a shaking water bath (JSR JSSB-50T) at 30°C for two and half h. Then the sample was centrifuged at 6000 rpm for 15 minutes and the supernatant was filtered with the help of funnel and Whatman filter paper (no. 42) and stored at 4°C in a refrigerator for further analysis. Antioxidant activity of the rose petals was analyzed using DPPH radical scavenging assay (RSA). This assay is based on the measurement of the scavenging ability of antioxidants towards the stable radical. It was conducted according to the procedure of [ 25 ] with some modifications. For antioxidant assay, extracts of each rose petal samples and standard ascorbic acid solution (2 mg ascorbic acid dissolved in 2.5 ml distilled water and mix thoroughly) were prepared into several concentrations of 10, 20, 40, 80, 100 and 200 µg/ml and methanol were added to make the total volume 3 ml. Then 1 ml methanolic DPPH solution (0.004 mg DPPH was added with 100ml of methanol and mixed properly) was added to every test tube and the reaction mixture was kept at dark place for 30 minutes. Then, the reading was recorded at 517 nm against blank (methanol) by using spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan). Then, the radical scavenging activity was estimated by following formula- $$\% Radical scavenging activity=\frac{{A}_{0}-{A}_{1}}{{A}_{0}}\times 100\dots \dots \dots \dots \dots .\left(10\right)$$ Where, A 0 = Absorbance of control (3 ml methanol + 1 ml methanolic DPPH solution) A 1 = Absorbance of sample Inhibition concentration (IC 50 ) was used to specify antioxidant capacity and was determined from the graph that plotted % radical scavenging activity against concentration of extract for standards and the test sample. The values of IC 50 used in this study were generated from the regression line graph that plotted by % radical scavenging activity of 4 concentrations of the standards (20, 40, 80, and 100 µg/ml) against 4 concentrations of each extract test sample. IC 50 means the concentration of sample which can scavenge 50% of DPPH free radical in DPPH free radical scavenging assay where lower IC 50 value corresponds with a higher antioxidant activity [ 26 ]. IC 50 was calculated by using the formula as below - $${IC}_{50}=\frac{(y-b)}{a}\dots \dots \dots \dots \dots \dots \dots . \left(11\right)$$ Where, y was replaced by 50 in the above equation; value of a and b was found from regression line plotted for each sample separately. Total phenolic content (TPC) (mg GAE/ 100 g, FW) Total phenolic content (TPC ) was analyzed by following the Folin-Ciocalteu procedure [ 27 ]. For TPC estimation, previously prepared methanol extract solution was used. For preparing stock solution, 5 ml of FC reagent was pipetted in a conical flask and added 45 ml of water. For preparing the 7.5% Na 2 CO 3 , 7.5 g of sodium carbonate was added with 100 ml of distilled water in a 100 ml conical flask. For the preparation of gallic acid standard, 100 mg gallic acid powder weighed and diluted in 100 ml of distilled water. Then different concentrations (10, 20, 40, 60, 80, 100 µg/ml) of gallic acid were measured for preparing calibration curve. For the estimation of TPC, 0.5 ml of the sample extracts were taken in a test tube. FC reagent (2.5 ml) was added into the sample and the solution was incubated for 10 min. Then 2 ml of 7.5% sodium carbonate was mixed with the solution and the resultant mixture was incubated again at 30°C for 1 hour. The absorbance reading of the rose petal samples and the gallic acid standard were measured at 760 nm by using spectrophotometer (UV-VIS PD-303 UV Spectrophotometer; APEL Co.) against the methanol as blank. Standard curve was prepared using Microsoft excel using absorbance of gallic acid at the concentration of 10, 20, 40, 60, 80, 100 µg/ml. TPC readings were measured against the gallic acid standard calibration curves and expressed as mg of gallic acid equivalents per 100 g (dry weight) by following the equation as below - $$\text{y} = \text{m}\text{x} + \text{c}\dots \dots \dots \dots .\left(12\right)$$ Where, y = Absorbance of samples x = Total phenolic content (TPC); Value of c and m was found from the regression line plotted against the standard concentrations. Total flavonoid content (TFC) (mg QE/ 100 g, FW) Aluminium chloride colorimertic method was followed for quantification of Total Flavonoid Content [ 28 ] using the previously prepared methanolic extract. For the measurement of TFC, quercetin was used to draw the standard calibration curve. For this, the stock solution of quercetin was prepared by dissolving 1 mg of quercetin in 10 ml of methanol. Then different concentrations (10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 µl) of quercetin were taken in Eppendorf tube and methanol was also added in it to make the final volume 1000 ul. After that, 100 µl of sample extract was taken into the Eppendorf tube and 400 µl of methanol was also added. Then each sample extract was separately mixed with 100 ul of 10% AlCl 3 (w/v) and 100 µl of 1M sodium acetate. It was then incubated at room temperature and was kept in dark condition for 40 min followed by the measurement of absorbance at 420 nm using spectrophotometer (UV-VIS PD-303 UV Spectrophotometer; APEL Co.) where the methanol was used as blank. The expected outcomes of TFC were calculated from the quercetin standard calibration curve (10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 µl)) and expressed as mg quercetin equivalent (QE)/100 g (FW) by following the equation as below- $$Y=mx+c\dots \dots \dots \dots \dots \left(13\right)$$ Where, y = Absorbance of samples x = Total flavonoid content (TFC); Value of c and m was found from regression line plotted against the standard concentrations. Minerals (g/100g DW) and Moisture content (MC) (%) Mineral content (Na, K, Ca, Mg, Fe) was estimated following the procedure described by [ 29 ] with the help of device and method of an atomic absorption spectrophotometer (AAS). For preparing working sample, 0.5 g sample powder was taken in a 50 ml conical flask after that, 5ml of a mixture (5:1) of HNO 3 and HCIO 4 (Nitric perchloric acid) added and digested through a sand bath for 3–4 h. Then the digested sample mixture was filtered with Whatman no. 42 (2.5µm particle retention) filter paper and final volume was made up to the final volume of 100 ml with distilled water in a 100 ml volumetric flask. For minerals quantification, 10 ml sample extract was shifted to 50 ml volumetric flask and final volume made 50 ml with distilled water. Afterwards, the intensity of Na, K, Ca, Mg and Fe was estimated through AAS (atomic absorption spectrophotometer; model-PinAAcle 900H; PerkinElmer). The following formula was used to quantify the concentration of minerals in rose petals. $$\% Mineral=\frac{sample reading \times Final volume \times Dilution factor}{Sample weight}\dots \dots \dots \dots \dots \dots \dots \left(14\right)$$ The fresh rose flower petals were used for measurement of water content. Initially, the fresh weight of the sample recorded and thereafter, dried to a constant mass in an oven at a temperature of 100°C for 48 h. Then final weight was recorded and percent (%) moisture estimated on the basis of fresh and dry masses of rose petals in g by using the following equation [ 30 ]. $$\% Moisture=\frac{Initial weight \left(g\right)-Final weight \left(g\right)}{Initial Weight \left(g\right)}\times 100\dots \dots \dots \dots \dots \left(15\right)$$ Alkaloid content (ALK) (g/100g) Alkaloid content of rose flowers was measured according to the methods described by [ 31 ]. 0.5 g of the power sample was mixed with 200 ml of 10% acetic acid in ethanol. The mixture was covered with aluminium foil and incubated at room temperature for 4 h. After that, the mixture was filtered, and concentrated to about 1/4 of its original volume in a water bath. Thereafter, concentrated ammonium hydroxide was added drop by drop to the extract until complete precipitation was occurred. Then, the solution was allowed to stable, and the precipitate formed was washed with dilute ammonium hydroxide and then again filtered. The residue was oven dried at 40°C and weighed, and the alkaloid content was measured as: $$\% Alkaloid=\frac{\text{F}\text{i}\text{n}\text{a}\text{l} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{s}\text{a}\text{m}\text{p}\text{l}\text{e}}{\text{I}\text{n}\text{i}\text{t}\text{i}\text{a}\text{l} \text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{s}\text{a}\text{m}\text{p}\text{l}\text{e}} \times 100\dots \dots \dots \dots .\left(16\right)$$ Phytate content (PHT) (g/100g) The protocol described by [ 32 ] was used for estimation of Phytate content of rose accessions. Briefly, 2 g of the powder sample was soaked in 100 ml of 2% HCL for 3 h and filtered with Whatman no 1 filter paper. 25 ml of the filtrate was thereafter transferred into another conical flask and 5 ml of 0.3% ammonium thiocyanate solution along with 53.3 ml of distilled water was added to the filtrate. The solution was titrated against standard ferric chloride solution (0.001 95 g of iron per mL) until a reddish-brown color appearance which persisted for 5 min was noticed. Phytate content was calculated by the following ways: $$\% Phytate =Tirer value\times 0.00195\times 1.19\times 100\dots \dots \dots \dots \dots \left(17\right)$$ Saponin content (SPN) (g/100g) The saponin content in rose petals was quantified by following the method described by [ 33 ]. For this, 0.5 g of the powder sample was measured into a conical flask containing 50 ml of 20% ethanol. The solution was heated in a hot water bath for 4 h at 55°C and filtered and the filtrate preserved in a test tube, after that the residue was re-extracted again with 50 ml of 20% ethanol. Then both filtrates were mixed together and kept on the hot water bath at 90°C until it concentrated to 20 ml. The obtained solution was transferred into a 250 ml separating funnel containing 20 ml of diethyl ether. The aqueous layer was collected; 20 ml of n-butanol was added to it and then washed thrice with 10 ml of 5% sodium chloride meanwhile the ether layer was discarded. The mixture was oven dried at 40°C to constant weight, and the percentage saponin content of the sample was calculated as: $$\text{\%} \text{S}\text{a}\text{p}\text{o}\text{n}\text{i}\text{n} =\frac{\text{W}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{f}\text{i}\text{n}\text{a}\text{l} \text{f}\text{i}\text{l}\text{t}\text{r}\text{a}\text{t}\text{e}}{\text{W}\text{e}\text{i}\text{g}\text{h}\text{t} \text{o}\text{f} \text{s}\text{a}\text{m}\text{p}\text{l}\text{e}} \times 100\dots \dots \dots \dots \left(18\right)$$ Tannin content (TNN) (mg TAE/100g) Folin-Denis method was followed to estimate the Tannin contents of the rose flower samples [ 34 ]. For preparation of Folin-Denis reagent, 100 g of sodium tungstate (Na 2 WO 4 .2H 2 O) and 20 g of phosphomolybdic acid was dissolved to 750 ml of distilled water into which 50 ml of 85% phosphoric acid (H 3 PO 4 ) was added. After that, the mixture was refluxed for 2h and then cooled to 25℃ and diluted to 1000 mL by adding distilled water. This solution stored at 4℃ and used for further analysis. Accurately weighed 0.5 g of the powdered sample was transferred to a 250 mL conical flask and 75mL of water was added into it. The flask was gently heated and boiled for 30 min, centrifuged at 2,000 rpm for 20 min and the supernatant collected in 100 mL volumetric flask and the volume made up of 100 mL with distilled water. Next, 1mL of the sample extract was transferred to a 100 mL volumetric flask containing 75mL water. 5mL of Folin-Denis’s reagent, 10mL of sodium carbonate solution (35 g of anhydrous sodium carbonate was added to 100 mL of water and dissolved at 70–80℃ and then cooled it which turned into a clear liquid before use) were mixed and diluted to 100 mL with distilled water and preserved for 30 min. Then absorbance reading was taken at 700 nm with spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan). The tannin concentration was determined by the standard graph of tannic acid solution at the concentration of 0-100 mg/mL. The concentration of Tannin content was calculated by using the following equation: $$Y=0.0051x+0.0789\dots \dots \dots \dots \left(18\right), {R}^{2}=0.9638$$ Antinutrient to mineral molar ratios The bioaccessibility of minerals could be explained by the determination of molar ratios of antinutrient and minerals. The molar ratios were calculated by using the following formula [ 35 ]. $$Antinutrient:Mineral Molar Ratio=\frac{Conc. of antrinutrient\frac{mg}{100g}/Molar mass of antrinutrient\frac{g}{mol}}{Conc. of mineral\frac{mg}{100g}/Molar mass of mineral\frac{g}{mol}}\dots \dots \dots \dots \left(19\right)$$ Where the molar mass of Phytate- 660 g/mol; Tannin- 636.5 g/mol; K (Potassium)-39.0983g/mol; Ca (Calcium)- 40 g/mol; Mg (Magnesium)- 24.31 g/mol and Fe (Iron)- 56g/mol. Antinutritional phytochemical screening through qualitative analysis The analytical observation was done to notify the presence and identification of bioactive compounds in the methanolic extracts of rose petals powder following the standard procedures as reported in the previous report of [ 36 ]. For testing the presence of steroids, coumarins, quinones, anthraquinones and phlobatanins, 2 mL of methanolic extracts were taken every time. After that, methanolic extracts were added to equal quantity of chloroform and 0.5ml of concentrated sulfuric acid was also added drop by drop and formation of brown ring confirmed the presence of phytosteroids. Addition of equal volume of 10% NaOH solution and development of yellow color solution indicates the presence of coumarin in the rose genotypes and addition of 1 mL 2% HCl and development of red color precipitates indicates the presence of anthraquinones. Again, treating the methanolic extract with 1.5 mL of conc. H 2 SO 4 and the formation of red to blue color confirmed the presence of quinones whereas addition of 0.5mL of 10% ammonia and formation of pink color precipitates indicates the presence of phlobatanin. Statistical analyses All the recorded data on flower color parameters, secondary metabolites and antinutrient properties represent the mean values of three technical replications and were subjected to compare by two-way analysis of variance (ANOVA). The mean separation was done following least significant difference (LSD) test at 5% level of significance (P < 0.05). Furthermore, correlation matrix, cluster analysis, were performed to note the interrelationship among the studied variables and the rose accessions of the study. Afterwards, principal component analysis (PCA) was performed to show the patterns of all the measured correlated color parameters, secondary metabolites and minerals in the reduced dimensions of newly obtained factors those were denoted as- Dim1 (PC1), Dim2 (PC2). The dendrogram cluster analysis was performed to sort out the most promising rose accession according to the factor loadings and the contributions of each of the studied dependent variables using different packages (agricolae, facatominer, factoextra, ggplot2, corrplot) of R program (version 4.1.2). All data were reported as the mean value of three determinations ± standard deviation (SD). Results Color The CIELAB system, established by the International Commission on Illumination, was employed to analyze the color of different rose accessions as indicated in Table 1. The system utilizes L* to quantify the lightness of the color, ranging from white to black. Additionally, a* and b* indicate distinct color directions, with a* ranging from green to red and b* ranging from blue to yellow. Lastly, c* is used to measure the chroma of the color. Table 1 shows that the R4 accession had the lightest L* value (79.16), which was similar to the R10 accession (76.06) for white and yellow flowers, respectively. The R3 accession had a L* value of 63.55, followed by R8 with a value of 61.08. The darkest L* value of 18.99 was observed in the R7 accession, corresponding to blackish red roses. In terms of other color coordinates, the a* value varied from 48.49 to -3.66. The highest value of 48.49 was observed in R6, which represents red color flowers. This value was similar to R2 (46.90, hot pink color) and R1 (44.85, orange color), but significantly different from the other rose accessions. The lowest value of -3.66, indicating white color flowers, was recorded in the R4 accession. In addition, the values of b* for the other color directions varied from positive to negative, ranging from 60.13 to -3.66. This corresponds to the color spectrum from yellow to purple in a flower. The highest b* value, 60.13, was obtained from R10, which showed a statistically significant difference compared to all other rose accessions. Following R10, R9 had a b* value of 26.07, while R5 had the lowest value of -3.67. The rose accession R10 exhibited the maximum color saturation, with a C* value of 60.19, which was statistically distinct from the other rose accessions. Nevertheless, R6 exhibited the second highest value (50.68), which was statistically comparable to R1 (47.77) and R2 (46.91), while R4 had the lowest vividness of color (13.35). However, the decrease in values of a* and the increase in values of b* are associated with the perception of darkness and lightness. Similarly, the highest luminosity (h°) was observed at R10 (87.56), indicating a brightening of rose petals close to a yellow color. This was followed by R9 (47.13), R7 (19.89), R1 (19.19), and R6 (16.86). The last three values were statistically similar to each other but different from the rest. Therefore, the values of the parameters accurately depicted the color patterns of the flower, aligning with the visual observations of the rose accessions' blossom color. pH and TSS (°Brix) A notable fluctuation in pH and total soluble solids (TSS) (°Brix) among the 10 rose accessions was demonstrated in Fig. 1. The acidity of rose petals varied among different accessions, with the lowest pH recorded in R1 (4.50), which was comparable to R7 (4.50), R6 (4.57), and R2 (4.70). On the other hand, the highest pH was observed in R4 (5.60), which was similar to R8 (5.50) and R9 (5.40), and statistically similar to R3 and R5 (5.30). Conversely, the highest total soluble solids (TSS) level was found in R1 (9.40 °Brix), while the lowest was seen in R3 (7.10 °Brix). Total Carotenoids and β-carotene (mg/100g) There was a significant statistical variation (P < 0.05) in the total carotenoids and β-carotene concentration noticed across ten different rose accessions (Fig. 2). The rose accessions R10 had the highest total carotenoids content at 108 mg/100 g fresh weight (FW). The second highest was R1 at 72 mg/100 g FW, followed by R9 at 67 mg/100 g FW. The lowest carotenoids content was found in R4 at 6 mg/100 g FW. All rose accessions were statistically distinct from each other. From a β-carotene perspective, the highest concentration of β-carotene was found in R10 (47 mg/100 g FW), followed by R9 (42 mg/100 g FW), and R1 (39 mg/100 g FW). These values were statistically distinct from each other. Furthermore, all the remaining accessions exhibited statistically equivalent levels of accumulation, which were below 5 mg. However, the lowest accumulation was recorded in the rose accessions R3, with a value of 1 mg per 100 g. Notably, the rose accessions R5 and R7 did not exhibit any detectable β-carotene content. Total Anthocyanin and Betacyanin (mg/100 g) The column graph (Fig. 3) clearly demonstrates that there were statistically significant variations in the overall anthocyanin and betacyanin content among the 10 rose accessions. In terms of total anthocyanin content, the accession R7 accumulated the maximum quantity of anthocyanin (196 mg/ 100g FW), which was comparable to R6 (191 mg/ 100g FW), R2 (189 mg/ 100g FW), and R1 (183 mg/ 100g FW). On the other hand, R4 accumulated the lowest amount (3 mg/ 100g FW). The total anthocyanin content varied between 196 and 3 mg per 100 g FW. Conversely, the betacyanin content was determined based on the dry weight of the samples. The highest amount of betacyanin was found in the R7, with a concentration of 22.63 mg per 100g of dry weight (DW) which is equivalent to the amount of anthocyanin. However, it also indicates more than double the concentrations than that of the R1 (10.43 mg/ 100g) and R6 (9.91 mg/ 100g) accession while the lowest betacyanin content was observed in R10. Tocopherol Content (Vit.E) (mg/ 100 g DW) The tocopherol content in the rose accessions examined ranged from 400.08 to 300.95 mg/100 g DW. The highest concentration was found in the R8 accession (400.08 mg/100 g DW), which was significantly different from the other accessions. However, the second greatest value was achieved from R6 (400.05 mg/ 100 g DW), which was equal to the value acquired from R1 (400.05 mg/ 100 g DW). On the other hand, the lowest value was seen in R10 (300.95 mg/ 100 g DW), which was statistically close to the value in R9 (300.97 mg/ 100 g DW) (Table 2). The total phenolic content (TPC) (mg GAE/ 100 g, FW) Table 2 demonstrates that the various rose petal extracts exhibited significant variance in their total phenolic content (TPC). The R6 accession exhibited the maximum concentration of TPC 533.18 mg GAE/ 100 g, FW, whereas the lowest concentration was observed in the R4 accession, with a value of 241.87 mg GAE/ 100 g, FW. The total flavonoid content (TFC) (mg QE/ 100 g, FW) Upon examining Table 2, it becomes evident that all the rose accessions exhibited significant variations in the accumulation of flavonoid contents (TFC). The highest level of flavonoid content was observed in R3 (27.77 mg QE/ 100 g, FW), whereas the lowest concentration was reported in R1 (0.76 mg QE/ 100 g, FW). Total Antioxidant Activity (IC 50 ) (µg/ mL FW) The antioxidant activity of rose petals was assessed by determining the IC 50 value, which represents the concentration of the sample needed to block 50% of DPPH free radicals. Thus, in the DPPH experiment, greater IC 50 values indicate lesser antioxidant activity, and vice versa. Table 2 clearly shows that the IC 50 values of 10 rose extracts had a substantial impact on their ability to scavenge free radicals (p < 0.05). The R1 rose accession had the most potent antioxidant activity, as evidenced by its lowest IC 50 value of 82.60 µg/mL FW. Among the other rose accessions, R5, R6, R7, R8, R9, and R10 exhibited an IC 50 value greater than 250 µg/mL FW, indicating their inactivity in free radical scavenging action. Regrettably, the antioxidant activity of two rose accessions, R3 and R4, was not observed in this experiment. Minerals (g/100g) and Moisture content (%) The results from Table 3 clearly demonstrate that the accumulation of mineral elements such as sodium (Na), potassium (K), calcium (Ca), iron (Fe), and moisture content varied significantly among the ten rose accessions, with the exception of magnesium (Mg). Moreover, within the composition of these minerals, the concentration of potassium was particularly notable in the rose accessions. The sodium (Na) concentration in the petals of ten different rose accessions varied significantly. The highest accumulation of Na was seen in accession R5 (0.092 g/100g DW), followed by accession R9 (0.085 g/100g). Simultaneously, the lowest recorded value was obtained from R10 (0.062 g/100g), which was exactly the same as R7 (0.065 g/100g). The analysis found that the potassium level varied between 1.408 and 0.984 g/100g where the maximum concentration was seen in R2, while the lowest value was found in R4, which was statistically similar to R6. The average value of calcium content differed across the roses where the R1 and R3 had the highest accumulation of Ca at a concentration of 0.19 g/100g, whereas R6 and R7 had the lowest concentration at 0.14 g/100g. The accumulation of Fe, varied greatly, ranging from 0.090 to 0.017 g/100g. The top accumulator was R4, while R9 was the lowest accumulator. Meanwhile, the rose petals exhibited a significant variation in moisture content, with the greatest reported in the rose accession R6 (87.31%). This value was statistically equivalent to that of R5 (87.07%) and the water content in R3 was significantly low, measuring at 68.51%. Antinutrient properties (g/ 100 g DW) Upon examining Table 4, it is evident that there were notable variations in the levels of alkaloids, phytate, saponin, and tannins among the rose accessions. The alkaloid content of rose petals in this investigation varied from 1.24 to 14.64 g/100 g DW (Table 4). Of the ten rose accessions, R2 had the greatest alkaloid content accumulator (14.64 g/ 100 g DW), followed by R1 (9.52 g/ 100 g DW), and R10 (1.24 g/ 100 g DW) had the lowest. Of these three metrics, the phytate content indicated a very small quantity of present (Table 4). However, R6 differs greatly from the others due to its higher amount (0.63 g/100 g DW). The majority of the saponin (14 g/100 g DW) was found in the rose petals of R6 and R9, with R3 and R7 following closely behind (12 g/100 g DW), and R1 containing the least (4.03 g/100 g DW). The data displayed in Table 4 indicates that there was a notable variation in the tannin content among the ten rose accessions, ranging from 143.55 to 198.05 mg TAE/ 100g DW. The highest tannin conserver in this testing was R7 (198.05 mg TAE/ 100g DW), followed by R6 (180.57 mg TAE/ 100g DW). Conversely, the R2 accession had the least amount of tannin (143.55 mg TAE/ 100g DW), and it was statistically comparable to the R10 and R4 containers (143.97 and 145.47 mg TAE/ 100g DW, respectively). Antinutrients to molar ratios The molar ratios of [PHT]: [Ca], [Ca]: [PHT], [PHT]: [Fe], [PHT]: [K], [Mg]: [PHT], [TNN]: [Fe], and [PHT + TNN]: [Fe] were determined based on the analyzed data of antinutrients and minerals of rose accessions and presented in Table 5. Out of the ten rose accessions, all except for R6 exhibited [PHT]: [Ca] ratios below the crucial value of 0.24 and [Ca]: [PHT] ratios above the critical value of 0.6. The rose accession R6, however, had [PHT]: [Ca] and [Ca]: [PHT] ratios of 0.273 and 3.667, respectively. Based on the table 5, it is evident that the rose accessions R6 and R7 exhibited a [PHT]: [Fe] ratio that exceeded the threshold value of 1, indicating a lower bioavailability of iron. On the other hand, R4 had the lowest ratio of 0.019, suggesting the highest absorption of iron in nutrition. Regarding [PHT], the 10 rose accessions exhibited variances in [K] molar ratios, which varied from 0.001 to 0.033. Table 5 shows that the molar ratios of [Mg]: [PHT] in rose accessions varied from 4.396 to 139.819. Among them, R10, R4, R8, R3, and R9 had larger amounts of magnesium, with molar ratios of 139.819, 138.462, 137.104, 54.842, and 39.560, respectively. The molar ratios of [TNN]: [Fe] were adjusted within the range of 0.142 in R4 to 0.871 in R7 rose accessions. The molar ratio of [Fe] for [PHT + TNN] ranged from 0.161 in R4 to 2.884 in R6, with R6 having the greatest ratio. Qualitative Assessment of bioactive compounds The phytochemical screening tests largely determined the presence or absence of steroids, coumarins, quinones, anthraquinones, and phlobatannins in the ten rose genotypes. This was done using color reactions, as shown in Table 6. The presence of phytosteroids, coumarin anthraquinones, quinones, and phlobatanin was confirmed through various chemical reactions, including the formation of a brown ring, the development of a yellow-colored solution, the precipitation of red-colored solids, a color change from red to blue, and the precipitation of pink-colored solids, respectively (Fig. 4. A1, A2, A3, A4, A5). The analysis of the ten rose accessions revealed the presence of steroids in R1, R4, and R10 accessions, coumarines in R1, R3, R4, R9, and R10 accessions, quinones in R1, R2, R6, and R7 accessions, anthraquinone in R1, R3, R6, and R7 accessions, and phlobatanin exclusively in the R6 rose accession. Correlation coefficient analysis The Pearson correlation coefficient was employed to evaluate the intra and interrelationships among the 25 variables under investigation. The correlation matrix visually represents the degree of both positive and negative association between the colorimetric parameters, secondary metabolites, and mineral contents (Fig. 5A). In the event of a positive correlation, an increase in one variable will result in a corresponding increase in another variable, whereas a negative correlation indicates that an increase in one variable will lead to a decrease in another one. The circles in Fig. 5, colored in blue and red, indicate positive and negative correlations, respectively. The intensity of the color represents the strength of the correlation between the variables. Vacant cells indicate an inconsequential association at a 5% level of significance. The Pearson's correlation coefficient and correlation matrix revealed a significant link between colorimetric features and secondary metabolites, ranging from moderately strong to extremely strong. However, this correlation was not observed with mineral matters. Among these factors, a significant positive correlation (R 2 = 0.95) was observed between the total carotenoid and β-carotene content. This suggests that an increase in total carotenoid content is associated with a corresponding increase in the concentration of β-carotene. The total carotenoid concentration exhibited a significant positive correlation with h° and b* (R 2 = 0.71, 0.79). Moreover, there was a significant and positive relationship between the β-carotene content and both the b* value and hue angle, with R 2 values of 0.84 and 0.79, respectively. Conversely, the overall amount of anthocyanin was highly and positively associated with a*, phytate, and betacyanin (R 2 = 0.89, 0.86, and 70), whereas it exhibited a substantial negative association with L* and pH (R 2 = 0.914, 0.819). Furthermore, there was a significant positive relationship between the betacyanin and tannin concentration (R 2 = 0.75), as well as a substantial negative association with L* (R 2 = 0.874). In addition, there was a significant positive association between the phytate content and a* (R 2 = 0.89), as well as a negative link with L* (R 2 = 0.77). Additional observations revealed a negative correlation between the minerals (Na, K, Ca, Mg, and Fe) and the levels of anthocyanin, betacyanin, and phytate. It was observed that the rose blossom became darker in color as the levels of anthocyanin, betacyanin, and phytate increased. Conversely, the flower's color faded with an increase in mineral content. From an antioxidant perspective, the IC 50 value demonstrated a significant inverse relationship with Ca (R 2 = 0.85), similar to the correlation between TSS and pH (R 2 = 0.82) (Fig. 5). A heatmap with a dendrogram was created using 25 factors to cluster ten rose accessions for the purpose of cluster analysis (Fig. 5B). The analysis showed that the 25 factors were divided into two primary clusters, each making a major contribution to grouping the ten rose accessions into three clusters. Regarding the variable cluster, Cluster I consist of the elements Na, K, Alk, TFC, L, pH, Ca, Fe, whereas Cluster II comprises the remaining 17 variables h, b, VitA, X. carn, MMC, Mg, VitE, PHT, an AOA, BTC, TNN, TPC, SPN, IC50, C, and TSS. Cluster I accounted for 32% of the variables, whereas Cluster II accounted for 68%. Once again, cluster II was subdivided into two subclusters, which were then further fragmented into smaller clusters (Fig. 5B). On the other hand, these 25 factors categorized the ten rose accessions into three clusters. Cluster I consisted of R4, R3, R5, and R8. Cluster II included R10 and R9, while cluster III comprised R6, R7, R1, and R2. Principal component analysis (PCA) The previous section findings revealed that the variables made a substantial contribution to the classification of the rose accessions. The PCA was conducted to ensure consistency of the data and assess the extent of variation among variables. Principal Component Analysis (PCA) is a form of multivariate analysis that transforms large, intricate datasets with associated variables into groupings in order to uncover the most influential characteristics. The PCA biplot diagram visually represented the relationships, both similarities and dissimilarities, among the various parameters in Fig. 7A and 7B. The diagram specifically focused on the first dimension (PC1) and the second dimension (PC2); the initial two principal components (PCA), account for 54.6% of the overall data variance. Specifically, PC 1 and PC 2 individually account for 32.4% and 22.2% of the variance, respectively. The factor loadings and scores for the first two principal components (Dim 1 and Dim 2) of color parameters, secondary metabolites, and mineral matters of ten rose accessions (Fig. 6) indicated that a positive score on Dim1 was associated with L, b, pH, Vit A, X.Carn, TCP, Na, Ca, Mg, and Fe (ranging from 0.05 to 0.3), while all the other variables had moderate to low negative scores (ranging from − 0.04 to -0.25). Conversely, eleven variables, namely pH, Vit E, TFC, AOA, BTC, Na, Fe, PHT, ALK, SPN, and TNN, exhibited a positive score in Dim 2. In contrast, the variables L, b, c, h, MC, TSS, VitA, X. carn, TCP, IC50 K, Ca, and Mg contributed negatively to the score in Dim 2. Upon examination of Fig. 7A and 7B, it is clear that the variables X. carn, b, VitA, h, c, a, L, pH, TSS, PHT, BTC, and AOA had the greatest influence on the selection of rose accessions. Consequently, the 10 different rose genotypes were clearly separated into three groups as a result of a positive association in both directions. In this case, the two accessions R9 (salmon color) and R10 (yellow color) that have the greatest influence on the variables may be easily differentiated from the others due to their strong positive correlation with both dimensions of the biplot. However, the biplot displays both the observations and variables in a given orientation along the PC axis (Dim1 and Dim2) concurrently. The orientation of the variable arrows signifies the direction in which the contribution of the related variable experiences the greatest rise, while the length of the arrows represents the magnitude of the change in that direction. Cluster analysis Cluster analysis was conducted using the K-means algorithm to group ten rose accessions based on 25 quantitative attributes. To do this, a dendrogram was constructed and then divided at a rescaled distance of 7.5. This division resulted in the formation of three separate clusters of roses, each exhibiting significant similarities in terms of the studied attributes (Fig. 8). Table 7 provides a compilation of three clusters of rose accessions in relevance with the CIELAB system and their visual evidence. The cluster I consisted of four rose accessions (R3, R4, R5, R8), which accounted for 40% of the plant population, just like cluster III (R1, R2, R6, R7). Cluster II consisted of R9 and R10 rose genotypes, which accounted for 20% of the population. Considering the contribution of rose accession in the CIELAB it has been revealed that the cluster I with the highest contribution of L* and the lowest b* value and which visualized the light color flower, cluster II with the highest contribution of b*, h° and cluster III with the highest contribution of a*, C* and appeared as bright color and dark color, respectively. Discussion The rose is a type of flower that is both edible and decorative. It is known for containing secondary metabolites, which have both nutritional and medicinal characteristics. Additionally, roses can be used as natural food coloring agents. The color of flowers is a prominent characteristic that is highly valued by customers and also holds ecological significance. The composition of floral color is influenced by various elements such as secondary metabolites in cell pigments, the shape of epidermal cells [ 37 ], the pH of cell sap [ 38 ], and mineral content [ 39 ]. The most influential factor among them is the buildup of a certain type of pigments [ 40 ]. The genus Rosa , which includes roses, has a remarkable range of characteristics such as a delightful scent, distinctive shape, and a wide array of colors. Nevertheless, there is still a lack of documentation regarding the measurement of color in rose accessions and its correlation with secondary metabolites, metal ions, and antinutrient characteristics. Additionally, the categorization of rose accessions based on these features has not been recorded. Currently, the CIELAB system is widely utilized for the identification, measurement, and description of color in ornamental plants [ 40 ]. The L* value in this system represents the rise in lightness from white to black, while the b* value represents the increase in color from blue to yellow. Conversely, the a* value represents the reduction in color from green to red. In the investigation, it was found that the flower with the highest L* value was R4, which had a white color. The red color rose with the maximum a* value was R6. Additionally, the flower with the highest b* value was R10, which corresponded to a yellow color. These findings were congruent with the visually seen colors of the flowers (Table 7). Prior studies have indicated that anthocyanins contribute to the development of red to purple hues, while carotenoids are responsible for the generation of yellow to red colors in ornamental plants [ 41 , 42 ]. In other study it was noticed that in potted multiflora chrysanthemum, only the b* value showed a high positive connection with total carotenoids (r = 0.881, P<0.01) and lutein (r = 0.804, P < 0.01) [ 43 ]. Nevertheless, the results of this investigation have also demonstrated a resemblance to the previous study, indicating that R10, a yellow-colored rose sample, exhibited the highest concentration of total carotenoids. This concentration was found to be positively associated with β-carotene, and both of these compounds displayed a significant positive connection with h° and b*. Nevertheless, the β-carotene content could not be detected in the R5 (Purple color) and R7 (Blackish red color) rose accessions throughout this research study. However, R6 (red color), have demonstrated a high capacity for accumulating anthocyanin, betacyanin, tannin, and saponin. Anthocyanins are a group of secondary metabolites that are derived from flavonoids. Betacyanins, on the other hand, are nitrogen-containing compounds present in a small number of plant families. Both anthocyanins and betacyanins contribute to the yellow to red colors observed in plants [ 44 , 45 ]. The rose accessions in this experiment have demonstrated the presence of betacyanin content, which might potentially be utilized by the food sector as a natural food coloring ingredient. The correlation study has demonstrated a strong positive association between the total anthocyanin and a* value, as indicated by the multivariate analyses as well. Additionally, betacyanin and phytate also showed high correlations with these two variables. Anthocyanin, betacyanin, and phytate have been found to have a negative connection with mineral content. Mineral substances contribute to the development of flower color by combining with flavonoids to create supramolecular pigments known as metal complexes. Our investigation has revealed a weak to negative association between the total flavonoid levels and mineral matters, anthocyanin, a*, and betacyanin. Previous work has indicated that flavonoids possess colorless structures that alter the intensity of yellow pigmentation in plants [ 40 ]. The current study found that the rose accession R3, which is baby pink in color, has the largest accumulation of total flavonoids. Additionally, it was observed that there is a weakly positive link between the levels of total flavonoids and the L* and b* values. When considering food, it is important to take into account the antinutritional properties of substances such as tannin, saponin, alkaloid, and phytate. Recent data has demonstrated that the ingestion of these secondary metabolites can have beneficial impacts on human health, contingent upon the dietary pattern and composition. Tannin, saponin, phytate, and alkaloid are polyphenols that possess antioxidant characteristics, which enhance the human body's immune system [ 46 , 47 , 48 ]. According to the author [ 49 ], tannins in food can create complex compounds with proteins, carbohydrates, and specific minerals. However, the development of these complexes depends on factors such as temperature, pH, and concentration, which must be suitable. Furthermore, the oral administration of tannin resulted in a roughly 50% decrease in toxicity compared to the rectal administration of tannic acid [ 50 , 51 ]. Phytate is classified as a nutraceutical and is deemed generally recognized as safe (GRAS) by the Food and Drug Administration (FDA) [ 46 ]. Plant-derived alkaloids serve as a valuable source for the development of medicines and pharmaceuticals. It has demonstrated antiviral, antibacterial, antiproliferative, and insecticidal characteristics [ 52 ]. In addition, both secondary metabolites and other compounds such as total carotenoids, total phenols, total flavonoids, and vitamin E play a crucial role as antioxidants [ 53 ]. This study examined the link between the overall antioxidant activity (measured by the IC 50 value) of several rose accessions and their secondary metabolites. The results showed a positive correlation between the IC 50 value and the presence of alkaloids, tannin, saponin, phytate, total phenols, anthocyanin, and betacyanin. In addition, there is a clear negative association between phytate and the levels of calcium (Ca), magnesium (Mg), and iron (Fe), as indicated by the IC 50 value. Excessive intake of phytate has been demonstrated to decrease the absorption of minerals, particularly calcium, magnesium, iron, and zinc. Therefore, it is advisable to consume 100–400 mg/day of phytate [ 54 ]. The presence of antinutrients such as tannin, polyphenols, and phytate in plant materials significantly decreases the bioavailability of minerals, including calcium (Ca), iron (Fe) [ 55 , 35 ], magnesium (Mg), and potassium (K) [ 56 ]. The molar ratios of [PHT]: [Ca] are less than 0.24 [ 57 , 58 ], while the ratios of [Ca]: [PHT] are larger than 6.0. These ratios indicate a positive effect on the bioavailability of Ca [ 59 ]. The phytate concentrations in all rose accessions showed a positive effect on Ca absorption, except for R6. The phytate level in plant-based nutrition is widely recognized as the primary factor that hinders the absorption of iron. In order to mitigate the negative impacts of phytates, it is recommended that the phytate content in the food material be kept below 0.1g per 100g [ 58 ]. Furthermore, a molar ratio of [PHT]: [Fe] < 1 serves as an indication of favorable iron bioavailability [ 60 ]. However, the presence of phytate in R6 and R7 rose accessions might hinder the absorption of Fe. The solubility of magnesium and phytate complexes is directly correlated with the pH of the solution. The magnesium complex with a molar ratio of 6:1 with [PHT] demonstrated that it is highly soluble at pH levels below 5.0. However, as the pH increases, the solubility of magnesium decreases fast and becomes insoluble at pH levels over 8.0 [ 61 ]. The cell sap of the ten rose accessions exhibited an acidic pH ranging from 4.50 to 5.60. This indicates that the presence of phytate concentrations in these rose petals’ products would not hinder the bioavailability of Mg. The impact of tannin on the absorption of iron has been studied in common beans, with the ratios of tannin to iron ([TNN]: [Fe]) ranging from 0 to 65.7, and the ratios of phytate plus tannin to iron ([PHT + TNN]: [Fe]) ranging from 24 to 90.1 [ 35 ]. In addition, the principal component analysis (PCA) and K-means cluster analysis were used to categories the 10 various color rose accessions based on the linked variables. The cluster-I comprises the following rose accessions: R4 (white color), R3 (baby pink color), R8 (multicolor), and R5 (purple color). Cluster II consists of R10 (yellow color) and R9 (salmon color), which is characterized by high levels of total carotenoids and β-carotene concentration. The cluster II comprises R1 (orange color), R2 (pink color), R6 (red color), and R7 (blackish red color), mostly due to their high levels of anthocyanin, total phenol content, tannin, TSS, phytate and betacyanin. This discovery demonstrates a resemblance to the findings of [ 62 ], who showed that out of ten different colored roses, the red ones contained the highest amount of anthocyanins and overall phenol levels. The co-pigmentations of anthocyanins in orange color to blackish red color flowers are regulated by the presence of phenolic acids residues and sugar content. These compounds help stabilize the color in various regions of the plants. Based on the present study's results, it is evident that the rose accessions R9, R10 (cluster II) and R1, R2, R6, R7 (cluster III) are particularly rich in secondary metabolites. These compounds have potential use in the food colors, cosmetics, and pharmaceutical industries. A study conducted on 30 flower species [ 63 ] found that the rose species had the highest levels of total phenol content, antioxidant activity, and acted as a significant source of bioactive chemicals. Conclusion The results indicate significant variation among the ten rose accessions in terms of the secondary metabolites screened (steroids, coumarins, quinones, anthraquinone, and phlobatanin) as well as the quantified compounds (total carotenoid, β-carotene content, anthocyanin, betacyanin, tocopherol, phenol contents, flavonoid contents, alkaloid, phytate, saponin, and tannin contents) and their antioxidant properties. The R6 rose accession (red color flower) exhibited the highest levels of anthocyanin, total phenol, phytate, saponin, and colorimetric parameter a*. The R7 accession (blackish red color) had the highest levels of betacyanin, tannin, and pH. The R10 accessions (yellow color flower) showed the highest levels of L*, b*, C*, h°, total carotenoid content, and β-carotene. Lastly, the R1 accession had the highest free radical scavenging potentials and TSS. The findings of principal component analysis (PCA) showed that the variables strongly influenced the grouping of the ten examined rose accessions into three clusters. Cluster I consisted of R3, R4, R5, and R8, Cluster II consisted of R9 and R10, and Cluster III consisted of R1, R2, R6, and R7. Therefore, the rose accessions categorized in cluster III and cluster II are suggested as promising sources of secondary metabolites for future application in the food sector, cosmetics, fragrance, and pharmaceuticals. Declarations Conflicts of interest The authors declare no conflict of interest. Author contribution S R Mallick and J Hassan conceived the idea of the study, design and conduct the experiment. S R Mallick, J Hassan wrote the manuscript. S R Mallick, J Hassan, M A Hoque, E Kayesh, H Sultana and M Ahmed contributed in sample collection, preparation and laboratory analyses. J Hassan and S R Mallick analyze the data and made necessary interpretation. M A Hoque, E Kayesh, H Sultana, M Ahmed, M H Siddiqui and Y Ozaki reviewed and edited the manuscript for further improvement. All authors have read, edited the manuscript and approved it for submission. Acknowledgement The authors are highly grateful to the research management wing (RMW), Bangabandhu Sheikh Mujibur Rahman Agricultural University for the financial and logistic supports to carry out this research work under the innovation project (ID: 008). The authors are also extending their gratitude to the Post-Harvest Division of Bangladesh Agricultural Research Institute and Department of Agro-Processing and Soil Science for providing their lab facilities to carry out the analyses. Our sincere appreciation also goes to the Researchers Supporting Project number (RSP2024R347), King Saud University, Riyadh, Saudi Arabia. Declaration on plant handling with the relevant guidelines and regulations The present study utilized Rose ( Rosa sp. ) flowers as the plant material. The many cultivated rose accessions were obtained from the flower garden of Bangabandhu Sheikh Mujibur Rahman Agricultural University, located in Gazipur-1706, Bangladesh. The rose accessions are cultivated and conserved in the university's flower garden for utilization in research endeavors. The field and laboratory investigation were conducted using established growth protocols and adhering to the scientific ethics rules and regulations for handling plants. Data availability statement The data will be made available from the corresponding author J. Hassan on request. From the link below: https://drive.google.com/file/d/12I1yTNQJ6ZWnXHI7wqRImJK6gKokUHX/view?usp=sharing References El-Sayed S, Abdel-H., Salih, A. B., Salman. M. S. 2013. Characterization of the Phytochemical Constituents of Taif Rose and Its Antioxidant and Anticancer Activities. BioMed Research International:1–13. http://dx.doi.org/10.1155/2013/345465 Soni, H., Sahu, N., Sihghai, A.K., Malik. J. 2012. 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Colorimetric parameters of 10 rose accessions Rose Accessions Flower Color Color Parameters x L* a* b* C* h° R1 Orange 42.00 ± 5.89 d y 44.85 ± 1.61 a 15.86 ± 6.11 c 47.77 ± 3.44 b 19.19 ± 6.31 c R2 Hot Pink 45.26 ± 0.36 d 46.90 ± 1.98 a -0.88 ± 0.76 h 46.91 ± 1.98 b -1.07 ± 0.91 de R3 Baby Pink 63.55 ± 2.53 b 16.72 ± 3.82 de -1.66 ± 1.78 i 16.84 ± 3.95 d -4.98 ± 5.14 e R4 White 79.16 ± 1.53 a -3.66 ± 0.27 g 12.84 ± 0.38 e 13.35 ± 0.39 d -74.09 ± 1.14 g R5 Purple 58.28 ± 2.21 c 14.34 ± 1.53 e -3.67 ± 0.59 j 14.80 ± 1.62 d -14.32 ± 0.73 f R6 Red 30.21 ± 2.10 e 48.49 ± 2.44 a 14.65 ± 1.34 d 50.68 ±2.05 b 16.86 ± 2.15 c R7 Blackish Red 18.99 ± 0.37 f 28.54 ± 1.07 b 10.33 ± 0.56 f 30.35 ± 1.19 c 19.89 ± 0.35 c R8 Multicolor 61.08 ± 3.07 bc 18.39 ± 8.99 d 0.61 ± 1.42 g 18.44 ± 8.97 d 3.35 ± 4.87 d R9 Salmon 64.20 ± 0.32 b 24.26 ± 3.08 c 26.07 ± 1.92 b 35.73 ± 0.73 c 47.13 ± 5.72 b R10 Yellow 76.06 ± 0.90 a 2.56 ± 0.30 f 60.13 ± 1.20 a 60.19 ± 1.19 a 87.56 ± 0.33 a x Color parameters base on CIE (International Commission on Illumination) system for color representation: (L*: Lightness, a*: greenness (−) to redness (+), b*: blue (−) to yellow (+), c*: saturation of the color, h°: huge angle). y Similar letters in each column indicate insignificant differences determined using a least Significant Difference test (P<0.01); ±SD Table 2. The bioactive components and Total Antioxidant Activity of ten rose accessions Rose Accessions Tocopherol (mg α-tocopherol/100 g DW) Total Phenolic Content (mg GAE/ 100 g, FW) Total Flavonoid Content (mg QE/ 100 g, FW) Total Antioxidant Activity IC 50 (µg/ mL FW) R1 400.05 ± 0.01 b x 303.07 ± 1.00 e 0.76 ± 0.03 j 82.60 ± 1.00 g R2 400.01 ± 0.01 d 293.41 ± 2.10 f 11.21 ± 0.11 g 5536.48 ± 1.16 c R3 400.01 ± 0.01 cd 229.20 ± 1.00 j 27.77 ± 0.21 a - R4 400.01 ± 0.01 d 241.87 ± 0.15 i 19.16 ± 0.01 b - R5 400.01 ± 0.02 d 256.48 ± 1.00 h 12.56 ± 0.01 f 5302.24 ± 2.00 d R6 400.05 ± 0.02 b 533.18 ± 1.01 a 14.39 ± 0.03 e 5777.53 ± 5.77 a R7 400.04 ± 0.20 bc 371.63 ± 0.56 d 7.15 ± 0.01 h 5618.93 ± 3.79 b R8 400.08 ± 0.01 a 394.54 ± 0.01 b 4.80 ± 0.10 i 1451.957 ± 5.77 f R9 300.97 ± 0.01 e 376.93 ± 0.02 c 17.19 ± 0.01 d 1507.33 ± 1.00 f R10 300.95 ± 0.03 e 270.68 ± 0.10 g 17.71 ± 0.02 c 4248.713 ± 1.01 e x In each column data represented as means ± Standard Deviations followed by different letters are statistically different at p<0.005 as calculated by Least Significant Different Test (LSD Test). Table 3. Comparisons of mineral matters and moisture percentage of ten different color rose accessions Rose Accessions Sodium (Na g/100g) Potassium (K g/100g) Calcium (Ca g/100g) Magnesium (Mg g/100g) Iron (Fe g/100g) Moisture (%) R1 0.079 ± 0.003 c x 1.288 ± 0.001 c 0.19 ± 0.000 a 0.102 ± 0.001 a 0.039 ± 0.002 c 84.81 ± 1.110 d R2 0.078 ± 0.002 c 1.408 ± 0.001 a 0.15 ± 0.002 f 0.102 ± 0.001 a 0.060 ± 0.002 b 82.50 ± 0.900 e R3 0.074 ± 0.004 cd 1.288 ± 0.001 g 0.19 ± 0.000 a 0.101 ± 0.001 a 0.055 ± 0.002 b 68.51 ± 0.510 g R4 0.072 ± 0.002 de 0.984 ± 0.001 f 0.19 ± 0.001 b 0.102 ± 0.001 a 0.090 ± 0.010 a 84.74 ± 0.200 d R5 0.092 ± 0.002 a 1.328 ± 0.001 b 0.15 ± 0.002 f 0.101 ± 0.001 a 0.037 ± 0.003 c 87.07 ± 1.010 ab R6 0.067 ± 0.002 ed 1.146 ± 0.001 f 0.14 ± 0.000 g 0.102 ± 0.001 a 0.024 ± 0.001 de 87.31 ± 0.100 a R7 0.065 ± 0.003 f 1.207 ± 0.001 e 0.14 ± 0.000 g 0.101 ± 0.001 a 0.020 ± 0.001 ef 81.06 ± 1.010 f R8 0.079 ± 0.004 c 1.247 ± 0.001 d 0.16 ± 0.001 e 0.101 ± 0.001 a 0.025 ± 0.001 de 85.63 ± 0.110 cd R9 0.085 ±0.002 b 1.288 ± 0.001 c 0.17 ± 0.000 d 0.102 ± 0.001 a 0.017 ± 0.001 f 85.38 ± 0.200 cd R10 0.062 ± 0.003 f 1.328 ± 0.001 b 0.18 ± 0.001 c 0.103 ± 0.001 a 0.028 ± 0.001 d 86.25 ± 0.120 bc x The column under each parameter, data were represented at Mean ± Standard Deviation and data with the various letters are differ significantly from each other (p<0.05). Table 4. The antinutritional components (Alkaloid, Phytate, Saponin and Tannin) of ten rose accessions Rose Accessions Dry weight basis Alkaloid (g/ 100 g) Phytate (g/ 100 g) Saponin (g/ 100 g) Tannin (mg TAE/ 100g) R1 9.52 ± 0.20 b x 0.26 ± 0.002 c 4.03 ± 0.07 d 164.54 ± 1.36 c R2 14.64 ± 0.21a 0.32 ± 0.010 b 8.00 ± 0.10 c 143.55 ± 0.69 g R3 6.16 ± 0.03 c 0.05 ± 0.002 f 12.00 ± 0.1 b 158.01 ± 1.74 d R4 2.77 ± 0.30 g 0.02 ± 0.001 g 8.00 ± 0.20 c 145.47 ± 1.18 g R5 5.52 ± 0.04 d 0.09 ± 0.002 d 8.00 ± 0.20 c 151.64 ± 1.89 e R6 4.04 ± 0.02 e 0.63 ± 0.002 a 14.00 ± 0.10 a 180.57 ± 2.94 b R7 0.24 ± 0.02 j 0.26 ± 0.001 c 12.00 ±0.10 b 198.05 ± 0.32 a R8 3.68 ± 0.20 f 0.02 ± 0.002 g 8.00 ± 0.10 c 180.09 ± 1.60 b R9 1.60 ± 0.10 h 0.07 ± 0.001 e 14.00 ± 0.10 a 148.37 ± 1.19 f R10 1.24 ± 0.03 i 0.02 ± 0.001 g 8.00 ± 0.20 c 143.97 ± 1.52 g x The column under data of each parameter, were represented at Mean ± Standard Deviation and data with the various letters are differ significantly from each other (p<0.05). Table 5. Molar ratio of phytates and tannins to minerals of ten rose accessions from analyzed data of antinutrients and minerals Rose accessions [PHT]: [Ca] [Ca]: [PHT] [PHT]: [Fe] [PHT]: [K] [Mg]: [PHT] [TNN]: [Fe] [PHT+TNN]: [Fe] R1 0.083 12.058 0.566 0.012 10.651 0.371 0.937 R2 0.129 7.734 0.453 0.013 8.654 0.210 0.663 R3 0.016 62.700 0.077 0.002 54.842 0.253 0.330 R4 0.006 156.750 0.019 0.001 138.462 0.142 0.161 R5 0.036 27.500 0.206 0.004 30.468 0.361 0.567 R6 0.273 3.667 2.227 0.033 4.396 0.662 2.889 R7 0.113 8.885 1.103 0.013 10.546 0.871 1.974 R8 0.008 132.000 0.068 0.001 137.104 0.634 0.702 R9 0.025 40.071 0.349 0.003 39.560 0.768 1.117 R10 0.007 148.500 0.061 0.001 139.819 0.452 0.513 Critical Value 6.0 favorable [59] <1 [60] - - - - Table 6. Phytochemical screening of ten rose accessions Rose genotypes Phytochemicals Steroids Coumarines Quinones Anthraquinone Phlobatanin R1 +ve +ve +ve +ve - R2 - - +ve - - R3 - +ve - +ve - R4 +ve +ve - - - R5 - - +ve - - R6 - - +ve +ve - R7 - - +ve +ve - R8 - - - - - R9 - +ve - - - R10 +ve +ve - - - Here +ve sign implies the presence of phytochemicals and – absence. Table 7. Flower cluster based on 25 variables in relation to color parameters and visual evidence among ten rose accessions Rose accession cluster Frequency (%) In relation to CIELAB Visual evident I (R3, R4, R5, R8) 4 (40) Light color >L* b*, h° III (R1, R2, R6, R7) 4 (40) Dark color >a*, C* Here, L* measures the lightness of color, a* ranged from green to red, b* blue to yellow, C* chroma of the color and h° represents the brightness of the rose petals. Additional Declarations No competing interests reported. Supplementary Files SuppleFigure1SciReRose17Jan24.docx Cite Share Download PDF Status: Published Journal Publication published 17 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 29 Jan, 2024 Editor assigned by journal 25 Jan, 2024 Editor invited by journal 24 Jan, 2024 Submission checks completed at journal 24 Jan, 2024 First submitted to journal 17 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3873110","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":269468381,"identity":"f7559698-2ed4-444e-aa32-6456a1163207","order_by":0,"name":"Sharmila Rani Mallick","email":"","orcid":"","institution":"Bangabandhu Sheikh Mujibur Rahman Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sharmila","middleName":"Rani","lastName":"Mallick","suffix":""},{"id":269468382,"identity":"66d5d50e-d6fa-4b0e-be0c-4a82760c0dc6","order_by":1,"name":"Jahidul Hassan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACxhkQWs4ALnSAgY2BhwgtxsRrYZCAUIkbiNbCPLv58ccfNXfSt/OfTvvws41Bju9GAtuDN/gcNueYmTTPsWe5O2fkbp7Z28ZgLHkjgd1wDl6/JJgxM7Adzt1wg3czA28b0IVAW6Txez/988cf/w6nG5w/u5nxbxtDPRFacgwkeNsOJxgcyN3MDLQlwYAILWXSvH2HDUF+YZY5J2E488zDdrx+MZyRvvnjj2+H5c35gQ57U2Yjz3c8+RjeEDNsQOWDoomxAYtCBJDHKzsKRsEoGAWjAAQAjhFRzMkbU98AAAAASUVORK5CYII=","orcid":"","institution":"Bangabandhu Sheikh Mujibur Rahman Agricultural University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jahidul","middleName":"","lastName":"Hassan","suffix":""},{"id":269468383,"identity":"0d22ae27-cfcd-4ce6-a7be-ae7729d75096","order_by":2,"name":"Md. Azizul Hoque","email":"","orcid":"","institution":"Bangabandhu Sheikh Mujibur Rahman Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Azizul","lastName":"Hoque","suffix":""},{"id":269468384,"identity":"6b6262c7-8982-44d1-a5f6-8de8900258e9","order_by":3,"name":"Hasina Sultana","email":"","orcid":"","institution":"Bangabandhu Sheikh Mujibur Rahman Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hasina","middleName":"","lastName":"Sultana","suffix":""},{"id":269468385,"identity":"09b3104b-bec2-4bbb-a3f3-03e0d94db6c4","order_by":4,"name":"Emrul Kayesh","email":"","orcid":"","institution":"Bangabandhu Sheikh Mujibur Rahman Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Emrul","middleName":"","lastName":"Kayesh","suffix":""},{"id":269468386,"identity":"8ade5e62-59b1-4fe5-9fcf-623ad19c62b6","order_by":5,"name":"Minhaz Ahmed","email":"","orcid":"","institution":"Bangabandhu Sheikh Mujibur Rahman Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minhaz","middleName":"","lastName":"Ahmed","suffix":""},{"id":269468387,"identity":"a1a9cdce-0510-49a1-bce1-1678cbee5ed0","order_by":6,"name":"Yukio Ozaki","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yukio","middleName":"","lastName":"Ozaki","suffix":""},{"id":269468388,"identity":"32a13159-f1bf-47a3-b5c8-ef64888dfe07","order_by":7,"name":"Manzer H. Siddiqui","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Manzer","middleName":"H.","lastName":"Siddiqui","suffix":""}],"badges":[],"createdAt":"2024-01-17 14:15:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3873110/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3873110/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-72424-w","type":"published","date":"2024-09-17T15:57:30+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50324850,"identity":"df876dd3-4b89-4022-a497-04a0ab083be8","added_by":"auto","created_at":"2024-01-29 19:12:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":246992,"visible":true,"origin":"","legend":"\u003cp\u003ep\u003csup\u003eH\u003c/sup\u003e and total soluble solids (TSS) (°Brix) of rose accessions\u003c/p\u003e\n\u003cp\u003e(Bars indicate ± SE and where statistically significant differences showed by different letters at P\u0026lt;0.05.)\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan241.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/e14b7d480198f13a752861d8.jpg"},{"id":50324853,"identity":"3a82c8d2-67fa-4554-9fa1-fe059920e3b2","added_by":"auto","created_at":"2024-01-29 19:12:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":217486,"visible":true,"origin":"","legend":"\u003cp\u003eTotal carotenoids (mg/100 g FW) and β-carotene (mg/100 g FW) of rose accessions\u003cstrong\u003e \u003c/strong\u003e(Bars indicate ± SE and where statistically significant differences showed by different letters at P\u0026lt;0.05.)\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan242.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/cd4e0a9671d51be8955dc055.jpg"},{"id":50325055,"identity":"b8a3f385-0bda-4660-829c-c3aeed8583c8","added_by":"auto","created_at":"2024-01-29 19:20:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":223564,"visible":true,"origin":"","legend":"\u003cp\u003eTotal anthocyanin (mg/100 g FW) and betacyanin (mg/100 g DW) of rose accessions (Different letters in bar statistically different from each other at P\u0026lt;0.05. also, Bars indicate ± SE.)\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan243.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/9d1196a4db7f8a3b7f8256ca.jpg"},{"id":50324846,"identity":"9f1e2a44-6b83-4384-bb7b-2600c08c6d3f","added_by":"auto","created_at":"2024-01-29 19:12:03","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":410905,"visible":true,"origin":"","legend":"\u003cp\u003eMethanolic extract color changes confirmation of the presence of antinutrients in rose accessions. A1) Steroids, A2) Coumarines, A3) Quinones, A4) Anthraquinone and A5) Phlobatanin.\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan244.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/34afd166ba2a8edf0897a98d.jpg"},{"id":50325501,"identity":"ff47606d-d264-46c1-b42d-7f20891847c1","added_by":"auto","created_at":"2024-01-29 19:28:03","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":371877,"visible":true,"origin":"","legend":"\u003cp\u003eA) Correlation matrix B) Heatmap with dendrogram cluster, in between and among colorimetric parameters, secondary metabolites and mineral contents (25 variables) of rose accessions. (Color Scale in the right side depicts that, the blue color indicating positive correlation and red color negative as color intensity increases the correlation increases and same as when decreases). [ L: (L*) Lightness, a: (a*) greenness (−) to redness (+), b: (b*) blue (−) to yellow (+), c:(c*) saturation of the color, h: (hº) huge angle, TSS: total soluble solids X-carn: total carotenoid content, VitA: β- carotene, AOA: anthocyanin, BTC: betacyanin, VitE: tocopherol, TPC: total phenol content, TFC: total flavonoid content, IC\u003csub\u003e50\u003c/sub\u003e- total antioxidant activity, Alk: Alkaloid, PHT: phytate, SPN: saponin, TNN: tannin, Na: sodium, K- potassium, Ca: Calcium, Mg: Magnesium, Fe: iron, MC: moisture content].\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan245.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/6f22b062d569a135fdc4a2e3.jpg"},{"id":50325057,"identity":"fca0dfbd-f2b7-4fd6-ba91-041c368cdea3","added_by":"auto","created_at":"2024-01-29 19:20:03","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":236739,"visible":true,"origin":"","legend":"\u003cp\u003eFactor loadings for the first two principal (Dim 1 and Dim 2) components of color parameters, secondary metabolites and mineral contents of rose accessions. [L: (L*) Lightness, a: (a*) greenness (−) to redness (+), b: (b*) blue (−) to yellow (+), c:(c*) saturation of the color, h: (hº) huge angle, TSS: total soluble solids X-carn: total carotenoid content, VitA: β- carotene, AOA: anthocyanin, BTC: betacyanin, VitE: tocopherol, TPC: total phenol content, TFC: total flavonoid content, IC\u003csub\u003e50\u003c/sub\u003e- total antioxidant activity, Alk: Alkaloid, PHT: phytate, SPN: saponin, TNN: tannin, Na: sodium, K- potassium, Ca: Calcium, Mg: Magnesium, Fe: iron, MC: moisture content.] \u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan246.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/2de804622834acf084b9e867.jpg"},{"id":50324852,"identity":"04a5a22b-5856-4b7f-beff-e40e4799792c","added_by":"auto","created_at":"2024-01-29 19:12:03","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":335259,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis (PCA) of color parameters, secondary metabolites and mineral contents of rose accessions. (A) PCA of variables showing their major contribution; (B) Biplot diagram of PCA illustrating the clustering of ten rose accessions towards the major contribution. [L: (L*) Lightness, a: (a*) greenness (−) to redness (+), b: (b*) blue (−) to yellow (+), c:(c*) saturation of the color, h: (hº) huge angle, TSS: total soluble solids X-carn: total carotenoid content, VitA: β- carotene, AOA: anthocyanin, BTC: betacyanin, VitE: tocopherol, TPC: total phenol content, TFC: total flavonoid content, IC\u003csub\u003e50\u003c/sub\u003e- total antioxidant activity, Alk: Alkaloid, PHT: phytate, SPN: saponin, TNN: tannin, Na: sodium, K- potassium, Ca: Calcium, Mg: Magnesium, Fe: iron, MC: moisture content]. \u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan247.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/bbbb2f06b54a1e62678b3b92.jpg"},{"id":50324847,"identity":"bf07ef06-1f79-4a22-aa54-19bac1376710","added_by":"auto","created_at":"2024-01-29 19:12:03","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":198456,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram cluster of ten rose accessions in associated with 25 dependent variables\u003c/p\u003e","description":"","filename":"Figures18SciReportRose17Jan248.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/17cd84c3495176e237ba51c8.jpg"},{"id":65104225,"identity":"be3e20ab-cf70-4c45-b29c-73f56013c605","added_by":"auto","created_at":"2024-09-23 16:12:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4315737,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/4319afe0-5cb2-4bb5-9afa-baf842ce16bc.pdf"},{"id":50324854,"identity":"92a11d01-6f87-4e96-ae70-59a322ff6fb8","added_by":"auto","created_at":"2024-01-29 19:12:03","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":330330,"visible":true,"origin":"","legend":"","description":"","filename":"SuppleFigure1SciReRose17Jan24.docx","url":"https://assets-eu.researchsquare.com/files/rs-3873110/v1/b61765c86ae7f0ce875a9aaf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Color, Proximate Composition, Bioactive Compounds and Antinutrient Profiling of Rose","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRose is a highly significant decorative plant in the commercial floriculture business, with great economic, cultural, and symbolic value. Rose flowers are vital in the floriculture sector of Bangladesh, serving as cut flowers for various festivals and religious events, as well as being used for potted plants and garden plants. Rose blossoms possess not only aesthetic qualities but also serve as a fundamental component in the production of industrial goods. Rose water, rose oil, rose concrete, dried petals, dried buds, and rose absolute are the primary derivatives of roses. These products find applications in various industries such as cosmetics, perfume manufacturing, food production, and pharmaceuticals for drug development on a global scale [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The rose flower is rich in antioxidant substances such as polyphenols, flavonoids, and phenolic acid, which have the capacity to capture free radicals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Bangladesh, there is a variety of rose called \u003cem\u003eRosa kordesii\u003c/em\u003e. The petals of this rose contain high levels of antioxidants such as terpenoids, flavonoids, saponins, tannins, and phenolic compounds, which are effective in scavenging free radicals [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Furthermore, rose petals possess antibacterial properties that prevent bacterial infection in the bladder. Additionally, rose petal tea, which is devoid of caffeine, can alleviate moderate sore throat due to its high antioxidant content [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The rose blossom can serve as an excellent resource for preparing functional food that promotes blood circulation, making it beneficial for individuals with high blood pressure. Moreover, rose petals are rich in vitamins, and when taken in an edible form, particularly vitamin C, they enhance the production of red blood cells [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePlants create and store a significant quantity of natural bio-active chemicals and secondary metabolites, such as anthocyanins, flavonoids, phenolic acids, and carotenoids, possess significant economic and commercial value. They contribute to the smells in flowers, provide color, and serve as key components in pharmaceutical products [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among the secondary metabolites, antioxidants have diverse and important impacts on health-related matters. During normal oxygen metabolism in the human body, reactive oxygen species (ROS) such as superoxide (O\u003csup\u003e2\u0026minus;\u003c/sup\u003e) and nitric oxide (NO) are naturally created as byproducts, along with highly reactive free radicals. Imbalance between the production and scavenging of reactive oxygen species (ROS) and free radicals can result in the presence of redox-active transition metal ions, such as iron (II) or copper. This imbalance leads to significant oxidative stress, causing the oxidation of cellular biomolecules such as DNA, lipids, and proteins. This process is associated with the development of chronic diseases including hyperlipidemia, hypertension, and cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In addition, the rose flower includes antioxidant components such as polyphenols, flavonoids, and phenolic acid, which are capable of capturing free radicals [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The antioxidant activities of rose hips [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and rose petals [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] are known to be linked to their chemical makeup and phenolic compounds. The focus lies on utilizing bioactive compounds derived from nature to eliminate these free radicals. Within this particular context, the rose flower possesses the potential to serve as a valuable biological resource for enhancing nutritional attributes, in addition to its elevated levels of antioxidants.\u003c/p\u003e \u003cp\u003eThe genus \u003cem\u003eRosa\u003c/em\u003e has a wide range of decorative plants, consisting of about 200 species and around 18,000 distinct cultivars of roses. These roses can be found in Asia, Europe, the Middle East, and North America [ 12, 13]. The history of rose evolution reveals key characteristics of rose variation resulting from interspecific hybridization and polyploidization. The rose, belonging to the genus \u003cem\u003eRosa\u003c/em\u003e, is a highly significant flower known for its exceptional fragrance, captivating colors, and rich nutritional characteristics. Roses exhibit a diverse range of biochemical activities due to their high levels of phenolic compounds, phenolic acid, flavonoids, carotenoids, and anthocyanins. These substances are the outcomes of several physiological processes in roses [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The wide variety of bioactive chemicals found in roses makes every component of the plant an essential ingredient in the creation of medications. The presence of these secondary metabolites in roses contributes to their therapeutic effects in treating various illnesses. Rose possesses antibacterial, antispasmodic, anti-inflammatory, astringent, analgesic, antidepressant, and diuretic effects [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Moreover, these biochemical qualities render roses valuable as raw materials for several sectors, cosmetics formulation, perfume production, and food coloring agents.\u003c/p\u003e \u003cp\u003eIn Bangladesh, around 10,000\u0026ndash;12,000 hectares of land are dedicated to flower cultivation, with roses being the dominant variety. This plays a crucial part in the economic growth of the flourishing floriculture industry in Bangladesh [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, there is a lack of official statistics regarding the production of rose flowers in our country. These bioactive chemicals, which are abundant in rose flowers, are exclusively utilized as fresh flowers for events and are not employed in industrial processing. Conversely, Bangladesh imports a variety of processed rose products annually. Golden Rose is a highly sought-after brand in our country that offers a range of processed rose products, including cosmetics and perfumes. Consumers of these processed products utilize them without being aware of their chemical composition. Scientists worldwide have conducted research on the chemical composition of diverse species within the genus \u003cem\u003eRosa\u003c/em\u003e. There is evidence that the bioactive secondary metabolites differ among different species of the \u003cem\u003eRosa\u003c/em\u003e genus. \u003cem\u003eRosa kordesii\u003c/em\u003e is a rose cultivar that is found in Bangladesh. The petals of this rose contain high levels of antioxidants such as terpenoids, flavonoids, saponins, tannins, and phenolic compounds, which are effective in scavenging free radicals [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. There is a limited amount of information on the heterogeneity of secondary metabolites in roses in Bangladesh due to the large number of rose cultivars present. This provides a significant opportunity to categorize the rose genotypes according to the diversity of secondary metabolites. Thus, it has been postulated that the rose genotypes may exhibit diversity in their response to the color, secondary metabolites, nutritional and antinutritional profiling. The purpose of this study was to sort out the variations in color, antinutrients, and secondary metabolites among several rose accessions. Additionally, to find the most promising rose accession that is rich in important secondary metabolites to use as a resource for commercial products and as a substitute for artificial food coloring.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eChemicals\u003c/h2\u003e \u003cp\u003eThe chemical and reagents used in this study such as hydrochloric acid (37%), sulphuric acid (95\u0026ndash;98%), sodium tungstate, manganese sulphate, sodium carbonate (99.5%), calcium nitrate (\u0026ge;\u0026thinsp;95%), potaddium iodide, folin-ciocalteu reagent, gallic acid (98.0%) acetone (99.0%), hexane, quercetin hydrate (\u0026ge;\u0026thinsp;95%), ammonium hydroxide, diethyl ether (99.5%), ethanol, methanol, ferric chloride (97%), ferric sulphate (399.88 anhydrous basis), phosphomolybdic acid (47.5%), aluminium chloride, chloroform (99.5%), 2,2-bipyridyl (99.5%), ammonium thiocyanate, tannic acid, dl-α-tocopherol acetate, potassium permanganate, DPPH (2,2-diphenyl-1-picrylhydrazyl), ascorbic acid, sodium acetate, acetic acid, n-butanol, sodium hydroxide of trace grade were purchased from Sigma Aldrich (St Louis, USA) and used to prepare working solutions as well as for laboratory analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Design\u003c/h2\u003e \u003cp\u003eThe experiment was conducted at the Laboratory of Horticulture, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Bangladesh using ten (10) rose accessions viz. R1, R2, R3, R4, R5, R6, R7, R8, R9 and R10 as plant materials (Supplementary Figure. 1). The flowers at full-bloom stage were collected from the rose garden of BSMRAU at early morning and brought to the laboratory as soon as possible. After that, the outermost, innermost and basal part of petals from each flower of an accession were discarded and only the middle portion of petals from each flower were used as study sample those were divided into two parts [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. One part of the selected petals was rapidly frozen and stored at \u0026minus;\u0026thinsp;40\u003csup\u003e◦\u003c/sup\u003eC until the extraction and analysis. While the rest part of fresh flowers was used to perform colorimetric analysis, pH measurement and drying purposes. For drying, the petals were spread on plastic net bags and shade dried for 1 week at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003csup\u003e◦\u003c/sup\u003eC. Then these shade dried petals were subjected for oven drying at 80\u003csup\u003e◦\u003c/sup\u003eC for 48 h until reaching a constant weight which were used for relative moisture content determination. Then dried petals were pulverized and preserved at \u0026minus;\u0026thinsp;40\u003csup\u003e◦\u003c/sup\u003eC for further analysis. The study was designed following randomized complete block design (RCBD) with three replications. The petals were collected from the six flowers of each accession and used in extraction preparation for qualitative and quantitative analyses of color, bioactive compounds and antinutrient properties. All analyses were conducted on the data of the three biological repeats, each with three technical repeats.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative analysis of proximate composition and secondary metabolites\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eColor\u003c/h2\u003e \u003cp\u003eThe colors of the studied rose flowers were measured using a bench-top spectrophotometer (CR-5; Konica Minolta). Nine petals from three flowers per accession were randomly selected, with care taken not to include petals from the outermost and innermost layers. The selected petals were then measured at their mid-point of the adaxial surface. The color change was determined as L* indicates the darkness and lightness of color and ranges from 0 to 100 (L*=0 means black and L*=100 means white). Color parameters a* and b* extend from \u0026minus;\u0026thinsp;60 to +\u0026thinsp;60 [\u0026minus;\u0026thinsp;a* = green and +\u0026thinsp;a* = red; \u0026minus; b* = blue and +\u0026thinsp;b* = yellow]. A white standard plate was used to calibrate the spectrometer before use to ensure the accuracy of the data. The hue angle (h\u0026deg;) is expressed in degrees from 0\u0026deg; to 360\u0026deg; (0\u0026deg; = red, 90\u0026deg; = yellow, 180\u0026deg; = green, and 360\u0026deg; = blue) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The hue angle and Chroma (C) were calculated by following equations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$h=\\text{a}\\text{r}\\text{c}\\text{t}\\text{a}\\text{n}\\left(\\frac{b*}{a*}\\right)\\dots \\dots \\dots \\dots \\dots \\dots \\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$C=\\sqrt{\\left( {a}^{*2}+ {b}^{*2}\\right)}\\dots \\dots \\dots \\dots \\dots .\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003epH\u003c/h2\u003e \u003cp\u003epH was determined by a digital pH meter (Digital Hanna pH Meter, Hand-Held, Pocket type pH Meter). To do so, petal extract was prepared by macerating the 0.5 g of petals in 5 mL of double distilled water and stirring for 2 h. The resulting aliquots were used for pH estimation and this quantification was repeated for three times for each accession [ 11].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTotal soluble solids (TSS) (\u0026deg;Brix)\u003c/h2\u003e \u003cp\u003eTotal soluble solids (TSS) of fresh rose petals were measured by hand refractometer (Model: Atago N1, Japan). Firstly, it was calibrated by placing one drop of distilled water on the prism and looking on the scale as it is showing the horizontal line between blue and white color in 0 level. Then, a drop of juice generated after squeezing 1 g of sample was placed on the prism of hand refractometer and the soluble solids content was recorded as degree Brix (\u0026deg;Brix) by observing the scale [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eTotal carotenoids Content (mg/100g)\u003c/h2\u003e \u003cp\u003eThe total carotenoid content of the rose petals was determined according to the method described by [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Rose petals of each accession (100 mg) was extracted overnight with 5 ml of 80% acetone and stored at 4\u0026deg;C in the dark for 24 h in the air tight test tube. After that, 1 mL supernatant was taken into 1 mL glass cuvette and absorbance was read in the spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan) at 663, 646, 470 nm corresponding to Chl a, Chl b and carotenoids, respectively where, the 80% acetone was used as blank. For quantification of total carotenoids, the following equations was applied [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\text{C}\\text{h}\\text{l} \\text{a} \\left({\\mu }\\text{g}/\\text{m}\\text{L}\\right)=12.21 \\left({A}_{663}\\right)\u0026ndash; 2.81 \\left({A}_{646}\\right)\\dots \\dots \\dots \\dots \\dots \\dots \\dots \\left(3\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$Chl b \\left({\\mu }\\text{g}/\\text{m}\\text{L}\\right)=20.13 \\left({A}_{646}\\right)\u0026ndash; 5.03 \\left({A}_{663}\\right)\\dots \\dots \\dots \\dots \\dots \\dots \\dots \\left(4\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e\n$$Carotenoid \\left({\\mu }\\text{g}/\\text{m}\\text{L}\\right)=\\frac{1000 \\left(A470\\right)-3.27 \\left(Chl a\\right)-104 \\left(Chl b\\right)}{229}\\dots \\dots .\\left(5\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eFor expressing the value in mg/100g the formula was used \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\mu }\\text{g}}{\\text{m}\\text{L}}\\times \\frac{V\\times 100}{1000\\times W}\\)\u003c/span\u003e\u003c/span\u003e;\u003c/p\u003e \u003cp\u003eWhere, V\u0026thinsp;=\u0026thinsp;Volume of acetone used (mL); and W\u0026thinsp;=\u0026thinsp;Weight of petal sample (g).\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eβ-carotene (mg/100g)\u003c/h2\u003e \u003cp\u003eFor analysis β-Carotene, 1 g fresh sample was blended thoroughly by mortar pestle and mixed with 10 ml acetone: hexane (4:6) solution. This sample was centrifuged at 6000 rpm for 15 min and the filtered with Whatman no. 1 filter paper. Then the optical density of the supernatant was measured at 663 nm, 645 nm, 505 nm and 453 nm by using a spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan) and β-Carotene was estimated by using following formula [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003cdiv id=\"Equf\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equf\" name=\"EquationSource\"\u003e\n$${\\beta }-\\text{c}\\text{a}\\text{r}\\text{o}\\text{t}\\text{e}\\text{n}\\text{e} \\left(\\frac{\\text{m}\\text{g}}{100\\text{g}}\\right)=0.216\\left({OD}_{663}\\right)+ 0.452\\left({OD}_{453}\\right)\u0026ndash; 1.22\\left({OD}_{645}\\right)\u0026ndash; 0.304\\left({OD}_{505}\\right)\\dots \\dots \\left(6\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere, the bold figure indicates optical density;\u003c/p\u003e \u003cp\u003e0.216; 0.452; 1.22; 0.304\u0026thinsp;=\u0026thinsp;Absorbance coefficient of the respective absorbance.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTotal anthocyanin content (AOA) (mg/100g)\u003c/h2\u003e \u003cp\u003eThe total anthocyanin content was analyzed by following the methods [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] with some modifications. Briefly, 1 g of fresh rose flower petals were collected and grinded. For anthocyanin extraction this petal pastes were transferred to a 5 mL extraction solution comprising methanol, 6M hydrochloric acid and water mixture (70:7:23 v/v). After that, the extract solution was incubated at 4\u003csup\u003e◦\u003c/sup\u003eC in dark for 24 h. Thereafter, 2 mL of the extracted solution was taken in centrifuge tube where 2 mL water and 2 mL chloroform were added in each of the tube and centrifuged at 5000 rpm for 15min. Then 3 mL supernatant was carried to a glass cuvette, and absorbance was measured at optical density (OD) of 530 nm by using a spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan). The total anthocyanin content was measurement by using the following formula-\u003cdiv id=\"Equg\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equg\" name=\"EquationSource\"\u003e\n$${Q}_{At}={A}_{530}\\times {M}^{-1}\\times 100\\dots \\dots \\dots \\dots \\dots \\dots \\left(7\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eQ\u003csub\u003eAt =\u003c/sub\u003e Amount of total Anthocyanin\u003c/p\u003e \u003cp\u003eA\u003csub\u003e530\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Absorbances at 530 nm\u003c/p\u003e \u003cp\u003eM\u0026thinsp;=\u0026thinsp;Fresh weight of the material used for extraction (g)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTotal betacyanin content (TBC) (mg/100g DW)\u003c/h2\u003e \u003cp\u003eBetacyanin content was determined using methanolic extract following the procedure of [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] with some modification. To do so, the petals of ten rose genotypes were sun dried and then powered through grinding machine. After that, 2 g of dried petal powder was taken in the ten separate test tubes where 15 ml methanol was added and kept in room temperature for 24 hours with intermittent shaking. Then filtered through Whatman No. 1 filter paper and the filtrated extraction sample was used for total betacyanin content (TBC) estimation. For TBC estimation, firstly 15 mL filtered extract was taken in the falcon tube and centrifuged at 6000 rpm for 15min. Then 2 mL of aliquot was diluted with 8 mL distilled water and absorbance reading was taken at 538 nm using spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD-303 UV, PD 33-3-OMS-101 b, Japan). Betacyanin content (TBC) was calculated by using the following formula-\u003cdiv id=\"Equh\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equh\" name=\"EquationSource\"\u003e\n$$\\text{B}\\text{e}\\text{t}\\text{a}\\text{c}\\text{y}\\text{a}\\text{n}\\text{i}\\text{n}\\text{s} \\text{c}\\text{o}\\text{n}\\text{t}\\text{e}\\text{n}\\text{t} \\left(\\frac{\\text{m}\\text{g}}{100}\\text{g} \\text{o}\\text{f} \\text{D}\\text{r}\\text{y} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}\\right)=\\frac{A\\times MW\\times V\\times DF\\times 100}{L\\times W\\times \\text{\u0026euro;}}\\dots \\dots \\dots \\dots \\dots \\left(8\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eA\u0026thinsp;=\u0026thinsp;Absorbance at 538 nm (lmax),\u003c/p\u003e \u003cp\u003eMW\u0026thinsp;=\u0026thinsp;Molecular weight of betanin (550g/mol)\u003c/p\u003e \u003cp\u003eDF\u0026thinsp;=\u0026thinsp;Dilution factor (1),\u003c/p\u003e \u003cp\u003eV\u0026thinsp;=\u0026thinsp;Volume of extract (mL)\u003c/p\u003e \u003cp\u003eL (path length)\u0026thinsp;=\u0026thinsp;1.0 cm\u003c/p\u003e \u003cp\u003eW\u0026thinsp;=\u0026thinsp;Sample weight (g)\u003c/p\u003e \u003cp\u003eFor betanin, \u0026euro; (mean molar absorptivity) = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(6.5 \\text{x} 104\\)\u003c/span\u003e\u003c/span\u003eL/mol cm in H\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTocopherol (VitE) (mg α-tocopherol/100 g DW)\u003c/h2\u003e \u003cp\u003eTocopherol content of the rose petals was analyzed by following the methods described by [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. 1 g of the sample was macerated in 20 ml of ethanol and filtered in a test tube. Thereafter, 1 ml of 0.2% ferric chloride ethanolic solution and 1 ml of 0.5% α -dipyridyl solution were added to 1 ml of the filtrate in a new test tube. The solution was further diluted with distilled water to 5 ml, and the absorbance was measured at 520 nm. To prepare the \u0026prop;-tocopherol standard, 100 mg/100 mL \u0026prop;-tocopherol was taken in absolute ethanol and four concentration 0.2, 0.4, 0.6, 0.8 and 1.0 mg/mL was made. After that, the standard curve was drawn and the concentration of Tocopherol content (Vit. E) equivalent (mg d-alpha-tocopherol/100 g) was calculated by using the following standard curve gradient:\u003cdiv id=\"Equi\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equi\" name=\"EquationSource\"\u003e\n$$Y = 1.9283\\text{x} \u0026ndash; 6.2896\\dots \\dots \\dots \\dots \\left(9\\right) {R}^{2} = 0.9661.$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003ey\u0026thinsp;=\u0026thinsp;Absorbance of samples\u003c/p\u003e \u003cp\u003ex\u0026thinsp;=\u0026thinsp;Tocopherol content (VitE)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTotal antioxidant activity (IC\u003csub\u003e50\u003c/sub\u003e) (\u0026micro;g/ mL FW)\u003c/h2\u003e \u003cp\u003eThe bioactive properties of rose like total antioxidant activity (TAA), total phenolic content (TPC) and total flavonoid content (TFC) were determined from methanolic extract of rose petals. For determination of these properties of roses the methanolic extract was prepared. Initially, 1 g of fresh rose petals sample were weighed with electronic precision balanced (Digiscales, Germany) and immersed in methanol (25 ml) in the test tube. Then, test tube was placed in a shaking water bath (JSR JSSB-50T) at 30\u0026deg;C for two and half h. Then the sample was centrifuged at 6000 rpm for 15 minutes and the supernatant was filtered with the help of funnel and Whatman filter paper (no. 42) and stored at 4\u0026deg;C in a refrigerator for further analysis.\u003c/p\u003e \u003cp\u003eAntioxidant activity of the rose petals was analyzed using DPPH radical scavenging assay (RSA). This assay is based on the measurement of the scavenging ability of antioxidants towards the stable radical. It was conducted according to the procedure of [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] with some modifications. For antioxidant assay, extracts of each rose petal samples and standard ascorbic acid solution (2 mg ascorbic acid dissolved in 2.5 ml distilled water and mix thoroughly) were prepared into several concentrations of 10, 20, 40, 80, 100 and 200 \u0026micro;g/ml and methanol were added to make the total volume 3 ml. Then 1 ml methanolic DPPH solution (0.004 mg DPPH was added with 100ml of methanol and mixed properly) was added to every test tube and the reaction mixture was kept at dark place for 30 minutes. Then, the reading was recorded at 517 nm against blank (methanol) by using spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan). Then, the radical scavenging activity was estimated by following formula-\u003cdiv id=\"Equj\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equj\" name=\"EquationSource\"\u003e\n$$\\% Radical scavenging activity=\\frac{{A}_{0}-{A}_{1}}{{A}_{0}}\\times 100\\dots \\dots \\dots \\dots \\dots .\\left(10\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eA\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Absorbance of control (3 ml methanol\u0026thinsp;+\u0026thinsp;1 ml methanolic DPPH solution)\u003c/p\u003e \u003cp\u003eA\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Absorbance of sample\u003c/p\u003e \u003cp\u003eInhibition concentration (IC\u003csub\u003e50\u003c/sub\u003e) was used to specify antioxidant capacity and was determined from the graph that plotted % radical scavenging activity against concentration of extract for standards and the test sample. The values of IC\u003csub\u003e50\u003c/sub\u003e used in this study were generated from the regression line graph that plotted by % radical scavenging activity of 4 concentrations of the standards (20, 40, 80, and 100 \u0026micro;g/ml) against 4 concentrations of each extract test sample. IC\u003csub\u003e50\u003c/sub\u003e means the concentration of sample which can scavenge 50% of DPPH free radical in DPPH free radical scavenging assay where lower IC\u003csub\u003e50\u003c/sub\u003e value corresponds with a higher antioxidant activity [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. IC\u003csub\u003e50\u003c/sub\u003e was calculated by using the formula as below -\u003cdiv id=\"Equk\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equk\" name=\"EquationSource\"\u003e\n$${IC}_{50}=\\frac{(y-b)}{a}\\dots \\dots \\dots \\dots \\dots \\dots \\dots . \\left(11\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003ey was replaced by 50 in the above equation; value of a and b was found from regression line plotted for each sample separately.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eTotal phenolic content (TPC) (mg GAE/ 100 g, FW)\u003c/h2\u003e \u003cp\u003eTotal phenolic content (TPC\u003cb\u003e)\u003c/b\u003e was analyzed by following the Folin-Ciocalteu procedure [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For TPC estimation, previously prepared methanol extract solution was used. For preparing stock solution, 5 ml of FC reagent was pipetted in a conical flask and added 45 ml of water. For preparing the 7.5% Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e, 7.5 g of sodium carbonate was added with 100 ml of distilled water in a 100 ml conical flask. For the preparation of gallic acid standard, 100 mg gallic acid powder weighed and diluted in 100 ml of distilled water. Then different concentrations (10, 20, 40, 60, 80, 100 \u0026micro;g/ml) of gallic acid were measured for preparing calibration curve. For the estimation of TPC, 0.5 ml of the sample extracts were taken in a test tube. FC reagent (2.5 ml) was added into the sample and the solution was incubated for 10 min. Then 2 ml of 7.5% sodium carbonate was mixed with the solution and the resultant mixture was incubated again at 30\u0026deg;C for 1 hour. The absorbance reading of the rose petal samples and the gallic acid standard were measured at 760 nm by using spectrophotometer (UV-VIS PD-303 UV Spectrophotometer; APEL Co.) against the methanol as blank. Standard curve was prepared using Microsoft excel using absorbance of gallic acid at the concentration of 10, 20, 40, 60, 80, 100 \u0026micro;g/ml. TPC readings were measured against the gallic acid standard calibration curves and expressed as mg of gallic acid equivalents per 100 g (dry weight) by following the equation as below -\u003cdiv id=\"Equl\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equl\" name=\"EquationSource\"\u003e\n$$\\text{y} = \\text{m}\\text{x} + \\text{c}\\dots \\dots \\dots \\dots .\\left(12\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003ey\u0026thinsp;=\u0026thinsp;Absorbance of samples\u003c/p\u003e \u003cp\u003ex\u0026thinsp;=\u0026thinsp;Total phenolic content (TPC); Value of c and m was found from the regression line plotted against the standard concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTotal flavonoid content (TFC) (mg QE/ 100 g, FW)\u003c/h2\u003e \u003cp\u003eAluminium chloride colorimertic method was followed for quantification of Total Flavonoid Content [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] using the previously prepared methanolic extract. For the measurement of TFC, quercetin was used to draw the standard calibration curve. For this, the stock solution of quercetin was prepared by dissolving 1 mg of quercetin in 10 ml of methanol. Then different concentrations (10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 \u0026micro;l) of quercetin were taken in Eppendorf tube and methanol was also added in it to make the final volume 1000 ul. After that, 100 \u0026micro;l of sample extract was taken into the Eppendorf tube and 400 \u0026micro;l of methanol was also added. Then each sample extract was separately mixed with 100 ul of 10% AlCl\u003csub\u003e3\u003c/sub\u003e (w/v) and 100 \u0026micro;l of 1M sodium acetate. It was then incubated at room temperature and was kept in dark condition for 40 min followed by the measurement of absorbance at 420 nm using spectrophotometer (UV-VIS PD-303 UV Spectrophotometer; APEL Co.) where the methanol was used as blank. The expected outcomes of TFC were calculated from the quercetin standard calibration curve (10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 \u0026micro;l)) and expressed as mg quercetin equivalent (QE)/100 g (FW) by following the equation as below-\u003cdiv id=\"Equm\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equm\" name=\"EquationSource\"\u003e\n$$Y=mx+c\\dots \\dots \\dots \\dots \\dots \\left(13\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003ey\u0026thinsp;=\u0026thinsp;Absorbance of samples\u003c/p\u003e \u003cp\u003ex\u0026thinsp;=\u0026thinsp;Total flavonoid content (TFC); Value of c and m was found from regression line plotted against the standard concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMinerals (g/100g DW) and Moisture content (MC) (%)\u003c/h2\u003e \u003cp\u003eMineral content (Na, K, Ca, Mg, Fe) was estimated following the procedure described by [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] with the help of device and method of an atomic absorption spectrophotometer (AAS). For preparing working sample, 0.5 g sample powder was taken in a 50 ml conical flask after that, 5ml of a mixture (5:1) of HNO\u003csub\u003e3\u003c/sub\u003e and HCIO\u003csub\u003e4\u003c/sub\u003e (Nitric perchloric acid) added and digested through a sand bath for 3\u0026ndash;4 h. Then the digested sample mixture was filtered with Whatman no. 42 (2.5\u0026micro;m particle retention) filter paper and final volume was made up to the final volume of 100 ml with distilled water in a 100 ml volumetric flask. For minerals quantification, 10 ml sample extract was shifted to 50 ml volumetric flask and final volume made 50 ml with distilled water. Afterwards, the intensity of Na, K, Ca, Mg and Fe was estimated through AAS (atomic absorption spectrophotometer; model-PinAAcle 900H; PerkinElmer). The following formula was used to quantify the concentration of minerals in rose petals.\u003cdiv id=\"Equn\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equn\" name=\"EquationSource\"\u003e\n$$\\% Mineral=\\frac{sample reading \\times Final volume \\times Dilution factor}{Sample weight}\\dots \\dots \\dots \\dots \\dots \\dots \\dots \\left(14\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe fresh rose flower petals were used for measurement of water content. Initially, the fresh weight of the sample recorded and thereafter, dried to a constant mass in an oven at a temperature of 100\u0026deg;C for 48 h. Then final weight was recorded and percent (%) moisture estimated on the basis of fresh and dry masses of rose petals in g by using the following equation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003cdiv id=\"Equo\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equo\" name=\"EquationSource\"\u003e\n$$\\% Moisture=\\frac{Initial weight \\left(g\\right)-Final weight \\left(g\\right)}{Initial Weight \\left(g\\right)}\\times 100\\dots \\dots \\dots \\dots \\dots \\left(15\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAlkaloid content (ALK) (g/100g)\u003c/h2\u003e \u003cp\u003eAlkaloid content of rose flowers was measured according to the methods described by [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. 0.5 g of the power sample was mixed with 200 ml of 10% acetic acid in ethanol. The mixture was covered with aluminium foil and incubated at room temperature for 4 h. After that, the mixture was filtered, and concentrated to about 1/4 of its original volume in a water bath. Thereafter, concentrated ammonium hydroxide was added drop by drop to the extract until complete precipitation was occurred. Then, the solution was allowed to stable, and the precipitate formed was washed with dilute ammonium hydroxide and then again filtered. The residue was oven dried at 40\u0026deg;C and weighed, and the alkaloid content was measured as:\u003cdiv id=\"Equp\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equp\" name=\"EquationSource\"\u003e\n$$\\% Alkaloid=\\frac{\\text{F}\\text{i}\\text{n}\\text{a}\\text{l} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{s}\\text{a}\\text{m}\\text{p}\\text{l}\\text{e}}{\\text{I}\\text{n}\\text{i}\\text{t}\\text{i}\\text{a}\\text{l} \\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{s}\\text{a}\\text{m}\\text{p}\\text{l}\\text{e}} \\times 100\\dots \\dots \\dots \\dots .\\left(16\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003ePhytate content (PHT) (g/100g)\u003c/h2\u003e \u003cp\u003eThe protocol described by [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] was used for estimation of Phytate content of rose accessions. Briefly, 2 g of the powder sample was soaked in 100 ml of 2% HCL for 3 h and filtered with Whatman no 1 filter paper. 25 ml of the filtrate was thereafter transferred into another conical flask and 5 ml of 0.3% ammonium thiocyanate solution along with 53.3 ml of distilled water was added to the filtrate. The solution was titrated against standard ferric chloride solution (0.001 95 g of iron per mL) until a reddish-brown color appearance which persisted for 5 min was noticed. Phytate content was calculated by the following ways:\u003cdiv id=\"Equq\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equq\" name=\"EquationSource\"\u003e\n$$\\% Phytate =Tirer value\\times 0.00195\\times 1.19\\times 100\\dots \\dots \\dots \\dots \\dots \\left(17\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eSaponin content (SPN) (g/100g)\u003c/h2\u003e \u003cp\u003eThe saponin content in rose petals was quantified by following the method described by [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. For this, 0.5 g of the powder sample was measured into a conical flask containing 50 ml of 20% ethanol. The solution was heated in a hot water bath for 4 h at 55\u0026deg;C and filtered and the filtrate preserved in a test tube, after that the residue was re-extracted again with 50 ml of 20% ethanol. Then both filtrates were mixed together and kept on the hot water bath at 90\u0026deg;C until it concentrated to 20 ml. The obtained solution was transferred into a 250 ml separating funnel containing 20 ml of diethyl ether. The aqueous layer was collected; 20 ml of n-butanol was added to it and then washed thrice with 10 ml of 5% sodium chloride meanwhile the ether layer was discarded. The mixture was oven dried at 40\u0026deg;C to constant weight, and the percentage saponin content of the sample was calculated as:\u003cdiv id=\"Equr\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equr\" name=\"EquationSource\"\u003e\n$$\\text{\\%} \\text{S}\\text{a}\\text{p}\\text{o}\\text{n}\\text{i}\\text{n} =\\frac{\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{f}\\text{i}\\text{n}\\text{a}\\text{l} \\text{f}\\text{i}\\text{l}\\text{t}\\text{r}\\text{a}\\text{t}\\text{e}}{\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t} \\text{o}\\text{f} \\text{s}\\text{a}\\text{m}\\text{p}\\text{l}\\text{e}} \\times 100\\dots \\dots \\dots \\dots \\left(18\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eTannin content (TNN) (mg TAE/100g)\u003c/h2\u003e \u003cp\u003eFolin-Denis method was followed to estimate the Tannin contents of the rose flower samples [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. For preparation of Folin-Denis reagent, 100 g of sodium tungstate (Na\u003csub\u003e2\u003c/sub\u003eWO\u003csub\u003e4\u003c/sub\u003e.2H\u003csub\u003e2\u003c/sub\u003eO) and 20 g of phosphomolybdic acid was dissolved to 750 ml of distilled water into which 50 ml of 85% phosphoric acid (H\u003csub\u003e3\u003c/sub\u003e PO\u003csub\u003e4\u003c/sub\u003e) was added. After that, the mixture was refluxed for 2h and then cooled to 25℃ and diluted to 1000 mL by adding distilled water. This solution stored at 4℃ and used for further analysis. Accurately weighed 0.5 g of the powdered sample was transferred to a 250 mL conical flask and 75mL of water was added into it. The flask was gently heated and boiled for 30 min, centrifuged at 2,000 rpm for 20 min and the supernatant collected in 100 mL volumetric flask and the volume made up of 100 mL with distilled water. Next, 1mL of the sample extract was transferred to a 100 mL volumetric flask containing 75mL water. 5mL of Folin-Denis\u0026rsquo;s reagent, 10mL of sodium carbonate solution (35 g of anhydrous sodium carbonate was added to 100 mL of water and dissolved at 70\u0026ndash;80℃ and then cooled it which turned into a clear liquid before use) were mixed and diluted to 100 mL with distilled water and preserved for 30 min. Then absorbance reading was taken at 700 nm with spectrophotometer (Model: APEL, UV- VIS Spectrophotometer, PD- 303 UV, PD 33-3-OMS-101 b, Japan). The tannin concentration was determined by the standard graph of tannic acid solution at the concentration of 0-100 mg/mL. The concentration of Tannin content was calculated by using the following equation:\u003cdiv id=\"Equs\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equs\" name=\"EquationSource\"\u003e\n$$Y=0.0051x+0.0789\\dots \\dots \\dots \\dots \\left(18\\right), {R}^{2}=0.9638$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eAntinutrient to mineral molar ratios\u003c/h2\u003e \u003cp\u003eThe bioaccessibility of minerals could be explained by the determination of molar ratios of antinutrient and minerals. The molar ratios were calculated by using the following formula [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003cdiv id=\"Equt\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equt\" name=\"EquationSource\"\u003e\n$$Antinutrient:Mineral Molar Ratio=\\frac{Conc. of antrinutrient\\frac{mg}{100g}/Molar mass of antrinutrient\\frac{g}{mol}}{Conc. of mineral\\frac{mg}{100g}/Molar mass of mineral\\frac{g}{mol}}\\dots \\dots \\dots \\dots \\left(19\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere the molar mass of Phytate- 660 g/mol; Tannin- 636.5 g/mol; K (Potassium)-39.0983g/mol; Ca (Calcium)- 40 g/mol; Mg (Magnesium)- 24.31 g/mol and Fe (Iron)- 56g/mol.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eAntinutritional phytochemical screening through qualitative analysis\u003c/h2\u003e \u003cp\u003eThe analytical observation was done to notify the presence and identification of bioactive compounds in the methanolic extracts of rose petals powder following the standard procedures as reported in the previous report of [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. For testing the presence of steroids, coumarins, quinones, anthraquinones and phlobatanins, 2 mL of methanolic extracts were taken every time. After that, methanolic extracts were added to equal quantity of chloroform and 0.5ml of concentrated sulfuric acid was also added drop by drop and formation of brown ring confirmed the presence of phytosteroids. Addition of equal volume of 10% NaOH solution and development of yellow color solution indicates the presence of coumarin in the rose genotypes and addition of 1 mL 2% HCl and development of red color precipitates indicates the presence of anthraquinones. Again, treating the methanolic extract with 1.5 mL of conc. H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e and the formation of red to blue color confirmed the presence of quinones whereas addition of 0.5mL of 10% ammonia and formation of pink color precipitates indicates the presence of phlobatanin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eAll the recorded data on flower color parameters, secondary metabolites and antinutrient properties represent the mean values of three technical replications and were subjected to compare by two-way analysis of variance (ANOVA). The mean separation was done following least significant difference (LSD) test at 5% level of significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, correlation matrix, cluster analysis, were performed to note the interrelationship among the studied variables and the rose accessions of the study. Afterwards, principal component analysis (PCA) was performed to show the patterns of all the measured correlated color parameters, secondary metabolites and minerals in the reduced dimensions of newly obtained factors those were denoted as- Dim1 (PC1), Dim2 (PC2). The dendrogram cluster analysis was performed to sort out the most promising rose accession according to the factor loadings and the contributions of each of the studied dependent variables using different packages (agricolae, facatominer, factoextra, ggplot2, corrplot) of R program (version 4.1.2). All data were reported as the mean value of three determinations\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eColor\u003c/h2\u003e \u003cp\u003eThe CIELAB system, established by the International Commission on Illumination, was employed to analyze the color of different rose accessions as indicated in Table\u0026nbsp;1. The system utilizes L* to quantify the lightness of the color, ranging from white to black. Additionally, a* and b* indicate distinct color directions, with a* ranging from green to red and b* ranging from blue to yellow. Lastly, c* is used to measure the chroma of the color. Table\u0026nbsp;1 shows that the R4 accession had the lightest L* value (79.16), which was similar to the R10 accession (76.06) for white and yellow flowers, respectively. The R3 accession had a L* value of 63.55, followed by R8 with a value of 61.08. The darkest L* value of 18.99 was observed in the R7 accession, corresponding to blackish red roses. In terms of other color coordinates, the a* value varied from 48.49 to -3.66. The highest value of 48.49 was observed in R6, which represents red color flowers. This value was similar to R2 (46.90, hot pink color) and R1 (44.85, orange color), but significantly different from the other rose accessions. The lowest value of -3.66, indicating white color flowers, was recorded in the R4 accession. In addition, the values of b* for the other color directions varied from positive to negative, ranging from 60.13 to -3.66. This corresponds to the color spectrum from yellow to purple in a flower. The highest b* value, 60.13, was obtained from R10, which showed a statistically significant difference compared to all other rose accessions. Following R10, R9 had a b* value of 26.07, while R5 had the lowest value of -3.67. The rose accession R10 exhibited the maximum color saturation, with a C* value of 60.19, which was statistically distinct from the other rose accessions. Nevertheless, R6 exhibited the second highest value (50.68), which was statistically comparable to R1 (47.77) and R2 (46.91), while R4 had the lowest vividness of color (13.35). However, the decrease in values of a* and the increase in values of b* are associated with the perception of darkness and lightness. Similarly, the highest luminosity (h\u0026deg;) was observed at R10 (87.56), indicating a brightening of rose petals close to a yellow color. This was followed by R9 (47.13), R7 (19.89), R1 (19.19), and R6 (16.86). The last three values were statistically similar to each other but different from the rest. Therefore, the values of the parameters accurately depicted the color patterns of the flower, aligning with the visual observations of the rose accessions' blossom color.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003epH and TSS (\u0026deg;Brix)\u003c/h2\u003e \u003cp\u003eA notable fluctuation in pH and total soluble solids (TSS) (\u0026deg;Brix) among the 10 rose accessions was demonstrated in Fig.\u0026nbsp;1. The acidity of rose petals varied among different accessions, with the lowest pH recorded in R1 (4.50), which was comparable to R7 (4.50), R6 (4.57), and R2 (4.70). On the other hand, the highest pH was observed in R4 (5.60), which was similar to R8 (5.50) and R9 (5.40), and statistically similar to R3 and R5 (5.30). Conversely, the highest total soluble solids (TSS) level was found in R1 (9.40 \u0026deg;Brix), while the lowest was seen in R3 (7.10 \u0026deg;Brix).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTotal Carotenoids and β-carotene (mg/100g)\u003c/h3\u003e\n\u003cp\u003eThere was a significant statistical variation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the total carotenoids and β-carotene concentration noticed across ten different rose accessions (Fig.\u0026nbsp;2). The rose accessions R10 had the highest total carotenoids content at 108 mg/100 g fresh weight (FW). The second highest was R1 at 72 mg/100 g FW, followed by R9 at 67 mg/100 g FW. The lowest carotenoids content was found in R4 at 6 mg/100 g FW. All rose accessions were statistically distinct from each other. From a β-carotene perspective, the highest concentration of β-carotene was found in R10 (47 mg/100 g FW), followed by R9 (42 mg/100 g FW), and R1 (39 mg/100 g FW). These values were statistically distinct from each other. Furthermore, all the remaining accessions exhibited statistically equivalent levels of accumulation, which were below 5 mg. However, the lowest accumulation was recorded in the rose accessions R3, with a value of 1 mg per 100 g. Notably, the rose accessions R5 and R7 did not exhibit any detectable β-carotene content.\u003c/p\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eTotal Anthocyanin and Betacyanin (mg/100 g)\u003c/h2\u003e \u003cp\u003eThe column graph (Fig.\u0026nbsp;3) clearly demonstrates that there were statistically significant variations in the overall anthocyanin and betacyanin content among the 10 rose accessions. In terms of total anthocyanin content, the accession R7 accumulated the maximum quantity of anthocyanin (196 mg/ 100g FW), which was comparable to R6 (191 mg/ 100g FW), R2 (189 mg/ 100g FW), and R1 (183 mg/ 100g FW). On the other hand, R4 accumulated the lowest amount (3 mg/ 100g FW). The total anthocyanin content varied between 196 and 3 mg per 100 g FW.\u003c/p\u003e \u003cp\u003eConversely, the betacyanin content was determined based on the dry weight of the samples. The highest amount of betacyanin was found in the R7, with a concentration of 22.63 mg per 100g of dry weight (DW) which is equivalent to the amount of anthocyanin. However, it also indicates more than double the concentrations than that of the R1 (10.43 mg/ 100g) and R6 (9.91 mg/ 100g) accession while the lowest betacyanin content was observed in R10.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTocopherol Content (Vit.E)\u003c/b\u003e \u003cb\u003e(mg/ 100 g DW)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe tocopherol content in the rose accessions examined ranged from 400.08 to 300.95 mg/100 g DW. The highest concentration was found in the R8 accession (400.08 mg/100 g DW), which was significantly different from the other accessions. However, the second greatest value was achieved from R6 (400.05 mg/ 100 g DW), which was equal to the value acquired from R1 (400.05 mg/ 100 g DW). On the other hand, the lowest value was seen in R10 (300.95 mg/ 100 g DW), which was statistically close to the value in R9 (300.97 mg/ 100 g DW) (Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe total phenolic content (TPC)\u003c/b\u003e \u003cb\u003e(mg GAE/ 100 g, FW)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;2 demonstrates that the various rose petal extracts exhibited significant variance in their total phenolic content (TPC). The R6 accession exhibited the maximum concentration of TPC 533.18 mg GAE/ 100 g, FW, whereas the lowest concentration was observed in the R4 accession, with a value of 241.87 mg GAE/ 100 g, FW.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe total flavonoid content (TFC)\u003c/b\u003e \u003cb\u003e(mg QE/ 100 g, FW)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eUpon examining Table\u0026nbsp;2, it becomes evident that all the rose accessions exhibited significant variations in the accumulation of flavonoid contents (TFC). The highest level of flavonoid content was observed in R3 (27.77 mg QE/ 100 g, FW), whereas the lowest concentration was reported in R1 (0.76 mg QE/ 100 g, FW).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003eTotal Antioxidant Activity (IC\u003csub\u003e50\u003c/sub\u003e) (\u0026micro;g/ mL FW)\u003c/h2\u003e \u003cp\u003eThe antioxidant activity of rose petals was assessed by determining the IC\u003csub\u003e50\u003c/sub\u003e value, which represents the concentration of the sample needed to block 50% of DPPH free radicals. Thus, in the DPPH experiment, greater IC\u003csub\u003e50\u003c/sub\u003e values indicate lesser antioxidant activity, and vice versa. Table\u0026nbsp;2 clearly shows that the IC\u003csub\u003e50\u003c/sub\u003e values of 10 rose extracts had a substantial impact on their ability to scavenge free radicals (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The R1 rose accession had the most potent antioxidant activity, as evidenced by its lowest IC\u003csub\u003e50\u003c/sub\u003e value of 82.60 \u0026micro;g/mL FW. Among the other rose accessions, R5, R6, R7, R8, R9, and R10 exhibited an IC\u003csub\u003e50\u003c/sub\u003e value greater than 250 \u0026micro;g/mL FW, indicating their inactivity in free radical scavenging action. Regrettably, the antioxidant activity of two rose accessions, R3 and R4, was not observed in this experiment.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section3\"\u003e \u003ch2\u003eMinerals (g/100g) and Moisture content (%)\u003c/h2\u003e \u003cp\u003eThe results from Table\u0026nbsp;3 clearly demonstrate that the accumulation of mineral elements such as sodium (Na), potassium (K), calcium (Ca), iron (Fe), and moisture content varied significantly among the ten rose accessions, with the exception of magnesium (Mg). Moreover, within the composition of these minerals, the concentration of potassium was particularly notable in the rose accessions. The sodium (Na) concentration in the petals of ten different rose accessions varied significantly. The highest accumulation of Na was seen in accession R5 (0.092 g/100g DW), followed by accession R9 (0.085 g/100g). Simultaneously, the lowest recorded value was obtained from R10 (0.062 g/100g), which was exactly the same as R7 (0.065 g/100g). The analysis found that the potassium level varied between 1.408 and 0.984 g/100g where the maximum concentration was seen in R2, while the lowest value was found in R4, which was statistically similar to R6. The average value of calcium content differed across the roses where the R1 and R3 had the highest accumulation of Ca at a concentration of 0.19 g/100g, whereas R6 and R7 had the lowest concentration at 0.14 g/100g. The accumulation of Fe, varied greatly, ranging from 0.090 to 0.017 g/100g. The top accumulator was R4, while R9 was the lowest accumulator.\u003c/p\u003e \u003cp\u003eMeanwhile, the rose petals exhibited a significant variation in moisture content, with the greatest reported in the rose accession R6 (87.31%). This value was statistically equivalent to that of R5 (87.07%) and the water content in R3 was significantly low, measuring at 68.51%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section3\"\u003e \u003ch2\u003eAntinutrient properties (g/ 100 g DW)\u003c/h2\u003e \u003cp\u003eUpon examining Table\u0026nbsp;4, it is evident that there were notable variations in the levels of alkaloids, phytate, saponin, and tannins among the rose accessions. The alkaloid content of rose petals in this investigation varied from 1.24 to 14.64 g/100 g DW (Table\u0026nbsp;4). Of the ten rose accessions, R2 had the greatest alkaloid content accumulator (14.64 g/ 100 g DW), followed by R1 (9.52 g/ 100 g DW), and R10 (1.24 g/ 100 g DW) had the lowest. Of these three metrics, the phytate content indicated a very small quantity of present (Table\u0026nbsp;4). However, R6 differs greatly from the others due to its higher amount (0.63 g/100 g DW). The majority of the saponin (14 g/100 g DW) was found in the rose petals of R6 and R9, with R3 and R7 following closely behind (12 g/100 g DW), and R1 containing the least (4.03 g/100 g DW). The data displayed in Table\u0026nbsp;4 indicates that there was a notable variation in the tannin content among the ten rose accessions, ranging from 143.55 to 198.05 mg TAE/ 100g DW. The highest tannin conserver in this testing was R7 (198.05 mg TAE/ 100g DW), followed by R6 (180.57 mg TAE/ 100g DW). Conversely, the R2 accession had the least amount of tannin (143.55 mg TAE/ 100g DW), and it was statistically comparable to the R10 and R4 containers (143.97 and 145.47 mg TAE/ 100g DW, respectively).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eAntinutrients to molar ratios\u003c/h3\u003e\n\u003cp\u003eThe molar ratios of [PHT]: [Ca], [Ca]: [PHT], [PHT]: [Fe], [PHT]: [K], [Mg]: [PHT], [TNN]: [Fe], and [PHT\u0026thinsp;+\u0026thinsp;TNN]: [Fe] were determined based on the analyzed data of antinutrients and minerals of rose accessions and presented in Table\u0026nbsp;5. Out of the ten rose accessions, all except for R6 exhibited [PHT]: [Ca] ratios below the crucial value of 0.24 and [Ca]: [PHT] ratios above the critical value of 0.6. The rose accession R6, however, had [PHT]: [Ca] and [Ca]: [PHT] ratios of 0.273 and 3.667, respectively. Based on the table 5, it is evident that the rose accessions R6 and R7 exhibited a [PHT]: [Fe] ratio that exceeded the threshold value of 1, indicating a lower bioavailability of iron. On the other hand, R4 had the lowest ratio of 0.019, suggesting the highest absorption of iron in nutrition. Regarding [PHT], the 10 rose accessions exhibited variances in [K] molar ratios, which varied from 0.001 to 0.033. Table\u0026nbsp;5 shows that the molar ratios of [Mg]: [PHT] in rose accessions varied from 4.396 to 139.819. Among them, R10, R4, R8, R3, and R9 had larger amounts of magnesium, with molar ratios of 139.819, 138.462, 137.104, 54.842, and 39.560, respectively. The molar ratios of [TNN]: [Fe] were adjusted within the range of 0.142 in R4 to 0.871 in R7 rose accessions. The molar ratio of [Fe] for [PHT\u0026thinsp;+\u0026thinsp;TNN] ranged from 0.161 in R4 to 2.884 in R6, with R6 having the greatest ratio.\u003c/p\u003e\n\u003ch3\u003eQualitative Assessment of bioactive compounds\u003c/h3\u003e\n\u003cp\u003eThe phytochemical screening tests largely determined the presence or absence of steroids, coumarins, quinones, anthraquinones, and phlobatannins in the ten rose genotypes. This was done using color reactions, as shown in Table\u0026nbsp;6. The presence of phytosteroids, coumarin anthraquinones, quinones, and phlobatanin was confirmed through various chemical reactions, including the formation of a brown ring, the development of a yellow-colored solution, the precipitation of red-colored solids, a color change from red to blue, and the precipitation of pink-colored solids, respectively (Fig.\u0026nbsp;4. A1, A2, A3, A4, A5). The analysis of the ten rose accessions revealed the presence of steroids in R1, R4, and R10 accessions, coumarines in R1, R3, R4, R9, and R10 accessions, quinones in R1, R2, R6, and R7 accessions, anthraquinone in R1, R3, R6, and R7 accessions, and phlobatanin exclusively in the R6 rose accession.\u003c/p\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation coefficient analysis\u003c/h2\u003e \u003cp\u003eThe Pearson correlation coefficient was employed to evaluate the intra and interrelationships among the 25 variables under investigation. The correlation matrix visually represents the degree of both positive and negative association between the colorimetric parameters, secondary metabolites, and mineral contents (Fig.\u0026nbsp;5A). In the event of a positive correlation, an increase in one variable will result in a corresponding increase in another variable, whereas a negative correlation indicates that an increase in one variable will lead to a decrease in another one. The circles in Fig.\u0026nbsp;5, colored in blue and red, indicate positive and negative correlations, respectively. The intensity of the color represents the strength of the correlation between the variables. Vacant cells indicate an inconsequential association at a 5% level of significance. The Pearson's correlation coefficient and correlation matrix revealed a significant link between colorimetric features and secondary metabolites, ranging from moderately strong to extremely strong. However, this correlation was not observed with mineral matters. Among these factors, a significant positive correlation (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.95) was observed between the total carotenoid and β-carotene content. This suggests that an increase in total carotenoid content is associated with a corresponding increase in the concentration of β-carotene. The total carotenoid concentration exhibited a significant positive correlation with h\u0026deg; and b* (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.71, 0.79). Moreover, there was a significant and positive relationship between the β-carotene content and both the b* value and hue angle, with R\u003csup\u003e2\u003c/sup\u003e values of 0.84 and 0.79, respectively. Conversely, the overall amount of anthocyanin was highly and positively associated with a*, phytate, and betacyanin (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.89, 0.86, and 70), whereas it exhibited a substantial negative association with L* and pH (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.914, 0.819). Furthermore, there was a significant positive relationship between the betacyanin and tannin concentration (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.75), as well as a substantial negative association with L* (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.874). In addition, there was a significant positive association between the phytate content and a* (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.89), as well as a negative link with L* (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.77). Additional observations revealed a negative correlation between the minerals (Na, K, Ca, Mg, and Fe) and the levels of anthocyanin, betacyanin, and phytate. It was observed that the rose blossom became darker in color as the levels of anthocyanin, betacyanin, and phytate increased. Conversely, the flower's color faded with an increase in mineral content. From an antioxidant perspective, the IC\u003csub\u003e50\u003c/sub\u003e value demonstrated a significant inverse relationship with Ca (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.85), similar to the correlation between TSS and pH (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.82) (Fig.\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eA heatmap with a dendrogram was created using 25 factors to cluster ten rose accessions for the purpose of cluster analysis (Fig.\u0026nbsp;5B). The analysis showed that the 25 factors were divided into two primary clusters, each making a major contribution to grouping the ten rose accessions into three clusters. Regarding the variable cluster, Cluster I consist of the elements Na, K, Alk, TFC, L, pH, Ca, Fe, whereas Cluster II comprises the remaining 17 variables h, b, VitA, X. carn, MMC, Mg, VitE, PHT, an AOA, BTC, TNN, TPC, SPN, IC50, C, and TSS. Cluster I accounted for 32% of the variables, whereas Cluster II accounted for 68%. Once again, cluster II was subdivided into two subclusters, which were then further fragmented into smaller clusters (Fig.\u0026nbsp;5B). On the other hand, these 25 factors categorized the ten rose accessions into three clusters. Cluster I consisted of R4, R3, R5, and R8. Cluster II included R10 and R9, while cluster III comprised R6, R7, R1, and R2.\u003c/p\u003e \u003cdiv id=\"Sec36\" class=\"Section3\"\u003e \u003ch2\u003ePrincipal component analysis (PCA)\u003c/h2\u003e \u003cp\u003eThe previous section findings revealed that the variables made a substantial contribution to the classification of the rose accessions. The PCA was conducted to ensure consistency of the data and assess the extent of variation among variables. Principal Component Analysis (PCA) is a form of multivariate analysis that transforms large, intricate datasets with associated variables into groupings in order to uncover the most influential characteristics. The PCA biplot diagram visually represented the relationships, both similarities and dissimilarities, among the various parameters in Fig.\u0026nbsp;7A and 7B. The diagram specifically focused on the first dimension (PC1) and the second dimension (PC2); the initial two principal components (PCA), account for 54.6% of the overall data variance. Specifically, PC 1 and PC 2 individually account for 32.4% and 22.2% of the variance, respectively. The factor loadings and scores for the first two principal components (Dim 1 and Dim 2) of color parameters, secondary metabolites, and mineral matters of ten rose accessions (Fig.\u0026nbsp;6) indicated that a positive score on Dim1 was associated with L, b, pH, Vit A, X.Carn, TCP, Na, Ca, Mg, and Fe (ranging from 0.05 to 0.3), while all the other variables had moderate to low negative scores (ranging from \u0026minus;\u0026thinsp;0.04 to -0.25). Conversely, eleven variables, namely pH, Vit E, TFC, AOA, BTC, Na, Fe, PHT, ALK, SPN, and TNN, exhibited a positive score in Dim 2. In contrast, the variables L, b, c, h, MC, TSS, VitA, X. carn, TCP, IC50 K, Ca, and Mg contributed negatively to the score in Dim 2.\u003c/p\u003e \u003cp\u003eUpon examination of Fig.\u0026nbsp;7A and 7B, it is clear that the variables X. carn, b, VitA, h, c, a, L, pH, TSS, PHT, BTC, and AOA had the greatest influence on the selection of rose accessions. Consequently, the 10 different rose genotypes were clearly separated into three groups as a result of a positive association in both directions. In this case, the two accessions R9 (salmon color) and R10 (yellow color) that have the greatest influence on the variables may be easily differentiated from the others due to their strong positive correlation with both dimensions of the biplot. However, the biplot displays both the observations and variables in a given orientation along the PC axis (Dim1 and Dim2) concurrently. The orientation of the variable arrows signifies the direction in which the contribution of the related variable experiences the greatest rise, while the length of the arrows represents the magnitude of the change in that direction.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eCluster analysis\u003c/h2\u003e \u003cp\u003eCluster analysis was conducted using the K-means algorithm to group ten rose accessions based on 25 quantitative attributes. To do this, a dendrogram was constructed and then divided at a rescaled distance of 7.5. This division resulted in the formation of three separate clusters of roses, each exhibiting significant similarities in terms of the studied attributes (Fig.\u0026nbsp;8). Table\u0026nbsp;7 provides a compilation of three clusters of rose accessions in relevance with the CIELAB system and their visual evidence. The cluster I consisted of four rose accessions (R3, R4, R5, R8), which accounted for 40% of the plant population, just like cluster III (R1, R2, R6, R7). Cluster II consisted of R9 and R10 rose genotypes, which accounted for 20% of the population. Considering the contribution of rose accession in the CIELAB it has been revealed that the cluster I with the highest contribution of L* and the lowest b* value and which visualized the light color flower, cluster II with the highest contribution of b*, h\u0026deg; and cluster III with the highest contribution of a*, C* and appeared as bright color and dark color, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe rose is a type of flower that is both edible and decorative. It is known for containing secondary metabolites, which have both nutritional and medicinal characteristics. Additionally, roses can be used as natural food coloring agents. The color of flowers is a prominent characteristic that is highly valued by customers and also holds ecological significance. The composition of floral color is influenced by various elements such as secondary metabolites in cell pigments, the shape of epidermal cells [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], the pH of cell sap [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and mineral content [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The most influential factor among them is the buildup of a certain type of pigments [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The genus \u003cem\u003eRosa\u003c/em\u003e, which includes roses, has a remarkable range of characteristics such as a delightful scent, distinctive shape, and a wide array of colors. Nevertheless, there is still a lack of documentation regarding the measurement of color in rose accessions and its correlation with secondary metabolites, metal ions, and antinutrient characteristics. Additionally, the categorization of rose accessions based on these features has not been recorded.\u003c/p\u003e \u003cp\u003eCurrently, the CIELAB system is widely utilized for the identification, measurement, and description of color in ornamental plants [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The L* value in this system represents the rise in lightness from white to black, while the b* value represents the increase in color from blue to yellow. Conversely, the a* value represents the reduction in color from green to red. In the investigation, it was found that the flower with the highest L* value was R4, which had a white color. The red color rose with the maximum a* value was R6. Additionally, the flower with the highest b* value was R10, which corresponded to a yellow color. These findings were congruent with the visually seen colors of the flowers (Table\u0026nbsp;7). Prior studies have indicated that anthocyanins contribute to the development of red to purple hues, while carotenoids are responsible for the generation of yellow to red colors in ornamental plants [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In other study it was noticed that in potted multiflora chrysanthemum, only the b* value showed a high positive connection with total carotenoids (r\u0026thinsp;=\u0026thinsp;0.881, P\u0026lt;0.01) and lutein (r\u0026thinsp;=\u0026thinsp;0.804, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Nevertheless, the results of this investigation have also demonstrated a resemblance to the previous study, indicating that R10, a yellow-colored rose sample, exhibited the highest concentration of total carotenoids. This concentration was found to be positively associated with β-carotene, and both of these compounds displayed a significant positive connection with h\u0026deg; and b*. Nevertheless, the β-carotene content could not be detected in the R5 (Purple color) and R7 (Blackish red color) rose accessions throughout this research study. However, R6 (red color), have demonstrated a high capacity for accumulating anthocyanin, betacyanin, tannin, and saponin. Anthocyanins are a group of secondary metabolites that are derived from flavonoids. Betacyanins, on the other hand, are nitrogen-containing compounds present in a small number of plant families. Both anthocyanins and betacyanins contribute to the yellow to red colors observed in plants [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The rose accessions in this experiment have demonstrated the presence of betacyanin content, which might potentially be utilized by the food sector as a natural food coloring ingredient. The correlation study has demonstrated a strong positive association between the total anthocyanin and a* value, as indicated by the multivariate analyses as well. Additionally, betacyanin and phytate also showed high correlations with these two variables. Anthocyanin, betacyanin, and phytate have been found to have a negative connection with mineral content. Mineral substances contribute to the development of flower color by combining with flavonoids to create supramolecular pigments known as metal complexes. Our investigation has revealed a weak to negative association between the total flavonoid levels and mineral matters, anthocyanin, a*, and betacyanin. Previous work has indicated that flavonoids possess colorless structures that alter the intensity of yellow pigmentation in plants [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The current study found that the rose accession R3, which is baby pink in color, has the largest accumulation of total flavonoids. Additionally, it was observed that there is a weakly positive link between the levels of total flavonoids and the L* and b* values.\u003c/p\u003e \u003cp\u003eWhen considering food, it is important to take into account the antinutritional properties of substances such as tannin, saponin, alkaloid, and phytate. Recent data has demonstrated that the ingestion of these secondary metabolites can have beneficial impacts on human health, contingent upon the dietary pattern and composition. Tannin, saponin, phytate, and alkaloid are polyphenols that possess antioxidant characteristics, which enhance the human body's immune system [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. According to the author [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], tannins in food can create complex compounds with proteins, carbohydrates, and specific minerals. However, the development of these complexes depends on factors such as temperature, pH, and concentration, which must be suitable. Furthermore, the oral administration of tannin resulted in a roughly 50% decrease in toxicity compared to the rectal administration of tannic acid [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Phytate is classified as a nutraceutical and is deemed generally recognized as safe (GRAS) by the Food and Drug Administration (FDA) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Plant-derived alkaloids serve as a valuable source for the development of medicines and pharmaceuticals. It has demonstrated antiviral, antibacterial, antiproliferative, and insecticidal characteristics [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In addition, both secondary metabolites and other compounds such as total carotenoids, total phenols, total flavonoids, and vitamin E play a crucial role as antioxidants [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study examined the link between the overall antioxidant activity (measured by the IC\u003csub\u003e50\u003c/sub\u003e value) of several rose accessions and their secondary metabolites. The results showed a positive correlation between the IC\u003csub\u003e50\u003c/sub\u003e value and the presence of alkaloids, tannin, saponin, phytate, total phenols, anthocyanin, and betacyanin. In addition, there is a clear negative association between phytate and the levels of calcium (Ca), magnesium (Mg), and iron (Fe), as indicated by the IC\u003csub\u003e50\u003c/sub\u003e value. Excessive intake of phytate has been demonstrated to decrease the absorption of minerals, particularly calcium, magnesium, iron, and zinc. Therefore, it is advisable to consume 100\u0026ndash;400 mg/day of phytate [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The presence of antinutrients such as tannin, polyphenols, and phytate in plant materials significantly decreases the bioavailability of minerals, including calcium (Ca), iron (Fe) [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], magnesium (Mg), and potassium (K) [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The molar ratios of [PHT]: [Ca] are less than 0.24 [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], while the ratios of [Ca]: [PHT] are larger than 6.0. These ratios indicate a positive effect on the bioavailability of Ca [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The phytate concentrations in all rose accessions showed a positive effect on Ca absorption, except for R6. The phytate level in plant-based nutrition is widely recognized as the primary factor that hinders the absorption of iron. In order to mitigate the negative impacts of phytates, it is recommended that the phytate content in the food material be kept below 0.1g per 100g [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Furthermore, a molar ratio of [PHT]: [Fe]\u0026thinsp;\u0026lt;\u0026thinsp;1 serves as an indication of favorable iron bioavailability [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. However, the presence of phytate in R6 and R7 rose accessions might hinder the absorption of Fe. The solubility of magnesium and phytate complexes is directly correlated with the pH of the solution. The magnesium complex with a molar ratio of 6:1 with [PHT] demonstrated that it is highly soluble at pH levels below 5.0. However, as the pH increases, the solubility of magnesium decreases fast and becomes insoluble at pH levels over 8.0 [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The cell sap of the ten rose accessions exhibited an acidic pH ranging from 4.50 to 5.60. This indicates that the presence of phytate concentrations in these rose petals\u0026rsquo; products would not hinder the bioavailability of Mg. The impact of tannin on the absorption of iron has been studied in common beans, with the ratios of tannin to iron ([TNN]: [Fe]) ranging from 0 to 65.7, and the ratios of phytate plus tannin to iron ([PHT\u0026thinsp;+\u0026thinsp;TNN]: [Fe]) ranging from 24 to 90.1 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition, the principal component analysis (PCA) and K-means cluster analysis were used to categories the 10 various color rose accessions based on the linked variables. The cluster-I comprises the following rose accessions: R4 (white color), R3 (baby pink color), R8 (multicolor), and R5 (purple color). Cluster II consists of R10 (yellow color) and R9 (salmon color), which is characterized by high levels of total carotenoids and β-carotene concentration. The cluster II comprises R1 (orange color), R2 (pink color), R6 (red color), and R7 (blackish red color), mostly due to their high levels of anthocyanin, total phenol content, tannin, TSS, phytate and betacyanin. This discovery demonstrates a resemblance to the findings of [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], who showed that out of ten different colored roses, the red ones contained the highest amount of anthocyanins and overall phenol levels. The co-pigmentations of anthocyanins in orange color to blackish red color flowers are regulated by the presence of phenolic acids residues and sugar content. These compounds help stabilize the color in various regions of the plants. Based on the present study's results, it is evident that the rose accessions R9, R10 (cluster II) and R1, R2, R6, R7 (cluster III) are particularly rich in secondary metabolites. These compounds have potential use in the food colors, cosmetics, and pharmaceutical industries. A study conducted on 30 flower species [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] found that the rose species had the highest levels of total phenol content, antioxidant activity, and acted as a significant source of bioactive chemicals.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results indicate significant variation among the ten rose accessions in terms of the secondary metabolites screened (steroids, coumarins, quinones, anthraquinone, and phlobatanin) as well as the quantified compounds (total carotenoid, β-carotene content, anthocyanin, betacyanin, tocopherol, phenol contents, flavonoid contents, alkaloid, phytate, saponin, and tannin contents) and their antioxidant properties. The R6 rose accession (red color flower) exhibited the highest levels of anthocyanin, total phenol, phytate, saponin, and colorimetric parameter a*. The R7 accession (blackish red color) had the highest levels of betacyanin, tannin, and pH. The R10 accessions (yellow color flower) showed the highest levels of L*, b*, C*, h\u0026deg;, total carotenoid content, and β-carotene. Lastly, the R1 accession had the highest free radical scavenging potentials and TSS. The findings of principal component analysis (PCA) showed that the variables strongly influenced the grouping of the ten examined rose accessions into three clusters. Cluster I consisted of R3, R4, R5, and R8, Cluster II consisted of R9 and R10, and Cluster III consisted of R1, R2, R6, and R7. Therefore, the rose accessions categorized in cluster III and cluster II are suggested as promising sources of secondary metabolites for future application in the food sector, cosmetics, fragrance, and pharmaceuticals.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS R Mallick and J Hassan conceived the idea of the study, design and conduct the experiment. S R Mallick, J Hassan wrote the manuscript. S R Mallick, J Hassan, M A Hoque, E Kayesh, H Sultana and M Ahmed contributed in sample collection, preparation and laboratory analyses. J Hassan and S R Mallick analyze the data and made necessary interpretation. M A Hoque, E Kayesh, H Sultana, M Ahmed, M H Siddiqui and Y Ozaki reviewed and edited the manuscript for further improvement. All authors have read, edited the manuscript and approved it for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are highly grateful to the research management wing (RMW), Bangabandhu Sheikh Mujibur Rahman Agricultural University for the financial and logistic supports to carry out this research work under the innovation project (ID: 008). The authors are also extending their gratitude to the Post-Harvest Division of Bangladesh Agricultural Research Institute and Department of Agro-Processing and Soil Science for providing their lab facilities to carry out the analyses. Our sincere appreciation also goes to the Researchers Supporting Project number (RSP2024R347), King Saud University, Riyadh, Saudi Arabia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration on plant handling with the relevant guidelines and regulations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study utilized Rose (\u003cem\u003eRosa sp.\u003c/em\u003e) flowers as the plant material. The many cultivated rose accessions were obtained from the flower garden of Bangabandhu Sheikh Mujibur Rahman Agricultural University, located in Gazipur-1706, Bangladesh. The rose accessions are cultivated and conserved in the university\u0026apos;s flower garden for utilization in research endeavors. The field and laboratory investigation were conducted using established growth protocols and adhering to the scientific ethics rules and regulations for handling plants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be made available from the corresponding author J. Hassan on request. From the link below:\u003c/p\u003e\n\u003cp\u003ehttps://drive.google.com/file/d/12I1yTNQJ6ZWnXHI7wqRImJK6gKokUHX/view?usp=sharing\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEl-Sayed S, Abdel-H., Salih, A. B., Salman. M. S. 2013. Characterization of the Phytochemical Constituents of Taif Rose and Its Antioxidant and Anticancer Activities. 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Industrial Crops and Products, 111, 430\u0026ndash;445.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Colorimetric parameters of 10 rose accessions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"928\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.081984897518877%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose Accessions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434735706580367%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFlower Color\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.426105717367854%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.057173678532905%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eColor Parameters\u003csup\u003ex\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.19774011299435%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eL*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.19774011299435%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ea*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.06779661016949%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eb*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.19774011299435%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.338983050847457%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eh\u0026deg;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eOrange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.00 \u0026plusmn; 5.89 d\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e44.85 \u0026plusmn; 1.61 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e15.86 \u0026plusmn; 6.11 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e47.77 \u0026plusmn; 3.44 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.19 \u0026plusmn; 6.31 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eHot Pink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e45.26 \u0026plusmn; 0.36 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e46.90 \u0026plusmn; 1.98 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.88 \u0026plusmn; 0.76 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e46.91 \u0026plusmn; 1.98 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.07 \u0026plusmn; 0.91 de\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eBaby Pink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e63.55 \u0026plusmn; 2.53 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e16.72 \u0026plusmn; 3.82 de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.66 \u0026plusmn; 1.78 i\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e16.84 \u0026plusmn; 3.95 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e-4.98 \u0026plusmn; 5.14 \u0026nbsp;e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e79.16 \u0026plusmn; 1.53 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.66 \u0026plusmn; 0.27 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.84 \u0026plusmn; 0.38 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e13.35 \u0026plusmn; 0.39 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e-74.09 \u0026plusmn; 1.14 g\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003ePurple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e58.28 \u0026plusmn; 2.21 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.34 \u0026plusmn; 1.53 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.67 \u0026plusmn; 0.59 j\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.80 \u0026plusmn; 1.62 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e-14.32 \u0026plusmn; 0.73 f\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eRed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e30.21 \u0026plusmn; 2.10 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e48.49 \u0026plusmn; 2.44 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.65 \u0026plusmn; 1.34 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e50.68 \u0026plusmn;2.05 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e16.86 \u0026plusmn; 2.15 \u0026nbsp;c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eBlackish Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e18.99 \u0026plusmn; 0.37 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e28.54 \u0026plusmn; 1.07 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e10.33 \u0026plusmn; 0.56 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e30.35 \u0026plusmn; 1.19 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.89 \u0026plusmn; 0.35 \u0026nbsp;c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eMulticolor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.08 \u0026plusmn; 3.07 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e18.39 \u0026plusmn; 8.99 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.61 \u0026plusmn; 1.42 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e18.44 \u0026plusmn; 8.97 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.35 \u0026plusmn; 4.87 \u0026nbsp; d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eSalmon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e64.20 \u0026plusmn; 0.32 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e24.26 \u0026plusmn; 3.08 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e26.07 \u0026plusmn; 1.92 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e35.73 \u0026plusmn; 0.73 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e47.13 \u0026plusmn; 5.72 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.095032397408207%\" valign=\"top\"\u003e\n \u003cp\u003eR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.44708423326134%\" valign=\"top\"\u003e\n \u003cp\u003eYellow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e76.06 \u0026plusmn; 0.90 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.56 \u0026plusmn; 0.30 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.578833693304535%\" valign=\"bottom\"\u003e\n \u003cp\u003e60.13 \u0026plusmn; 1.20 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.442764578833692%\" valign=\"bottom\"\u003e\n \u003cp\u003e60.19 \u0026plusmn; 1.19 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.550755939524837%\" valign=\"bottom\"\u003e\n \u003cp\u003e87.56 \u0026plusmn; 0.33 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ex\u003c/sup\u003e Color parameters base on CIE (International Commission on Illumination) system for color representation: (L*: Lightness, a*: greenness (\u0026minus;) to redness (+), b*: blue (\u0026minus;) to yellow (+), c*: saturation of the color, h\u0026deg;: huge angle). \u003csup\u003ey\u0026nbsp;\u003c/sup\u003eSimilar letters in each column indicate insignificant differences determined using a least Significant Difference test (P\u0026lt;0.01); \u0026plusmn;SD\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e The bioactive components and Total Antioxidant Activity of ten rose accessions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose Accessions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTocopherol (mg \u0026alpha;-tocopherol/100 g DW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Phenolic Content (mg GAE/ 100 g, FW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Flavonoid Content (mg QE/ 100 g, FW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Antioxidant Activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIC\u003csub\u003e50\u003c/sub\u003e (\u0026micro;g/ mL FW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.05 \u0026plusmn; 0.01 b\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e303.07 \u0026plusmn; 1.00 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.76 \u0026plusmn; 0.03 \u0026nbsp; j\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e82.60 \u0026plusmn; 1.00 \u0026nbsp; \u0026nbsp; \u0026nbsp; g\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.01 \u0026plusmn; 0.01 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e293.41 \u0026plusmn; 2.10 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.21 \u0026plusmn; 0.11 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e5536.48 \u0026plusmn; 1.16 \u0026nbsp; c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.01 \u0026plusmn; 0.01 cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e229.20 \u0026plusmn; 1.00 j\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e27.77 \u0026plusmn; 0.21 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.01 \u0026plusmn; 0.01 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e241.87 \u0026plusmn; 0.15 i\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.16 \u0026plusmn; 0.01 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.01 \u0026plusmn; 0.02 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e256.48 \u0026plusmn; 1.00 h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.56 \u0026plusmn; 0.01 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e5302.24 \u0026plusmn; 2.00 \u0026nbsp; d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.05 \u0026plusmn; 0.02 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e533.18 \u0026plusmn; 1.01 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.39 \u0026plusmn; 0.03 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e5777.53 \u0026plusmn; 5.77 \u0026nbsp; a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.04 \u0026plusmn; 0.20 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e371.63 \u0026plusmn; 0.56 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e7.15 \u0026plusmn; 0.01 \u0026nbsp; h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e5618.93 \u0026plusmn; 3.79 \u0026nbsp; b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e400.08 \u0026plusmn; 0.01 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e394.54 \u0026plusmn; 0.01 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.80 \u0026plusmn; 0.10 \u0026nbsp; i\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e1451.957 \u0026plusmn; 5.77 f\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e300.97 \u0026plusmn; 0.01 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e376.93 \u0026plusmn; 0.02 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e17.19 \u0026plusmn; 0.01 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e1507.33 \u0026plusmn; 1.00 \u0026nbsp; f\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.686468646864686%\" valign=\"top\"\u003e\n \u003cp\u003eR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.94719471947195%\" valign=\"bottom\"\u003e\n \u003cp\u003e300.95 \u0026plusmn; 0.03 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.801980198019802%\" valign=\"bottom\"\u003e\n \u003cp\u003e270.68 \u0026plusmn; 0.10 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.792079207920793%\" valign=\"bottom\"\u003e\n \u003cp\u003e17.71 \u0026plusmn; 0.02 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"bottom\"\u003e\n \u003cp\u003e4248.713 \u0026plusmn; 1.01 e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ex\u003c/sup\u003e In each column data represented as means \u0026plusmn; Standard Deviations followed by different letters are statistically different at p\u0026lt;0.005 as calculated by Least Significant Different Test (LSD Test).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Comparisons of mineral matters and moisture percentage of ten different color rose accessions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"930\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose Accessions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSodium (Na g/100g)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePotassium (K g/100g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalcium\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Ca g/100g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMagnesium (Mg g/100g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIron (Fe g/100g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoisture (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.079 \u0026plusmn; 0.003 c\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.288 \u0026plusmn; 0.001 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.19 \u0026plusmn; 0.000 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.102 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.039 \u0026plusmn; 0.002 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e84.81 \u0026plusmn; 1.110 d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.078 \u0026plusmn; 0.002 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.408 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.15 \u0026plusmn; 0.002 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.102 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.060 \u0026plusmn; 0.002 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e82.50 \u0026plusmn; 0.900 e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.074 \u0026plusmn; 0.004 cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.288 \u0026plusmn; 0.001 g\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.19 \u0026plusmn; 0.000 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.055 \u0026plusmn; 0.002 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e68.51 \u0026plusmn; 0.510 g\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.072 \u0026plusmn; 0.002 de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.984 \u0026plusmn; 0.001 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.19 \u0026plusmn; 0.001 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.102 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.090 \u0026plusmn; 0.010 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e84.74 \u0026plusmn; 0.200 d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.092 \u0026plusmn; 0.002 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.328 \u0026plusmn; 0.001 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.15 \u0026plusmn; 0.002 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.037 \u0026plusmn; 0.003 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e87.07 \u0026plusmn; 1.010 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.067 \u0026plusmn; 0.002 ed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.146 \u0026plusmn; 0.001 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.14 \u0026plusmn; 0.000 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.102 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.024 \u0026plusmn; 0.001 de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e87.31 \u0026plusmn; 0.100 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.065 \u0026plusmn; 0.003 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.207 \u0026plusmn; 0.001 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.14 \u0026plusmn; 0.000 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.020 \u0026plusmn; 0.001 ef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e81.06 \u0026plusmn; 1.010 f\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.079 \u0026plusmn; 0.004 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.247 \u0026plusmn; 0.001 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.16 \u0026plusmn; 0.001 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.025 \u0026plusmn; 0.001 de\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e85.63 \u0026plusmn; 0.110 cd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.085 \u0026plusmn;0.002 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.288 \u0026plusmn; 0.001 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.17 \u0026plusmn; 0.000 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.102 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.017 \u0026plusmn; 0.001 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e85.38 \u0026plusmn; 0.200 cd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.32258064516129%\" valign=\"top\"\u003e\n \u003cp\u003eR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.483870967741936%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.062 \u0026plusmn; 0.003 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.548387096774194%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.328 \u0026plusmn; 0.001 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.193548387096774%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.18 \u0026plusmn; 0.001 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.774193548387096%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.103 \u0026plusmn; 0.001 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.028 \u0026plusmn; 0.001 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.838709677419354%\" valign=\"bottom\"\u003e\n \u003cp\u003e86.25 \u0026plusmn; 0.120 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ex\u003c/sup\u003e The column under each parameter, data were represented at Mean \u0026plusmn; Standard Deviation and data with the various letters are differ significantly from each other (p\u0026lt;0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e The antinutritional components (Alkaloid, Phytate, Saponin and Tannin) of ten rose accessions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose Accessions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.82828282828282%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDry weight basis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.170731707317074%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlkaloid\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/ 100 g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.390243902439025%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhytate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/ 100 g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.390243902439025%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSaponin\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/ 100 g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.048780487804876%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTannin\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mg TAE/ 100g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.52 \u0026plusmn; 0.20 b\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.26 \u0026plusmn; 0.002 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.03 \u0026plusmn; 0.07 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e164.54 \u0026plusmn; 1.36 c \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.64 \u0026plusmn; 0.21a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.32 \u0026plusmn; 0.010 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.00 \u0026plusmn; 0.10 \u0026nbsp;c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e143.55 \u0026plusmn; 0.69 g\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e6.16 \u0026plusmn; 0.03 \u0026nbsp;c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.05 \u0026plusmn; 0.002 f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.00 \u0026plusmn; 0.1 \u0026nbsp;b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e158.01 \u0026plusmn; 1.74 d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.77 \u0026plusmn; 0.30 \u0026nbsp;g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.02 \u0026plusmn; 0.001 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.00 \u0026plusmn; 0.20 \u0026nbsp;c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e145.47 \u0026plusmn; 1.18 g\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.52 \u0026plusmn; 0.04 \u0026nbsp;d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.09 \u0026plusmn; 0.002 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.00 \u0026plusmn; 0.20 \u0026nbsp;c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e151.64 \u0026plusmn; 1.89 e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.04 \u0026plusmn; 0.02 \u0026nbsp;e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.63 \u0026plusmn; 0.002 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.00 \u0026plusmn; 0.10 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e180.57 \u0026plusmn; 2.94 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.24 \u0026plusmn; 0.02 \u0026nbsp; j\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.26 \u0026plusmn; 0.001 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.00 \u0026plusmn;0.10 \u0026nbsp;b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e198.05 \u0026plusmn; 0.32 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.68 \u0026plusmn; 0.20 \u0026nbsp;f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.02 \u0026plusmn; 0.002 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.00 \u0026plusmn; 0.10 \u0026nbsp; c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e180.09 \u0026plusmn; 1.60 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.60 \u0026plusmn; 0.10 \u0026nbsp;h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.07 \u0026plusmn; 0.001 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.00 \u0026plusmn; 0.10 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e148.37 \u0026plusmn; 1.19 f\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.171717171717173%\" valign=\"top\"\u003e\n \u003cp\u003eR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.24 \u0026plusmn; 0.03 \u0026nbsp;i\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.02 \u0026plusmn; 0.001 g\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.00 \u0026plusmn; 0.20 \u0026nbsp; c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.232323232323232%\" valign=\"bottom\"\u003e\n \u003cp\u003e143.97 \u0026plusmn; 1.52 g\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ex\u0026nbsp;\u003c/sup\u003eThe column under data of each parameter, were represented at Mean \u0026plusmn; Standard Deviation and data with the various letters are differ significantly from each other (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Molar ratio of phytates and tannins to minerals of ten rose accessions from analyzed data of antinutrients and minerals \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose accessions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[PHT]: [Ca]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[Ca]: [PHT]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[PHT]: [Fe]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[PHT]: [K]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[Mg]: [PHT]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[TNN]: [Fe]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e[PHT+TNN]: [Fe]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e12.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e10.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e7.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e8.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e62.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e54.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e156.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e138.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e27.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e30.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e3.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e2.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e4.396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e2.889\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e8.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e1.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e10.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e1.974\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e132.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e137.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e40.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e39.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e1.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e148.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e139.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003eCritical Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e\u0026lt;0.24 [57, 58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e\u0026gt;6.0 favorable\u003c/p\u003e\n \u003cp\u003e[59]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.851485148514852%\"\u003e\n \u003cp\u003e\u0026lt;1 [60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.900990099009901%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.881188118811881%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u003c/strong\u003e Phytochemical screening of ten rose accessions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.447495961227787%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose genotypes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.55250403877221%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhytochemicals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.470588235294116%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSteroids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.823529411764707%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoumarines\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.294117647058824%\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuinones\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnthraquinone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhlobatanin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.475728155339805%\"\u003e\n \u003cp\u003eR10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.592233009708737%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.533980582524272%\"\u003e\n \u003cp\u003e+ve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.62135922330097%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.50485436893204%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.271844660194176%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHere +ve sign implies the presence of phytochemicals and \u0026ndash; absence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u0026nbsp;\u003c/strong\u003eFlower cluster based on 25 variables in relation to color parameters and visual evidence among ten rose accessions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"798\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.30075187969925%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRose accession cluster\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn relation to CIELAB\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.3609022556391%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVisual evident\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.30075187969925%\"\u003e\n \u003cp\u003e\u003cstrong\u003eI\u0026nbsp;\u003c/strong\u003e(R3, R4, R5, R8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003e4 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\n \u003cp\u003eLight color\u003c/p\u003e\n \u003cp\u003e\u0026gt;L*\u003c/p\u003e\n \u003cp\u003e\u0026lt; b*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.3609022556391%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cimg width=\"76\" 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\" 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\" 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\" 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\" 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\" 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\" 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/ZJByxnWZA+p0bqUqa1itt9Cqq8EFZeM9GkFt2tBxRWr+ISYAU1hU5mw/Mh6Vh51bhny9obCp9sqi6qEHWPuli5jTRF9YR9yZOV/jU/+n/C6M1LaN5/iyce2WzqcI+vQrwa8WffUTU45Na/XIeoFu3wcQc/6asguxSa8e2AVPEdJH7UP79P0+PjY4WdE0w+/uiuvkmtWzoF96LaBJzTKPTPBngZt39H3zD7gzDbo2jpk7KHNk9+kmm/Ivb+jOvLQ8siId2YReGwZfOUQdYGJv6CknzOz59TcN7VIF7j4M8/cj0qkT8rkHUqhCQsESxg+9QPCNrDB2r/BNfqlBavgk4xLm5jFnBlnFZt0TEjfR0YC1V3VoEw/thq4q9l7V6NfRH/0vvGcGm5d2n1fmTb6yKIPpZX366PyG4+f31Wck3bZ0Wacmgec2oYdWgeCfJzUJiwq4c4xESeOIVe84m/h9ZeJzwbUaEumQfa0LI/0d4bsXIS8a5JdYKs5r+Ys5MkZPXPVhDuljF2x9Vu24K9b+SxrEAdE9Q6sfU7N+UsSttMihk2/ynwnpLfckquUEOlAaQbd/i3ugYgAgWgWlXp9S2nmsT0IoiOboGtC6gUh+QwTB8cTUvL/CaxY0va4Cq67iGweViTO6HBnscmexb2qpDSEBa8W2oouOe974vtdesGsAWdCCd0lpt8pqrdkQF/SokxLO4yImV+5J16YB0/eNe35Ves7MrZd7/FzB5X4RzdeOmtH3vin34Mb7XoKbbfk1pTxC5LIQ0PvC1TECTL01DXiyDXymJy8oYhbcwwBXX7lVzugTJw2FFDT2xn5XY+REQhpTCozf0SXlHsY2DxlDPDCm9SijSuhx2Qcx2Tsex9bL6gCT0BNiNsAK1oUR/4w9D9V5EygdLIeI4LuIzKk7uU8FokRvT2M1WmTlZ1SQC4ruC/Kue/qMI8gaeyDT6hpK6rEOXm3bbeYQ27BWUDpmCZ1hJDpUz5mGdqmRctF3LcKBzfoYdNmMXk7rilHhGzAmXUTHlg/q+g6JePwe0DOlqEnvCiMNUP+tib9q4jB2/uarx6qNCpL18g9rJS7mSsi8kncqE/S/I2ozoI+c07GCfThmip5QsxqTgp1ZO2/bsRetQsEubpsH5T9D7W3MrhdtwJFYgoluxNhI3hiE9S6zKr+ahj6VJZ06l194JK0aR22bRm4pE0/tw4G6X6JitvR5K4rEmfFnQ5N/c/M/DdksBMS9h0i2u0PdF6JqHwS1ZiUcFpVJS8r4ZcU0OCzTXX6tiEXkhHU9pCE1ZaF97Cs+4qZ/xYmekCH+16DauFZpoRPFXIzVu6AOagOUulTafJbZVaLImXCIWLbJXnW0GtEEfuNV3ZgGX7iEH1sFrSqzjo19VuRw11hYg812Ruq5KGHpoMPjaal7ddVCOtq5H0Tr009xrYe68CEv6SMX9eibVv5TsmiZ+TdQaCuWwZtWAR1aTCndQOGA19KISNZeV/VaHkI9N9YhPKr67eJe65I/6jK3mTk7JOyV+zCl0x8APyn1MkzauQZFfyYnOuQlCOg7ykx48Q9/ggVdeIQcmApOEUGH6PCjgENrfwOrXxPXEJ/Z+QcOIYPS9uu6jFWdKmrBswda8GcNm3TIWrdOcOKX4uJfoFQJesychFaDIQyLludnOsc/lzaKXGWVLyKz9vglRwyStYd4k9IuZv24WuWvmvGXGBZC+rURVXKES7xlFdxSs08dk84wMQc4qJ3USEnxLhjUtyWofeOpe+1R96IJuGrtOOSpc+Wc/g+OnIDFb6OjjFyjQuoHFUnpMs4RYrZBNw19tYBtVw0gNCg5FHSOtUIuYS4DjVCtqB0XMY26gOvfAmfOqTBWLMK2HSOmDD2WkOGHjPT1hx8zz2LAax2nSJ2HUJ37YLAzxvmvAlFyqwSa1KOViNmWPpA/6WMQ4eiy5AJ65M2sV2b/F6NfsKvM6XnGnsWyTiFW/pWqhBTcfFvdOn5TpFtCHTcezVqnp5nBQxlbIYZrw6OnlldysjEYXTMMiFtnZy3SSletk+csY6atQpfRUatu8atWkWuWYQtGvov6/mBpp/V4myYR0xoscsfW31QxL1XIncregwo09rVqV+M+KOEVO+83l/U6Ta8MoQy0ZCeR8/+zMrrNeSUmPg9QeBTPkMtkDO/2vo12oU8RYW3ITQ5mPgPN038gTpKOiX0o+OmCCmLzJJ1etEiKmnJJXkVnSGkoTbhPVrsHnP/h3c1yh7bP1WlftRgjxgKujXoPbq8XnVWtWP4A32OhWfJL5psM24pQpUq55ZsxikBbkrK/KLsnsIq7JXHpyCAgCjic4npX5VwWeyiCaCqNv7N5n7N8m7pjlHvdZgVRpwaWdd0QlKnR1oPLWNAEZ3pEPRSyjnN0LPalP9EAZNuxmuAtg6kxj6g9YZxEDLoGTbmjai5nwG1AKHiYcCtumsR7Bb7FrqPmW9dWNOSJiWbUzysRs70LOhXxaUh2CVjLsmfnOM7fGrnXBPbPSsm6EUDhHTgrnPetbOgy4FX2Ua99qqZc0/vdEvv4tfNAX3V4JQzqqYMg9rY1TPMsjHgPLo+dXZx77jVs7j0L5yqKSVWCXBAVvkkLr+fWjJqH/M24OkmKukjv34R/supnXFO+wxU0aNsEMEumwTq4hL/ybN8yjzoqXftPHApu8jXQGDw2f22kW8oBSPAI7DpPcApkEmfPStnPSunVdiVwD91ePVAQX2b1oEoI5M+umf18Vs3tPi1wKeBQAuJYcmEbdwHmJZJ6HOYJS63D6gz0GUgzaTCAVrVDLVkWMiVGcXCD6tphaPAcYGgOid8sot4Rc7phwfdM3q8axctQ54Dx/WqnrOPeQ/MFuYkRykkFYypeta4Z/V6NSx7lEw5JX5CpXxhVM7o+9RTisbs49qBhbpl96HSujg1C2qcapgxXOPTsIAvGnHL7XXP7gemahX5BkHM6sWld1v5twJDJ2T2eBSM4jO+WgS1UXOHgZujU7qBQANXBubOKhxFxr6HKRIy+uRJefAsI0EzRMeVnDGc1snP7iGldzGKJwwFzWCScDal49jMr+AYn4YViCOxYNAq/JXvk0V25Zh9Qgd4SPhJf/kEAp30CTQJKr4dnoZJ6aLmjwBVRyV00AtH4M3sI1+D24FuO8e3e5bPWENapH/dz3zzV8Gnk+CCf5e861LH9uvQ95npe9z6HY/aBYe0WYsIZt6wKquCUjwCpttGvALKbx72klQ0quPzhFo8DnQZndrJqpyFPIOgI0CZgFwBaQGCySbsBSlviFcz7xT7nl40DiTfOuI1uN0m4p192EtKVs9GdNOENndIlTWoQh/X4swY+y9Zhi6a+8/r89aM/ea0uWfc5i33/HmL6GS/RuHXEEmgWMZAHUC6QM5iCwZoxcPk4jFc4bBH6RhIGpgHAl6aV7NoEfIcBJNVyDN22TQuuRMsBt/41C3r8Rosgp8Czp76115xyjdAn+h6z+j6LJkGLJkItlFxu64Je+jEQ0zSJT3ne3Tjn+mvwT1H+JRt12i36Df2Yc9BJ+Gy+ugVs+BzcAB4AjLPJbUL5uSe0wdiEGER+IxdOm0X+ZZVMm4V/IKY2e+W+AlS0jnuQ8CTdR12pVXgM35m3zW/7hSbtWbku6TjOa5Bn9JgrJj67iKj913jDjEJPwJr/pXw6kfMi39nfv5Pec+fpV//rOk7YBQou8SiIl6YBz2DNIQCIeT0edZM28e85jWu4rP7XNI6mRUzCEgobFonBB7eEmKPSfgI6SaOSnaOfofN7AW5A8p3l5z+jVFx6ppyaBu2ah5w7V/1e+yz/8S92nQMW7P0O/csPCBnHHkVXwY/+Rnx4j8Zn/9K7/gzpu3QKeE/kS+tcQm/mQVBTqh7VQEwoFI/6/s3surmoRAcIQWLhhH0vCFseh+Uu3XIy7CWTU1qIWgmA3YFOvqte9wHTVoplphzQs09RafvWgfvICN+BNad0QrPWKXApg7wqeesrH3nqBNy5hEh6ZCQcsWt2MHEn9ALvwfWXofU/+TW/wxuWgisi0rqsI96A1KJmDsIdeGe0U0tHIS4uKZ1I/iV0+jkLzAD17j3hLQvqtQCfNIHaVR8OLukT4nw+pHdGTPzilp44BADM7jil11yS88o+UduiVsW/hvazEPLgF0z710b3z2HwGO3mDNS6h+c0hVd+hk997t//e/p7/ZQiZd+FZvBrTsxbz4mfQS/GgS2Msqntf1bwA3IhI8ISs4QNCQANVO/VnouVFYRLa1zj57aI4/tUSLvYKLBvgt8xp5V6Llv2aVX2bVX5SU979Ql5swm/NRYsKqEW1REzyu4Aq/fs/GBxy8dI9ZU8CduSeeU7DNBDUi2GU3auDJxh1Oxw6vbCmzBJ38h5Q3oCZqgFJ0TPyGo2f3mfo1QadrMUr+KcSVs2ogmfUCJ8lWZ+uKR/SUr7wSfeegYu2cODqj4xqu6oOVfktKOzHx3FYgbcvgRMcMBEd0VFXdgs1smnF0Trx11woGRz+/kzGtKxjfP0mPf0ikZ521jwbF91LJbyoZX3bZPHRS/vm8DJIFF6DMEpJ60W4ZVYIs6pQAZ3Dqs59MH3V2J9E4We0hJ/h5S90NQfoqPXbXxO6XnXzEKLwgpe4Ze69LOk/eNvjnFtN9Re3tDvv+BAbw3kMRNDeqAiOk3VOQ3dNx3z7wVXeYFp2Ba0n5eDn1kEfzdt2LEKmSDW+oa3Gwf+ZKQ02MW3Iaw9G8y4ddYCRpgTLgl9et7g2x9I27bJoW6Dqj4GdLwh1/NmVv8d1rmGTnjzC1RGHhl4ugdnWtU7IWh/9MbsiBUXt2QnZFHrqrgZyWQ53bB5w4hVy5x16Dt/cqOUBHTj21mJexPbSKPnGPfq1I3yQUb+HRs/Evr0BZz/waEbYDwQwaXiOf48OeD9mGDRt5dsm4T9oGQR9fe5VdeRWf4ZHjXTSPPQ7vgPSPvTUXQgeFn1oJzy6AVGeyzO0r1v0jAPPofmk2I211aBl3bh1/YRVwjY67wyafk1GNa+qYmcc/c+5ycuo1N+KLmATTHj1VAiHsuYhPMLRtFOAY2cgoHpFGxa6G1ncqkDgm7j/oe38ObL71LzihpZ7hEeOMFaZcpcWuQPkvSrtP3TXsfWJ2bBZ3p8eckXFruqZb9KtFwQ+rlDYVtbdaFVeiZRfAlMvrEMezELujIPuQKFbZryISC+h5ee53c1qVMW0bFW2IjUEF1Su7xgTXjCD1aPjb+vRY1Z1SH8VLK7pmY5SG36JxZCJxYyEWtBAtyzsMiegMi2t23NYbuGfbf0TpxjtmSwW8oEj6KqBfeES345VGjiOzAA9MVRcK+PvfSOuTYNnTHxGfXJXRewX3PyX/XgPvDq/AqqPJ74tOv6h7zRoIdl3hUWLOEfZBXYRdC1DqUlPhe2T3tvaTTASZq3cr/Oqz50KNg2yl8w1Kwokk6cgk8MGNuauLaf1MEddx+R+vSMbrhpnTFTYlGXZEiMfF0UZEnkhKtN2VAWy5Jo05sAv7gF4PzIArfyOkX1JTvweVHyMhTz7w/E1/2aFKG1ehrTjHOoU1i1gG3jHkISbtoXOJHAz3eGa9sDxW+os+Y0qEsmPusWvCX9Oiz8k6X2PADU69lOddpEePe25qg5M8tQlpkZZ7qSnXizdMkHiaK3isRf9B6S3ZODjknYb+ny7rGJl/ikq4JKRe4+CO3+BN29qKC2wkz62fMs0NWxrQGe8kyxJxXpuWRpU7JQMhh0qB57Ac3XvCrd90TZtQJ3WJGXx5brphxlnQpcwrOQ/d1p1VQ+0bcRTHLsTs6P4npp/YhKY/+WSJ7k38Lkf74nufNX/LF77U9kFpSc5uTdNpWpZw7hoPR526xUAh7qKg9YtySvNueR/rPyLYpS+9JTfa6baQyPtlSUHPThIdQwaY7CJ58y+s+D25acYgYU8H2Pbb48kCnR8JqQZuyqOoO1XyOjTuzCTvV9Rq4obGnxtpUJn9GKaYoiz0zkgt5dDtD5F7hg1s1d8QnpOyWZF121T3O7IPPXYSfHxw6h5/gYn7wCudlXfcoaZeC2klT9pSu9967VR16DiOnUx4TjdBhlamTsr8XdB94V4/re48ouQ1K2oEbYB4bxsw1mIQielrK7hsu8czSv+em+okGe8+a88pC0v8uIlHit9jHt98aa8XcudEoJTkp67gsg15VIh6a8C8cwmEGACQnlJQ1efdZJdyBR8ZVcMP/JrRN6nhZ8Kuk3RIIae16rEKEKiX/Fz3fs6gX65j0CT3vCR3WgDRyVB45LGk3LO0woegyo4CekrIfFjO/cIpaeOi8LUU6VmPXq/xSYyaSKHk7T+qe3/0bRdIPG6UfdWsYz8g4LitgQUcfGHjtW/ofukT8GVS3IO286xx5xMw+8S0d16DOWQU5BDWqMYrZxUPymEQELafvgU3YBKVg0zlpyy15ycx3RNF9RhU/Jec8Im7VK27x5Z4hvOLQQ4sTbOKiFHpfh/W7a/Qrg8fV0vff2ss3GNyNuP1rrtjNZgWJdiWjrfr4cVn7BVnMjg57z9xn29Z3VcZ5Xtl90zYIOMSxd8Gme3SXOm0PVyDiEImJfa3JyEO4RL4WtQxdZ9cv2YQfknIPXJNXjHjLevR5FeycvMu4tMMeIXJNlbSiiF9SxB9ZhgyJmnaI6L4QUX6lLv9BT6dZRbxU4faTB/K9EhYdjw1WLb2vGtKmHtksyrvt6jAWpBy39bkTsqgFI/YRM/fPqCaAyLpH1uMGwQ9MBVZBDRr0XAQp7auEQ8wep/mLrmDDIXzPOWbHLmzPJnhNn7mqRlhX9Ti1DjvQ897TZm4qk74Tc/e0mOPiVh13NTtljTvkjGoeiTwTU37/UHdZhQDtZ/iRxb9zkhbkXKB77Zn6bhn5rJt5Tyu7rdv4HbrFjmvSN4kpTxRRDXIuCuhkc/96j7T3CNeoV+JWYauEkveqnkf8yiNy3o5TzL5jxI6Z36mV4NQm+Mg69NgyZF2ZtqPmAah3YR2+Ku22IInql7D8cF/9taj6B1G1rnt6iwo4mMSSIm70kdWqEmHPwOvAUgAN5Rgbu6pLndGkjiqSNu3DP6sSVpzjW/HuPuVjyuQMZkEPwrtgyCO2tdsorEka/0TKdYuWu4PO2LCOmNfjXjOyT1Hx5w4xR4aCHQ3OujxhXQH7By71UMNrR95jTg7V88CkW1Sn+77uopw7lMCOLgNM39Jlfrmlt65MPbYO2ncMGpdxHZVwXjfxXzYWrJkFfVEgzJsET3EquQV9N4y93ZPegg/eaGDSXsvT21U5T+U9KsVRS85xq7Zh4+qUESXMGSH7wj7myDLswEiwoc7eUPFYlHbbV2fPPHQeE7caeGDcJ6q/oojd0vTY0qZt6jD2TbyOLXx2TXjzCphtE+8j13BoDeuGvDWzgBXzoHVjvxl9vx3nbGrGp4f2IRa+tRYBDQh8YrsevfitIrtd1fuNmtdbdc4hPe8InzGpzeqVcRlQcFl3CD5Gx80bsgDqT53Chx4hj+0jdox8F+Td//4CEAesZEuLvmXI3Tfh7hpxDi0EF84x726qzim7j0vazsD8TPiLBp4b1gFXuIxDl7w8jxJS8odbZj78slFtdjHCLqDxkW3kDLPuk7bgjTJrk5BxxCzeQidCzOb0OZPq1Ek10owqYVaFMCbnumrnf4RPuyCnCxcIOYZuGXsd2giOHANPncOObAL2LfhwfoFP+J2aA2W8oEVc0iKv6tE3zb2W9NkrRtxNVGofNlvJLRUV1nLT0MunZECVkoNQxmYYssrI0e8mnDM/aXgv49OO+NX71Jxd54RVm8BFEy9I5kVt+qIGZVoZu+8We+5VesEqOsEmn6BjNy340L63bHwuSEnHTmFX2KgZZcKZS9IVqE951Ia1H+TBrn3AnmPImm3gqmvsfW1KZOOcnEsMLb1DAZtMiH3+0CYUIYVK8CoaNvOqfsMqGTANm3PPPgmq33ZN33RO3HOJ37QJXLfwXTH0XNKmz6mSgaNeB9ZeepedEtOO8UkH+NhjUtyhW+QBPvoaFQmcYM8++A9eVbeUw6Cy2xYyDCK47x695Rq1RUmhZ3YhVPDRLcu3TfhJrzbuGnuTU9+LO0UiPNK+2Ac23TISUJI/yVgEPTf267AJGjPy3kUnADZs2QTDDDaMuKt6rEUNj2tazrF7wiE6dgcZvmbJX9ahzalTgI/vmPG3jDldEg5vxa3eiFt1yjjNWfvNWPrMOwXNIoNWCImr8a8MPDL1SekOftXKmDivot6bemxe6YBNQD3CwqeOkTdgxKywETQ9doxmpX2Rd05YImdu4FNn9DhrVgHLdiGTuqwtXOySg88ZLQPkw7F70iEqetcuZM2Ct27KObAPnlUFJsH6Im5bLKZfcc+gXcH1kzJ6wITZIu34QhE35xSPEHe9q+vpldutSkxVIyQ7Rj4z8SrHJ70jZX5BuMa+UyRk4xI6dGlFlr5Nyu7pv+oLhvxqRlyEX7quYrO2sVlzFmH96qxuddKAGm3GRLCBjFtziJjR9xpVpE4oekwp01e1+Ju6wf2y2CJRg0oR49cSDl9k3HrU6O0a9K+GPoP2kQgJl9sG3sSEd4ou0U5hLTq0PELiO2xSOwVm4FM5LWIXZR/QrEHJQ0e/tvZrumPi7xrybMKzcAIVte6Rv8UoW8NkLtrGj5sELtvHbronbtjHAsXYtolaMQyY1+Et6fE2LMK2rGKeils1Sjq8knHrkCcNa3K6lKnv1D1GXWI9eZUy9uGahLTwuuk7ep52gXWP7MPJaR2OkS9YRYMIQnK7pHO8uU+tFjUPm/DOUlB304Bn5VNvzC5f8CqewCdvc0rXiIVb9PI527gl29h5q4hp66BZu6A5q4ANu/A1m7Adl8Ql24hl24jiRxZfNVm9Ot79Orwhbf5nDcYbY+8ecpo2KcuUkSftGBHeMCNm7g9ApMsswCZ90OOWkzM6EVb+rXLEbOiQ/9DluUa/tApoxKd8dk/6qELIdgh+OhRQ3+8cOU/JXvesWESnLLkkLjunrrqkzNtHjxgKBvX4ogj5EjnnZiX8S1VGnwF/1NSvW4vzVcOzX5P72IgnZRemS8l5bB0aXT9729iXldOjgk11inh2y8zfLqRFi1Go61mEsAp55hTzxj7khRajxCHsuRohF/SrHrPMLf6jXWArKuwlKuQFwS5m0CZ8Ap38HjAKFbOIip+yCh60CEKI2UoZsjVcYxGyuHc67C9arAETv49qDE15pINXma1XuTouhZbScduQH9K4pILPAIvv2YTaBz6RdU+BIySBCiUTYcyrRce2uyd0WAa0YpM7JVySUFHvzP1aabmDyuQiStpXSM8bhoF2gU/vW0Y7BryQQaXSMvvMvOq1PEoeOcTb+bcYsKv+YRRg6dfiGvVOm1qECnv+ixbb3KvKr2wcoeVJze59aB8V1rgsahsGlETOLVmdkIFPeC9sjDm9MuhEhDqtBN4Y3lWVWmQmaNJhl4P19x3jIBZO4a9do9/Dn5q0UmTEGxVSkQmvUZtWahP6yi35Kzml51fzyODGDQtB822LCCtBs0v4q9smQQbM0t/0+Yae5bTMbjiCJr5tGcrK7oH3Roa2oCPbVAnpruFP1UhpvhXj4vahCEreoHf1gkfBqEfBMKN4jF407hjXziqfdEn8aB/1xqtKuBwMn91LyBviVExDfrBKxhlFo0b+LaQC4df6KvQSav4QMX/YOb7dNuo1v3aBVjjilt6Fzujya1q3i/0AEp1bOaPBqfSEf5VOqnErGRWTHiUT7Ko5Xb8mt+w+ds28t/Cb4HmrqFfR7eeC5g12xRS7ekbbu4ZYMMiqmuY3LpsEtjjGvaeVjdKKh42CWvAFA4TCQeuI1/SiUbgYmfwRl9Xj07CEyxkQrjCrFi48IOT3catn/Z8swYu4JHd4lI5gc76yq6eYZWNOSR/cs7vhHJfX5Z75CQGvQs7ptw57Rcrp59UsuiZ1ouLbOVUzjOIJM/82j6IxauGoQ/Rb94weesmEbcQr/8Z1uMYloQOX1YfPHSTlDcEF8C9ibr9F8HPhZ8KJn2AeYKd39Zx72ld0yldK0Rgy4SP4lFY8psIsZ5RPU4sn4ajhWetZPY/PHyIVjYa9OdLzbwYfBbRs+jSuMStmzKPfoTJ7wcucqjkd33psTu9/l9HZxbcjUzqJJWNwEvxy36d5Xbjio3xauOCufMoy6p3wM9OiYUxmN7wgo2qGVjZuGfWGXDYBg1g0xK+fpxaPOGd0U8on6RXTws8vwABSdp9z9Dt8ei+8mUv8J3bxuFflDDb1q3lQG0QV+qxd5FtSziCzZNw8sJVTMUsrHIXL0IldLomfsRk9kBHo5C+uKV802FUQeXiuPr/eo2gEgq/NrQ1q2YD8QiV9hGvI+cNanBp2xQx4llu9oOnd4F2/TKuYgFl6lI6B48Bybu2ic3In+BSV8gWV1kUpmWCWTpn6NzvHffBpWPaqmRN+Xl0xCcM6+rVLKlwwjssbRKd/5TWsWIW/ck35DK5hVM7wnwjXm1PLxsBm6+iXdOGXiePozB54I2rJqEf5OBzZ1XOU4hEEp3wWm96DjH6PSfoC1uJSvkBS+DUs49J6CJk9/Jp5j4IxsI2Y3gVlbRf5GpfeHdK6aeT7hF+9SC8cIWR2O8W+B8vBPPOQ59zKOaELvBsinx+4JHdaBD+FUvKqmNP0rGXmDrlFv02Iefsy8f1q0sv9pCfrUVUbic1jQUVbUc92w96cRnecRH3cFzzfYtVvMuvWqBXzxMJXYa8qS8cjqPmYhHbwKZQPNrPXOeUTIafPObHDNuY9q3zaIfq9XfQ7qMewV4fWUW9DXx6AEyFloFIYZRPcunnIfK8a4dcwYDC5eIxdPe8U/4Gc1+dZMSFchwOZjM/sc0n+JKyljK9gISSwR+EwLqMXDPBrWnVL/eIU9wEiiUnphIrwyBsBT+l41ZHyBhilk+ZBz1AJwgmZBrZZhr4WNK6BmxQ8iikFI/ZR7zDxH1OjXx4ntP1vSfs2PQVo+oASZUSNPqjqAaNHidqrSu2SJ/QqUGYNebN6nAk1DxjDqtQVh5gT9pND5pM9Us0qpmDOMnrSKHjZLYOQ2oVN74bchLI3DmjFpH2BqKJTuwCYmGXCdfnuWX1QDh5lk3COzfxKLRymFY86xHdgs/v59cuuad0AQ9RSEKgDnpWTADTUkgnholzIakgzZvGYsMgTPwLsQdpDOkCT8CydBrxU9igKqF/mVc+hkz4xisexaV3QyphlU+AmVUY5CxLVrxV8gc/uhwya9S7e5ZfPYhJ+RrTsYhLnDfxm9fmTOrw5w4BxLa85Q795I8GyWfCaZdi6Y8yma8ImMmbVNmTdPmIfFb+LjD90Ttyxi9y0DN51DF+28p+3CjjmVGxi84C1bqFSQehs0fLM2OXuiR3sopGU9mPAZqgss9AXEF5i/ihUhH1cO6N0nFAwDBADsQG8dEnrxOf1Q8kIV9FWzoBTIJvgHAqQVzOPAPvN/Zrtwt+wy2YBvSB0AGnuSV/0uTVWwS9o+aPQfqBdUbP7iem94CB4S4eoN8Z+LdTcYXRiJzwXzIZ8sQx6Sc8Z3vYsPOPVXPFqT0i5k7qcJW3Omp73hIbnuKbnlBZ3Xt9nSstz1TxgwypwxyFiH5O0hfr7uwn3lCNM4hE64ZyYeu1d/EdUy79T3vw74/3/5H3+T+6nv7I7fqS/+1dp1//U9e9hYg6JSRfeZXb8GlrGFxVyDjHtMwRGnVUOgO2a1sOpWzYPewkNAhoBYCQ2dwBijsvqJuX2elROu2b2QZMCF0CzwOb1AVJwahYQNuEvwVSIJzl3wD7mvU3kG0gzAEgDn0bACABL5/iPEGHvqlmh5YJGKBwT/1azgBYIPlygQCr0LJs04j1xinyzwck/Z5ddetac00qPXNNO0anT6nShWtTzmlT1GFYkDikQxtQYY2rkVTP+qqX/rnPkNjLiwDVmFx23S0g6pGV/86+C3Pkj+tlfMW/+iH31Z8K7P+M//J7U/u+Kvn9X9vxPcdcfWR0/Czr/r+rBa4+ib97VZ4IaDYcQh6BGXMpndVYlgCjkpltmL4QaBvRa6AvCRlg5ZRb2zD2nHxqwQ+JHaOHQC1zTv0B2QLNHGPMbSRk9XlXz7qlfTH0brYKfeZVMAtEBk/iV03DUYZXJuKWRM7pt/RpVCFn4lI+EpA51ci4tt9/Gv9E2oIWU9FGTnLfGytrFp/xgV1xRik5cU06cE/Ztwq/QCatmgsug2p9hjdc+1ZfeVdf8OhiX3OqrwIZ/RT/fsAncQkUeElPP6LnHlJwjcvYxNWMbG7dLTD5mFsBTfo9oO/er/RHw5HtA05V//aWg5piRveMYdmQfdYiM/8lv/DOk7dy/zi/1nTElxzXyhWPsG2rBgAQ2DZP6CaqdWjLMqppkV0wYBzR61kz7NC1BH4H+6vVkEcgFICC9ZARhF/EKwkgrHIOmpcmugMDahr9CxXx46JLsVTZhH/byMSrRPuy5W8J7HUahukchCBsQFJqkXHpKZzIpb8SQ81YauUtMOKVlnRJzITjHyPgDm/ADm9Bdm5Af/lXnnJIjet45s/iUnHdGyb+kFRzh00EGghDdMPRe0WZdIqO3LIU3c+zYBx25Rh26ROyhIk7cE06JKSBKz+kFfwU1/09E66IWdds2+NAj45Cdd8IsuAp68jPp1ZlHyQWl8F/BLVeB9d/Dm1d4VYepnTt5vfSQZ9iUL5DkgBFAXuI6Lk1C2qA0gC84JrajUzsBPnl1C8S8QcB4BKAA2O8Q+c4l9oMOuxrYIWChZeAzQ+86j5wBu5CnGrQix/AXbjGvJWzC7Bxj1gIrBlQJPbLuvfL4Dmn004fWZ7SUS1bOMSH9mpwH8T+0ido1CbwOqPoRXH/tU/lTUHciXFNZfEbLPyGkHrvGHjtHH9qGnlgEHJsKTiz8Doy9Ds28l9VIS2r4ZQ3iroX3no3vgb3/gVPgOTbuEpf0nZL7jZCxqeuxoIw9do64IKYe4dOOqVmnnNLzkIZpHfa8tue2bcg+K3cBn7VAytkLbN0Pfbrt27AV0LwW1lYa85KY1WsS/AyaAnAB8IJV9Fu7pI+c2jlLIWr0IdilE8B5UTFv1TwKLfxbfOqWnaI/GHo32AS3ga5xDH+mRcu3868fFxQPadL6FYlf5XFdsu7dCsS3Uuh3Mq6n1LRTSsYVreAcL1w6eYqKP7KLPKCkXfLKALSuvSqvuBXfuBVnjIJzj6wjl5hL17gTy+Bzk8Bjba9LI78NJdK8lOOMhPW8nNOiPGpBwXVOHr2lT9829tw04exa++xbCg7MfQ8N2PPidpuatHN0/AU26Rs1+4Kac8ksuvSqOAuovo6smVFAT8q4Lmsx9y2CdiyC100Fu4zSFXLBDr9hx691jVu14d9kzK/7O/PH9ARN0FPRKZ1q7EpgFgggP5SsHnR8hwkw9oR2GCZeVaDa7AKbUaFPjRkl9e5JE9rcMQ3mgAoZLO9VpX1SpLyUxqwhw87omcfMnO9+pVfekN6Jx46R++aBm6aC7wHV3/iV15zSb9yyS3rBBTn7DJ964hSxb+63rUJeFXdaeWQ3LWI8K+70zSm25752523lz7eU+u7rzMqhNrRp20ZemwbsHRPOtgFrXYOyoUocvm8y9tDmu2vsny4xP9Ax1/jEn6zcM2LyNSXnnFVwxM75HlA5KeU4K+OyrsWAORxZhi3rcAcsAiacYhdIeVv82hXP0nlelUvcG4/CQSO/BlTiO1AN5Px+0DUIQc0CZDsMRWIOKb3LKfS5kluakns6Pesril0+YiIY1ucNqLMHlGlDarRuRdxbSVSbuFPrI8cjZuZVQOnPkLqfQbXX/LJLRuaRW+SWKeeKkX7pXQI1fEHLv6LlnuKSzt3ij8x8t9Soa9Iuy4+sJ0SM/iJn/sAkXdtGHul5vbop3/abzPObcq9vyH++pzYobraiQVzXoa1qUFZV8CtyqFER83O74EvHiEunsGt07A9swoVL7Dk++Q/f0t/5BesmXkfE1J++5VMStnMyTtOS9gvy7kcWf3/6i0/qMfT+qMEaMA/e51SuEnNXqQXI8FZk1FMT/xqHuFecykkJt1QEIbXTMeK1nmeFfUAzMvSphU+tjGuSc+izuYDKcdeEVY+CIRPfUUPeqA7zi7TzyweWP6Oa/4xu/RFY92do44/Amu+C6nPPwitG/jkh7cw1dteMf46Ou6BlnOGShN9GO0cfmPD3tBnrSriZB1Zj9wx6b2pducSd20Yc6flsK3uMilg2/yZb/4tE0w3plr8d8fG2xpiU7aISZkbKafyh/YEx79Qy8MIm5Mw25Ngq8BoVLfxuFQY26YKacUxNu+IVbtkF/q9/2cgD85nHdtPitnOymGP7qDOXpAOXuG4N+kc1arsaY5NcsEsv2sSnm3uXoaOfSiAjjHlVmNiX9MIBBDP7qzmvUtMjxzXmlVNIqx4tX8Iu1C+07aM6vc+Y/1WT9lEa9VHSsf2x/Wdl7EVA5YWg/MK75JpX9p1ffu2Zd0HPPCclHblCCfhtqFNXFLGQjRu6jANznx199o4mbVsRvybtvGFI/52e+Y2QcGETdGkZdGXuf27IX1ckDz+yfCmiUfObVPVvEnCs/0Wy7Ybcx/vaAw/Mjoy89o28T82Dzi2CwQvntuHn9hFXztEXThHnLtEnTpF7NsGHzpGH2PifgtINHeq6BmlJ1+OYkvIzoPxnZP1VVN3P9Bef1Ty+qtN71OjTTjHROZ/uGXDkHEKxYU2ahBRFbCIyvJkDLkBHPlXGJCmgk9Exr5xD2oxYxY6CuhEzfo8y4ZOsy5tHVq2iJs8emv/fWR/PBPXnXmWnzMIDfOouOubQNfoQFbnrELRtyltVI83LoibFzMceGA/e1RsSNZqSspt8bL8kg5wRsxq/a9Dzm8aZTcC+CvtI0/tUi3eqwV2WcRt8YPxFXq/khnjRb4+LfhEv++Vx7W8SrTdlu+8brqmS9/W4h4b8AyPBlV3EiVkgHC+RUWcOYWdOQncva5AXVQjb2oxdPeaKvNu6CmFLk7ZnzLlg5fwIrPoWAhjZ8C2h5Ufay151xhcF0qJFyJ5L/FlsmagJFxv7LKhiWNza386/mpr8GoEKf6aCz0CGPyWndKgTMpTxqYFBT9pl0W9kkE0ixusOgfsuEevWvn8lvr4MbDxlluy7J287hm1YB6xb+O5Y+i1rUpeV3QDP++/p9d7V+npH8+sd9a931T/eUv50V7XznnaviN7nm+qXbgnnyLi5R47TYtaDD0zf31ZvuyP/VFz2jZFC7p1Hqb/cLxF53PBA9qmk/NOHcp/vak1J2U+L2y/KuG6pU48NfU5tgqGmTtCxh6ioM4+U/5PQeM1MO8NEnTqFwvGcknhGjf/GSj9zjb6iZ51zci98Sy+Dqr/HtF0mPLsSlHUrkEfUWTNGvmvOcb3Jz5zDm4PrJm8acRXd4ix9yhDyrgkyzvGq+BzgfJjoV9KOUeO4mBNKyparMMfWbfyW9FmzOtQZa8E5sxDs3wL7bQLXLH03LXzX9Jkzck7DktZn+KgTp8BdQ+aaGm5VwXVFxmHsnl7PXa2nv8lAqfeIWwFNvLQKfX1Xs0ZcMveGSNGd+/Vyt99ZK2Q8uh99+07IrdtxInfK5cQrxR42iko035T+dEdz7JHllLj1nIT9qpzblUPosW0oYM0VXvgdwiUx5ZqcBsdvlPQzQtIJIemKk3vuU3ho47uiSjxAhp165gEl/Rbd+mf66y51/Liax6Qme0aPt2oTukXL1Wfk4ZPeiNsHq+JTlLFJCG1qgYhluGPYK0papyGz9CT++b/i31wLao89sredwjbMvcYVMGMKzn2PLcdV3ZbNvFbMvdcs+StmnHkt8ryq24yMw6CoXv99nSkFpz9I0TuGUP/UuYeW86Lm03cNR25rd9/UvnAK+4ZPP7AIbBNTfKIh8d5a4ZWxdLO1dK2xhODOjeAbCBYCEXr/bp74g/yH91seSrfdkXl1S35eEbUg57Ig7bws57qvxTy1DTlHxUA2XbgnXAHWYuLO3OKPXSLheIiOAS+c0NOPrAXLStgpRewhLfM8oPbPmOcn/hV/hFcOKZPBBdO6XCiH/zNwqUZKc45osfCpUHBPEN6Kq0ErkHSOd497h417a84p+5b+6TL86amg7oBRsOkas2TmM6NFHpCy63pg2Cmq/VFE/aOowYIOdUHPY8WIvmZAm1FwmZFxHBe3GJGwuSLHX6JjALq21WlL4nbTd40Hb2r3/qb9b1LmT2L6ugGrWvqXDhflsHuIHLnfCjRvRov9kvj4TozIPwulxELu/hb78G62yM16abEWMbG227KTsshVJeySrMuilPOmMglI5IlN8CmwQ0zsETL80CnsxDVKODDRx25xxyAfvfK3VYjLCu7TWlSQGCdeJd9Cmr6HNQ8bMkbU6JPa3DkDnwXbcBVMnAoxNbhxzpxfroxPFrEUIMx5dQqYVGrKZy1yriY+6zT782X0q2NB/ap7yrS5/7AqeVDedVQe1Stu8fWh8VdR/W4xo68PTec0CeuGzFU9+oKa+6yi67IyevqxDRTwJTb23CHswjL4h3nIjKh1302N3l8095Wpl9Zh3xzC+4218xT/8c5dy+/Bb3EPb5bLi7XZa3LuIorExaplxEMe3W5WFh90Mqy///jdffUxSYcNVfKCtNAF26rUHW0mkItT2+Aj+5Bzl4gD+8AjZ+FShiNM9AEm6piW9qdHCpTMvDxmFxN3RM8+4pVfBzeeB9b9DK0a06RN6HiuWIVhwlvZud3q5HSH4Eb/6gkxpwh5dAxCxj1dk1GGjm0HR+gScy8T34ELDljla8gE4EIjqpQBecyQAnpYFjkq5zAkbTsmhxyTcRySsB6SsgcXrOszgMNAGwduOythDwU8KGp2hgw7dwifeWA5fs90Ww53psk7VeTsKXg81RB5afhwgKnjJ4KIkb6ZLXP7q7tpvZ5yprhI1KM7oSI3q9UUc27/+kRWuuOxNkDMijJuQRa9qoBZUybuaNP39T2PTH0OTHyPLANOHMP27IOP0DFHhMQzz5x/B1evy7otyaI3rQN33WL3qennvhUnPuX7vuUzpt6zBpwZA28RBYpdSAuvdESRlIVOeBfzfFODnqtNz0NIuyRj49uRYS8UMSmSdlGzzKJ9n/oZ89Bp06Bp88Bl27AlM79FI+6wImZM0XVCwXVKATUh4zAqaTsq7TAgaf31kXnXA5NBSbtxSYcJKbt+URMY2xaCfduQdRnMwkPUhgzhUJGxI0s70/ftNJHrd1Lqwymly/7zI0476uENz38iKvVEPP6J8L7xa4WiRMr9W80aUh/NFT/p6vdbGb+4r96v5jArj1pRwi7KYRZk3TbVqHt6nDOroGPb4BOX8EN01DktfVHJfVnG5ciAMSPvtoOK2ERHHtGzjr1LjgXFR56Z3crYOceQCQPffZfUaW4VOe2TMiVXz7uSXzWhTEhTJWUg7lqEU7N6cMmfbpsEmLHKllm1J4EtG8iEbff0E4/CXfeULafoRSPvaQi1Nn1NnzGjiIHMB0I+Lmk7Les4KmXTL2oK2m4PGfh/imr+HZn6gxZ6ZO27Yxdy6Z50bOIzKe7Ye9+oU8Sw85FR/S3xbrRKyW2RaulbrZoSNfLijSoSdcqi1WqijTpi9WoSjeqPPtuovpBSeSmh2qVs1a+EXDLz3CwI/fNNLvCOOUkncMS2Fm1X13PHgLtr5j310GrhsZ2wUgzYk7KoVSPOqoXPNjr6AArBq/jAO38bE73lHlsjZvlOkfBFkbHlnLnLrHvoEKnrWWToXUZJb5dxj0doM0udoz8IqhYfO8T52kRsejYsuhdsuyRv2kceYNOOsOkn2NR9VCyo0XULP1D1wvs/tKhrmtRZOddVFdK6qseuLvfQ1P/IULCv7QnKD6BrQ4m4qUxeUiD+xOUc6PvMSyGHxcw/3tVpv68FRf7yvmq3gV7TQ6Xn0kpPxKTaFFWeajzOF71f91Dm2QO1z49MRqTsIcv6H5r1iBk9u60yqUPYzQqYk3GekrCblUbu6giXU2xqMnYNuDsG3qs67DV9NoiIaQW3TQv+mgVvwZBzxMz9EfpkUpe9YOO/io+veWyZd1fvrQpp2EDwQtpdxypUl1MMSoGR/5WQ/B6hTMrFJn3E/w2HU9SyVUplv2nkWxXOtGv8IS13F5O475qw6xi5bRu2axe6CSzY1HdVn72qw4RCvbQJOjD3O7MJ2zESnNmEH5sF7evx97TY4IhVedyKrPsPfNa5bdSRvu+GIgFiBRx+VMyy675ht4zpaxHNd2I6r8Q0nkkotYnJPb+r8Pa+Svs99dG/Sf6iAm5NlQQyaUneDRKt57HJHEgsBdy+LmfPgLdtyDsAEW3hv2novWsXsukUOCXnvKBJ3nHw23YI2LYJ6JNGjyqTV2wCN1wjt9CxA4Zes/bhTRqYEiWzUHqmW8xrRUKGsU+1U1gLp7AH4RTcho39AAJRxjZqllA4jUzvNgh6Lk9tkcI2S6F3PYsvePX7bhlbjvG7TolbNuFbNqErRrxZLTrMYN+QD8h0jow+d44/t4s+MvHfVvfcUmMC+V+TE65SXJHFAKRv63GB4Z4ANdbwPlBmLkq7jUs79oqbQnOB0fVYv0NU8/0d5W5RvRkZ5IIUelkBv6HhsW/E2dRhbGrSgO2sqRPHxG0W5DHrikTAAoj/rqnvkU3Qrm0gMKUTTNykFHJM0nlSgbSq571i6Ltq6r9qHgSznbMWtMthOuWJqzYR72Ww0+hUZfeUoIZ5afdkSXQc5AIh7b3wnnTP3H4b33plZMx7+9hO/aBnCrRnitRGGWylqGONOGrMOWqDnL3lnrntkrJuF7Vs5j9v4DWjzTrAJ5/R8r9R8s/sYw9MQ48tw05Ak+r5bKl77mlz1hRIO2r0TSUiuACo0U9MolAaaHntK9PWFPBTUo5DD017RPUHHhn3iul9vac1IWGzokwAafDfIVw+o0Xf1KELtZa+0OYNbdqyCm5GGrWmTNrRYUP896wC9h2Df9JSZ6QBm1DT8vgNE/918+AVE79lk4BV08Aty+D/T2Z7lyJ5Uk+wbBm7gcx0EdToUzOBILvFPpdERtuFtTrFvkSgIl6QUjp1qAVyLklT+PwOJfZXLcFHZe5rRdZrdW6rEuO5MmPKKWLCKmBAiz2ixRpQJg7Ko3se2395aP7podnv3MJD1/gjdMKJW9KpU+y+WfCBWcCOqf+xdeiWnvemhue2OmtZnniOid/T85qVdl9VpsxKuU48tgWbR8XNhx+agsTY0hZKTOh8G+qUPUNPoJiHlvw9M69jC75wByADT6FktgkUcmSHkK67hnNwsS5j18ZvQtoZ4r+ggJtWIu1aB+1YBK4Z+axb+K+YCVYN+csm/DFt/qJp1C4yc5dY7BraHFw7/U8tuhoh1S6gwZRXJY1J0mIVIRiZPU6hTw1Z5Q9tImxRcV9MIz5qCNrVeO/VvAARunT8ug34Wx5Ze7Q80Ei7bmnr9hHL5v5z+sL7g2e06ROqxAk1/KQ6YU6bMaGMnVB0m1TCjsi6DMk49YPg1ySvWggOnKJP3FLOsCnHrrH7DmEHtkGbBpwtPc8Nbfq2HnPPmLttwIJz4Z9GHCjyI2v/A3M+jD1T70Mr3wMrP7D83DnyHLiwfVj7HY3Oe7rj0vZD4lZQUHPKQneAWtk191kz5q6Z8pZMhcavmglmTYLWrRPWobRJOYb0AivfmoCqCREzHzGbIBDLnlmdCD2OOj0fYelTK4tKALGsTy/m5PYNxHZM4Is/GwSD/e9UmF26/H1u6ZFv1Qm38phetAMNAp++6Ri1YhGwZOID2Durx1o08Fwx5C7pMOY1SOPy6DlV4pA0akLeDU6OKKmX3OIzdsEpJeuUlHlGTDvExAG9F26SYRt4aBe4Y+59YCvYseIfOAWeucfCOHYKOXEM2TLxPkUGnbmF79r7XbhFb5kIDqwjLzCZ1+T0YVnHKRW3bSv+poW38GjOXdCjwfmisSeIl00rvzVznwVj7yVs6jwpD+db5V/Sr4JNNWQWGXGK8PGvEOrUu5YBjqHNqNCm3wy4Ipb+CFTYc0mnOA1akV1gMy29S4OYE+kct8Kp7zOP6NTyXXBMnHNN3/GvOvKvOeZVH1Dzd1ApK3bRm06J+24Jy1Z+oJqXTbyXjTyXDdjzmh4LmhThMihVIowlTeqRa8ypZ8GVf/Upp/Qbr+LSI1uYC27xgGF7jiFAb7dsBHugxx0DDlHBx+5RR/i4c2Linq3/vCxuWY26qsfatgk6cku+oOZ9YxVfkFL6ZBxHld2WTLnrdkFbjsE7zsG7TiH7zmHrdgHwyLZrLIw1TLxLQC075TVCFk2Kf0NN+oBQoVp6lSHUyJzsz/dMfGSREciwJnRYEzH5rRY1B6FEzDL1qQX7BRWT6OjX6qRsc68qj7TuLL/acVLOHCl/Gps17Z42RUietY3cQCXuuKcfknL2MSlHmNRD18QDp0hI9U0bwB4BNEvIhTl1yrwaZUmNuqxOv6RmnJPTTrCJB4SUH8G1J5zCE07eObfglJFxwc7etPOFYrnkZID4vyQlnJMSLj2SQf/vmQlOrIPm1UiQ3r2yyM8Sdu3ilp1Stp8krLtlnAY1iKsOwcs2/uvOIWuocBgbrhELjsGrbrEbHqlzPmVmtFwDVlFow5yoGV/CKZJT2OcY3CSBjFAmpHhkfkaokBDy7iCQqBkdgoZZBUIqQgmXoUrJBaXsGPJMh14ihUzExb5zDnkKZPm+SYAFpxIb9uKxsZ8eKmGDX7FKzezV9pjQYc0CLbEL33OI3HOK2nEI3bD0n9XygCwAFyxo0WZUCZAFK9qMc2rWKS3nlJh2BMLWPWHfMeIAGfH3nad+O5a+25b8DSPuuhF704SzqOOxpEtb0WNtGnut6HHHZAgfRM0bH+i1Slu9lLJ59tjyhaT1RwWXHm3ygD5jyMRzBFS8FX/Eijdm5zuODHivTpq0jv4maHVHhkpaBUhZBzDTPxJin4uY8vWombi4l6JmPjqUTEz0CzOv0pv6nvct/Mgp7dySYdvgZsRty1DrwBagRvrcGmVivqXvk4DqBefIt9qMcl1GqUdqp0vYcy1y3gPLCE5G3xw5awITN4dLXsalrePSl9BJm7j0dfe0NZekOdPgSQPfEQPvL6rEZxK2r6Rt38s6vBS3uxBUgmI54xYdkFOBuu6go/ZcovfQ0bsukbvOQo8sGXhNKlHH5ShjsuR5VdaSiteKpmBOmdsj7VopbpwvolP2yKTkvn7jA7NXknavH1q/e2jzQdzurSSq9bFDs6Rjo4TzezV6j5HvgFXoglcxQsRBxi5ExMALE9rGzfqCUMSJ2wS6hLVZ+1UrkVLB4Kin617FQzKuSVqMQlrOV2pGJwIEEibqra3giRaj5KFTHDXtC2SEHq3wsUOMoVc1/NeUU6mKy5RxTiDGviv5fDURVD+BS5rBJUzYha5gU3bpRVuk/F1q0TaxcAuTte4QP6LrK7zZR9trRN93WNd7wyl6xSFizTZ6yTxsxz5uzTJi0VCwauS/oi9YM/Sf1eDOa3BXdH1WDHzmNL02DALX9QO2TSPntQU9iu7l4uYlYiZt0sgnj2zbJJDvpNAd0m7dcvhBZWq/OuODEuW1EqVL37vHWDDhGjeKTbH0qrhrzL+p740Oa3HwrSHEv/2HDgtagJ1vNSbmmalXuS4li5j0npL5RcolXoNebBfyNKBuTrgo3j3xg5lv/SPnBFTMW1TEK8fwF4rYdHm3VPiXbXCboWe5mHWopGMMKemjS/grDVymJ6tihpE7gokdx8QtUbMWiJnr4AhGyRohfx2bu4XLX0Nnz9vFzllHLNnHzFmGzdqHbmDi15yjN5Axy9YhixYhC2ZBG9YRy6YBwGRWLYJBjG7ahs4a8rYdY7dsQY/E9ahQih+ZF4gYv1ckfFKkfFKlfVJl9GpwBrW9+zQ4XfKkbg3mey36Oz3WJxOfQVRsJ7cIFdSkhU8z9Mi9Z+SrTshw8KtFhTX/qs24Z8JTwMQ7BDe4xL64ZxvsEvfGLeGdPC5Nh1up71XhXTWJCH6yaMSpsPFv1KYVYxLa2YXDOqwyDUqeXVATIbkdKIMJv+43IwEcgUEZc6ulUAlaHkW2AS1quDxjl7QhfPIYZIRbwhI1Zx6XvUIv3WBXQhOZd0xcsE9YtotbsY9ftk9cdUlbtI0dNfYdMuH3G3FGzfjz1oFzZoI5M/8ZM/9hQ+9Fx6hBY96ItaBWyrHssX3JI9smSdcubfaALq9Pk/tVw7NXjz9g4Nun6TVhGNCvySVbBJQq415a+YaRM1VdY/+hTFZxT1NAJ9r7VP2mzVbFp8ArERJeK6Fj/6nFVifnWvjUuUS9eGgXJotJcgp/GtIwr+6RZ+Ffq8MuRDhFfzAWNMrhso34dRFtmy4xbw2YpaL2kdSsbgAIfGI7NIu7NhFuCcITXUbxY2QCI3fIyr/VjFd3zzJMh1KUF94ySMrscop4ay4YJaQOOkW+1/Hs0OV0GfK+GHBH7MLmMYlruMx9cv4mJnXJKW7BKQaOk1Zhn5AxN+7q/vbQ7KaklY6Fd6su84Mu55O+d6eu11dt7ldNVp8OB6Ldqc7o0fHq0+N9VWd2qzHe2wXgQpvdgxsRCkQph0hZx0h7n2oJm5CHVoHQ9rGxL24aeYvZhprwqxk5X1GRT/9pwIOWBygQUDd7zypYj1GADH8a1rhIy+mSRMU8co5C2Ia/tA15quZRbBf8nJY7iEvqlEanm/KfMAtGnKPfWAU0a1ILIfhQHWaCJ/qcal1mmUd2Lyrmvblvs6VvE4AFOfWLkVeDNr3ypnEoM3tYHZ+f7Fn+2T11Ap814pbaauTdbuk3YBc+ZBsyYBmagkl19nmiQ8p1j3z9ixrjsXWINiHLhldr49vgEvn2gX2CmU+jOf+Jk1+TV86Ql3lIOL3MCJfJSvhAjHz2qzLhtib9n8pkB986TFgrQgrzD3W6TUBjaMPir4Y+kshYM6+qgOoZPVaxAjbVKrDRI7s7tGlJjZytSy80YhUz83ttAuofO0aacos9C/o8iwb/YciXcI5FYOI6HEJf6nFqSdl92OQux5AXd63DYR78ynnhln7Bz+UwKdLOCQF1C0a8ejNBkxmvwT2xAy5wi/8IjsAlfLILfAo+knRO/EVbEFi3ah/0zMa/9bZFJD6l14Tf8k89f0vfVgNOnU3wizvW0R5Zgy7R7y39WtxTuhVIxRr0cqfId27xn3UZ5abetQ+RiXrsKmNuLSWti1cyLmYTBcPIswwX9x4b23HHyEedkGXqXQP4HVgz+6u+jy6rFILkUzWD0PKUdI43ZJUlvdzxr54SsQnV8ihwi3vDKx6mpHbIusTIuMTFtq06h7QAHdSkZJNS20EvQuLIOEUinCPfq3iUyhHy8alf0UmfbEOeq1KL3GLf+1TNOYW/hrqA5Kdm9WCTO2HeisQ8anY/PK7jUXzHIoqWPQT2EFO7Yd73rKPuWkW6xHZYBz23C32lzajEJHw29W2Wx+Y+dkw282k24D55gEx1Seiy9GsDN+mxa34xiwAvgGvgES1GOT75C8IgAJox0BM7/yaw8zcDP0W3DHTES1tBAxB5hAJZwSXe0rfewKuWVTCgRs2Tdkk04lR5l02IO8eJO8boM0rC6+dCamZV8BmG7FJjrwpi8gdTThmwAGgE0S2r/pWTsq7xD6wDfctGPAv67QOfPHIIRRDSvpBzeoWrbDN7UAmfOBXTmOSPzvEfOOUTzNJRUm4vu3ycWTpMzuvhVU7Ag8jY99SCAWbZmGVIK79mFpclvAGVkNPLKBmhFg4b+DTw6xfpJSP8ujna3wvezINbfOsXqcXjJqHPPSun2RUTxIJBi8jXrGrhmi96+YSsRwG7eopXN+f7ZNk09Cm/cRmb00stG2NUTMIbwSPOCe/hdVBJ7bSiIVb5OKlgQJ5e5N245NO0YhH6jFUzw6lZcEpopxSPUEtG3dK7qEXCzX+FSylCn2Ezvvg0LHCrp+nlY4zKCbesLuHSo+ppdEYXvXSYXTPOqhhBOES/J+UNCJdY5Q0g4z541y66pnyhF40yS8bRyZ/dUoXnMAN0+tfAphXh6suIV+TcAXblrEnwM+Ea3Mweq8g3hJw+MIBZOmHi38wqF67nw+cOYjJ6YGh6VnIrZ7DZ/QaBT1mVs5zaOaOgFngKuXiMVj7lVbdkFf0WHCR4ssiumVdklTskfHCIfSdoWWNX/D/LpLh18zABeH3nxA+4rG7wjlXMa3xeP7d63jyoDcymlU6aBLZBAMCtpIIRZPJHcCirapKU3UPM6RE6Pa+PUTEOj+Dzej2KwO9j1rGv8HlfOdXjjJIhBCb5E6t00qNgmJDV65rUySweM/Frsot8zatZwGf3u6V/BSPhxDrqLTiFXjhiFfoCXOBVNa/IKGOVT/vWr5iHPIfngu/wmX1mgU95dYsepWPgUJfkT561Cwr0Ut+mdeGf6d3gAv6TVceEj6YhzylFY7TicXbVnFFgm3NyJxdiVbsIbiUXjrIqZ5ApncKVtYXDql6VEENwKMTAKanDo3ycVjbunt1DyBvyrJ63jXnv27IBvtP2rmOUT3PqFsGzWj4NhPyB/2YTNq/Po2wS5oPLG/SqXzAPfw4egfxyzf6Kye31rJn2rp1FuCR0QBWQcgbBMMeYD7zqOaeYd+ACWv6oR8EoOrULEsGjaMw26i1chsvoNQ5oJWT1u6d91eBUM0onvWuWneI7KAVD8F9q/gj81z2rDwxzjm93T/0CPsKk9oDZ1Pwhy5Bnka8PeA0rdrEd4AVmxRy9ZIJeMa3GqYapw4lP49o/rSNJeUPCSKZ00arnueDf8OcQf2LhiG/zqq5vI6NyBp3Zox/cRv57EalD4sf/bndqHPQUngVZwKyaBf+C8fTKSXCiS8YXSCXhJnwFQ/TqWffcXmzmF3AKrWrGOfMruIZXt4DAZ/b61i1ScgdcUz7bRryiFYwh49qNBM3cimlidp9z/EewFubqkvgZHsFnfLUOfQ5IySyasAh+Di6AdADvUApGSDkD5NxB04BWVvkUPI5N7ybnD/MbVsxCnsPT4VyFWc6pnocrLSPemgY9JReOUYsnoVK0+Q3h708hKSBHdHybIBfopZPC4ioYIRQMyzNKo94cQpJDKkHMhfHMESaUa3o3WKvr1+T/dBfqSN+vmVE2xYKJVcxAWrmmdVOLR8EjUBS0YmGBuOcPelROAnAARrDrFsAFjkmfIJXYkAWQ5OACVsk4JqWLmD1AyRlCJ3xExbf71C6AGeACt9RuRvGEsV8TJvkzVLVpQJtbSqdwixNyIWCBZ+UsxE2f/wROIIm0udXwX7DZIVq4eB2CbxbY6lk+BUDrGNcOmQ8vBYXjnv6VVjRJK51mVs7KMYoCW7cAPsB4m+h3gG1gv8XfC2oFrZtmoS8guWA+HkUjBoInYACtdAJSA9AHgg/XQ8l4lI4bBT4De+glwlXm7jn9FuGvIPiQBTq+9ZDq+MJBfNEIoXiUWDiESv0MZgMMGwa0CkGxchIBgQVGIKhfgkbtkTNgH9qGSfxo6tfqCYmdN2gf8ZZbOUfO6bcPewlZQC8at4t8CyfwFCPfJ6iEDnLeMDl3yDbiJat0ApylzaliFY4y8ofVGKXwCvBEWXwetWDcPua9BrvKKbYdfK3Pq+NVTLklfgLs4NfMa7BKffIGmnO6RzK/fEp4l5T51Qm6oF+zZ9k44ItZ8DOvmgXwvqBhWcmjCFIAjLQKfyEsvYopqEGnxM9gvL5vI0SeXjYlfDCpQ41bSc4fhCSHlsEoG2ZVjBLy+2gVE1A1rpld4AJoW6ikj25ZwlpAsEqnvCvnuaXTECiwGQiia+JHwEWvyhnP4nGHyHeknCFawbBr7LvED2cwY/vI1/5PViBZLAKfeeQPgOX82iVATQAICLtZQAsAKuALlAkgCEApFA4xs9829JVL6Cu/9K+VMW+/hDbupz/fS6yH41hQ4Ubi0/2oN/sR744jP5zFfNz1aln1qNpg1c9hC5aj3+Vz6581raYCRpZOAPqAC8BI4Y5BtYvYzK/KrAqIECQgJu0LOvWLX8tm4LMt7/plQ79mqCxwgX1cu2fNrF/zom3US8gLwEjIGkglr6pZ1+QOZEI7vBQCzPPIHwIDnBM/BTRtAChADgMoQJEDEFqHvYp+fUzJGwa/AGWAjgCaAjwFSKlCLwMqBZc5xH4gArPO6iNkDwk3xRG+wntNz2qYHDr+g65nRXhm/0JM07eSL3/V9F3FNX2LqTuPL/ufyo7zxKrPyi4jxqxPKoQpS/4qLnqfnXUW1HzEbdlnNOxQazawhTNW8dOmETPWUSmZPdqeNQDP8I4QcELOALQJ6CBQEYBZXjVzMA3AC4BbgElIcpgSnAD1+C/mgXUAKNzqWWTSZ6hHYdcsH3dO7AB3CO9HgI5FzO13TRLyIkbxGLjAJvw1lD3EECCAUzkD10A1AuaDv5Ax7QAZ4DLToFZIFgBLI/8W/+Y16NJWYW8cY94Bj4D8BHIhXNEf0jYV2vgz9+1ZUEmvNm1AjQZSf1iNNqBC7VEggubvUxWuZRxUoc8Z8KaEW+cId8+Z1vM8IJeceDYfMRpW3Yo3MbkL1sL7EezoZeyyKV7tLCQCKuULmASsDEzlVM0JGtdswl+C/dCGoU1C74D/MssnIDDQROnlU+AsqAIYqLQueIRbNUUvG4UUcE3/gsCm9/g3rkLoIObwWnDiFPsenfyFXjAGwQfXBrVsgAvAQWHPdsBBthFvoHaEt9h41cLb/xfe4J2gZRj7P9XnN5DSu0BWRj3dehnx9DoXiqdgRJ01qsEZVmOCqZM6XmMabDgf0vBcto2YMQucMwlYMPNbMQ9aMQtcNvZbNhYI77Q28BlXZx5QSo7YTQe0mg3XrEWbmEVkyrx3MTnnK6AsNrMX4ICc1wczgdYLTQHcAS4AfsFrWraLbxfeiVQwiM/+CnGGjgCtFPouEA3oJtAyofsAIgJqwBMR0P//u9DeNux18NMdIDmQ/ACNgGqAedYhL4E1OUa8BggIf7YDAAasAbATDAZfgGuAKYDWhCPE3DzoGY5Ts8kv3WaVTLtEb2OTFsyDp7W9ZvV8J7T503qCSR3evJH/innwokngqnX4vnvqlkvcml34hkPkLjJ+yzbqwCVp2y7ywCl20zpkyzFs3lSw4BK/TS7YxeauOyXtIJN2XVNq/Wu4hSOsv4UsEHag5ML7w8pmFBkVbmm90BQZpeMG/i1gNviIWTZhFSXsDhggfhlfgVZAXQhvxyoQbkwLXBMuEK5BJmX0gM32Ue+gzIDSmANdi+2AosCmdUFHAAeBNLIMaPWpAwTqNfIVbtQLzdIu/A2jaAJA1CKoTdCwCs4y92ve5pWdCupOPSvWXOIHdFibRn7z+j6T2txpHf6cvgB8AdFeNvXbsgtbsQ7dQSfsYhI3naP20IlHbskHf29btYeJ/8Er+R7R8CO2+Wfy898zXv+noOM8vmXZOWrbKXzRQnDMzI2qX1Qn50KuwQyBxYE9kAv2cR+BcXgDVBcMQQOGmofHwWyIOcicv5nCOHRct8xeOCcVjXrVL0KDh+AhqNmD9Dygbi8g+KziSbDEyKcJl9INj0PZa7JqGIXj5MxeRWKBX8My5IgUNjOkbccxpt2Q3wgtwznuA+gCz9Jp+5BXBM/qU9/qK9/6c0bZun3EmrHfloHPjAZzSsdrQsMTxpQWd8nId8MyeMsmdMsxct8tYdMxYt81DszecYo6cUu6oGf+Hlz3n4RX/0l//1fmh7+yO/7M/ADjZ077f6p6j4LK99xjTz0LZogZSm7JuPh3uOQOUYcYCBuUsGtaj0XkWyCCwH/BbFBNkPlgqn38e1aZ8D4l54xuXuMqtA9cxldyyQi0RvuEDmgcCGj1AOxgORjMLJm0CX0F3Q6T8JFRMMYuEt6qyCwYAaWsQimEbu+a8EmBnM+tmIWLgSngUr7Yhb5QIOTDNea+TQvk5DNO5QWn5oxUeOiavG4euAEGG/Am1elj6jQ4Luh6T2syV4x4q+Z+u8jobSTYH3OISThyS7wgpl5xC/8V1frv+Jf/in31PbztX6kdf2V3/pXx6Y+cT/+q7Pnf6sG/ynv/T+v4deHHPwKfLGBTHCiZ6PCnIhbBkH2QjM4JndAjIcggGYApQBYANRB2ioR3lKJB4a/D5A5ax7wDogG0QlgOxeNAN4GqC3cABEoDWAiNALoFMB+dvxkeZAgyrkPJo4RdNg1pb+jTAHwRuj00Z8B8IIJAoqE1wuOmvs2EtB5UQOsxM++MVf6NU3tBKjhFp+/ZReya+2+bCpZ1OaPKZED7cU3GqBp1Wpe2aiGAUj8A+9Gxey7Ra86R626x1z7lf4Y3/U/Cq7/iXv8R9eo/KR3/Snz/r4T2f+V1gQv+Xdr9n/wv/yn++kd57xW34pxc8EdoSys+VQObbMQtd0/rgjakw6tHJX32aliG+Gv7PgFNCYhoFfOSUjyMy++HohDuOVgsVFkeJRPgBeeUTyAoEMCFQM+AhkHFv4d2AExGhVYIZU/JGzQPbLUKbAOkACxUohayi0acIl8ZetfBU+B6XV4DcCRTn3oDdoVr1JsNbv4BMfOCWnJOLjp2TTtExp25JEwqUxZN/JaN+BuE+N/Dm/6Ke/F7VNu/Yp//Gf10WfiNmHAV6zY5aROfeEjNOqRk7lHSDj3zj3jlZ36138Jaf0a9+hH+/Gf8+x9J7/6V9vH/Bb6If/EztvkIl37gGP+NV3clAIFZ9NCY7574Hmiulle1dcRLaAFQCNbRr8EFgS+27RLegs1AisyiXlMrprC5A1AdwJ0JhYPs6hklZjmClN4DIA/JD6QIrDUTNBlya9mFo97l09qsMku/FmLaF1PfBvugNlp6FzrurRw2zTXqlblPvbpHoVvsW4fgVgVMKj2o+ZiVc0bJPyXmXxBy9x1jDu0ihbcn2IZuklKvAmu/+ddc86q/+dRfetdccOvOvKt/RLTuEJK2bPz/vyVdW86x5/SCM1r+KS1nB5e4i0/Yp2ZeeFdcBtR/E259VPXNr/7a78m5T/Wlb+URMWnDLGDHJuzCo+hfQU9/hDYfRj1lxr/Gx79VpxfIErJIub3M0lE1VgmtbJRRMW4T+QJYkE/TEir1o2v6Z071rEtaJzqrm1M7xywbQyW1I9yTPoNAsgh5BQQB0tvYt1mVVhbavAGlrsOuxCV14hI6IM62AU2EpA6IuRajhJ3Tp00tkEImElI7HYKfahOyd9j5h+S0c2rBNbkA4nNgG3FsHwH2XwkqfgTXXvtUXrJLL5il54ySK26l8GcxSFnQDsDgfbfY/zu6acc25IyafUbOOaVknJJTj/Aph4QU+O+VZ8mlV8VfYW27jmEnlKwTTumP0KY/WPnH3PzL0Pprevl374Y/glu/hTVfZ3ycCn7SG/vSilMJwWOVTqJTOwn5A8yyKce494DikPYgkCzDnmMzu4BQwoOM0gkg1PYxb4WfF4AIUaSVAPkFIAAX2IY+d08SRl6ZnIeJ67ALfWbMq7ELanKNfYOKfiPrnuaR9sUhoBlNKe5l5H1SdHsl5XjOyT3Ap56RhPcmnTrFnzlF71gEHjMzvwsqL7mlF+yiE1IuDEgTsPMEm7ptG7Jh6rOm63liE7pnFbRp7rNt6XeCid51CNl3Dj9Ex5zikk6JKZceuT951f8KbjonpSxpe+y5x53wimctAn4EPbmKaPmZ/BoQ4Zxe8kdo82VAzRqr6DDuw17Glw9hLbjUL0Bwsdn9/q1bdrEfgP7i8/phQPxBcULLABEBxQJiiZLfj7AMaAZuA5wHChtwEQiPS+w7YnoXWA6pLtxBIP6dMbfSnFdt799gwa8xZZUtRdSP6zG/SKO/yLq+fmRzykw7ZWQeEzLPiLnC27OA29iEHtIyL/nF55ySK6+yC1bRqUfBCSHnjJh5hBZ+ubpjEbCtz9k39jm2Ctw05m2b8lZ06Vum3AP7wA0rn12HQHDHd2rGGT75J7vwD045HBdVcUfI8GNi8gE547t//TGn9DSiaQOduGEddkzJufStmMUkLDCK92Le78e/30t4Oxv9khr3AbIA+j2IK2iWwJFh4HOHiSUTjqmdgAhA7UDXI6yCX5gFPgXlB3TQNfGzVehLIALE9K8mPk+Eiw5CnloHthh6lqvhMxkJ7157lWy4RPQrYPvkcQMq5Ffijh/kXS7Z2Re07Aty9jEmFVywYxq47xz1e2j9laDqglsK6A3jkll0Qs48wSaeoeOPHMKPrAKPTf1OzPz3TbwOjDg7+qx1bcqyBnFdn3Zs53/kEHCCDD5FC5dYX+DTvlNyz5Fha+r4A6uAI5eYI1zyCTEDPHviU/k97tmynteKER9efN49aRKTskgr2vVv2/Kp3xI0rAU0zUQ9dw5uc0vvYpRPAx22jHwJ3RFA0TWrS/i5XuUskGsEyGEgBYKaBY8c4QdnQpGbN0JM7zXzbQAXoCJeOIc/l0MnOUMxxz/pUsCOaHj0K+C7ZXDvZdyePrI/JCZeMbMhYyG9z7BpR05xW8b+1z4l34PqAAIuOCXfvKvOmcWXrIILag60wFPhbRXCWyyODPgXZgHrapRlBfclJcySEnpe3gXsXFYnbBmxdy14x05BB47CBfinyOhDQ8a8lOOuueASl3yOSwV3X7KLL3mVZ6ENk6acGXn3OXXKooHnnDZjVImwR0zbYpetM0o3vGs2/JuW+XXjYc+ga+KyeowDmqEWoGVq8Wux6d2guIVZACoYmh858yunZMIq5Bl4gZo7DFxIl1mkjM/Ep3xEhrbpI2MvAksHlEhfZbE9CsKb9Drl8c/EHbZco84ZWUIkI+aeuqdDI/xvFZx5FX8XVF/zKq69Kr9xK645pVfsQuEe/ug4sP/cKvRM32dXlb6v4Tkv5TQjYTsjbT8tZQ8uWFJ2W9EgbhsAs2bvmHsLd0wy89nWYy1KOy1KOp46RUESgQuuKTnfWMUAlhdARsOfTCqix6Sc5pTxm0Y+m6b+oLI2XBN26GXbrMo9/5ZVLsiWuujkDtAOtlGvMWndkBEOCR9cEj/9d1tjhFPkG1zKZ2iHuORPFv5NtkGtPpXTYLkyLl2NmEXL/ILhV12ycgZVKQNKlF5FEmjbz0qU11KuY4aeZx7pZ8ycM2rOKTbjDJMmXHFmHbblEHnJL7/0KvvGr/7Br7lkFl/Qcq9oOefuiUfWQXs6nntKlC0pzJok6sLEf0UR23dPs09Ea0TMeEHeeVOLuqnH3DP13jXzEv56kQl315CzpUEeF7VYlnU/sQv7gU35Rky7IqVdUzIuKTnnnsWnfBAUtXPyLlPSqA0d1oFV2IlDzKlj1Ipb8jwmZZlRKrxJ0bNyO/wFt2pWk1uFz+6lAVPK7XOI72BVTfPqF4W/wEfPG4h/fQRor0zKtQlqFe6jEvHyvmWwrkcB1q9+zi50CHS+ike/IrFHxaNTkdqhQm6Xdzulph3TMq99S7/7llywc87xSdvGvgcWgd8EZef8UigBiNIPbuVPqCBi+hkm7tQ+dN/Ie0vebe2x48IDs2lRs119/k9k9Oebyh03FbvuqI2KmwPm7Rh6QqfYNuLsmnI3denrauQNFVz/bYMjU94PdNySAvHKPf6anPKTX3TqEgvJdcouOPYpmZJ3hSRaVMItqdFPbSIPLINhAiPWoZPOiRucyjVu+Tqvurh8FJ30Qd+nlpDZDSLayK+BVT7JqZpCmPg1AfmBLDDi1ep6VoAL3GPe2Qa0AOHBhr2Ysgkb1fEeBYWvTu9Tofao0b+o0FoeOqzYB5965v0MbxDelSkoO2Nmnnuk7Fh6j8s4fw+ovPIuF96nyCg898gB+0/RscK97A04m3KYVXH76fumg7f1rxzDvzlEHZl5v/5V7u0NhfZbit131UcfW+8YsndNvPaMuetaHju6jE0V3IiI6bmN/5GV378JqZfI8CtM7DUt63f/8nUj9rFD6IlH5rln/qi0w+Rj2xkZ5IoK6cAs4NQ2fN026IseZ9A0YNopbtOrbJVZuMgqQsW8tgppI2R+Qad2WIS0umd0A0EQ7urjkd1Lz+3/+4vjSkvfJ84hT028quRck4dYOZPmAQNanH5VOiRCpzTmkxzmg6x7s5j9snPEtX/pn+H1f4TU//CrueYWnpGTTtCR6wbMC17RBavgFLKUkn1GSj/FJhw7he3oMLdVSUvidjOiJsNiVn/gUr85xZ4YCHrFTJ/+Jt32m8zLG3JvfpPvvq87Lu24rkMD+1dUiesquIkHlsfmPuf2Yed2oRdOYReoqG+QBdjkH56Ff/iXLWrTL4mp33glkzJOUxJ2MGaknPaM+PvmgYe2YUf0rE5tzidtz0VC5iolfxWfw0z+YBf0xFRQzSobNgtusQ1/TsruEW7+CO0QFf1KmZSt5VFASvlk6VMPKJDlFDrkEDVhFTRq7DuoyRpSo36URr0Ut3sh5TLlEPwjqOp7UBUwvz9DG7/7VH3jlpzjkw/sg5d0PK44BZesvEtq1hk+9QKTAIE6svTb0aQtPXaYvGc4cFvnyiXuwibsVM8XELFHzKjpV6knv0qCF17dlGu/pTQmZbug4raqRlhWdJ8RdzgzF5zZBh1bBVzYh1w6Rly5xly7xp8h48DyK3bOH0GVy4aeV4zcaQDURzaTD62nxe23dDindlFH9lEH7omfNRjvVEgT9tEbpPwDejEluk2Dmu0Q3EDO7Tbzr7cLacGlf0aokPMIad3/XW6nSclFhj2zEjRok3IXadnzhKwxh4gRU58BbWa/EuGThONTCYf/JL74I6zxj9Anf4Y2CHdcENR84xSfU7JOXeMOrQPX9NkXHhlC8AfjHSOObYMPDDjrUKKSyCkR05F7BlAp/8KlnpoHH2pyNpWI3aIGzTdlmm5IgyOeQi78KjsobjYtg4Q2OfPY4UCffWoZeGYVcG4d/AMVcwo8Ghoq9BToC8RkACNgpasOwefUtBEx83Exi6lHNrPSSGBcF+iUY1TCKSn9kxr1gzKl11hwwK7YIWYzY1/eMfVBhjUx8/u06AV6nGLL4GaECiGLnvXVIaBRyS3ZmFPOzu3VpeR+YGb32QYPOUZ8NfTu02J8VSF8lnTqkHD4M7r1W2DttaD2p+Dv37nhlwibIiX1EBUNvAUAeUObvm/jf4wMF+7/aeF/oMfdUiYtSaNOMSEXLqGXdhDMoGunyCub0HND/qoc9uN97ad/byrc8Ktk02+yz27IdorqDj+yHHtos6fLPDb2PTLyOTUPuIL4O0Sd2YSd20ecQWvExF2R04X7DROTL70LvrEyV1TcNzQI0FDP0JEXhMRLz9w9UtIxKa1LnfZZhfJZgwUpsErICigZUkLHEuKeBdSMP3AMl3CJtwlpQejS8zGxL63960RsQlHhz+ipHzXcEhZJGUPmfn3GvE/ybp2yrmB8+2P7i8CqU0HZN9+KH77Q88uuPQsu6JmnpJQzXPyBXRAQ3g1V8qK8656hpzDzDbh7uqxtFfK6jOvsQ+s/2VnXxCQAMyCFVxaBp4b8Q23POWmXD6Laz0VUq36Tqv5VsvZXqcZfZV7fUuoVM15SxB0b84E+npgKeSS44MIu4sopWnjDKjIC+NWJU+ShU8SBa/QlN+8CG72pRVnTphwjg7/xi74FVn6PbriOb7qKbepUpnQpU0eNfN57ZBtR0ggxz0SMuWru8c7hzVZ+1bKu8cjwpwhzrwpWVpcpr0IGnegS9YKY8M6RVzVs6N2lSumUc3v30Kr9sc0bMfP/ZH26Cm/+Fvzk2qf8gp13Sc85wgk/6gG0P3IM3TbyWpJ3m5dCTolbjz6ymldwX1YhrCngNuQxcw+sJu4ZDt/W/Rc95xoZc2EadGnkt6vKPNBgjYlbv7mvUXlDqvyGZOk/xWt/lQBQaPlF6quI0ZYm7cjUB1xwaOx3ZhVybBpwZhcurALHsGO7EKg4YE2HdsEnqEgIwJoqCVwATXTPVnDplf8jrPZvFzT/yHjxVZMBjbxblbHkkjCFDKHEPdV0T1BxjyMlvYYh6xKlzxD+iksbLuaVkWeZonuqc0gbO/NLgVfxoBrliyL2vYT9i4cWTwG0xcyuop6d86ouvcoPgeoT00DJbdgEHjqH79sFrOkylhTcZyXsJ0SNRkWNBu7r993TH39sB5R2UcJh/K7R0C2tvrtGEMxjDa9zHZ9jde6ROmtWwqH7gVbrQ5XCXx8W/SJe8ot45a+SjTekX9xUXFDE7OtxDgx4/7X/0jb8yMQfXADMAlLg3DFyTYuxqELYFHZN1poyfkMZD/RhW4e+bet3xSu+Diy7Dqv5Ht9ynfzsP0nCe5ZHdb22HGMXzH2IwdXm3EIlTIytTwUu7rkcKkKXmo5wCmpyDG4xYJdJuyQ6hLS4Rj7bZWR1yqFfSTq0PbJsfWA+qEVasuZv07IPPHLO6Llg/y4qatMmcMfaX7j5ppn3oiJ6TtJBaPxdTRg9f9+z3HNXZ/iByfB9o6G7On23NX/Ssk/NA1cfY/YUqPuqHosyqJ772h3Sqr1IrYIbj/J+fVR2U6runkzLfdl3d1UnJOznZTDbWnSAkhMTwal50K4h79QxErIAIObYOmjXjP8tsnhRyR3SbUOf+TsjdVWDClQalOU3XtGVf/l1WN236MYff38A3a/qMabDndTxWjALWHaP16Xl3Dbx1qdl4hOey7tESjmHIRhZ3eSUj5aCOgmHSE5+LybmRZ827bUEsvmhxVsph23n0H3nsDlz7+vQpjPvqhNy9p5L7KZt8Jq5YMPcZ9fcZ0UVvyiPmpay6bmt/fW2Vtct9a7bqu03FD/eUfl0R31Iwqz7rnb3Hf3fGfnHRn5TIlZz4nZd9/We3VR4ek/hnb5Kvsj9rBtiGb+J1IrJ1Is8fvJA4vltudFHllMSDsJ7tlXI+zqe+wa8c8fwS2ziCSbuwD3u97CKPwJLT3AxwmX7yOALYvyFR8IZM2nXPkh4L7Nn3hWv8CKg8jqi8Ufii6uUZ31K5CENFrC7ZcvQXUImNemdtHOUNiOLk/fFxKvooW0ggpryyYJfA1r4oU0oKbGdEvvqk4L7JznUhmPAjnBj7chtm4ANatJlYOMVv+6ImAkuWLPw37UL2bIUbBp5Lii67Vh5HTjwNw1p2waUXX3KooJT/30d4DnAdgDbPorqjMuhfydnAbw335KtuSVVfUuq8rZ4h53ySzPZHBHRIrHHqffvp4v99tZKuUlCtum+1IfbqtDnxx5aQXFtq1JOLf1PncJ/MHP/E1h1Rcu8ICSfQkfAJV2A9MZBd0w89Ui88M75V2TtphH3nJAE7eCMX/w9ovH3pOc/0p+CuhvTYI5oMGdNAvYJWS6CGsiCRw7BgACuEa3iNoEITNhzQkK7IatCyjnOt2yMEfN6B59wgIs/I6UcoqNWzYV3KG6gwo+pGUeUnF103LZ9yKZt0KaV37qJF1D6cQnLn/TkE5eQY2vfdQ3ClgZ+VR459cAE8h+Yb9OvMs2/ykMM/yRk7Wixau9K1kpKFN56VPnodqvOgwLZ20mi90Ju3PBFINLFbuaL3m2Wkmm8KfH0N1l42clHVpMPrRalnE9MeEJG4Bx97p4gHPika3KacPt3SvoVJU04mMIb9n+G16woE1a0PQ7JKfus7Muwxm/xz37PeDmsSBpXZ46psSa0ufu4NGtK+kP7EHpWhwWvPKZtSQYVjaCndLpHvbMObLltFshM7dyLeXriU37lXXJMTNp1CFwyYMyqEcaVMOsOgbNmXqtWvhvWfps2gjUz7rKOx5wSevSR8YCY4YlT4IEl/8jUe1+PsQwoKG45LWI8dk/v9U2lll/kfhBSf5JydnSZjWJSVY9Eix/cfGstE3EbkSBxK07sXsIjkRTxBzG3b2Q/uFcn87jljnTLDeneB0ZQC5AFC5JI0IjH5oIrdPw1LuW/XrjEJQl/PNYt/swt9tgt7oSQdExNO+UXrasSACAOcAlHnnnfw5svQhuvklqHFYkjSuQpLc8pHe4OJtUr6d0Du2Bznwpy6ntUZKupdynCPqjFwqcRaLIaIRsX9uJb7IvLwAbhfkzE1G07/zkd6qQyZkTGsU/CasmEvWzmJbxz39x7QY82q4qdlkdOPDYHtTsqYbaghT909t/QJK3LuSw+sp69bzx5T7/vptaGJhGm/qdHwayGW4O4xEsTmUq5O8VKv2Qr/5qm9IiFQDQaafJ++zXp/p3sB3cqHoi0PZB+ekcGiPOystuKPHpJ1gXIJcjES2Q00IFTlxgoAeGnSdjEU3T0ObgAHXuAEW64cO6VuySLXlRw23ONOuEV/xX34jyw7iCgZFiNMq5Bn9bmzBsJ9ok52JCme1b+uoxcu6AGbmGPPrNQ+FOHtsFtBuwKA0ZxT1DDZfjTq4DGI1bRETVrFx29qE8fU3Dul7AU/uzeA4MlI8aiMWvZ1BNcM6eBn1d1+/sn+EyFW/krOEyqYq4xkZtqhAVIYFGLydv6gze1z8wEP8gZ/+tZ0iljUif98IOzconSrY9uan73EJmKosnit6Ju/iP4wT3+vRspj+5VPBRpeyzZeufxoLQplNXfmxegNlUIB/qepzaB0BQuXeOEn7tg4k5co45dIo9dogEXjjCx+9i4C3rairzbrBxmzT7okJHzI7Tp96i2Xe+8XkXCiBodamHO0HeTlI0Jb5ZyibXyq3UKa/EpG5R0jkT4VU7hE9st+XVOIa0jeV1XcW8uQ9oufGt28CmgiOcNWRPKmL7HFt0PDYT7F9zXXTQgL+rTFvQ8lnQ9lrRIs/LIaSk78MI1JeESG/fdNfbKKnhDEbcgajV+S2/wji7olv9lFvzEpb6WUnpuIhopgkiX+uc7F80IMUSypEi1sXKuhFi8yO0kabFYsVvFD++9VpR6cudhxz1t4LzLcq4rcqh1Bezfvxnoe+YQduEafY6OEQ5MFGTBvlPooUvEkXvcGSPj36ycZTnMrAJmFxt3yik85ld8D285868YVaeNa3qOqrPmTPzasrsg8poeWeq0HBBL6OinaoRkBD7+gyGzRLguOvp1Yfr768T3l5HPT3xrt7BJcya+kxpkAIJROYdecdMvD3Q+3deGXNgwZi4b0EEXr2pRFxTRkAhTknbjsg6XuIQr55gfDtHnxn6bMm7jd4SFsC6H/hcm5couArD9g93jDAlEivw9f5FfCx7+VmXw6AlSN/DOLyl3bvnf+yVbQqRU7Eannkr9bYn2OxrLSlgwaUXWdVXObVuTCXBw7hh67BB86hx28vcWDgdOwZAIJ9joPbeob175UC+rwNBU8KAOjjwLrvxqvwU3Hnnlj6iTRzToE3r8OasQS68S+6BaI26xsVeJPrsg6dWaDDIMQU7uNPeukUbG+ZdPlCe8vE78cBb2bJuWv+wcO2PMG1bCjsi7/r2Rh8VnEZ2eh4bdYkadD4zWTT2X9WgrOhRAxHkFV3DBxGPrb/j4c5eoC7uwUyP/E03u0E2d3lsae4q4C/PgE8vgM0vBcyuJcu3ffEV/i3p8I1/qfpGySIzSPd4tRKHY/TTJOxGPbuXfRVTcv/tMVPHzfb01NcKKHBY6wpK066Yadd/Q68Q28NReeAvfCTIUWOkRMvzAOfIIE32ETzhhZa7JC122pO8pbF6eBd/Dmi4C60+CqheMvcc06Ism/jOeBZD2JtwSG/8aTUq2Ea/c2r/GyrsMgYx8BUCgSc5zS3jP96mBLDgJbN7xyJ+1DIZnDipghxSEu1gMStn0PTbrf2TeK27RK27eL2m7Zkhf0CCBOJmTR09L2k9J2o4+NPuGSzx1jjizCz3V8+y7qdn9m+qmJPpCT7Cr5rlMdCuV/SVVCvHcRfGZq0qS1K1c+ZtPHdRzZcQzRW6lSYv43/2lUPx+nbT4G1HVrw+NV1SJy3JY0B1Q4btajEND7qGpD1DDMwehF/7rglN8IijlE0oqZMGavLvwh0GQEdvwIL/8xKfyLLj+Irpl1pDbr0wBLAws7PnV1EefW0JM79Bh5GswCuzDmr2KBxD8ylkDr1oTrxpy6pfDyr7L2NeHgifr7mkTet7DqtRBJfyQImZQxnlY1rFfwmpI2nZU1mnwsRV4ZEDKYcOQtabtsaxOAHkPQn3ikdWgqNmUvOs3TBwU8Ogd44m7Zn9Zhl1o+pwpcUdVDFu07n9BydVa3gsQRYALSuVFnlmoJIvdypIUC39wK/HB7fjbiGZFmepHj79KGM/Juywpuq8q4SDDN9UoIJx29FjghSPLgCObINBmR6ioM0LSNSf/yqcEIBNcMK+MP0DH7uDij1h5J7zSE0HFSXDVvJHXoDJ5xi7Mr2pSeHsqJSekdRVksrmgzkxQTc/+gsDEfzDyqtOkFyNDnu/GtH1PfL/HqV51SJg2FIxrsxdM+DP6nuOquNG/9/IYk0MKP6WTd4I2OShpB35ZUMUtqGCFW6zJOo2JW42JWQyImP5Bzph76Lgi6bKjQDlQYpypcI8V2aNKBq0atzrs5V7by7wjakQ9+jVV4k7m41v5UmJZj0V9bv9SqSSd9/jXBpmHTdJSHRraQ0o207KOoL5BCEF4VxTxoL4hFwAXDy38hR9GoSL2XSKuvIr+DKxdV3BbkHZZNuDsomP2ycknXkUX/tXHguJ5M+9xLY8RXeaqa2JYTo8cOsEuqMmzYkISk6TjWYJNeONdMojQY5bZ+Derk3OBKbtwK05C2vaoRfMW4dOmQSv2Eau2IYumPkOK7hPK7hN//xjslJzTqKTtkLjVkJR972PLXgmLrw/NwC8Tkg6DYub9oia9ouYbJr7zMm6rkm4/jf125MjnGrxTDe8pXfuPphKfrR+PsI3TZRGZ8oiAe7+MeRr43PmFe1eYCCWy4nni92oVbr9SUH6nodR4W7ZfxX5C3hFSbAOKQgG3rIDfVKeDiIZEOLQLBOZ26Bb73TNvSRoFmTInh9q2CthxjdrGxh0yc098S48FhYsW/H4dWq82a8kyfAOTJe8aq+dZRsjslsWlaTHyPTI/U9I/Iiz8Gm9ZhABBwsW+xblnbQrqdsn5K7Yx665JW+j4LVT0vJH3uBpxVoO0oEWdVnabUXCZkLIbk7AWekHCGuzvumv4zSVkWZU8J+c6Im45JGF7hk89J6Ts63BmxZ03lYjn5n7n1sEtd+TrZe42adwuk7jZpCJWpvjPN5byMzzTXOnbubIisfdupt//Z536w2dG4k+lFPrsjFvvqPaauV305K/40aalnOYkndeUidAa9vW5e0beh9b+W5a8fXt/0OMAmSvK+Gl5zLZN0BYybA+beM4tOfYuuQwq28XGvlLEdGhQJo0D1m0TFmjFbnFvvcrH1Ki5ksgoc78aTOxzhEPoSyVijj6r3Ma3oYtRtsKoWkEnrTnGH1HyD0k526i4DZugRT32gi5jRZ8BLpiWd52URULMwRHjMnbH5uwFNfd1M+9vgsz/zS3+tyDhyj1ww8h7Hxl5bBMyLYEaFrP4Kmr88b7++4e6r4ylG5QelT24VSCGyBP97bmOQunj2zVq95+ZSqeL/hPa5Dsz5QGk7oCW5SsJzT5Vx2FV9wknxml7yqY+eeaxw5w08r+gAImwY8w9shbMPbKZfmQDCfINFQ5z27QUrNkG7uASz3klxz4lyyAlKalr2Jgn4nbd6uxZs/Bd9wJiaAsq+iUq5vkdC4Ghd5lP1QgCqKE8OsVG0MRI/TJMKFgglm64pa7ZRe3iMg+IOce4jC2HqC2b4DUT/poxd0GTPK+Cn1XEQCMEL4xI2Ewqov/f6c1bNvx1ddqinDvMRrjZnZTrprbnT2z6hVXohLhtn4ghsIkOMb33DzSbb8t8UFUCmdAsJ9+iKPlEWbJBWXQAa5gheqv8gcTrh5pfHhmNyNv3yFg8u63yRdZ+0dhz2py878adkRJ+UwDQsKyEBy9MPbKdELOaeWy3okLaNub/xMQADEMkFgzZu8TkM17ZVXDdrIUv0PwNYlyFmOkrBfcBLe8Np/RdfptncT8158sda38gSI6hzQgQSPftYiz9WsJr5lc865dJ5UMWUUsWQVtO0fvuqUfY1CO35B2HCOHOxdb+awaei5rkZQ3ykhoeqOiBHndNyWPf2Gdb13tXm7OlQllTwK8rEjaVSesq5H/TSo4tww71PCcfWvc+MOm4p9V+X+utiPrTu/JvtdXr70s/lZRvlJRrVnr0RE68VOxR4wOFjsdGPeIWY1JC58JT2h/ofJa0mNB1P0V5zUg5Tvy9l8epqe+hofeuLuvAxHdDx3NDn7tjypsGONSmroN+MeUtWPtfCaqA2i5aCNYwMQeeWeVixoV3DTuUaR3K9GYpN9f4N9iU9vvWgfLuSRY+FQgwXp1abMars/OpX2XWbpAqRyyiF+wjt5wid1Exu8joHaeoPceoPfuwfduQHUs/4W3V2rRFFcK6CmlRFg/zOLUOPbUI2dXy2tVi72qy1oQ72pDAFwc24Veo1CNDwYosZk7SAXIBON+7O+ofH+m/ENN4L6H/Vkq7/q5Mq45om4Tcc1GlVw/UvjwygRRbVMAtKeLm5dCTknZvb6u9l9CdkXOal0UtyKK3tOhHZn57pr4wIPg7ZoINM59NC28oz01L3pZ94K5TyKKF7zk2cVSNugBXEtN2KOltiuhCcfM6Wef8+6ZbcU9tQ1s5pcO/GPFErQL0WbnCTX1AJjqFPg0vn1hj1C645Xfq+rfJUddJmfuEjB3n2H3nuH1k9K59xIFjxLpwOxvOton3ph5zRNTmxCIA+tOhedCRRfC5rfAr8z0d7oYSZVOZvK6AB0vOnRIOjf3PjHyEqkHKETJ54IEpCI23IppvH2h/eKzbel+xy9DwhYjSq3uKb++pfX1gOCmFnJdzW1ejbGpQV5VxU1L27++qzcu7QH2tKhE3NRmHpoJNaH7/jwv8DlDhl/iYKTnnNTNP4XY2dv7bVr7DCrgpHfaaU8Sue8IqMmLIyGfEJqhIwaRMyUkTFa3nWcqvmrDwqxe1DtagZiKknOMUsZn4xI9x3Iptdt2EQ1q7uvcrJUadBPqYX3nJrT5Ep+0i4/edYsELG5YBa0Y+awbcTQP2oiIeXLBvLDi2DDmyC/+Gij8w8tvX5q7IESALVmTdF6TQW7rsK4eoQ1P/PQ3mhgx2U859Wtxx8JHlR1GddhGNjw+02h9qvxJR+yCm8faOEgiQ4UeWM5IuK8pgKk24aZIaeVnBfQ7IyCMroAbAEff1vfeNvPdM+fsWfltGvB2YgEvUT2YqcLZVA8aete+oPK5PGr1g6L1iHtSv7vFZldCtRt1Fp/YZ8JsUnF20zW+Z+FoG1PErR21Dmv6pxwWyiFDBZjy0j8HGt39hl006po5ax79T9XwqS2qVwdZLoI68q44ohdvOyTuOCdt20Vs2obt2oauGvEuXaIAA4XZjVsFnzjEXzvHH5sF72t7b6qxNVfq6PGlVFrci6zYv4TwnjT42D/z/0/QXQI213fY4yL2v9NuOu7u7JWgChAQSSEICCTESEtzd3aFx6W4a2qBp2gVr3N3dre2V7/vu3P9/aqqmaqpm9un+TdVTp0I4OTnn2WuvvdZJ8mwQyLtq9DN93o6636ySR4+45dtbJqCC34obv5Yw6Lqu8fqm3pCU7Yy824w8blGNuG0YsGsWuK7rB2ND329BDTdwy2ZRxWtTm75twtq24O7ZCA+cwvdALBOSZ7S8xmRdx+CF+oHzhhxkUR+bsA1U1IZd+AsVz24591mr0BGToFca5JSMbjm3BGViFin7Na9mVMkrRYWYJmbFqlF2Tw2vGX0fUDGPK4AseKxGv69IalUgtMi7zXunbpIK9n2Ldz1y1tDx6z+OO2cUuOUUceSReOIUfUnIOMMmH9pGHlqG7BlwV9Xpm9oBP3MBgLCkiJtRxJ06xf6JST0zEhzrcDZUfOeV8CAf+iUtP9w27ZEwfXdT//1N/QEJywVlzx81BSH8VR3ypgHtx/pV7C1jBszCpILrpDwGWdfIMHDbImjNjHPoEg7q6Cs1c1LBfULOfVzRa9M6dMmUv2QRvGAhXLePXLUQvtckv1H0GtJjLdhGbROL6ElPTAOKDehFUAgi7i/edIpUJKSKmQIXkHIZWW9qWXdGnTM7tdnNssRWJZ9GaY8mOdw9VeKyT/Y2ueDAu3DZMR781rJV8KRBwLQB/TP3zhm18AyfuWMJRjD2yCZyzywYgLBvzF3XpO/o+K+r+qwoey2qEL64x19Yhx/qsPc1/TdUSLNKnjAFQ1LWfRJm/eKm/eLGAxJmC6o/899vXQfpCbaBDL9No4BtUyb4gh3TwE0Dau91S1BHKxoUkEZ7dqIddMiOa9iUIg4OOKGIWzJkb9pErNuGr9mEr9lFLJgJFi1Fb1V8Jkz4y3axy+i0UXxBQFa3U0jjbbTIJaLFv6TXKqRJBp8qpuaVLY9Jpma8iYl92GsWcV/Ku0ud0anq36nJeKTuVyfr8VCDskLIWHFLWUQjXZanDBmjGsQxDcKac+glo/wUm3pgG3nqmnjsEHtgEwF0cGITtqnHOjAVbOr6b2r6zcnhJpXxe8ZBJ0a8TXXyqioJavuYDOqThOWglEXvLeMBcYtVbW9IdeTjEH3ajnHAppH/jjlr0yRgz5K9b8E+sObtWfBgInYteJ/E7UAIIHRow99zjfzimzyl6DGrTJjW8Nm1D19DlnYKXbEJgSnYtAkbMuMOaDOmjUVbThnH1FpjSoEV5w4x+ekNO6G9sMkn50102wo4BWSxPwfBPXr2e3bW29fa7G7VgLfavOeqzA6NgMcazPuq1CeafhukrEEj9ic9/yEdv14Vzz5FbJ8csrTTCynbU9/sY1zKsVf6ASZhH4UsdrZpGrRrG7ZjIQR1tK3HXlEjf/NKO7QN29JjgsJfUPaaknMZk0EPS9oOSljCXKzpkta0fcARLmuQfoCfiVy5LW/XGvmiBTDCnjlijRAD7hQJJmVc0XVJlwK1+RQXi5QPVcKUste6VRDSg9gSaqRwxUa4YR+6ZMQaNWDPmUUsWSZs4YqmQ+4D/7tFt0U3T6NF9eaBVRa82pDmWVNejZghvUzRLdUzriMy+917kxC4+NdavOeanA4tdqc2bFkr3hk7frmbxJxjavEuLhW8I5TcIXXvXpgIZexHBZdxI79tt5gjYtqOQ/i6TdC6czDY+EPXmF1UyI5N8IIWpfe207592Jlb4rFj1CqISFWvBXUCskSkAmZJzWtVi7Si+f//RAzS3jjg0E6wY4V0xtuCLLDmIQs82Qafu8Zeeia+vmHy/DdtmIhFA/KwtP2kvMu0Cn4VZJKdaM2SB05x2Zy3aidcNOOtWQXPmAZvOqbv4UpnyRV2nGoZpxiboDvkrG5CcoeUU7RlUF1k65J7wlMxGecENXwWOf21W1hbi3X0S52gbi1utw73mQ7ruRb7jR5vm5q36Zd3FFB+Qi9ddY5fsgtdsBBM6PuP61BGtUijml5Ter6TepRpPeqYKrK01bgKfkABM6To1ivrvGLLX7UVneDSz4k5Z4S0U1zyEdKxMWjDiAmXisTcHFnOC1n73IAO0UY68qFDtq24+zZBB7b8PWvepiUXTOGxY9gFPumLd/rLawZvbxi8v2k2JOMwIoMCObBs4LdkSFs3Z69bcVcsuSvWgmUrPhTvU9+iBeuYTdecdWIxIaodG9F63UZkzauKaZnxSnys5pFEyXjJrRoh5yEd7vI8Yh8z8nsdBE2fUl8Oumb3WsU8VWM802K+0A58qxu4HVB4yKo4pJUe+ObtEdLXnaMXrYOXrPmzJqwxbfKEtu+Etg9c/4w2aVLDe1qTOK1FGlFyH1LAjqp5brjHnvkVHHpnnlNyD398j/LcK23XKXIPHbprK9izFezaBh27hh1jwo+w4ciNIJfwQ6cwxAVagABj7zsEH7qGHbpFfaPl/Sug9AAT3ydr/0nGbkjRcdeGu2JEW9T3XUaWAqJv2gStWbOXzFlLpkyAw4pF0LR99IZb9qJ7rhEpFygfE9kq4xLrGt4SUjOCjbonpkk28MvzTn8R3jL/s9/vC3DKrqJ7BqT8BWF7HzrllZHwhQ67W4vxXp+7Sis85tQeBlQe+RUf+uRueySuoqOWbUNmTFmzJsxFM86iGQum4MeiTj4zmqQxZc8JNfwUSBoj+i4p/ZRVehlYdumPLBEPlHGKTz7xTNpxDNt3CNl3FO7aBSEdAByFB5iII3zCCS7+wDlszy54Dx18io8+wIRdEGL30RG7NuGHzskXpNxBZZdhZdcZA/KmXdA2ir+DClqxYKxaBm7ZB4FB2HEOXwIg2AYv2IYseGU/DL97U4ei7ZXOLOx1i3yg6JGA4lX7pHaq+WRdtw2WQIVwK4ZIaZ1ikg6xvmmvbPnNhr6FV4z5U/Fd4/jiXusY0IgvNRmj5mGb3MoDfs0uo+KYWbnvk7+NSd3GJK85RK+gQ+Yt2Avm7GUL1rJZ4JYVb1rLd0GXMqftC7Mwp0maM2Md+qaf86vOWBUnjNILehFg4ZiQso+NPcAiH1XuO4XuogXb9kFwqUfu0Wc+qeek1CP32B37YMDFobNoTNFjxSjwyCn2Ap9zTsr/GlA8ouo+puWFfJxlJ4DtlgPy0dY6CnmMrDDlFA5medYqyAoVpOcW4Zv0WEzW7YpZkB2vVlQ9LGkvoqZ1JTxYtuTekXeOvmbO0fbJSWpfFfOIeWInaLEWNKp4psN0YIT3B7h188SyDyYhb3Q4y9jsHVHtrqjuRNh4zL6z75237pq8i8vc8UhZRofC+8GsAwrWLDkrJsw5XUgH8rwOeVbLZ17LZ0aXekpM/xzWeMSqPGdXfmaVn5GyYAoO3eMP3ZAljPcxEXANP7pfCvewYQf4eORra17xh7aiGSWvZQN/4PkDt/jPfiVfGOXfWRWDarhhdY8xbeKaY8gONmrDOWwXE77lHLblGrHhHLHhErXhFr+JS+wTVEpacW+b+cc0Tokp4H/RC/BLf8EpfPeHKUsZG4+JuGtAy79tI9D2ybTgVJHSX4gRM96Q0l7qUopu20dZsGsQUmDWDPtVDjskzWIz18nl04TcXVHtSXDjpmfOOiZ12TFxl5C9i89Yd4zadIxYR4Vs/viiASThggEdZgFZ4EyPtqTjt2YddIGs35/zNeLuCbfyjFl64J1+4p22T0jeJyRtecTsecfteUUfEhO2AAVe8ftecUe+Sfu46EUtypY58vV0yPB9j4S/eLVf2RXvZNH9Km6D6rgRXTJEe805fMsjet0lYtUldA0TvoGNWXeP3yCmLrEKxZSJN6xFty24PkmPfzfliaNCwxumHEPr5bGx9vwaZ2Gdvl/eLVSIIi7RWtDALusXCyjux0Y/UnBPvWEXQUx7wS35pIrLkDLmv/TKHcJlLFJKp/A5Ix7JM+5Ja9jUHXz2FiFrh5Cx7Z66g005cEvcdozcdAiD3IYpWDZmLBsFwCws6Pohy7yZcKBSnpEy4LI/C2su+Hc+8+8cs4pOAwsOqBmfeSWDCthpK//PnJxLcuoZKenIN+GCnrFmwgb3CS5gSt17WAX3Tt75lazDaznH94pO7xVcelTdFx1CFlHCJcfQdbfoJdeINffoFfeYJffYRULCmn9ebN2YmAbligVf0zvVlFmiiEvWJGZFtsz6ZHRJu8aqE1LpGc/cou7/tzFT3j0eHXHfO/WZmEtEG1rQBDbBTtDELh00oZfdsgqTsI2kxD9x5dRVWIm6UBGv0JFHEc09uv6rrnHIssDYxB1M4o5L7K5z7AYqDOhn1Ya/YBywZsaa1aFMaxCX9OkwBetWgnPk24fpZ8T0A1wi+BlggQ3HEEjdZWsOUsbMmEuG/vN6FEgceNWqGQM034Y5e82UsYcWvZZxeCnn8FTC5omkTZccuksG9VrJtU+POocWjZgHTtjyptDCBWzknFvEhIto0TtpxSvrRHgPI6g29c1ScI5E8yq949u94h6q4JLoea/x8W03bIJv2gqF5X3MorfiDmHqPpk6tAIN70wxz+QuuHhxhzhsXAe3fNSAUgwokHNJDC4b1vPOlXeKV7AJTaqZjsanL9MK1khpA3CRpmyo9lsOUXsucWuoUOC2JXP2rAENSQR92qQGVEfIZNq8EePMvwhZ6ZGYCUBAlrx0jd51idp1CN20FWxAzbfmLBkFbFiy1syZU9qkeX0aTOKaBXdChdwjje24bVZ327RdHtUmZfNUweGxDPq1Br7XkNJrQh+yYk2gBSOooCEUbxDFm8VH94AkpVQcBN/zEDUKS3p+M2BeM2Ob+uVFN0z+bhxoEVgWmPvKmlsN1OgR84Ce81IZl3IbHaFNLbTgVIvh4jtMGJVy2JSAgn5i4gt9MpBCjGt4W8KDVWt2jZxjnBWtzDaw2oCYt+hfPE/K3KQV9howYBZAh67aAy3FQoZDKu7jEhfsgzfw8Xt+GVukuAU79rp7+Dmr7Miv8Mg358Q3e9ctbh8bt+cSfYSNg3KwYS9ct4ECzlyzYgFrQNZMavjNaTFm1QLm1JgDsp7PpayKbuhX3DauuGl0X9quUxEDU/BSxe2jEaXfwv+jCfmBovMDJcxDVc8Odd/XeszjgOr1qAeY4AaYgl+1/ZQxMRJ2IcFVg2K6foB/z4SHAHu4Zkz0A+ewu07hd8EvAhdYCZrFnKMe6ftXGDLvOEU98c14b8qslXZOc458Qkx9o03Kl3dN0vXOo6a/s+U0fhJUTxMzpr3TwDsC6ta8s1eAFIk5qx7pqy7JE6bCUVP+Ww3fLmWPR7LoxzL2nXJOp8yiy+DaU17VEaNon5i+T0zdhonAJ25ho5GV/qA0okLHNanDSqRxFSqy0p8Wa1o5YMMoFP58KeuYf0OvSsqy9IZR3W2rx7LopzIOz6UcXso6d8thn8hh7ko7tsi6tCsRXuoxeiyCZ0nZiqZBXjHt9NTOq0YsMQXPW1ZBrLxXv5lw1QjpupQcMMhSLnFQEe2CGxklA9dRESbMCo/EDqTBrBIh2z601TPllRW3QdEjQ5dS4pXY5RTWZhxQ9ZsJHyVoRgnu6voU2nimzyG/3kmY8kqexaWsk3K3KcVb5JJVQs6iS9qiQ+ISOm7MmP9Ri/ZcCfde0+ejOglR03Zh8/aRi+joDVzKtmfqPCp00pg9bcieUKeNqvvN6jDntJlwwRPqUEoC57VY60ahm6aRM9qBT+UcC28YVkta1962bhS3eSTt0CmLeaOEf6+A71Env9GkPNeiduv4vzViD9mFLxOzR6h5RoRMn6SnoH/cwu9LoyOvW3AxoY227HIwSKCFKNmvHEOadSh52KgHooYZabdkM1aVGilHzJ7foutT4JX8nFU+YkivUPZIRwtbMOEPnCIfSjnHy2NSjWllSQ/W9Un56u5pWtZhE+SsUVziGDZm0jVmg1Kw7lu8TMhdweeveuYjPYBto2ftoobN+aMWojEz4apD7Lpr/AYmaQ+bvuWYuGYXt2YbtYWK3rAOXzIWTME163FmdVjzeqwpbeayYTCMdYvIdfOoQXXqPRl0yW2zFhmHVjmXJglUp7zbcwXP9yqkPlXfAU3qex1alybltRGr10Iw5BQ94ZHaJrojhQoHL1Dw4sg97O5NM54xrdg4oIic8lTOKcrYv8Q5tCWyblwcHaVLLQQU2AjvqnllO0W2ien7lYFfdo5qd4l+TMl6B+pA07fQO+k5WgR75FrwGkgpLwAUptQiTc9MR+HdelHDCCFlCBs75Za4RMoGHbpCKd6gV+5QKtbcs+dQiSsu6eO2EaMWIWMWoVPW4fvknE2vNPBX2y4pa+jYPdfkFeuIbYf4NZvIZbOQJZPgeSMuTMGkDmPeVLhhF72JSli2iuzRIFVJ2ZaJWz1R8OhUwD1R9HqpTn2rRu3VoA9o0D6qUV6p+3br0Z/rM3ptQibIOUP+xWKKBHbeB1z4Pc/oBybUgisGAfbcO7SMLnVcMsgBWUyMsX9xdvehmneWSWB5xP0lbFKXCinHPKhOzAr53Wkxr3rSM+UFSngPpgPEonvsE9cY5FOmgIJeQdUoCEx9cqECNiX10TY+6tG0oG7MJ2PEPX6BkrtIzVvxK9pkVK76lix65KwSCldweQuuaVM20dO2MTP20TP2URteyaseMDWxi+jIZXTkEipi0TZi2SZixSZszS5i1T5s1TZ03pyPtI12STlyy5oyC25XwBTdMq+6bQOX+kqV/ELd74NO4EctxrAxf8w4qE/br0uL2q5BemstGHVPHiJnhZd++sOYreAQSYh9xCnu45T03rTkmdGLvOMfpT1dFzOg69MKDZmlbvFPzDg1sthESmFP+stTE1aVCa9WzDqoXgaTEJDXA5AwZdcA+DllQ1acGsgTMW1/38xX+KROevYbFL/+FyNuQusaNqLNilo2FdoIGTHhkz5Jypij5i5Ti1copZvUyiWfkiWvwmWP7CXX9Fm72HlU7CIqYdYu+pNZ0Lxz5BQ6ZMYxbM4hbAEVsWAjWrOP3HSMmrIQrDjFLdiHL6AjdjzSdrBp7w3pxRI2FZK23eq+vfrsXn3OB9ga8QYMeING/E8G3Pdq5A49/ycmgV3Wgl73JA3H8KjayZtWQoi8tH2YZ/R98ELXzHkmfnleSU8Ise3a5HxlfKq8e2LSow3HiAfGjFLwiEG146Ca5AhZ4BoLXCPbvVNe2ofcN2LeuWYT4ZHYZS9scgi9q0LIQIfdd4t9As/bB99V9syC3YAmrbh18i4p7tFP39ALB9zjh3AJsz5ZMAurfuUb7IYFUuE8Jn3aIXEenTCPil91TVt1zVh1ywA4DFvx4fKGrXhTdsJJK/6stWjWNnTEgjtuJxq1DZlyjuyxYlfLOlbKOTfIuj5RJX3QZ/YZcIaM+R/0WYMWok/G/GGT4BETQaeOf7KVoMmI/sAxREGPYcMsF1UOwxSIKRFkUOHUzG5Wca+YFlXRNRotbIx5sCLtkvCHtUiDlENIfU7KfCWDidPwzYtpXyFnvZTFp4uZsmv9CweJmW/tI9rgUi05teTMN5ZBjdi4J7+YcMA1eCQ9B2rUppZA7aQV9sN8WbDrxKQJbjFPcSH3RhilMAuf3OPHCOnT5PxFRuWaf+WKT/4SLnMem7zglrbslr7qlgWpseSauuCSOOMUO2kfOWDM+WTC7TMNakeHUOgJEXKocgWXOnnMfTWfJ1r+T7Xp8K8BU36fIatHPwBppG7EHTAVfNQJ6NdmDBhw9T2SjDxT/FK7/kuLruISq+uTG5D5Ws4p5roJSwoVEdU4Q8l+I4GKUnCJ4VcOscs+Af/dco5RImQktK/Eti6rEzNthPXc6lFe9bA6OV/MkNUQUDIcWD7ilf7anFtvGlBJTO4GakSHPZDCJNsENeCSu0E7yLgmesQ9dQhvhSnTp1fJYdMxUY/tBPd08Tl9wTUf3RL7PBLfucZM+OZ8sBG9NOF0GzA/WvD6bEOWiVlL+KxFt4w1XNa6W9q8SyKy8CcmucdcoCSNllBzQ3tFid20SLTw7zQKfGnEfmfC6zMPfg+XbRDYb8TugVkwZP3s5P5GnfpaP0BSz1/WRmjhV4iLaoPK95suDR1UR07pBNqTQYfesg11Cm0BFMu4JblG3AcVEFQ1YhlUZ8SssBM1Y2MeAigUPJIgL7Bx7Z4pHbedYpCWksyyUWTBothODXKJYyjyIz1IChPGHU1SAYgCh/A2W1HrDbsoz4QueAw7aFPKYBYCCj6Z+FeZ0MvV8Vn0tHfM2I6SsLYq2+Bpj7Rh14QRt6QPdiGvLYNGXWMXvDNWCBkLmERA+ygqbNQx6pmdUM8+WMmcpYkK1nEMEZP1MCSkWVLzPTg1D8y4L7T93+oFvDNkD1qFjNiFfzRivdFlVDsL2Qmtxm7RiqgwCYsgdfckRs5bC2aFmCQWmMsp9B4m9K6scywkL7AYStSsTszW8s2xC23xTH1uK2hQcEs0Zd8BOqTlvZdwiJTGJtqHtPgVfjRnV4p5pr/h184iveYF9/T8qzhVk47hj6yCWsy4jQB+VGgrNvqJnfCupGuSX0E/lAmXqEemnAZVUjERJCP/rklAlQapyDvtg3fqOwfRw5u2MT7C1pcBJf34jHHvnE5r4WPLoB6niD50eJ+18BU2nhv5SB2TquKeZulXoolLsw6ssmXVXDcXwozbBj9wiep0CGn7bwMuPeM9lducQa8Mi3osZxmCYlbJo8LRzGL/1M4/9JlyDpHyjlGQCDa8WhmXBCP/cpSwxUHUAuBX88rilA8aB1ZC2qt6ZThHPqDnf3AKaZF0jFIjZqt6pVPSXyhi4xVxqZjYR3ighrQusZCmJWpun23wfZgCXXrlq73/L+hFW+FDK8FdTUopTI1zeLtZYI2KV75/6Rj86R7boUWt8EhB2uLD6f6XcbCYJhPO3i+rx4RR8196XHL6e0pmLy7uhSImy0nYRojrtg2694txMDm7x4xRa0SrumodrkctRYe2WwTWesQ8JaW9lnFNteQ1wzs6Rz+F56Wck9DBrda8ZpSw1TOm87p1mBW71pxeTkx4Gpj3Xkyb8d96LB1SDjXjtRw2VZGQbciowsQ+DqmZknCIVvBE+uF5pXXrUArkMPEG9BJqzltSahdcs2lgpbZPHtQ4abd4UMo2nBpQyj5pL8Tg+vGJL0g5fSa8Rh1quWfSS6eIxwAETUq5rl8FkAL4SEzEI1m3DEHjAoho18hH4s4JlJxeG+F9AIIeudQmqAmmCXjBKeKpBrHQOKDaN6vXVtSm7lPuHNXlGtFhL3gg65aFje92juyAOCsT8kzYje7Jb634rW4JL+CNYH6N/CsdIh6hwtrBp/xiIrDmNMBhDelVflnvYArMWbV2vIaA3A+07PfG9EodnwJLVh2zqJ+S+1GFmOcY+RCX9MyMUSXtGAuCT5dSxK+Z0PLJB1CYMSs9Yh/GtsxLO8cREp86ihoomS+1fXKAC6yD6uyCqtlFvWLMsnGnqA586ltc8ktTVj0x8719aBsq7JG2X6VD2EO4VHzqS0tO/R82UcKGBZgmuHI5bLJP5gd+9QzMkbhDgmNoOy7puQW3Ca5Qnw54vu+d9paQ8lYBl8uunAJEGPnfue2cgkl44Rrfbcxq0PEtx8R0YRNfoyOfusQ9h2dUvAqNmbXwdoAmTNTTq9aRAAErdj1YeLhmMXWqHrnI0K/UOaTFP+8D8PRvpgIozOScd6H1c/K4DFNOnX3YvcyOQ3H7SHNGOVR77p1Rda8sSXQkXCQm4m5m585VC4E+OR/+C1OgQ86Wdo4xZ1eR0jqDKgbFaIVDbkmvnKM79ZjVlkJk2Sa7EGSZZzlclkvUUyiH+OQuMeMgAMjPVfwgVqrEPHbpqCXvrn3w/duOib5ZH0X1C4Bkr/T34i6pMKdWQfdwia+u2MZY8R94Jr2GoUosJWT02IU9sQ59JCbvS0z/YBTY5BCDrKFiL2q/ah9jEliHDn9sHdwKheYX02AItXNom7ZvEa9sVEyDpuWdA0EGk+OV8BSC9IdVmGVQPeQ/r2IEKhQIPit+Aynt5VULoSG1EFyAf8FHiL+UUzTki21QLcgEeWwCNrIVFdxESO64bR8iA6WUmu8U3pz8eB1Z3cox5im/cYGY2+OV/YFROY6sAlIwwK6ZJeb2eWX3BN9ddUp4Tin6hKxulf2BkPWeUjiAjnrsk98naJ4n5X9k1Uz4FvRTSwbIRX3eue9x6W+4tVO0ol5C+gvQEcFN87ZhbQxk3dRBVNRjWvlIQNW4Y2yHX8kQt25Wl1lNLR5k1U7bxT7xAdGR3IXLeAV/ema9Ixd/gn1swtoCKsbgsX30Y14Tsg4sPOY2zCGL1aa8YNyZgGesQloZVaMxj3eNghpZ9fOkkhGrqMfM2ln/yjFdbh23eYHVMOtd2Meon8ZmvvOvmWY1Lqgzq31Kh51TX4U83KZXTWqz6gLqpvwqR5Hu1CUDJoJG39LBoPvL5uHtgQ3z7MY5l6TnbmmvKOXI+qOOSV3chhk4T7/ST3AtCpQiUvHAzxUp4R3hfOC//pUjMDP08iFa2aBL0jNqxQjs45D4jN+6wmqaMxXe5TcvwhtZCO/xW5bgfYlF/byWxcCaGTPh3fhnh3AQ55RuZGme3I9wmUywL7kf/KsnBPeXcDlvKeWD8HJ8FjLPMOfwdkFNc/AgqHFWcHeOWTdJqxrxqxzmNM0Sct5FPNyAV7mkPuffW+S1zHtkv4EdqBWf6JWf+C0zlNJeakmvGK102CWh62dsfnbdJxcOeOd8/Pk8Lu01KAbPjLcQWmbVhEfGG4h9RNu2a+ILAI3o/qprcjfEEvYnZL+nlo4Q8vo8c3r8ykbgID9fy6mZNg1qYldPwZEdYjr9Kyeo5WPmoW1+FeNwzUbcJnJBP2DIkNdELPwEUwmXzWtc9Mz64FvwiVY6io7uoBQNBdZMwVsj67IV9gXWz8Bu2PS37pnvvYs+UcpGtZk1wXeXATqYlFc6nFpO4yIEj39/DaKrFVgbWDfnU4KsnxtQPa3PawJwCO6taTJrkMWd4Bzq5uAIBoIWQIZr6mvYB8Kv7FcO/+I2LZmKWvl3V/3vTEF0ISRw5oyaGYuwdkzaG0zma+/ifk7zkh6/Ac6KWTf9YznoPpekFxBR+p3xn2spAYDMQu9DmCmVI64Zr8gVw+TSkZ8reUKmGfNb4Dz9qiaMhPeQty4Z1gy4A9cCVwonD3hFlugqHw1sXnRMfgHHZNZOwsGD7i7AFeGz30P4ARx+d5C1qpC0+bH+s1vmG/estwE14+ymGZfUF3A5EHVM+gs4Q4/c9+457+AcPPPfUyqHaFVDAXeGhfcXxJCQZ7/zze+DSNhHPqEWDxNyeiDqvPo5j7S3uNS3vLpZ98RubFJ3UP0cstRp4SCzYhJIDHjCp3gIdobrYddM//wXu27ONfklvWKcXjHqkf7Or2Qk5N6aW9obr9xeyHi78HaIqE/hJ6OgZphN36JB4BhG5aRPPiTfXe+8Pshy38IBmHHYwSunxzu3DxX1FE4D8tsj6wOtciy4dRWu1r98FJPU7Z3TC+HxKR6xi+lAlgOtnbWJeAj4CGtdh2fod6Z+BgxmE87TJeWVb8mobfRTavk4rXJKm1nHuDMV+mCTd3cF5hrAAfuQigYhJPCMJqsWzJ6wdUORUspvXkbWQYbzLx+DSHiAFojvIldN2iV2k8pH/WqmDIKbSAU99IoR8/BW37IROAitcgIiDewierCJrNAsaPEpGRI8WIWX0+5MwnHgNGAf4Bh4JqB2hlo5DtTlUzwMT8KFw3wCjonFg4y6WaOQ+/ASwLpVZDtwCT7vAz7vI6QBUBqAgw4Zi6xWNwuX4JTyEv6Eo/lUjLrlfgxsnCUW9yPc0zwP9EbM/8hunnfNeocvGqDXzWCy33sV9VErhtzTX8J/kW7jLvHPIGWDGuad458D9wLzAwhgorHJL+EZbt08KbcHYYvSYYg0Ka+fUT7hENUBIPDIeAchh0jjM9/9XC6aXDyESXoZeGeaWvTJOa7TK+t9cNMiYAt0l3fGOxg/+/tbhDyAPSHb8NkfRffXnRO7AQ3wDBBAQOU4cAZUATg+s2rKXNQKmQpJaR35GLDFrptxTQTcjEOlwCa/gtcyq6fNhPeRtYgh4ws/ARvB8Q05jVAyoFjIkwpD27dh3u1inlHLJ5ySXoQ/2oW5NhW1ARTgsBAzgJdBUDM8CGpBAEEpH3VIeA5QAPSo0KoAZ3BkCKqgZQW2ttGdrunv3PP6CAWfYB+IBCAGMJr1/qsarQwy3jrqIf/eMpyzWcgDeC1AEwJsF9cJYYOQw/74/D6HpG7IfngvIADYcltWCQX9CN/cmTINvgdnBfD1zOv1r5k1CWmDI3Ca5oE7aVVj6IROqCxwcGRd8bpZOBom/RW9YhhJG+E9wAqAMqBhzrt0iAa8mP0WuApZ9zD3I7LAeN2sR34vtXqaVD5in/QcsAXcA2wKdCUGJR8iAcUeGFvDryygfNS/fByCAZMLMwtZCHlPzv8EUYfQemd/RJZKLkZWgvVIew2FAGYcMhK2JkEttPIxfOYHCJJ/2QhIDeuQVkrBIKdmVj+wBv4k5nz0SH3llYkcwTr0AbIkdCXUl3ec2jl0TCfUF3hfIH965QSkAuCGUz0LiIRwAhyBRVSoZYASIBjL0NaAqgnIY9vIx0FNS3GdR1YhbQBNVu2sQ9wzRM3UzdlHP4WaAkmsRC6Bq4NZM+Tfc8/8AJCilU3gc/u1WQ2eOX0wNfAvYBHTkHuQRsIHaz/KwZBbxjsAKIADGALiAawAYQaqgHNzS39rE/XEK78fk/EW5tGnfAQABG/EqJr4mTnmontwAlAWLcMfAoEDPwNXAxXDA6fk55SSQagaJoJmiDe8y09uIAKhQk0sGYY3BZKAS4MjYFNfw7uYhz1AVm/P/qjLawQoQ8yABgAHwHCADJ/ST3BMAAGjdsJI1ALRhUGuGgdwAEPg8j74106SSwdhQFEAWAAN+JQNwplYhLeBBoJDuaa9BI0iBm+JLHuf85F7ZwoT9yzwR48Ez4z3IAwhWpC7AUVDxEzEPHBrZ8z4zUAbrDuTTjDduT1QBdyTX0NyB1RMQF7CFsLsFNsBNACV3iH6CZAHUD0qpgP+5ZPbDweB5+GFgBhC1kcAAXAAzKBt+CN6GbIYOagHeB4YBQJMKRkGfMAz7ikv2ZVjtqJWVsU4UAucg3f2B0CVleg+vFFCx4GyT6FX5gcQK4AAp7gut5TXgKeoh7twYnqBNdGPdgLvTCKrA9fPAdCDG5ehxFiGPKRXTQdUwRyNQCk1Cm6GqYx+vOUKqVbUbxvWyq6dBIiDafXN6YGjQTkAeoD94cxBeYCopFRMBD/YAAxBjkLuchsWQNZAQQQoCFuWAb7aAVWgmYBObGKeAgiE91fsoh4BLEB+eWS/g4jax3baRT0BCAJc4PgQOYAOMBYADtQJQBAhnsiHIBihzMMOgEKIPYQQTtg25jEcCgSHNrOScWfMr3zAPqYtsH6K1TQDYaZUjAG28AU9EGlmwwxoTHjAaVkA9QB5D2XFOfkl0qmgdBAkMxxQjFe/AKIPQACZB/EDBQCCDsgfKIEMVx720CfrnV8B6IYPopZlj5Q3gAz4F/wJ4QTEgPMDBSdoQgIJT9KLBghpr1gVo3AcMB0wj0AY9pGPIEVoJYi58snr/bmSOuwMIYQiAtwO5AFHAxhBeCCWoE6Mec3wQNi8pEOr8Mn+CN7MkF2HSXwOJKQbUAMo4dXP24L6a1zg1M7IeeVDnEBtoGM7fy5fD3iCeMCJwSWQMt+Scz6Aj2IV9senPC/N/5ie84EW1BSc8CypeoJTPMDJ+0DxL3uc8WYytnMr6dVB2vvd5JenmT2HaR+OUj5sx3SvitqXQtpGhXd7Ilobg+/Wpb3IyXmTUDslrJ+lZn9Ah7dFtm2IWhaNuQ1wjfiMt4A55BL4TUDgEGwIHgg9GPZxT0HhApmB1wDtAluoIMDkYIuAIaBIgeUBDoaXAw0A/QBbWIQA7Y2DvsNmvIb/2kS0g1MA+QkVEGnCcWcCHYsgDMyIT9FHTsMku37CLe2FXyW4g1EgCZBQtOpx0KSwBVaA2gHyGZKckPUO5Ccu5z0ITGrZsFhA2TjMrGf6G+Bwa1Eb5CvMIJAzTCLMJgACwgPXBvwPzhBYl5jTx6qecU3ogij+oIQuz4yP7Jr5nzIepsAh+hEgAI5pF/EQrAGEHPwkHCTk7oplcCscH3aDN4IdAsqHUZHtkDSwp3v6W7hs8AvEvE9QDkA0wG708jFdZg0IEQAKhByf/p5aOKRNv6MTWAu1H2oKkATYJCg3nKpJMOsOwgd21PKcwsEnIU0LSe0bmU/2s57upTw4TG8/TH3wpejJnxWdpzn3znJbL/Lb/izr+Hf548WgqBVR/GXuvb+KOv8s6L7IeHqZ3nkU9/gw9vFF8ovvae9Pwp/t8B7ssu9tBTRv0hp3AprXfKrXSJVLngUrngUzzukLLhnT6OQxdPwUNm3YMysmsj2oegqclB67HhgeEt0m4hG3fgFoD9gemAO4ATIeHoPKgcoCTBz2YBOmEbjwZ+MEUDNghQA9AAKgBEh3qFNQlYAYrCNB2CLAckzsplWOw6HggJDKkNBgE0Ja1wKqRh3jwYKNQREB+wDPg+oMqJmBMsdrnIcyFNQ471vY65n5Gky1b1EfgBLQKUbM7oU0hVyErHKM7wJUClqW4EAgDwGSQO8QbMh4mHFq6ZBTHBTv5/AnCEYARGT7ll3EYzB+QIaQhV7ZPcja4ZGP4LXBzUuOUBeKh8FfuMQ9R2gmrstS9ADY/qfcA4QBt1uHtkO+wkHANQGZQwmAiQDXoBVQ6xD73K90nJD1Ad4UzkTRt/DnHJkJ7v0sH4T0t/jUl6zyEYzo3uOkrs3Mp8f5HV+KO/9T8+6fipd/lXX/mf5gxydl0SV8zl74UYMMo1eXesIpPGTmbpCSBs2YHzSIH9S8+9R9Pqp4f1Am9qr4DGnRBtR8PqkQ+5Xxg/AvFUKfGmGdEPdnTMtxUPMR58EB4+6ef8surXHbt3bT+86aZ/kKtnAFk7PklL7okDRjGzNjF7tAKS0pHdIil9LLRoj5/QACOH/hvRXIcrDBkOV67FooCk4JzyxCkIQGfICaQQx2Tg9UHGAFEECAkpTXn13T37CbFkHT/djOA26AMCDGIPshwLAPgAyYBp6E8gGe4kcFeQy5BHMI9hKqPjwD2gIhpPw+fNYbVs0Euw4U8SylfBDYBQAEZUWMVjEOJwoxAPCC3fcDZw+1MP4ZkAbkKDwDLwbKRUU9Bl6Ccgs1HhSiLZixkqGoxzvwPOwAUXdO6ALzBimLvDbnIyh8AApkM8hGbOILqO5ALVZh7SA2+c2LkOg/DOEQwAL2gXkx4DYC/kDEAT5IICOin7kkvARdAoUJRACYFw1aJYAALhiAYhZ01yfzQ1HpyED0/b309i85T/+Mb9n1TZswDRrUZw7pMMf0WQMa1H4NCoxPmtRhbfqQlv/gj/FJkz6g7f9JjzFmHDRswIb9J835o4bsPk3apBF33jJ4zow/aciaNebOGgZO6vovmfGWzYPmjFiLptwpXeaEdsCkfuA2Mf+E0bzv33zMbAVAbPjWbBLLNzzyV53T5+3ixkxDx01Cp/3vRGX3FCR1ecc8DG2Zd08DBI9ApCF94XqhHOAy32JTX0LKgX8mFg6BeYG8h+yHImId9gDIH6QGYhTrp4HMWY0LtKpJZb9y/5opavkwHAq5lZT3kZjfC9nMb1kEeIEO8CocAO0C9R5UC3gQsB6ksmFQG2BGAA2wJ7d+mlzcD+8OBAB7wtsBXSErodOKRzzT3jEqxkBqQfqC3IMEheIK2tsxFtAAIJgD4wdRBNoAQv7ZUck7qwdeaBP2EPYEAQjGHQo8pD7oQaCKH2zxDLgBJCEcBGgDDgJVH2IPFR30IOQ0MCFwJjhM2M2A3QD7QK4ALIi5AzBNcA5Qd9BwJrzmvLyPZayKD9yq6dD60ajG4ZCaDX75YUTtf/Ke7pPzIHgQ9TF9zrgBd8ZUNG4QNKbLBk04AjH70YRg1kwI/500Cpoy5kOlmbUMWURHLzrGrLomwIM1l7glVMSstWjJLnzKDPlkf9M5YQMVtWQVsu0U96OtePSqdcimTdiymWDVQrhuG7ZiJfr5i5dFh7hDZv0ho3HPr2bXF1ghc8Ehec0lY9UpbdkhacSQv+SZNsmpoqe+MuI2IJ14QH7l9v28HecY8xCTiPSgAmsGHg3cDdKSqnYG4g32EmIGrhWSGNQ7yEDIe0hr6+gnvmUj/vWzYAHoVciNVErJAAgCXM5br0Kk0RhIP7CF7OZ5UsmQa+Zb2JNaPYms+V2OFKbAhnlEfhb0AwKAAwCFIBHgIGJQaKFgQ+0HFQan6BTzjFc7DyGH0IruriGNbSrHI9o2wYYBk3umvwNxALXcIaIdLimobgHpl1I8CExgLbwP5CxsmLMAz531AawE6AbQ50D7JtxmMnBRxltwFnBYgJ158H1gCEblpAa9ErEDJUN24e0AQW7dvGFgPaANEOMc1+Vf+Okjs+hQVHca0ngR2nzEqj6glw6YB804RY4hX8hNXLcNnzbkzhjxRnQY43qcKcOgScOgaaPgOfPQCUM+hHzBMnTGlL9kHbpgFbxiG76OilqwCllBRa45xm3iktfcEjbdk7bcklZdonc8UmCsu8YfembsYBL33VMOcBlnxDzYwuM9t+RtbPyBT9o5r/g8pPJbTD2ycFj83b8yH/1v8as/858dRjdukfM38ZmrmJR1t9Q11+R1h4QNdOySXeSMXeiyXx6bW80pGXSNfGQfct83+71LzBNQlCCTgTVtwtogRyErjHh3SUXILSODoLuEvAGXlDfIqqw1M5iUF5DxkJzazBqABRR4oHfQ9jZRjyKe7ACfgwsFtQj5DfyBju+CSONye4A1kfsNOT1QF+BVUC+goHiAn8/tQUpJGZK3wPGkvF5EEwTXz4MXAiGNinyCSQL3D+nRgdynq56B6guAAMIHawSazim6E9S+oGkRYgbPx3YcmvORboiChiUIISWvL6Bk2C7kASETualnBhYgpxdwII3LxAI1lY2AeoCCAqlvH/4Y0BZYOQUkD44A2AI0hyGnPvzBlk3II+fYbkbpGFr0YIJ/50iItJo4C2q44DeeBdbALE9YBY9a8ibNeNuWwnXToEUD1qQ+e0wvcFyfNWHAHtVmACZmTPgACHhm2pi3iPw8J2TNLgz5kY5DJIx1pyiI94F35h4hfQ+fsuueeOCRvE9IRbpTeED4k7Zd45DO8V7pyE+NyNmXzOKvgipkZc/Ye98SH/yd9fTfuc/+yen8V+7zf+d1/5Xb9Wd2F9K+Iv/Fv0re/FX+5jCmfskjZtkB6Xi94xZ3RM644FQcsiuqSofdwx6o4jM4ZUMu0Q9Roa3eGW/ATGlQi4EYwDUAL4JhRiRCwgsAgVXUU07zEvg94+B7oAMAKOAFIMUhrszaWWB+fH4f1AuQfj9vGwdWj5PyP7omd4OGcM/+4JaBLHEMcMFlfwysm3PP+iG9G2fBLAC7AHSg+DKrp4GWxCwE90XNq6iwh6C0IVTOsV3MikkIEjrqKSQxPMClv4MgWQTfpxUNeiS9gBh7prxBRz6FPelFw3qMWq/Mj9T8AV16JT71NSBJj1aJDn9IzHwPJQMCD+yi4VeGCnsElcKI3QjMAaXHIuguLvmld8Y7RUKuZ8orIAlpXBY68jHAyDq41YLXxCkbK/bLPWBXnXJrznj1l4Kmr0Etx75FJ155O5jkGZMgoOUVE+6qMXfTXADbcS3/KQMORH1U2x/GuC4DkDFrzIMSPq3PmDPlrNmKYGyiIzYdo3bdEiDw687R29jYI0LKFibuwDP1lJiN/K7MI/kIl3iAS0R+OcAp/SuiASThn3Ft/1dG1z8pT/+T/gy2f2V0/m/hu38Xvf134du/c1/+u+DNP3mv/sl78Z/yj3+Wvvvnzof/1PT9q7b3/3l35FvF201W/kFA/r5/wb5/0QYlD08vuqbHFJYNooPq1LwyA0v6bfj12r4FnsndtmFtmvQKQIAuqw6T9s4r/5Mmsw4qPYQZQABkTsjtxed9hHgjHw1UT0Ox8CkZhorumPgSFd9BKu0nFfSAPwTmBwXgkd/LaEBaMgINgIAADHlmvAU1Rq+ZQHohNM0FNs5BcaFXTwGkxEDV8xuXIEGBhGFA7kKVImS9h7INKgbS3T7ySej9DdOgJkHjAhQOyHjvrA/uqW8g9vBC0ARgKcG167PqoNqBOQS77PDDE4KgA/IHuavLrAUTGHpvFZ4BELCqpnXod5xinvJrZ1WIBU6xHVBWDFkN6PDHASWjrrGdDmHtT9O79vwLjxnl56zaz9ymL5ymQ0rZqU/xgVvGsWfOpXce8gtcG9G6pWDDLGjTnLduypnW9R/VpI7p0sd0/EY1KcPqviMalAkd+pgWdUKHOmsUsGzF33QIW7IJ3sHG/hwAgj2PhH1cMow9j6RD7/RDUuY3dtlFYPFfoQ1/Rrb8FXP/P8lP/pPS8e/kjv+kPPs77uk/CZ3/Tu3+V8ZLpHlL1uu/02D75u/Ml/9T0fOv6t6/AAH1/f9T1/dP+Ye/i9/+507fv+sG/qrr/1fDp/9tGPwmbPzKqDqmlpyx7uzzq8PtgwnCRj1Cqpicp2vEA3NuPUwFkCWIIZfEVxAbDf8qEPygk5AbhQ3zmIy3MKDAY5G+jGM/bxhEd+6yGqadU7rod6BADIDgJ4JQKBuBlzDr5oD5HZNfAJLIYLtSXgF/QI0gFQ6ArQBw2EY/hX85JjwXA2IHuw/5+vM2MPgxKFSYxOcg6wA46OgnUMhFLYsO0Y+xSV0/PmR6BJUCCoR58F0o4XDSDlEdQB42oQ/QUY/5DfPmghbQhuGt6yq+RZi4ZxBp4Hw4LMDClN8MVwhGCMwIEAyQvzwh3yHikS9csE+xgmcmPvmVV/KLZhpkT+EhNf+UVnYZUP2FWX9JqzolFZ155R+6ZRy5p5/i0rfQ4SAfloxYK2ZBu/aRq6bcNTPerK7/kJrPgBppzDBgwT3qRFB9Gd74JbL5TFS9Q8tb+0HRK+iQVYewLdfobUwM4GAdHbpiJ9wlJP07/t4SPuHIP3+PmnvkX7hNyd4iZ21SMs4E1Rch9d9jWv+Oe/hX7KO/4h//nfDk76SOf5K7/k569lcibJ//K/XlPzlv/13W85+qXoj9/5R9/E/xu/8teftXzvP/LXrzn/yXQBv/d83AiV/JvlsGjM/+lRfc+n+i206DahcDS4xw8Zb+JfqUXKvgRveUbjVKCeQVSASoDj6Fn0AQANWDV7SL6wTmBwsAGcy7uwIy0CX9JbNhhlT6yTrmEaN2gloxhE7oBNeA3BfKfsdsWqDUTKISuoAYwGh4FyFd5ODlgAzQj8j94/ppoA1dXqOYKacJOBwIGQKP3M8R3qPm94PEc419CqbflNcCqR/WsiLjngGFgFr0CRL9x82+ftA1EDz70Fb3+Of0okENcgm8FgBkyqlzCG+l5vVoUYpdYh/55fcqeKbTCnp4d8a0qUUWwUAP7+CYPtnvYZjBziH3qNnvLFk1etRiZkHfU37NLrNwA59y5ld6Ri29pFV+plV9ppafEvIOsMlHbilnHun7znFHMJxilkw465bBk5bBq4SUXXr+14jmv2Nbv0Xe/TPi3oWo4c/oB18i7l2GNn+PbLsIaf4W8eBr5P2/Ytv/jGtfdY9HoOAUsWoTvO0acRFd/09U0w4x45hWcEIvPPLLP6QWHFHzDqjZ26Q02O74pO/75RwGFB4Hlh1x73yLav0e2/Ytpv1rdNvXyAffox/9E9/xV2Ln3yld/6Q+/xaHtHr6n4yufyU9/ifm/pfgqlN2wf87rX3HKe7YJWkbHbPnmvg5sPZf0Y++iuBU738Ov7sS3qBrycZFt3ond6p6ZeLTunkNMzqB1cD/qJhH4e3rPoW9KtSigKpRSnG/Ia+OfmcUQIDLfedXOYx4xYKP/tVjATXjlhEPQPbDk06p3QAFj9z3+IIeKP9QBSyj2uEZiD08AyBwy0Q+mmc3ziHdYaBa/xR02MSXguY1u4inYOQgszX9KkHxefwo/9w7M0pe+XbCVmpunzGrDqo4u3rKlNMAdR0Tg3xbipj6yj74ri2/GR54xDyxYtdSM9+q4bPsRC0BxZ80yUWEpC5c7FMtYp5Z4J3A4gFplyRLTm1E06Ievdw15olP+hsDapk1sxp4Y88/9zig4JCcfwa0SS6B8J/gIfyppx4ZP2Iff+iMtN7Zd4w6cIrexSZc8Cq/hTdA+JE2HMK6C071BevOJfPOGbPqkl0D1eSSUw/bC1btsX/lIa30NLDqhFP9Oazla8TdTc/4JXvhObv4/1P2dh0Tu+kcc0rOO/MrPKUVwzijl5z5Fx36ZO55p20TEg990w8p2UfUnFP/ouOAks/cO5dBtd9DW/6KbIWc3qMVwW4gNs/8iuAcvgUjzVs+ixr/jmq9FNSe0XKmTFhLVgJQJDsuCUfuaV/8q79zm79ym78L7/0V/gCQehbatB3/MC+g1NMiOLNskCK6a0wt9M19p0rM80h6Tsx5D9QLchtKu1lwE7sO3ARyuymgCvkwwlx0z69s0CvnHdAGWD5y2Sddbg2lFPkaC+zjnfcBl/n653cLnFO6kTtIZUOgFpl1CBPgs9+LQYwhqMh3TRO6eI2LDrHPfwp4LVoVoAHKvLpfRXT7LuwGg109bR/aBmWbe2fCIKDSM+mlbfB9Bfd0p8h2Qmq3Q/gDv5z32OhHBrRSQlI37OAY0U7MeKNNLbHlNwbk9UC6W/MaIORaxAJdYmFgYT/avzJe1NLGb3jpFDroFHoUWLhHztwlZZ7Tij/Tys98i4AADjGpR5jkn52ndu3DgQA2rIW7ztGnnJJvofWfhTXfhPWXvMqfjXiOKEXn9PJz/4ozetkprfQ8oPISyjC56MQn/8y3YM8zbdM1dg8Tu2ojXLXgb1gFr1sJ9hwijtzjdxwj1qyDVi35R/iUE+8MGIdeSJuiQ3zSvmfCrkfcLuzjkXBMyjgkpYFlQPrhBBRfBJR94db+E3b/n8jW/yu+bcmSu2bJWbcV7OASD2n5R+xyKCXn/OpxU86IUeBFcP2X2Aefkx7+T8ErQORnRt0XVsN3buN3AYKkv2Pbz0IaYIfLmAdLnKqt2Mf7uW93inoGsl7Epr1xj2wXNM4BCALvTNpFAflP4XN7LcLauQ0L2NTX4BpE91e983qQZuO1M8AfyCdSZUOouGegEsjF/cS8j165H30K++2jH3PqZ+GxffRTUJe4zLfwpBgq8pFjzGNgfseYp74FnyxFDyD2pNwenYA7gAYo/+ASwcv+8LUPIfW1/cqhBASUDGpTyuxFD6Dqgy8gZr6F6mDKrqbmvDUPrNKnFtBy3gEULNg1ngmd0i4J9kGNvLQ3FFJRGavqRUjLGCayR5XYo+rdLevaKe30RNpx1CrwiJZ1GpB35Jt1Rin8iQDwAqcemYeuSSeuiVD499GR27YhO46RQBWX/IovgurPQVUnjFII/wm9+IJZDkX33K8U6UlFKjjxKTwlI0tx7ePTIaL7HgmAm00wCJZBq0bMbYugTWP2kV34qWP0MWSnjWjDmr9pE7RhzUMWErDmbaKDYSC/osZEHWCjj9xj97BRB25xh56Jh4SkM5/0M3LWpV/+F0bxd071d17dN4BCcMO/+JULeuR104BlEwbseURMO2YWAldt++Z8DW64FMJovAhpuohr+5Ly9DS4ftcjax+fDad6ya7+FtL8Z3jzSVDFv+LbdlgVS8yqjZD7Bynde+mv97Pe7uZ+WErtHk5+lh/9mIDcpR2gFA2ZCu5y6udBA+oE1oLSIuT1gdajV01SK0ack1/6lAzZRD+CJ2HYx3b6lI7i8wcU/cpYjQuUslHkY8lC5OtJrNppMdBlEN3A8hGdgCpQBiD7kabgFWNg58AsMKum7CIek3IQiIA/hN0sgpodIx8KGxaQlnGgWZK7dWllkPTOUe2Q7oyCHjterYJLHLvgozG5AB/VHlrU9yawZIuZs+AQ3KdCQFpMqRF7lL0BAU8k0A8l7NrFbY/JqZesQhin9FyEUX0LYFz4FJx4Zh27pR86JeyhovbtInfsIvapuX9FNV+Kak7ZZTCQHjy8aqQNDafqLLD8M+sOZP8x0net4JCYdeCVBnb/0D1h3zX2EBOHtA9wjDi0C9k35+9b8A6tBWeo8K8u0Yd2wk0z9o41d8OUuWJIXzX0WzWmLxlQN61YGzbsPYfgTVvunqNwBy1AVhNwizr2iDn3Tr7wSTv1Tj0jpn2jFX4PKPseUP7Zr+jMO3PPkj2viV/Q9jl0ikAa4nilAlxOyUgROWdXngSUH//oa3QESZ/86Hvqw0VzwbIZf8UcMBe5i0v9M6T+Mrh6kZi5TC2e9slbCqzej3yyF/VkJ/rJVmT7ZkTbdnT7Zsyj9dgnc7GPSyJb4xunQcNZCFsZlZPgI0D8+//ovw7in1o+ZhTcjE1/i8/vM4t8TCwbxeZ8wGS/Z/zoKgtmAeDindfHrJ4Wc0t6BbkOyDIT3AMHD/4e2N6/eAhqP/hDds2sKf8ucENg5ZS1qI2U1QMW35Lf4pfXf8sxjpL7EcgfbK5X2gtC6ktrTh27qN+OXWvhntobVneW1vYlqmbGXtCjRoTA9yp79asSkSZDqj7vVEmd8m7tUk7PFNwOfVNO/bKOqFmn1NwTSh7ST8Yn90fbrexjj/Qjt9RDVOyOZeiOlejAN/1CVH0uqvtZ/k8Dyy/Yld/4tUDInzk154FVSN8oRtlnZtmxT84xKfOYkALMf4iJPcUmnGHiz13jjmxCz+zCji2DjywEpzaiEyvBhh5tU5+2ok3aNKAuaxGXNL0WNfAL6p6LmvhlLa9lXZ9NE/8NM8amReC2FXvXLmgPLdh3Eh27I9xwhk+EMF94p18Ss754ZZ1jE4/tBKvahEU1j1kV3K518LFb/IFb/KVPziU595iYDZd25Jtz5AfcUPNF2HgkqDmLbDnglc9o0+Z0aDPa5CUj5pI578i/YBGfvERMXfFOHrIInEEFb9NKtnmNO8Etm9yGLW4D0gCM17AZfHctuGUFnHfMo4Wo9peZrz3jOqA0eOX24nKQnsleBb1QC0D9eRX0mYe2USrGnFNfOSZ1+VdPuCZ3Qznwr5xwS3vDqp0VAz1vE9YGQs9W1GrOa/LNfo8KewAZDwLeI/UVIM8kqMU18QU+9a2V4D7SQiywWodc6JvxWotSCNkPsl+fVuwc0eoa1WZILWZE3H/tl3kSXrWOixrQJPep+/Spk2B8VCZ8VPLqVfF5r0J6peL9SMYFEDBkytz3TjmhZl0yC78yS74yy87JhSdeOefEnGN8xhk+88Qj7QhklFMc0MCqreicXwFZAuFHRAD3DnAADCDSr7w6pCcdE2kedsEo+RxQck7NO8InnxFATiaeusadu8SdoKLOUdFfUNGn5sIjQ+6xKf/QmLdrELCqQVxS9lhQxMwouMwpYWaVXGYVXacVXeZUsEsa+EV1ZA3HRW2vJR3Sij5505y5ZcnaQfEPnUP20KJ9h5ATV2RRoQNgFxvBEdQRTe9ZWac5OWfA1pFT9Cku+ZKYcUZIBxx8piAtAy/8ij8zK84Cys9YVedBtachDWdRTX+ntk9oeo0reUyqeE4o46bVvBb1aOumnB8GmAceeMGIDX543jZ0m1G57l++4V+1HlC1xa5f5zbth7dvCe8tc+pXeY1L7LqRxE7w2C7xHVD4CTkfLENbQedB4dflNICr9MzpMQ9rBXtPyut1jO8CJoCq4ZXfLyZoXEC+C1Q8CC4f9EH8o11l71zfnA9uCc+sQ1pBMILxsw1r49RMAzdA6oPg1/DOxsU90fLNs+TWOIbfV8alecY+oka0jvCLtv3SR/ToQzp+g5p+faq+/Wrkd4r4jyreH1V93qv5vFX1fa1Geizr+kTGZQEmERBAyzn2y4WwfaaXnvrkf/Yr++xTfOyRcYpL33GIBS+wj46GWrBlH/aFfwf4/5xb+TUYLEDVaWDlz9hfBlZ9YVeDkofJPYfw00BPFBzhks48kZWCDtER+5aCI3PBsWnQkS5zV52yruC5oeS9o0U/NuasqflMSDoM37IYEjcbkjAdlbYcl7GZVnCcUXReUPFY1iQAN2wa0jZNAvatONuWrHUzxq4Nd8eWu24RuGEeuGXJ3bEO2rPg7pqzdwz9dw0ok5KoGSmHOVnslnEgEMNnr7QzzxTA4jkpA3BwSswEGQFQOCPnn8LwL4FCdsa/cyy6cxnTtOUdPabgMi7vMibvOqXsuaJH37YM3rEOhSK4ax+1h45GZsMh5pBSuELKWyEVbPqVrzNr1jmNG9ymVVb9WmDNVlDTtvDuSsxjJ/+K8PZNiL0SuUTQsuSc2GUU1MhtXvAu7HPPeUfI7wHCcE7s9i4YQCd0Ih8lM6FUxCPtMglpr5yjn/pkfzQKrPVKf+2d/hpUvVt8Jyh8m6AGIHwN33ykh2B0uyo+wyvpma5PrkNwIy3rtS05f1BYvemVPG7IAAR80qIAAfSqAQGQ+9X9etSp71R936hRXmtQu1SJbZKO77RIe15Jh75pZ/6IEb9gl54xCo/peReMoiNSJszUhVf2GTYVwn/qFH/uEr9lEwL//SKqBSPwmY80YjtlVAD5Qwn4FlR/7l9+6V967IPUkS+04hOkS0Ya0m3RJfbIRrSj77+tRdlW9dlQxK/KYFaknedv20/esFlVJByY8L44xh5bC/pvGX28rvPhmsbbK+q9N/X6bhoOiZuPy6IBBJsGtFU9v3Uj/x1LDrKqlL3gwJ4PdQHpaWjJ2rVib5swYZ81bfKGtu+KmvvITasxcbt1LfKOJR+qz4VzNJzDKTb+q0/mNzLSM+3SN+sSnAUp44yU9RWhhNJjRukho+iAV3IZUXvimzqpgB2Xc55Wcke6C2mTkeVLLYW7NuEXrkl7thGb5oINc8E/oXcnXGInnOOm3NNnvPLm/crWWbXLAVWrzDvrrJqt8Pvz8Z2i+hnnhA631G56+ZBDXIcBt56CeIQP3oU9PiWffrTl7wczaRFyn9c4LwYaEPlwL+0NKeudS0xHVPuWHrPaIbzNTnQPXABIBFRoq7JXDr9myoxT5xr1mF06qOSWQojvcA5ucQ+sep30dM4lfsJUMKLL7NdAWit+0vKD8PfA0KS+U6d80Ax4p+73WoP8WN4dKQHGjANi6qFf1iGj4Dy48ktozbfQ2j9Da7+Jqr/wy79yS87pIKPStlGiGU3fZT3qmmHAshUPCsGPznw/etIiVb8CvNmJXxE4yXNq0SW18As1HxLu2D3xyCV6z4a/a87dNWZu6/rtavquymMWJdBLkg7z4rZj101Hb5gO3LCcUfI6d4z9yyPtDBX67obey6sa3VfUuq+ovvhd9fXv6u+u6vSLm47JoSfkXRa1fFYNaNsW7E2zQJCNGyaMbTPmhrH/ppH/ugFtQ5e6qUNe0yQtKmN7rhoN3rLeNmGcOYafu0Z/cU9Y06Gu61AvMNFfvFI+E1O/++f/zSv7J6z2P9EN80YMEKoX1LwL/wIkBwIKTtjFX4WVEyrYGSXspLzLBEBBATOv5rWs47cNNGYffYyKOUJFAw6WnaM+2YkGrEWfbMN6LUNGXZKmCFmrjIodYf0yq3yJWTFNK5mNaqfnfsAmdfrkfbQQtdiEt5Jy36EiH+CyXhIL3psKGhlV8LpnIA7c0l6JAeGD4Ieow8DGdVByejXIJWbcevfELtiiwx6gRfcNqSX4uI4fd3jqoeRIoGNsWTUh0Y9nIPxWomFj3rABZ0iP9UkTaMBvQJP6s8Um8D8IwFfKpBfKXk8UPO6JOwII1sBu0bJPeMV/xTZ/jaz/GtkIXv/P8MZvwtov/MovnJIL/5xDYtK5b8qBW/iqCW1Rh7SLjwOgfA2uueRUXDLKz+klkPoQ/ks6IKAA5vHcJ/MYl3jgEnmACt2z4G3q0bZ0/ba1fJdlXRakHJakUNO3rEevmfbftIYC8Z2Q/hWTeGIXcWwhAjJY1iV2XlF9ekUFxpPflZ/8qvSzheOba1ofbxkOSdmOK7iuGvjtmLM2jAPWjejweE3fb1WXsmvC2NKnLavgl5XdRsVthm7b7VkiTQo+gw1xiDhCI+v0X7jHfsbFX3omXuASvninf6HkfPbP/1NQ+VdI9Rktc16PsqBHO/ZIAFV0EVh8wSn+yi8fkXeakHEAgTIl5wRjWt51XsVzWdMXJO2+dSiwwr5d+L5T1CmzqM+C+8H4/4wB65BxTNIKvXiLVb3BqNwIqFjwKRgs7KFmvgTdZiNqdkt+hkt/bh5cz62fxGe/tQi561PQQ4ZjCO/RSofFQAla8Zsg76l5PYADsHxa1BJjVk14y5KOX7FLRJtLWLuyRzpK0KxOyDailfErRl3Zla3kpD77sDG78BEr4YiFYNRcMGzAGtYPRDpsqpOhFrxXwr+QwzyTw3YpejyRdbsn4dQi7vBS2/cksOiMX3ouKAMa+Cuq8WtYPYDgu6gBtN6forrPUBqo2ee+GQfuMbsuYQdOojVz5ndm/uegiq9BlRfMH6uhUQt+NG7OBfcPzA8EcIJLPMZEHzmEAwK29OlrqsRNFTyEf07CbvKmOWT/kLj1Z9Bo7klf3JMunOLObCJOLUJOTfhburSPEmYPf1dq/13p/m8KMNp+U3zwi/yjXxU7/1Dp/F3l9XWAgsmwLHpa1R204ao+GfzCqo7PqhYJFOW8AnZCHD0h6XRswz9GhSArTzpEQAk4d4q6xERfYuM+4xIv3OO/4FIu3BJPQJ96poBO/ELN/cIq/iaoACj8Kayc0ffbdQiFKgY4+L+jWiYUnKZk0FPSDtM/2qz9AARmThm3Ycg4dYw5cYw7dog9cUnYcUF6Nb3TZ7wxYHRr+z3XovZaCCZcExfwOSs+hcve+ZuUUpAOtMQn2Jg2dEgTOeuFU9RdC34Nr34Cm/LMLvy+T9Zrz+QuKPGU/A9iYO1M2bVu8V1gN/UDKl1jHpkyq1RwGS7hrTa8Oog9GAEZ10SwggAIDVxGYkHPvqj2vX3YJD5zjV426hg1ahsyZCEYs+APGbE/6dAHtcgflHCv5V27ZCD10Y8UsFPu0V/C6n/6eyTq4Q0wvkc0/h1975+oe4CAL0E13/jVn1nl3wKR5d5O8SlgvfbQoTs2/FWTgDNCEujHC0bBkW/WiU8WsjCid/qpZzJormPX2CN0+DE6HFkG1oixo+O3pemzrOA2fct26rb15G2LgauG/TfNvnumfnZLPHeO+wykasQ/1OPuajN2tPymJJ0/ipvd+1Xx3q/yd3+T/9m98v4v8g9+VWj/TfHxL4rACu9vGQ1IWY3JOYBNmFfDAwKWwTWoeMzKuU7KuB6ac07sRKcOYZcuUbCFsWMZhPQ5dY4GSgAcfCOknGORbp9fcKnH2CSkETKIRL8cMERnrMJLXumfojtLltw9cBnkzH+CK0GLjEnYTgB8pVGTUuhZKAoyzgvKhG1j3plzwplryh469ujH8mEwFd3qPt0alA41Yoca6ZUuo98yZIVYsONfecypP/QvW8Kn+cW0mjHLdSg5+MRHjqGNsthYj+ROx6gHJqwqj8QOW2ET684oJrEDWcwOYmwfch/QoOaVjU/osOPVa3nnULPe6FAKjBnl/rkfldzTgAOwIfc93RK3RFUjHgnj+JRxXOokLm0QHTFkxe81CBgyYfVqkXs1fd4pebyScX4h49Alif4S2fyv5IffY+59C2v5O+I+mOPvoqZvgjoI/F+hDd9FdUj2cytBEp755Z1TcsFNHbklgL0+dIwC37Vtwd0yYR04hp94JiF3ZggpoPgOnKJA9B07Q4EM2zXjIOSvRVlVISwreSKtpAx8dyz8j9G8cwfergltSgXzv+SMvwipfxHS//JI/Rc+47tLwne78DUV0oqy15g46s1N4/arau3X1O/+rnT3dwWAAoz7vykBDtp+VXj6m/KLa9ofbhsPydpPKjpDnZ6Sc5mUdR6XdtwzZh6YcQ+t+Of24UdWwguHyFP7sBO70C9Q6Z1iL53jTtDhFy5xSJdI4ABsAiiAz8T0c1L6KWxBDtNyzxBnlA1V4Htw5bZH3Llf9j8BmcOSdsPiSB/UUUn7MSnUhIzTlDx2Uslzx0qw7xR94pFy7A7Ml35CyvnCKH6p5vNClfRSk/xWx/+tHrPXTDDvkb5DL9ujle1RircY5cGFH8zoRZre6cyCN46iuqvWPEZpr11wvQ2/lpjWpeCZFlg14hL/RCywqM+aWwtJH5D/0ZJdRUh86h77UIuUjUt4asqowIQ/YBf1ituKVDDx9PhHC5zSN2bsd6bsQfuwT3aho+jwPhPWgAH9gzrpg5r3W0X3t/IYZIktaccuBcx5SM2XiIbPIfUXgh+qPqj675AWQMAXXhVIoXNm0TkT2V4G5J9SMkEYX3inHWJid+xF25b8bRMWWO11Xcqqlu+0Ch7psG3DP3JA1kQ9sBce2YuQpbANA8Dob6j7rCsTVhTdF+Vc/qZnfqNlXhATzjxjTt0ij1HCU5TwHB126RhxZh9ybis6seCfmvPBHG6oURYU8SNSaKR36TWtJ7e0m35XbPpdvuFX2fpfZOBx868KLb9AgVB6fEXt1S29D7dNP0nZDEnYDknYL6kTD8zYRxZBJ1bCI3PhmU0IPDi0DD5HRyCFwDnuzCH6BBUJWwABjCOHyHP3xHPPxCMs0vf1FJ98RkSgcAiPieknlMxvIJCDyv7mlazoIQ1ANw2oG0Z+O1bsU2zEAS7mgp6D3E0PyP0cWvU5suYypu7PlPuXMQ3dmqS3On7vtP3e69Dea/nB+KAbMIdJ2iQVzBOyvPyLb5lyWHmvUdxKGXQILbXDFUBgxiamdtxChxkwStwTnkq4xHGrRpHlq7ARrZaBlWD2KJkvNYlZjmEtXmndirhUz8QOx5C7BpQC76QneqQsFKO0P+3xoKWg14j9To8OY8SC+16N+FoJ+0zCDvK+Wxr9Qhr9XAo14BD8PfHRn4kP/4xr+xbZAiXgggfmvuaSVwnhh7p+HlB4SsmCcU7JPobM8E49JSSeE5LO8InIOt7mXGTRcw2fVTUvKLpzSBsU50UNL5Di4NY2jQI2DP039fw2tCnr6kQk/PKYJRnnWXH7yVs2E7etVvTJn0npf/nn/UnJAn0OaXpsGXxhE3puKQIRcGYq+GItOjHhLikRIaFHZVFdNw0e3tRuuaZS+5s80sb1V9maX+Xgcf0vckhj3/+WhwIBQqHzqsbrqwZjMo6g9rcNmQDBU+vgfXP+Ccg08+Bj69DPDjGg3ZA+p06xEP4zl9gLTPypc8yJU+SZS/SxU+ShU8S+Q9iRUzSyvC8qBCl2jhHI8oZusZcBeZ/980B1LmsR1/XIWyb0DTPGtg1nx0n4lVP8p7Dqs6DyUnQHPOTn2MaL+KY/Mx5+zXz4LefxC12/d5rUD5r0Hk2/Hm36qIWgzzE6yjwoMbLFhVWqh0+mpTxVw8RcNWLQM56pesQBGTiENOhSsrxTnjqENip7JvkXvEeWa8FE3HUOaTGiFLALPlowK6CEOEe0ahJznELvecQ+NqQVRTbN2HGqA4NqRrExg0bMAYOA95o+PVo+r+QwEPiXso7dcg7PZZFVJzskbQ9C6v5K7/qa9ORLZNvnsJZTbvVxYMUZq+KMUXxCAyufe0TKPPROPcAji1zuuccdeyYeYqJ30MIDlGjHOmjXjLWo5r2g4gHhn0JavaDGbluPSVj3XjMek0Ej7QO1iD8Q4Luk7Lmk6L4g67og7TQraTd+03T4D6Ohq0afrpoM3LQDfj4whiE4MRedmAkvzENODYIOdQJPDbhbGn6LCp4guD5JWPZImD6+pdt4XeXO73IVv8mW/ypT9ZssjOrf5Jr+UABWaP5F9v4VxfbfVbr+0J5RdVvSJG3qBxya8/ZM2ICAY2vRmV0E4ODSMearSzw8PrUNhz/PnWM/u8VfYGKhkB05R54DAbjGgXPZMuesmzAg2GuG9HUj/00LzpZt8L5T+L5N0Jqm74q6N7jNDV0yMAH4zz1L9pYd74ye8zmoDDFHYbUAgq9xTUhP2LS2L2kPvmc//jO3860efUA34JMeo1eLNmIStOqasOWRuo4scxv70J3sn/JQzyvJnJpLiLmvjIkWVPbbBVWJ2wlo2d3wQNYlMqDgtSYhScw57K5r2D3rwHLP2EdWnBotUq5H/FN5bBIquMle0GjLraGkPnfh143zykeMGJ90fHvUCK+VPZ7LuXTKOT2SRrVL2rXetrx/0/zBbcsnMvbjbrG7zOIVQtqiW/yccxSMRUzsCSX3lJyz6564g43ddY3ZcgzfQoch61qiBNto4boVd9OCtWlAg9hPyzvPK7hOStuN3DIbvmUyeNPo0w1DGH03DHqv68Pou2n86bbVmLT9hDQK1NPYbST7wfp/umrw6ZpBz1XDPbToi2fKF1TkhqLPtip1T83vSDtwT93/UIu5r+W/qUEGeI3J2H24of9KQmsIazqKQZX+Klnyu3TJ7zIVV+RKfpEq/W8pAEHdFQQHzb8rPLym3nVTZ0DcaloRO6+ENCjY1mfsGDC3DVmH5vx9s6Bjq9Az+/BLdOSJTdiRVcgJkIELhDz81Dn62DHi1Dlq3z4EHiAKxipoz4q7ZRG4ok1a0fRZ16Uua/ksA+Ep4VbUvMBurGv4AgsiwyhgxybomJAEcvifkLpLfgWA4As46pjmr/F3vya3XiTePYdtatu39EefDAL7dfz7tehDesxZS+GqfeS2c9y0edC8XfDzuDpdfLIVu4yW++qGDZ+W1eUV/+C2Ld8n9ak1pxzC7xHVgnRRdot+SErt1vbJcQ67bxPUYMWtYxX3AxOAJnAMv69OzPZO7qSIWsYsOZD9r1U9nyliHsk4tkqhWiVsHkna92qTFlGCVQfRukPwnC3/z8RHXyLuXQQ3fBU0XrDunPgVbXkgX9beBN5zjdl2ioCxbifasBVs2wm37QQbFqw1Q9qyhvesIha5gS/nCHk/fNtk4LpB/3Uk8EhP5qvaH/7QeveHxo/bOFrvruq8+kPr402jAQmz/lsmPVcNeq7pwfbdFd0Lr+R/BZafuCWcWAihUqzKeWwo4jeUvLfUfFaU8ePSaMj+1zf1uq6qv5TTe66p8Qlv+Aqt8kRfp/iqdN6vtwt+lyi9Il19Q6HhpnztNalWaaUOeY3nckiXlr5bZuOyDvPK7hCwn+3a1rXI4DD3DBmHpkEHZshA+t87RFxiEy48kqD8A/MfoiMO7cHjBG9Z8XcJMZdBRf8kNf6/8h/835kt/8vJ/+aVcO4edY6P/eqXdklOPSEnnvulfPFN3gX14xx+hku4JGd/AdnEyP/KLz/nlV2G1XyJbLyMbPgSe+970sNvqY8/pz3+mtUx5hjWr+U3CO5Aiz5pFDSmz5ozF605xG56pG/75thio3Cxbbj4dkW3WJ/0DlNmkaRjCKPglSmjwDSgUIOYKuUYJuYa1kpOe6lGyKRkvsZEt2t4Z1MzXiph4ux4tb6pL4z8isgJT+pZZR90yM8V3J/IOj2RdXgiaTug57PjHr3jHnuAS9h1jdpAi1ZsuNNOwRfR9z9Htp6Jmo/ZNUf0sjO/okNi1j4ueRsTs2YXso4KAQSs2wWvWvHWrYLWTJlrJv5Q76cVMbMKLkjjZBnb/tvmn6StVw28V/S95tXdlrRwY7I2/TcN313RfnMFCrMm2LauK2rd1zVBtz+/qtMjbd4jYfbmql6/hM0X7/S/aUXnmORLu4hBSbtXV3W7rmm3/6F8/w+Vlj+Um64otlxTbIYYS0iO4h0fGaoU3bpRcF0i/6pk9m+3M3+/VXhLuvD2bXjymYVeg9LNbiPdZnHpFnHZ+1fln/6mCjgYkbKDOgKifUbWBcayiue6us+mJgWIYd+Cd+EceewShXR3BqFDyfrMK/13VMP/xjV/Cy7/wim+pGSdeSV9Jqb+7HoKOvGCkHDpnXTunfzFL+uLf87ngKxTWsoZJ/d7RNXfwvJNG8GpR/xXWu4lPfczu/iEmX/GLUXusUY2Agj+Tn38Z9oTpFd47qNBK+6gNm1AkzqkHfBJE3DAHTPizFiGbOHS9nzzL8peeSc8BCkA1iC0YVwOGyuOEjHy32p6p5Izn6vhk5SxsWJWrGp++bCie4qj6J6Jf4U+uQgX90TdKwtUITxQxaV7Ag34p75S8ezX9d3EhEPsD4lJcEl7uPgdbMyWU8SyBWfOmDGpR9kgJR8Hlpzwqs94tZfc2kNq0T4xc9Mtfss1etMpYtMxfAMduumArI++ZS9YN2dvmjMXtLxnVdwXdPDn5MRLctKFd9yRi3DPhg02b8PId9uYvGNE3tQlrmt6zsk5jNwyGRE3BT4AB/8YXNx/KyBNyX9Xu/vfSp2/64KDOMcmfiflXjjG7BqyXtw0bPlDsf4P+Zo/5CquyFT+IVv+m2S9pNRTPcUXtirPUapdKPVCyWu5t2+WSsvl3hJPunE9S1oi8fofFWo375vLNqpL1EpJ1N4SbxGXa/xDpvUPxSe/q/bcNB6RtpmQRYOJn5Z1mJN3mZFxBGu6ok7aN+OcOISdu8V9J2d/I2dfkDMvfDIufNIg8GdeqZe+mT+7P8O/4PEXSjb8Fx58piKdsM980i+o2Z8Z+Z85BZdBJd8iqv+MqpvV8V3Tp8FFgYo88Eo+peeeBBad8yvOQ+u/xbd+S2z/lvbwS1obgKBXz/eTuu+wFnVUN2BcnwnbCUPOtLlgySn2wLdgmZLrzqv2Snik5J5ASHqsR86SdQx3j76vTUoPyHuj6BZ/zZwjpkHIoqS8UMYkYyLajQOqLNh1XmmvFD3SXMJboUyouSYmBtUehDWcC+7ASRzRsk/9sg5JqfuecVvOIUhHNrPABUO/OX3KlDZpxsR/Axu9iolawUbtEpKgBGy6RK7aizadwtdRwi3HUKRHAQzboBkd8pIBdU6DMK3sOihhDqy+5cw9847dceCfuoSdOAiRHjgW7HUd31VNr2UV9yUFp0U5x8lbFlO3LUevG43eMO69ptf1h/rdXxXByN37RXlc3eMSl/iVmAkgOLYI2TViPr2uWX9D5rG2+hM9zUYF6ZJr1+rkbj+3VW43l8mU+T32qli+0s3Yq78l3riaevtW0q0bibdvJonfypQST799s0DiVrnkrSrxW80Kcq2SCg+uK979Te7BrwovrmqDOAAymJJ1mpJ2mJF1WlBwnZfDbGiStvX9D62Q+4bA/+duiWe45AsC0u37i08meEJwQAgOiGnIIKRcEtMvScgXUpB26L6ZF76Z4JLOqFmn9OwzRv5FUCm4wQO38BVNItAkjGUz5hktb5+ee8guOgmp/RKLgOBr0qMvqQ9BHvZaMIbUfIfVyWOadBjzpkFjOgHz5sELNqEH3tmb5Dwiv9o6sFTONTr87jQh6SFwgFfyEygETmFN+n55mt7pYmqeGfi4DgXXVHt+Cy7xhUFAJTYO9sg1oJaw8nqLbNgXSe1A8l+j7oHd/8K/c0TLPSCmbmMiN9DBG7bcBRP6rJ7vpIbXqKr7gLzjJwWnOTP/eVvOkn3QvBVnwZq9bMtdtQsCxbDpINxEB69YBs7pk+d1SfPahGlV7IQ8aljCAti+74beoJztgQN/146zbsbYseYc2wn2rTjHVtxjs8A5acc5KfsFKdTcbavpG+bTP6AwdMPow1Xdjl/Vn/631gU26jMx/S9Kwd/U4gPLkCVdctsttftSig0SEi0q0i+sdcukfqvXvPYCo/HQUTlZUuyRs07kzf8Ku32d99t/x4tfC7v6m+jGH7HiNwAN2RK3imWksm78UaUkUy19+/5tudZrCm3XFFt/V+j8Q61X0mJe1QPEAdKzTwEDDnZF1ROsypYW5cCUdWwrvMTGXbgnfSWkX+BTT3HJ54QUAAFE/TMp42cT+HOvVORJz4Rjj7gTfMKxZzwYpVNS2jEM3/RDasYxI+9cUPYfQemPFknei2qEGW3SrmfCATX7iF16Gd74DzjwuPbPkXdPI5v3w6q/R94Z1qKM6viNa9MmdOjjuowJ/cBZM8GiXeSBb+FWbGtoSY+hX/4VqyDv1A6UsE6PmmvBqRB3CPPLfaWCTzZllInp+5UQU1/IYVOx0R2O4Y8M/O8EFPQCAlD8xqbMV0fwZrHwfq2nwfUnnDsXP77LBWZvD5+46RS6bs+fN6aNaxBGVbFIM12kybJtj5TlBymrQVXssiVj2Zq1bIOAAOlCb81asgpcNKXPG/jO6hJntQlzGp4zKpgxGdSQuPnQLWPQd73XdXuu67+/pvvupvGkPvFPn4QNYxoim9U956VRAIJ5cdvZG1ZTV00nr5mOXjPp/8Pg42/6J9a8b96AgLzPpOz/MMpOHaNHtFybbssCn1frSLbbyrXo3a5WuNKqK/0Mrc79RSxZ4UqS3O9NNjp39FWjr/2SKnEtX16yXFOJ9fsvouvX0iVvZ4pfyxW/WiJ14474jXsSMm2SCq3X5NquKjy5qtIrY7Go44n08VLFgSxYUHSblXOG7YoqYVOTfGjG3rNGujyfucSCLTwDieoO5R+BwgkuEcYZsAJgwjvlABv946uL8Yfu8ce4xEPPxH2PeGQZfHzCASX1jJmzoEmCYy6pEhbVvCbVvOBf+/T8I27Z95h7/4/Ujv+kPP0rvv0wuHIvuORSUPxJgzysTR/V9gcOABDMmAQtWIoWbMI3ibmBnkmM7BdSzpGgBvBJT9W901wj7nsld+j45oJa1KXkKHokiCl75ZAz32iS8pyjHlHzenTIhS4RbY5gGpl3xlM7ThM7Psc/uYxqv4y4fxrUcMqu3qcV7vpkHZAygPBX7IRzZowpPd8BeechRcceKeuPUmZvbhm+lzCB8U7C7IOMzYoFDdCwaBawbMGEsWLBWDChzun7LBj4Luj6zKrjAAeT8o7jMvZD4pYDN03mdQn72LADTOihS+geOnjHOmjTOHDHMGBdjbAo67Qs5Th3yxpwMHHVZPgPo09XDHp/0983YX4hpP3Lv+gvv/x//Ar2UMIuKb02DcU7qtcqtG88dtbsxCo3monnyIq98tLLUhXL15UKE/81TvL3WlP1Yg3JfIVbOVLXK1Xl+Nd+CfhdLOT2tbDrv8bf+LVGUapeTrxZVqJdXuahtNxDCcWnN1TeS5rAOS9rEcEmQOzn5DHgaWdlXdfVvDc0fJEOz5bcQzvhqWPkKSYGxjEmGmTgqQeMeEh98C8/w3+Ci0cawXskHLrFIX1x3OOPvJIPvVP2iSlId5SAnFU1qIN4AMG0kvuEpvc6NmqPmo18s5J/5yKk8Vt067+SnvwZ1/Y1th40wZAWdUiLNgjlQC9wUj9wyoCzYCFccoxdimzAR7RwS3u1fDKVPFM4VYM6tAJbUYNbbLuie5JvereEY7i0S4SYGaMqsLAfhCFa2EzOeIUWNFmza/BxTy38KzqzX5xlvfya+vw87tFl3OOLiPuHvOpNasGmV9qGW/yKQ9iCVdCMIW1U02tSy2tY2XVAHv1R0uKDpOl7CaO3tw1g++a20etbsDVbMqaumPrPGVGXzekLhtQlyG9j+rwWaVGbOK/uOaPkOqXgPCXvOCplNyRhc+YV95Wc9tkn7ZKQ/NUj+dQ+4hIdfWIRfGzM2dOizt60nb5uPX7ddPCKwcBVw97fDBblMCdWwn9IOX95Z8H+W/q0SXPrXjfVVy7yT9BycbfEHjppQAmoM1XgXRWLFxd7gtZsR2smS/9aZiCTpHI9RvZGmsS1WjWlMnnpWnXlBOkb4bd/z5K7mX/rSvGt3ytvX+mz0H+iqNz4h1TrFcXua7pjcg7Ix7tqXkvKyE0t0AQL8tglRdz/YQJz7omdaM9WcOwYdugUdu4Re4iNPHWLvsDFHWPgQeyxW+yhW9SRe/Q+JgJgcQg7eMafEJP3vRJOqJmngQVgK3asuasq3sAE88qe02qEWTPGGi5u3Ttlj56/41+IfHU9/O73qNbvUfdPgiv2vOMGtciAg2Fd/xFdJhSCKWP+tIVoGBPrGdIE6R7WMH7NNtiAXsCu7Lfk33GOaHEMbZR2ifJJf6bsEa9LzhBzj35CTO5W88y04dQR4ju1iblmARWEmCdmtLLkiOaTvLdniZ1fkp6dRrUdBjds0otXvTLXPFMXHCJnLPijerQRTeKQmuewiseYmsegonO/rP1HSat34sYwAAcACHjwoy2o+ZCKK9DAmlUgoGFeD2SB74Kez5wWfkrFbUoRAyCYVnSZVnAak7QDKIB3OsMj99tBb585xVygoo7MhRdWYWcmgkNd/8kbNkADfb9q9/6u9/6/dHY1fPY06ed2EX+7p/zllrStRT8yYr1WU33nrt5qKdluJ12kdYV5RYzxq1io+G9JkleKxK92o/U6HHSqjaXCpMWCJX4Lv3GlSOp2q77WHUWZBNnrvOti4df/q0lJolbm90/Oxo2S4nVXpVpvqjz8Q+XVDcNhGcdVLdKyGnFN3XtB0WNVBbl3uaKMX1f33dVn7pmwT2yFB7bBp07hh2jwCzGfcYnnHoCAaOTzbtcIAASCAwyAAPky+x6kuBuY7ehdfNwx8qX73O+B+WuqxA114pKS54IqfhoEAT5xj5y+Q87cZxZdCGvPhPXfw+9BQsKD46CyT+a0UT3wh5Qhbb8pY96cVSiMaZcYZniLNDqclv3SlndH0iEcZCA2+j6Ug4DCD9rkXGV8KjhGKbTomgVbzJBewS0f1fEpsObU2Qc1qOMzldxSAvI/ahOy0xOenBe9v0zpuoh/ehL24JDfuE0vW/FMX3aNHzfnjxkE9KsSh9S9BlVxAwqYYWXsuDoOQDAgZ/9e3AyUQY+EKWwBASAUeqVtPkhY9UjbAiWsWzBhIG3tDCkL2kTAwYyax5ImYREoQcEF+TRdBj0iaTun5vYPmBGP+EMX5HP6MyBYa9GFVcipMXf0mlnfr7off9d+/6vmyFXzNVnsrjrlb+eEv9yS/8SnffdKPfGI6HU0brWUrjO8XqL1610nTeCAsNtiSXK/pcldyZC9UqIp2WimlKPwS66BJAsU4vVfAQSF4tcbVaWLVMUjpa6G3Pr1sbFmldzNMonrVRI3msRlntzSeHFDBy4NaVSp6b2m6bumRgJ/CAiYk3VdU/WCcrClS4OKsA8K0Sb4yF4ETuHMBfmiw7FLBNAAIAAG0gLQJXzfJRKkwBE+6YSUcuKbuk9IOgA/ySr8U1i1o0+H4gIHhFqwoEHcsBNtuicgv4Oj559wK0+D6y7Cmi5Cm7/EPjiPvncU3fg/qW2TxswxA/9hXdq4AXveQgiSsK5u1CPinoJHArP4gwYxXc0r1SP2ISG5wym0JfLeohGzQoOc45nSIYuNJaZ1immSi9iVY3K4LO+0t9jYZyaMO/KYZL+cj/rkorspjy5zX18kdhxHtR8K724zqjaIuYtOCTOWIUA7A+pgT31GtXx/kkGfnMuYqieQAVIX5OxBHwxIQ+xth5WcBuWdBmVRg7L2vRJWgJJ+OYdtG9aGOXNWmzSr4T2v5T2v6TWn6gmqexr51i9mWt4ZDBhCCdL243IOfxFTP3ulQGm49Eg4sQs9NmEMXzPtu6Lfe0UXaGBJ2nVd0fsv6/BTPd6JGutMk72hTPyoY/hA+/YjU6kulOxLjGKZvthjD+VMrf+qsZVPUriSpXwjT/H6M0fdVivFWmPJZKnfs6Rupt/6I+3mlVIdRWCCkBu/xt76I/nar5m3rlRIXG9RlG2Sl+2S1n0nZdIjZTEi5wAgWNH0WVTxAgEPFWFRyR0p4arENU0ygGDHiHFozkEco63wyD50zzr4wA65c7zvEIaYfueIPcewI2zciWfSuW/GJT33jJZ97Jd9ySqCQjCp4rGuTAAQALxmFN0XjQKQHlKk1F3ftH2/nCNm8QG77Bg8mqDmLKzpPPruaVzLOa9szoI7Y8YZ1WcAE0yZ8QcDSqDee8Q/knKJETVMy+NSFfHpyDcJIlo1Kbmeyc/MeTU3HMI9Uzt1qfmU7FdiSoTsgJJhbUqZU8RjUsZ7JVymjHOSR0yHMbnoKK/7IvkZDADBEb9l169sg5C75poyrB/486bEiA4QEW1Mnz5pQJ/QJQ+r4AaV3IASwC4CFJDYyzuNq7qNK2OG5Z2G5R1GFZ0ABOAj+mTRQBvgERagLmgRQQkvaHmDIZ5T9ZhVdkNAIOc0LoOCAZQAKmHgluWoAuYbKfPUJXZW0mVeynlO0mn8pt2cpMtf1qFn+twDdeapJudCi3eszjrWZo6omfQ5aT23lK1X++9HlhKPUVLVpr+3eagGXRWLlv41ReGPfKUbVaoS+TJ/lMjdKpK/1aCn0oEyAyjESl8Pv30l9NqviVd/Sb/xW/o1sWG8aauqfJ2sxBMdracami9VjD4p2k+ouEAJg1MF4IJNAP8CIFjVIK1rkde1KOs6YBcDD8zYQAm7ZhxghT0L/oGt6BgNlBAFxHbgGgV68MAtDpjglJZzzio+55T+GVL3b34ZlBiQF6sqBBCec7rULaeILbe4DffYHWLKnl/mASP/mFcJIDgT1h4ElR8Iyv43tX3cgD5l6D9vwR7R9Rs1Ys15JBtp+yW0rTJLB343DwptmFbEpar55gsa56xDWpS8M31y3tiH3TUKKMElPLbiVbvHPRRT88p1CmuzD75rzqrlVU2pk4okHeKDykeUXZP7uWX7EfdOYx7tC5p3/coX0HFTluET5qHABOMm/DmbkBkr4aJ96Jw1f8aMPabnN6btM6jqAfpgSAkzouIGUBhTwU6oYEflnccVnUdB98k7jig4AjKGFJwBB/1yqI9SNlAjAChTau4zGjjELCi7jcs7jsmgx+TQg5JI+GH7ScIGKuumtfAQHTF5ywFivyjtPn3L5cIwaFuZvClH3JL3PdPiAAJOdbgnetwJHZtXpnL9ruofnBSHfYzypMUe2stlKYk99zaIFReLvCUWefOXqNtXEiWvNptKttkoJcrcDL51VSRxnX3l13ipa3nS1xAE3LiSL/HrJM2sRUX8iZZKh6Zml47OQxWlTm219uuqnzTQE+rYCSXkFwrzykife8TOKeFmFXBLqt6rGj4AiG09+oEJ5+d3T45sgrctgvZshEfOkQeYiD3X8D33mH3PhGNKxllg0X/CG3fMWVBWVpRxa+qEOSW3GfCcqNBDQtKmW8yud9K2d/JhQP4xp+yQU3oeUnMUXH4sLD8VVfRrEgc0iEO65AEDOtToaevQFaeEDVz2IqsaF9V6014UUj8B5G8UWO2c0GEdcu+mUwy9uE+LUiCDiWOV9ulTCxAmkHRKMPKv9Ep7pYLPZpUM2fIabliH+ue8dRHexbFrhykFxzEP94VNO5TSVZfkRVTcnG30nH30KjZxDRO/4hy1jA5ftBYsWwfPGAcOa3iPaBDm9CmTWt4z2qQpDcKUKm5cCQOxn1BwgtDCdlQWNSyLHpC265Ox+ySP/lE4bN6LW05reRyiWN9xEav6ZCgNk/Iuo7JoiP3H66bvrpu8v26BfKfILX4HGwsPtrSpq4qEWUnsuTF7Q4W0oex7bsg71uMeaHP2DXmXNuE9GtZPtZUfaUu2697qMLndi1Ptp+kVqlxJEhd75qJ8z1Ky1VYh+oZYtqTYOMui20OLf+2/edf/4F+9EnL194gr/50tfrVRRznzxm85t3+vVPxjjGy5E4J/oqbdqaXTpi7/REW96Xf5TknjPl3M8b3Mw7akl9JGU0ouQAxzih4Lyp5zip5QKYASNrXpKxqUfVPelhF7x4y3Z410CT5yDt9GCbYchPvgEbwSL+lZS5peywpuyFDCQX3ZNwkAW7io77fjGLHhFI7ckvGIXfeM36XknHEqz/nV+6ySXXbhEb9kyzt+2Tlk3Ia76ZPyTNPrlTb5kxF71ip81SFh1yN3i1TqahcZWNLvGvPollMsq3IYHdUm55ka0jijTsxU9Up3impV980mpT8X0yQVuSc8gyHnkU7MeOMY+kDRLRUX+9QhuCXHp2iBUbcYUH0Y3rLknrbkmLDslLhLyNn1ydsj5W0RMvaJmcjvfJ1jVmyEc6bsCW3fUQ3itDYZxhqUfB2fGS2vaTUcov9V3P5PisshLZ8hwAgUpGxAJQzJoHpuWb67ZgpMcOggvMDHn5ISdrxCtz35MxY+U7qeMzqEESXXNTMWgOCIkHJGykC+XWgftqlFnZBwGb6NHpKw779t9RNYQDALRsSnt3Ubb0m0GYl32svdM7z12ka3WubGXTXpOoWrrbqS3XYqPR4GLx012vSlZwKca9WvPTAUf+uq02YiUyR/vUzpVr2GVJXS9TYTuUada29dNTtt5e8qSz+QUb4nofRG17JH1/GNkt1rOftRfe9Zf/bWk/SLjwWfPxT8Oz8JUD4j6zInj1nXJgIxgHjc1KPtGCCWAfhgyzhw3wbBwZ49f8seWIE9J+e8IOu0KOcCHAA+c0GZsGfJHlfEglTatAlat+FvOIRtYaM3PeJ2SemH1LxjZtkxp+IkqOKQU7xPy9r1TgY5uUlI7DNjtCli2xWxL1RJfXrsSYuIVce0Pc+iHZ/ye+F3nfh1v1gIvNNfGLPK7UTN9qFNt1AhXilPzXmV11Ait9gHYureBa7RHa4xT8xZ1ShBMzq4Rdw+yi/tNZpV+x6Xsx7YvEytmSOVLHqkAs+sY1K2cJk7xLxdUv4uMXefkLPvlbWNTdxyil605C+ZcZHVQ0xZc4b0JWP6gqEfSL8lXTLwAQICNQ+oowCFSQVXmKyfrAAksapP7JWwPost/Sux8n9EJReEuAUT2rQGYUbNE1TCkrrXvBoecUpy7lPy7mtGrDUL/p5z9GeP5COb0ENT7pik07C47afbVn23zD7cNn19y/jVbeO3cuZdkvpPJbVabsk33ZRpuiXdoaPywVnnvYvOfT3ZKhmJZxaGT4w1G1SlS6V+b9GQemarmfyHWLXm7/Ms5+xbV/JuXiu+JV51U/aBtPpzGYM3sqZ9Craf1NAD6qgOcd226+pPJfRH9HHDut7zFoHTJv5LoHPzIr60Zu+7c2cVXcHjTMs4Tsm6zCpiIbNX1EnIzxP0aBt6tF1j5r5Z4L6ZP+wwKWk/JW43JYUG3Kxo+u6acw/RIV894wAE4yruK+asdRveqg1/xV4AmuCAmn3MLD5kITeLDvkV32IaV5wjVjFRh77p+77pO5T0PDGdJmn0XWnHJ/KEfn3OsJFgxiZuB1d0SGvoEz28YS3CRLUQJGkAAEKcSURBVD9QIaQE1Y7aiBpuOoaFtczo0PKAEjDxD8Tk3dIseA0OYQ9/MQ3GJ77wSn4h7RhHTX2Jw6UtMhvXmE0rlJol77I5l9R159g1dNSGc8IOLnPPK+fYt3Abl7aLS9/xSNt1S9pxjTvExm+iwzdRYWu2wjXrIKSru7H/ooEfqL85TS9wAXMahFlVT2D7KUU3YDzQgwfWvBOU6EeP4KBDu5Bd86AVHdqGDn1F3WdREQ9jRY20o+O3ru4DY1kZxJfvsjp5UZ/53bfg0i39xCb80DQISHhSCj0kbv3hpsm7HzjovmHw/KZ+922Djts6D2+odUhod0prPFZXqpOXqJWQq78t/VhF4ZWRzlsro3Zttfsast0W6s2qN1/b6zVoSt9RlC6/JdEornT/ttqjWzqvJS0+SFkNyKFA1Q7JoYYUHfrk7D5KWz6+rt3+h1a/OmbJKnDBlDGm731em7rlzgBVOynrCMJ2TAo1Kes8r+S+pu2zrEFa1SLPKxHGpZxnZJ2mZV2QG45gAjV8FjXIawYBG0asbUs+gGDHigM5M6lOgNlbteIsmQcuWATOmgVueibtBxSe8qpOg2u+RrXM2okW7ISzdsErmJhVr4RVUmLJVaM74ua1UjaNUugnivh3GgGfDAX9+kGDhqIlXK6SpZCU9ULPv4he/BET1yaDiSFmvVAkpIIwVCWkIL1igQkwcc9ViAWeSS/16VUS6DhCfOcDfNZSQP06vXmVdGcKkztoG99vJkK6O9qFbmPjdz2Sdj2ToRbsuicfe2XuuSUiAxO/6xy9hQ6HsWEj3EaJNqx5KybMRQP6qpH/qgENWAHc4KwKDiZlA+q6qu+sPGFTj7FrytsHxWQXfmwdfmaNxHVTO2BTkwIDdgPzvalJhoEYcS3qpo4f5M13Uv6fvsVnjvGAgzML4YKCJ5DwhCRqEOqCuMWbmwbPr+q8uKn/QtwQxnNxvU5x3WdyBi23VB9IaD+VNXgipdchp3dXXPWupEqbonqt/JURommDrHizlFKLhPJ9cbWHkprdCibv5KxAvU6qe/w4bfyskgeMGSUs1LUhKdteSYuum3qPrul0SZj2qNvv54cCUMAsAAGA0UV+L6DosannB9m/a8ZFfhJpIzqwCoYB+mDdhL1lEbRuytm1Dob5gWIHUV8zDphSxc9pEheNaFuOok0H4YotH8aqnWDWhrvrm3HGLvubVwGObNKIsWAbvIKNXcEn79LyjtjFj7Xw9bLo0tuWedeM6xScujSpj5V97sm5Vd6wybliouocR8x6Je2eRC78AF7xFzNuQOEHTVJGVNMUOrhOTNO3xE7YKqiZVfEGB9mNFt1Xx2fxSwYHfcpW6PXbjOYFfNkIKvmtoeilXtBzbf8VXOIOhB+fAlDYwsTtYhMg/NvOMYCAQ/ekDVTEjlM0kMEWKnTTVvRjKZCgdXP2kiFt2SgALnJey2dDlwwcPiOPA/sEMwJOGsJ/7hhzio4+tgmHsWcqODAV7Blz9024yHe59BjgvwEQq6ok4INVVSJsF7Rpf5KLv3hmnzvGH1uEHJvxgScW5N0XFdympR3AWEKBGBC3BG54cVW/+7rBG0mTdwqWHeL6z6WNX8qZvZQz7ZIzar2hev+m8n0lmee2yp0aWo+lNKCCPL2t3imu/ey2btdNndc3jQel7YG0ltSJS+okAN+6DhVJaw3ivJLHnIr7pLzzkKxd9zWdh7fU/xLGwjPIFySVENMIHmFTn75rzDq0RsK/ZynYtRIc2IVsmHEh8JD3u9bCLQAEKmzdPnjLOeTCO25CyW1cAbNg4Ltqy9l0Em25hu64Rqyhhdsu4buYyH3XqBFNn0E17yFN8qi+/5JjxJpb3BouYYeYvu2duoyNfaFD7tIlN6phiyWt65RdysRtyyXsGpQ9TjvWzBiVXukgGHKEjdPuSR3S2ER2+eBVK76wZljNK1kMJWyx5NR6p7/U8C30Lxqw5zepYJK5CR1LgfUbgY0b9IZJ15x+q9i3BsLn2pwOjYCnWv6fw1p2AsuPOHeOGRW7xOw9z4w9t+Qtl3jY7rmChk/ccoj6WRe27ELXrYWr5kEbFsgqcyvGjBXgAw3SkLgjWOdzp6gzx8gzVOSJXfgJKgrGKUDBKfbQPuLMIebIOuzYQrSty1zToG5p0YADNjSADMjLSoSlH5XiBB11iUk+d0oA9MDOZ9Zhu/rMDUCJoueyvMe8HAbU1qSU47g0GqQoKNCPslZQIDpv6nbe1O6+rfdCXP+FjNEzSf1HtzQeSWg9vq355KZGxw2NZ7e0um9qPb+m9eqG/icJ6wlZ11klz2kF3LyKF1A6DEDDug5lRdNnVct3WY24rI6fVcYgxHDTHEAwJY8FSfjzhsG+MRuswbYxZ9886MCKD5LwECXatxXtWAmABnasRNvWwm0H8Iqxh4SEr/S0MSXnUUUXAAFyc92GDWSwgQ7edhSBPhhSJYyok8a0qDPGrEVr4YZLzKZb7DY+cQ0bPe8UOocKnbAJGbMJW/NIG7WP6Dbzr9K1z7c2ZegY+sa2S9iFYGPaLIPqrtuFsSuG9OglAAh0SNNvZjxiZreSR7KYDbde3jWJUzakRixwi3vmENKq5Bj/OLhllVG/RKpYIpSOOKT2mkU812J3qPk/VqW2K5Huy+PbVEn73DvHgrpjTsMx886eV+4BPnfPPWMXm7KPSdlzTd53TdxER6/ZhW07RAAagBVWLbirpoGrJsxtU/aqHn3TkHVqH3ZsH3FoG7ZjJTx0jP7smXriknDumgQkD3ywY8jb0mXtGbDXNGjrmvQNDeqGGmVDzXdNhYSAAOF/3LyC+7w8bkbRc92AeWAlOrEMOTH++RN0vwMN+p4GbVPZd1mBMCPvNiYLFR39Vtz0nYTJe8n/s30rbvxGwhgo/dktHcBE5w2N5zc0u69rvbim/e6m4ZCM/ZQsZkbeY04RvwT0o0PdMwncMvBf1vRFfhOhR90ypIPi+0ESXsjXJJXdxmQcB8XtpuVA5yNfN9rS8QdrAGSwY8oGzgMmAARA+HdthYfosH2HsH2X6HNCypZL5AEu7rtvyoCk7YCk/aC046iC24ii55C856gyaUzNd0KLNqPHWLZElmZdtg7ddopbs4+cNubseCZ0K+NeqXm91yT3aNOXUTEL6NhhK1GnOqnmms2Ye6QgpEHTO+OarSji7gI67N5NxwhR46Qhs9Ql7hE64i4oA1zyU1AGyKeIGoRsSvprdUI2Pr4TH/cYzSp7x6hYplTNeeQPoZLfGYd0AQI0Ah6p+LXKE9sUiffkPO/JedwDT0xM26IXHXNq9ygl24S8Hc/cHffMPffMLefkTYe4dVTUlkPMjlPMhh1IBNG8MWtaj/YPveDcM/nYEfmdxp51MEzKzx/pXXimn2GTj+whpyO2jYP2jIN2DFgbWv5bOgzQB+uafkAG66rkZUWvLQ3KuhppXY24ogxQ8IASMK+EP3WNu3SN/+yS8AUVc6DNOtRhn+rxzg34+xoBB1r+SwoE8O7gSvrErZFb19LgJ20/SJi/lzD5IGn65hbygec7SYM3t/Tf3dR/f8OwV9xyQs4R+dqIEg6qDCBgWY0EA8rBqg5lWYe8YUjfNWMhv4AwCoAHMLZNGOt6lFUdn3k1XN8ty0/idktqyF3kfX3mrkEgWETQPSB+oRAAAnZRISfYmD3niG2nsCNc3IlX0jdK5rgcdlLBfQLwKoMdlfNY0mNuWohWzYNXzIEJRIvmggUz/pyZYMkqZNFStAM4sBStOoa9UMF3K+K65XD9WvQRA868ddicdcSgMfeTCf9Q9ICX9FQJE3cbFR5Y0msuqHNLfIoKvSvpHB12dx4V3gLuwDm69RfLIDFzRiVa0CysGjOilxKTOhk5r9UxMd2M8iHvwim3vI8W0d36/Ieq/o/U6I81aPcUiHflCc2yuLsKuDpp5zvi6CWfjHVq/jo5f4dacuBXtoXP/wGF7B1s2rZr0gYarCNyAXOmnFlD5oS+P4y/ueUXfvlHHsnn+IxL75wL78xzXBqEfx8koW0kgGDfLGTbgLutx943CtrRY+8ZcHf1OUAGO9r+6+qUFSXStiZ1Xs4DoAA4ADIYk3b94pl06hzzHZd2iY451uOeGwmOtAMPNBk7atRtdfKKijcABYh6WNruk6RVv4Rln4RFz22zj7eMkXHbsEfc6ONt/Z6bBv23TSH84EghhOBEYCD3fPRo2wb+a9qUNR0qcMCaLmXTgLZtwgQQAKuBtYPtvgVvTZ+2ZRywZei3oO45KuM4cMsOfD/gYFWdAn4HigJ4nz3Qy9aCE9fIHXvRgXPYjnPoKTHxGBMxKecGBhhwMKWAG5PHzWrTIfxbtuH7DnGr1iErViKEBqxEq7bhAIIFgIJF8Lp9+P83//VrVWKvFm1YP3BQhz1tFjJvFTljHb3ilLbhXUJlljHSu25YcF3CmplF7zWI6X45L3Hx7XLY2NiHK5w7Q8rEDBCJ8vg0MefwB+asalzsU2ACFL+JXdiv5pKQxa3u9cgdtE/p0GLdV/BtlCLclSO1Kvk8UPZtkfMCKMDjh+qUVhVSowK+Vsb9k0PEknfmGil72zt3i5C9hctcc0laRkWvoCLnLAC/3EUL3rQBHXTNuJbvkJH/n8KGL7zqb+w7F6T8M0zqgW30oc2PYRd1go6F7aFt+IFlyKltBBSFfRP+tgEHMLGmRQdigAIBWxAKa2ogEkkQYLAGS5qkc5fIz27xh8b8I13OoR77SDdwD4qICmld1QecBZAzRHdExn5IyvqThOWgpEXfbZN+cdMBCbO+20Yfb+gPSVpMyDmAtgdnvwaEr+u3pU+H8IMIgPCv6yIif8uYAbGHYG8a+UPqb4DU1acBFOB58LoHlkF75uwd00Aghh1T5qKGd99N20U1AtQRAMG6fgBgZdOMvWXF20OHbqKEe9iIM2L8sqn/tBJUNNyMsuecite4In5Kg7xuGQyJvmYZumYTDiCAqrpmhzTbBxCsWofB81u2kYv2UX+FNPVq0Ps0/SeMBbNmYesOyUt2ydvuBZ8Z91Bu6QF572x4NUruCR4xDxQ9En634AqqR2z4tTdRYdTCj2rUfHbNqHP8I1lCmhgm6qGyZxZy2xiXZRZQyS4aMKaUsKIfzvhW9hgFP5Ejv9II/GDAf68n+KAf/FyD9Vo3qFOT0apI7tRlNSv61Mjg76uS21R8Hqv5DtoIx2xCZuzCJywE05bBEyacaVP2mD59RJs8oe3br+Q2pOwxpOw2qOjaK4fuVXL5Flj6OaDkFJ956BiLDKe4U/eUEzdkycJzl8Rjh9gdC+GeuXDPIvjAJnTHjL9nJkCGRfCOSdC6bsCGTgDIBUDDsjLgAL9hyvm/mKXnzrGAkkNj3qKiN0BkWs4DcnFRxQv50Zm0/ZgM6gcObIelbfpvmw9KmA9KWgE9zKhg1vV8wNADAhZV8LBd1UDMPQhASHogfxg7ZoHbZswti8ANU+aeNW/LlLFrwdq1YO+ZsyD2ME5sg5HFMcy5x6iwIxjokCP74D5x2zEFpzk4oJ7ftgV304KzbR205xiyj4k4JyRMKuGA/8F8zqkSplUIk8peczq0HbvQLbuQTdsQwAGQwQ8CCIW8X7JCNMGqpWDRmLNixvv/Zr0YNeKNGgTNmQE+4hatYzdcsve8y7bo9YyYR7+b8hLaV+wF9des+NTMblVCiiGtyCm0RYWQoUstJGW9MufWsCqHNCj56Ij7Yt4p3TZBDbTcHlVchqPwrndilzYxj5X19o1j3Csd3gu1QBivNTmv1NndaoGvdII61JlPNJiPNZmPNBgdOmx40KET+FyPsQr6gJK9S83f9so88s079slbdY5dd47ecAifM2cPqHn1K+M+yrl8kHV6L4N+I2n3Wsr2rQzqlTR63Tn8zCfjmJR54JV2Rs4B83nqnXGMSzpwjT12id22DVmx5G47i/Y94068047cErZsQrYsBJumQVsmvE0j7pYhZ9uQBeLrHIyGQzTITHj+wDZs3zZ01zIY5Oe6tt+cMn5G0X0a+eqK66S805SC87gMekIWPSUPzO+xokn88ZMg4qoWaU0TsX8Q+y1Id4TeGTA2jAP2LDnbEG8w69acHSs2hH/NECoCY1WPCgPoAQhgxwwpDQe2ojOnqEv3pHNswikm5s1Ns3c3THpvW00qu89pEheglFix9x2Fn2QcQKtOyrtMKmAnFNymgAY0fBH3iArZthWuWfLWLPgw1i0FKxZB82acJSv+kpVgxVKwZMIF471iIxzWCZw0FMyaR687ZG445+zjS9aJJVPkUkpYc2jN+C3b0OiWOWtOpQI2hpb7SsE93iOuzSn8rj610Dv1uRmn+opNiHfmSz3/ElP2HbGolkU9ajEhqUvZM8NRdM8/96OiW2pY4UCLZcgri6jXBsFd6oEvtbmvdfnvDIQvdHhgFJ9qsrq0OM+1uS90g7p1uN26gVuUvC1aPow9evE+reSIXnZMKzkk5W9ik9cco8HSLFgETRgwxvXok3p+Q+rEEU3imLbPsAZhWB0/okEY0yaOanlP6lHGdXxhhzljxqgGcVDJfVQNP6LqCfwxrIIbVvH4pIiFZyY0vad1fIBaPqni502YM1rUSTUijBk9+r5rPIwTT2TdmmO3hBNM/JFTNDjyFT06ss6IAX1JwwcKB/LjLw3vH1H3hbGh74fkur4fqH3IezD3YAGQuJqzNk0Yxygh+LoTx7BdGx7y42gr9o4l58CWD7CABz//e+YcceQounCNggfnrjFn2FjkZ8juiadusc+v6j3/Q/vZ75qvruqD+B9XdJ3V9IQHw9L2o7JokA4TSm6r8KZm4JsC1s1Yi4b+GxacNcCcnXDDVgCuatmKP2fOWbLmr9kKV22Ea7aiDVTErGXIrFnooiXkWMa6c/Y6JneRXN4pevBf6mRczENCYqeCeyK7tMeSVfqLMYOe91raJSqg8IOCW+J1GxGvcvAGKkLOLUlQO6FNLXSIbBXzSUGWn8FEtoFXNPQrJyQ8l3KIdeT//1p6D6+m0rV9ODNnnGpvIIr03iG99wYkJIEAaaSQSgqEDqEjXWliQRFUioIVFbug9N4s2MaZOec9v+97v3/iuzPzW+tee+20nc2+r+cqO5tn9/jgLC+0F57Rq8YT7PdiTNDyW8GaIT/ZSLAKyMC94ptxP1R9N1gxR3Vuiqs2U6t3ZM2fM1o+SZs+iU65f1lIqthmFGzRnKt4ywrasIzUgTmYjZQBFKZDUycDU/4ucAmC6RDh66DkN8GC+fC02WDxlG/SlA/vjV/ia1/+K2/O5EnutH/SyxOsicOEZ56Upx7kxx6kJ8do8/GKVaJxh++eUXiHW/p7UsXXRNe3ZNdnbvFXfvGfSWVfuCW/c4u+sgo+kK3gxnewhvco3XuU5l08tFO9HSvfQal30Jq3Ccr3GPVHvO4DVrOD024js3aw2e+Q6k94A9QOwfCZYPyA0UHK38FoQAig9240xCu3QA4w6s8U43u89gNe/4ls/sJw/M4t/FNQ/v+l1f3BLfpAsNzfH3dvXzTkEXcqOYSePE795wz6jA/nn5XlMNFSqGg5XAIgcJ9lD5euRKcvRKYuxWSuxioXo2TLsYq1hKy/S7MSmwUI+F9l5xzKvkIo2iC7NuiVS+yqZ5xKpKDSm1V8hGRnWvuY9iuHSLakomGUqu2XaLm5/dWPkZlUQ3d8xinEyURl3ThS0QaRgVM4HCCqLR/77JYDb3YZTnOWlzdI0l+QVo7vilLHSVsYxkvUpLpZ28ikuO05zTWBzhuPtd4IUfcfTx0OyBz2k0LdCpbfDVN8SG9ck9R8VLVtp536lN76Ob0ZmGBHUPOeX/6OU7xBd27+fW5xi2hdxQCKTcAKc1Hyf3AwGy4FwwijfzY0bSZEPBeWOhskWgyXzAQkzwQkTQICTnCmfRNngBg8aS+8GDMADm/OtB8f+GObnfuOV/TPvOTfpPXuktR+EbhnM/nMK/nELf5DUP47KAgr/xMjd4dmh1D+gWjaRmveo7X/9PX/Np6Y/YGge0/QfaIYv7KsOzTzF5b9E8P+le1wr9BzPpFMH4lGAMQHtNrNB6isHZzmHU6zQ9J/opuh4G3f+AX/I678X3HNDsa2g3P8ziz5k1f2lVP46AjuqSfxmSfxhRdlOpC/iVLAB9cT5OuxmVsJ8ndo1VaCe2UpQrKJUsJubGPVW5ist7B9kmEdrd7GZq/EyRejM4AdQRY3cIYPydWrzLL3wsZ1bu0SryY1Ol1RPBghqd+LtaRW3ouQNKRW3gHt34+3sHMHEhQtCH8hy9F/iGQBLeA4+39DaiWu0aMU278iZYqW58dYBe7rCRwXl705pYcIdkn5nYDESqZ1IEHe7s8pt3XNHcXba6sezJr6ZzM6XzGrHmOcDxOsYyHqId/0UfAB/un3QpSPI3XvZM1vFS2fDd2fNR1f1F2f5We+ZJ7+mNb4UVT3IbnyHcf9C9M7etEWOXcNY1lBmQAKyyjdXIxsOlw6Hy2bjcyYj1bAH7kSp1yOzgQczAWLl8LSAAfQ/jc+vL+XfGCCKW8u1IwPf94/eSFO8RW4R+T6Q9n8Z1brX+ozv2c2uWeEE9d9S637S3rqq7AC0PCJWwisAKMT6jPL6b7cm+q+tucTxfwWq4Z+wCCGgnXo6Eey4SPN/Ilh/cLL/yO5GOoj0+6eSIaZ+5lqeYfVAUN8JOl36MYvfPt/paUfSdkwfBeCxAvBaRsxmh28DRLdV0bpn9zKvwS17jnV0uqeeFOeelEnfdnzEeJNtGrD/SOydguvW0NnbRO00Ox1pAJqA6XcQGUtJyhWUaptQvYmXrdFMGyTTZsEwxpGu4bVu6/uR2rm5Q1ZukY633EiTKSuvUc3dP8ao6i68f4wKSdcXCcqHfVi5AlLhj2o9kNEC8fZh1Y074rIEIH2S2rDMxsTi4cPEsxc+6W9SA0YRlbewE+xqqymCQTF0neUkg8+gOMc8k2sFleMU3OuBAtqDO3TB/H2yJRTyaLmOce1N5Iz07yGSbrrUVzOzUDlWKDiVoB8EmmDmqYWbGvPvMvu+Kjv+pJ99vfsni/Kjk+y1g+S+rcc1zuW6y2jbJNS8J5RuknN3yA7gBXWiOYFlGYFrVvD6AAEb8LSgP3mI6UAApDDtWjZQohkMTR1Plg8EyBYCpNAARTmA4WzvonTYKR9+KsgzGznR37RH6qWP3Ttv2e1/ZnV/gdkToV7uvM/Mxv/Sq3/wv9bEfhuUQAQ7NAdQAkfyJb3JPNbghGG2hZG8w6fDV35QMwGJnhP1n+kmXYY5k9cx5fEgj/EZR/5BTssx1euEyjkC9H0H7p97gTvtQfzzXEO9B6QCm5/C6Xfodi/sEpAjP4S1kH9V9r434ym/6ZWPj5Oe+nHfuHLehXIX4VhTTa9o1q2SO5fBLb+PiW8Rcx+SzG+oxjhpbcU8we6FV5dx+k3YA/pjnWqdYNq26Tb16i2JYbd5hoKolvSCi8fwygRPtzk/GsYZRvCg6NtfQpM8ENYBt10Ea9u1zQ+/CVG8XO03NIxGcAr2RUpN3W8DhZUHSRasbqO3fFZgIxjNHucohmt7jiId191gkBndVMs/btRZpHrbnRmGyd3UFR25yjVCWiIkrbEy86klN4+gs65qu2e1/fOSztfkUsfxZrvhmpnSMWz5JJldtWGqGld3vLO0Pkpp+ez8exflt5Pqo4dSdM2r+I9p2KbXrrNKNmiF+/wKj8mVuzwy95zCtdJ1iVM9hbRsobJXkFpVxKy1tHaVaR6NV4BOFiJzABphEMMOHDP+BsunfUXLgZLoNYj0xcD3etrcapPnHwg/E+C8v/XeuEvY/e/DWd/V535S93xh6LlL0XLN1EVMMEXfukOy/mFV/Se4fjCzgccbJMsH2h296VdLAck9fcU0yeWbYeR855mXsNlfeE7PnFtX5PyvwoLPybmfxEUua8E5+d9Y0L7E1cDxNsRitXwzO14FZiAtzg9qMxHTsG/0xr/k9H8H1nr/6Nq/19V+zdB8QNPyoQX7dlJhrt82a+CBSsYzSbZsk40bdGsUO+Ytk2yaZ1oWMHpYPmWbl4nG7fpOR/YeZsU6xbDscnIW2c7N/mFG8mlk5rTewPE3NyrBzDZyqpbR9BZ+2Llhrbn4aIahK+obuxLhKh6T5zm1O3fvaiONNfIr3EKX15hUf9quKQGAEE2du9Dab15RQRDNzAE1zmAVLWluMao1ktgFbVnXiKi5O3coptebPfNScLTmrxYJbJTT3wTK2nWfmRWlx+/MrXifrCg9ucoNc90+bqw7kVay1xq0yyncll4aiOtbT21dTO1bT6x5jWnZCmt5rOh611awzqrdItV7r78hO3aZpZBbTJLPgtqQRreMot3WKXv6QXuX5toeRs40zoWxoQRrO8WzrCB0gAOFiPTwSGuRmUuhqWtR8sACjP+wrmAlPlA0VKgGGo9LH2HkPOHqOLfqdXfUtwmYIdT9EXeCJTwZ3aH+7psRdNHceXHFNdnceWnlDIAyidR+RdR+U5i4Tt+/ntB0Rdp+bf08j9krt9lFb/LK75mwKuFO/zcz/y8j1wHIOCzsOBjsvOjIP/31JLfeXlLoenuH37iNTuo7NXw9FXYvYi0lYi0TaTqE832kZX7P+l1C2jFraOEu56Ee0fx457EiRP0B8coEydZTyHOxMlXcPoVgmGDYtmk5mzSbet0K9QaxbJKsbzlONbolnWmbZXu/l/eNbZzjVewwnGuCUvmpRU5LRNBrCKEfyrTPrAHZVK3gDm2IgKEwpLB3Sg9aH/u5WUPWl6g0CVvnPgpTsNwuC8e2U80W8/N+fLLvgtK1bc++S1WCYDw4ZX+itKKK8e+j5bnXFmNUp72ZOZz8q8hoN+knD6y+TIx+zx8zV60GafrCUiugpghP/X4b5fQz87pD0mqllY98iDmqSvvyRxXsnCmy3jzXUreBLPkJdf1OrHqTVLlE2b+Q6ptVXbqeYx6FmNepeS95VeAkfkorP0kqNqg5r9nl+6wi7/yyj+yigEB7ygO8IkfKPYtgmmbaN7A6LdweiDedaRqKSoDEACiAHwAy+XQNACBu3wFAIK1UClk6P+k1XxLqfxdWP63ASyGck+Bw877LCiFlv9b3fJ/DO3/Y2j/K7vlv/q2v9QNfypr/6Oq+5DofBOQ9Bo0xS9p1j95LkAA5mM2WAgPp46zX3jQXx1nwzNgToGNNmIVMOghuW1Gy9/GqTai5bA/4OEnfXl3DuNHD2JHDqBHD+NuHMaOHsXeOIgZ8yCMHsXfPUa+40mC5b3jtAd+3MlY+SKMeJJpAaOdQalnsFnwcJWes0TLWWXaV1i2ZUbODEk/SzbO0swLLMcCJ3cpseit9NQ3/dktR5/MdRPG/Q9BYh9m3p4Erbhi9ATdsSdexbL3HmPkcfKuppTfgARIy7lg7Hy9n2Dg5l/B6bv24o35/SuHyDmHsNk8e++u8PScc9PRmQ1gBTSnnwWmVOi6X9Pz+sPS6hOyziD8kqr4hTewunMU02WGrd+TVggcoGx6GZVx2nx28Ri96CjZyc4Z8CTlsWxXd0VqfVllaaW39yNNRPVZb6IzhO1Sue5SsTlFxNz66KzOcNmypn1d3rQtrR05wX4QmPIyPH0RrZtPUG/gLZuEHGg8xIS3ZPtbou0dyf3z0jbB8pHueE+xAgjWke7/df8HAcAEYA7mQyQAAugQeIKlEPFCUMpykARy/0a89i9J/X8yGt2z46dUAid/BuvHKwIn+IVfDOvA/LDZv8v2jw8AeL3F6cDfQRDfgta6r3KQQkGP16IyYVhDzQUJF0PFUODeIf69Raq3E7LgzbA/23Hq137C8cPUkX2owb1xI0fQIx7460dxA4fQVw9jYHn9KBYeQg0dwY16ke/6csaDk59HZ7xGZ83gdM9jM1/Gg4tSvsZpponZUzjNa1I21CRJ94qonSJnT9GNC3zHa0rOFNHxLqXxm+r8H6Yr9YlF+MzGvVFymrY9mFsYJihPLR0+QbMzzecI6tMnGbkpRddDkssAFplVd5CyZi9KDkTB3+KV4BAlFbc9aQ6MsoVmPIvwSRSXj8CT3tzCzPoHe3Amiu3KCW4pStPhzSlGhIhPcQpHwBB40AsFpbcOEPOYjkGR6368vJNtvR6UXANhgeO47sMpQyk7qKZLSAU8vPZzdBZVf1FYcCOIX5lZcT+M5zpOsLPMfZ7EXLKqc11/dklSs5xSuZRcuiZ0AeQf+QteQQiMVizFa7bwZmj8Osb0nmx7R7G9JVt3WMAKVjAHkBe+Jpe8CBC88EucDhaBZQMDuAC6EJkOw3fKj/falwd9mvZPeh0m/jO9Dgzgt/RTXyQ1n5JcX5Ndn5PKAAfuE4vcwvdUO2z/A9XmDoc0+yea/R8cuM05RgNBcRuTBQXNXovJgHgGsW0tXgYQhHgCyy2UdiECrIns1UnBlLdoMUj20jPltbf48VHO7QPYwX1RZw9GN+6LaPgttOm3sI590b0emEtH0FePkfqP4K56EMZ8OXcC+OMhgv9b4SkvUYoncZkv0apnaPkrfNZLnOoxKvMpVvUUmzVJ1r8gZ1/zTRr2F90LV8yR8r+kd/ypvvg5uzckWqauvovLbNLWj3/vL/JnF+F1nbsiZLbuN77sgu9D0/IvL3Hz+r+PyNS0PYVccIRgAvLHZXcSzL2ypqeBgurEwqGApLLjTCfVfB4UIURUo2iY+A2l5xcNYfTnqLlXidY+xBFqvrTmYXL53VhVR0rl+GF6Ecl6TVQ94S9s0LfPoxTd0oqHEtdDT3oZWEWOc+QExyWpvP9jXDbYxlTXPX+Oi6rvDUuq9WWU8h2Dh7C2OGmrwHh5JevMQkrlvKB8UeBaFVdviGtWkyu2BBUzeMvzSNlkZOabGMU8Uj2XoF4hWz8KqxcpuQtE2zzGsoi2vIpULmIMf8kb/q1u+iKv+lPd8Je+cZFnGfKl9R/BXD7gniHr2mH88HHmN1njN/Xpb8rWb7Lm3zMb3OcMUqshHH5gFfx9w0P3VFlbFKAf4J4cAMRbkukd2bwJno5k2sBluyfZQCo30erVWCXgYzpE+vxE8kuv5Elv4Rtf8UJg5kpI1lKAfNFPAbUSmDXjk/nSS3j3COHmEUzXodja30Ia9oY3H4g6fTCmaU946+6orr0JFw9gBo4Q+w/hhzxIw0eIw4cJNw8Thw7ihw7hrx/EDRwmnN+HunAQc/Yguvsgtucwof8kZ+Akr/84/3aY7F6k8m6E8jXJ8SG95b2i3clwIg7SE6QNRzB6VfXtHwJEu4JSI1OqEZ4svv3K9yGpCC+2uGToBCv/BKcADMFejJ6ff5Vk6glIqYxVnUHpe44wClKr72Ozu5NLR4NEtcc5JYqW5/Hqzt1YIzP3qk9yJc0xwCwYQuwjOZnO4cymF2HprcLKcYyhN0Tawi+965/SQLVdZ9iv+yfXK5unjtJKCIa+tJrH+wm5rNwhpOos2dDHsIJVMeO15yJTm3y5LpplABEoixA3G5qnOJGqeUXrnLhqTuCaZOdP84unOUUz7MLlxPKN5KrtlPpNQe1Gcs2WsH4ruXZbULfKLt/iVq5RS9z/14CyzmNsM0jzm3j905CM+/4pt3z4gx60keP0MR/2mDfrni/vng/33knePM74SVL9Rdbwb137XzpwAF1/aE67b1yXeepTWuVHSeWOpPxLWuWOsPRrasUXWApKP/ILNyGgxqpeBkmm/CWTPqJX3sLXvpJpP8mLY4IZP+lcoBQ6PR+YOe8vWwxULAQol4O1a2GGjXATrEz7Zjw5zr/pRW4/iqrZHdp8IBbIuuMwumVvbMcB5NkDqIsH0H0H0NDsYU/37Z1Gj1DueDDueNDvHmPfO8G/fTJpzCdp5CR/0Cfxmk/iwEn36L8ZJL0dJp+Iz36CNLyhORcFVbdouSOa9ihOEWI/mW299FNEBt3Q80tExmFcDlLWijgpACYAmd+foGbnnI8SV8VnNIaIavcTckimc7tileAKa25/CZHUIkLSuYXDgSlV8lOPSMYLu9EmVduraMUZcIHcopGIzBZd55uw9CbEicSaeOVZ4P8j5IIYWTtQQnBqU3LZ/X14hxerjG69cpxdCl0PEzcEJFYpTz35DWmSN7+U1j8hGC4xbdd/js1GKjqi0ppPMEsYOf2/xOlDk2uNbVNB7FKB/epc3sBUSsULTsFrftFMorvmuYUzjLxFVtEKr3xdWLsurFtLrNkU1G/warYS65YY5Zvc6jWGC9CwSsqfQ1mnYw2Tkdpn4co7J0V3/UQPg6VPI5RPQuVPg2VAGOsk+yrBuoQ1L2BMa+S8NULeGi53k5i/RSrYwOW+JRa+JxWuIi2rCcb5KM1cmGopQjMfLIOa9s947Z8xF6KcC8qEh4uhKqiFEPlsYMa0v3Q2ULYYol4JUy+HajaiDFvRORvRFqjlsOz5UNWET9KVw9jTh1FN++Oa98d0HEJdOkY5dxh/9iC2ex/60mHi9aPUYQ/G4BHaTQ/mvRNJ4yeSHnknTfimTPiLnwSn3w9KvemTciNAPBaSAe0fj1aPhWRC+18RbPOckkVe2UKS66m4Jtl6iZ599jt/Ed95/acoFdPa92u0Kl7Wmpg/vCssE+Lifpzxu/AMor4boj/H1puQ2YTw4nKd1yAvRClaslqeRWc0JBUMge8LTT0lb3wCTHCIkitvfu4jrDnOd9EcV/2TqzXtUzHKdgRIQJS0DdrpxSimmvuEZbf9hDXcotFoRUdkeltK6e1DxNy06kcRqU2YrC7g/8DkGrLxEt02cJDkxOt7j9KKiPpL6Kxu8I9ADD9EqpOc1x09cyeoBWh5OzKjDccqfq0+84xb+IpXNMUtfMPJf0YwzTLyZlmF66Ka9+ktS4nVK4k1q0m1G8LGrZTmLWHTO1HLCqN8nVa6iHfOYRxQs2jrNDoH6mWsfjLeCPUqRj+PtU2jjNuwHYZzgwPLgi164Vta8QbBCSB4Ry4EHGzi8rYJeesYy0q8CWob51iI0K7EGBYjdfOh6pUoPSyXw9XQ2uVwFaBhOTJrNkQ2G6qE96xGu2srwbZDKoZaj8uZDlNO+ApuHad3HsK2HETV747pOIgZOEa/dpwJy8se9D5P1uCJpNt+KTe8+Dc8eeO+ovvewse+kid+qU/909y3APF3z0F6J1g6Gpw2GpoxFpb5KEH3HGeewJpmklyvk10vkly3Mht/8xfIa8ajJPWx0lMMc++eOI3pzORJZn64oDImtWZvrIpmuRAqqkJ4srGa9v0oLVbRhla0MsznyOZz/sll4ANIxvNe9HzDmcmUstEDJLv98qr7pKH0lLbjday6U1L3mGQdOEh14k29GOMFRPqppzHKTiAAcANgC1RtU4HiBmXblMB1D6XuATk4xiyNlJ2Jy+oOS20GwtiDtYF8pNZOeHFdgBWc8RK8LaPmkS+vAkLmrzG6KHFDOngLYi7Lfo2TOxghrGMbL0+o2malNa8Si15w8qc4Bc8otiVhxaKwEmo+0bUsrFkW1q2ntqyJm96mta0LGtZ41evsSqgFSskas2qV6ZonF83i82bQ9tcgEyjL82jdIjFviZQ3gzWvsfLfi1ybScUb3KIlon2TVgBxdIuSv4a3Q61grbNxOlhZiDO8JTlXEsxQa0jLUmw2dHo93riGNC3F62YjlEtR6k2kEVagVlGmdbR1EwvhpeA9ufgtoQA+9TQwdcyLBUO/5TC6+RCq+QDy8jHGmI8Auj56MvnGScGQd/JooPRuUMaDwMz7ftKJgExgrGch8tdRmuchmY/8JOOwhQDRSGDKSJBoOCR1NFL+EK0HDX7OyH/CLXohqurTn8PJWxE+QoFzMIRXui8hG6+CCCeCMe3DKiLpuri2Xgj9SYXXo1NrfomWQTo4hNKq6h/EpTfsRWrptt6fkRplG4RA9wwEvOIb0OawtAbwBJ7MfG9emfHiUriinV4wgrf2e3JLGfmDbhD8PdX9mZTKewGiOo5zKLtr5gijkGofYOQNxSnagTQipM0kUx8M/ZjMVl7+ELAKwXwJAsVRWgHR2Mt0XEOpu6mWy57UPIrxwo/RWdHSZkP79K8JRprliqVnwZtVwnNc45j6XGn1M7qOBVnjbGr1M1be66SSGWH5bErFYmrNkrh6TdqwkFK9KmnYlLZtprUCFNaSG1Z5tatJpzaETdvC5mVm5TK9bIFUNEdwLuCdsxjHPN6xgHMs4nNnUDlvEkyzOMss0QKAWKY71uiORZJlkWRdJOTM48zgPRfwllmUAeRjneBYRhrXMBb35ZoYyyoafKJtNk6ziDEtoU1b5NzpGA0USMw2teAj27XDKId6Ry2eizfcChI07E9o2B/fdBDZdhBz8Sj1VoDobkAqdH08KPN+iMzd/jDFo1Dlg0AZ1PNI7auo7FfROsDBQz/xuK/wlr9kKFgyEinrCxQNRcnGEjS3kNon1NwJZuFNcc1PJ3iq2od+nJIfI5X+3OKfwzMCOcUZlXcPYy3mzjfeDCdR2xmTVu9FsTJtlw7hDAh/IUSD3XGqxIJru6IVP8VnHaXmwoiXtzwJkdZ7MJzi6vtxmi5kdk9Gw+PD1DyUpktQfT8qqyOrfYpq7z9MdQhctzHmiwj1mSm/5EpO/mCwqB6ffV5QPAZdJxovK1snydYB0P5AYT07/wa/ZCxG3sYvGKZb+/CG84KysV9QhnhVe0bDE4z+vPr01E8xWpq5F6vuxGt7pNXjfvzK6PRWXsGID68iQdUJsTNYWKeqe4ImOh/mXJpSnX4ibbzDdD7lFrwRlAEgpgVlkCaWxLXLovpVUeOyoGFd3LImaVlPO7OV3rGSdGqRVQmOYYlWCjgAxzCDsrkRgM1bIxfPY3NXyUWgHUsk5wLZ+SJG9yRSPpmgmcLoJrHumsJpp/EGgMU8wbREME/HqZdxpjW8ZQltWMYYF3DGqXjtG7R+mWJfpeYBl8wTLAvEnAWCZZXiWCbZ4FM9x+mNh7BNh3H1e5GnjxC6DhEHvHl3g6RPIpVPI9XPIzUTYcrH4apnsdmPo7XP4w0v401PIjQTIUqQLcDBw4DMiYD08UDptTDplWDJpWDxYKxyGKUBIh1n5g8KXWmOvlBuMcKLp214EpXWgDgphN4jjnNpuk4vsh08ICvnwi8xquy2lwxb33ch0uSiwUhxlQ/LmZg/CM9rW54Hi+vcw9J0EYRfc/rFEVruHowxo/5RRHqTsOJOgrozPLU+tfJOnPIMJAJt55tgcQ3ZdCGpZGQXyoBIb3iGM14kWq5EZJ4GzpfUPNpHdhIsV8Q1j0LSmim2qyAHUfJ2kADwERRLH9M5CASQVHzzAMGG118AOYAPwqd+QpnBRtCB/zNPQ8sPUguQ2nPW3jUPeiHZfDle2eWeIbFw9Bi9JELaCipzklY8lNX5Iq3+ETP3IdX2lJn3jJ77hl8yk+yaF1bNJVcvihpW0ttWZGc2MttXxU3uG3rwqmapxQsUdy2SC6FWKcWr9FKodWbFKt1tKsFMrNBKNhnlczj7HM7mviFHgu5RlPJRhOJ+qPRZtHIqQT0Vr34Tr5tBG6CmMPqXaM2zePXt8PTRCOmd2IybcelXQwSdxyjtHqSuY8y/i332OPecN//CMd7AieSxoPTxcMWzWN14KIz+DMDBozAZLB+GZj6KUD0MVz2O0sDyUbD8aXjWi0gNMMHzCPXjEBVZVPPdUZZXbJY/UlvQ/iqEWwS2PMl2BXGMi5a14NWdCE9eSsHwMUquFzUvJr1pV0hahuuWB8n6fVBabu/SSXaxuvVlkLDqh0iluunpQaw+TOgCT3CIYLVeWIRe7CXa0k9N+CS6+CU3fZMqAlNqlM3PYAVSIkp39qcEbdbpV/DkEVZhav3DAHG16vTzGFWbn6QewXTeSND0YPWXqY6hGNVZTuktjPkyznRZUjsB7aTbrgUkVZNNvSllt3z5lYlFY0APgBUgAGACwB0wjLh6PKXqwUn3zbDbMdrzURmt0HUoYAh4JyJMHp15BhrvJ6xj5t0A54HVXYDNHqEWkgx9FG7py/yrM8azryW1d/DmRzT7I5rjJa/kMcM5mVw+LaqdldTPS+pXUutXJfULPNcsq2iSZJ9nFEwRba9J9gV20QzVucItW+W4lhnlkC/mqSUrjNJNdsUao2yD5VqmFS5Q8peo+fN4OxTwxDwp90W8fiJaewdrkoYkevrSfjsQR+Iaftwb/sP3PuX+iZfCJZeDhNdC0m5EKW5Hq+/GaG+GKW5DaxP0D6C1Ee56EpH1ICQDun43QHwvUPIwNN39MFwJWjAeqpyAV4NlDwKkDwPT750UPgjO6GXkS+x9EZyiYFYBRXX6BMGcUjC4JyH7KN4akVzxS1gG13r5OM2JOJ6ob332nZ+IZjyXWXvvKNZgbH2+H63/V4g0+8yrfRiTvnOK4ej/FWnQtL4MTKqIk7cCMUAcSAFW1/ZA5AvLbPYRVmWfnYlSnP4ZbaRaekGmde1TZMslL3ahsPIWUt2ON13MbHwCTACEAaoRr+1G4G2DpNwRqnNEWDNxgFHCKBxFGXsp9kFN94K/qJFkvQY9C09rgq6DYcToL/BLRimW/rS6x76J1byCm9z8YWrOlVhV1yF6CTABKaf/+ygtQAGXfRFepdqvHWEU441X6I7hBPX5ONX5GFknbDCl/N534ZqojHa87iJecyFedsafVtRg7BtLrLxFdgxjzSM40zDWOEq2TtDzJml5z4jWxzjzQ7ThBdk+jtTdjlLeAGsdpbgXr5nA6ed5JTPswtXkynVh9QqggVWywSlfYRTOEuyLFOccLfcF1gy4mSY5XmIsD1GGekEpAnHSK1SI+DXOKzL1Nx9mLNu2L1iIOEILoznC6XYky2Hm5F+MzbwZIR8OzbgVJr8VmnkvFCRfCkMf6l5wJvQbuu4GRKz6YbgcnoSH48Hpd/wl94OksLwJDYnKUotqucae/bFZaYWDHhhDeJIrNMm1L0GnP/3qlzgtLqsjJLHix2ApObvb/XNwpBL8/O54nT+3NC6z5YfQjNKRHX9B1W8oPVbbFZBcAfqLM17wTnSxC4ZPcEuTymBM9u0hWPOubgVJThHMvTj9uaP0fPWZyZC0xlBpE4xDL3axsWcOqe44SHak1j7wE1Zzi0fI1t7DjDxZ8+MYeUucsg0BXeeV3KHnjciaJ8Mz26WnnkNeQOnO03KHvROruPk3IAKEpjZTbYPsghtA/mm1T0EmEktvA73TrFeh36GSJmiqn6AOtACcxK5YfXLJmKTmAdbQC9sBaQAmSCq+9SvKomie8k2uBxwkFd85wSqnWQZ4zmFPWiE3bwhAg9Zc4BbeCRY0p5Q9/CHSSNRfSXM98mO5ajjlTxglz1mlk/zKSZ7rGb3wJbP4KSUX/NQ4ACVG9QBrfEq0PCdZZ+jOGRoQQ+kM2fYSpYd6jjZMYPV30ZpBoiU5tS6QmhebVB7CcCL2kU8SLIjjvABGXjA9L15c488s+DVSEcgt86YXMYHtFN2IQFW8+iLTPMA0XhE6b5Dpxe2gjijVKEp7J0F7B+QApb8dk3UXqQN7P0TUn0ksZgqqlI4+P7RulyedllF7LFaGFJZ5IHXf+QpZxvOHULpoSbUn0Yo4kUTRdf8Wk6U8NYHXdoMNBHr34ZXvilYbuqY9qc7QlBq2/aoHxSmtn/DhVyRkdbDyrh1nFeOye/jFN2AcQ+8jMxqdV9bB+UObuQVDwSm1LEc/iIgHLQ9AEKMAce+g5PRGShsgMeK0HQcJRknF7V/Revgsu2DIi1vKK70JS8iNbhCk1D7G6C+KKh9582to9iF+8R2S5aqhZ/k4vxoIXNb0IljSQjD1g2RAMfNvAlbU7bMo7UV4c3LZ/Vh5B4AgKOUUyApYB0REFiq7N6n8PlJ3kWK9jsw6B2iQ1D4JSG0h24dpztFoZQ/VNhwhPY3V9Saoeo6zK2jW6/+K1ieoL+KNAycT683dq4dIxThdn7D0ASJCG5BUz827Scq+xLcOexMLUgwDXeZLl7glHeyiMoKxOrHUKevQp5+W8aoz1BeJjFJD3s0k89V9CTmU7EvhoiZRyV2M+tx+nCM6rQ2l6mLYrkWmNvkwS1DKzp8i1bFpzbEZbZis7rTKhz/G6HHZlwJTGmMU3bCTv2Jy8eargMvUmidAYwfwuUBasKsi14PozI7vwrK8aCU0Uz9BezFBDmHdQtD2hCbXkLN7AvnlP4ZmEDVnINAn51/zINgQfhKcqutfYbKUkpsBvDLESQE4gF9jNZC/wI8HCGoglIkr7v2CNCYVj3qzyzCabrHrDrguZ9+GB6MAhJyZexX8O/QP3D50DpvdA8+DA4hXd/2UkJ1YOgqEkVI26sMpAT9o712OzGhWtTyHpU9imePSCgz3AySr+1Rxoiu5/HZ4RjPQSWLpGIRGsesWAjhAXPMYqbmQUvHQT3iKX3o/veGV+5bYtc8O00qg6+KK8V+QZuDzxJK70PjUuufHuNW8knuxWecBK3CA/FPq0Zqz7hOIjkFx1cR+UgF8PK3xRWwWwPZOWGozIbtXXP1wNyEvTttLtg0Fp50OSeuAwxotP0s2D/wrMptqvroXlwvqALA4Ri8zdS4eIhbEK86xckcQfhkAFEBSeu1TgMX3MSYAinPgc3Bqe0RGd4L6UmxGt6J+Mia9yy/xVILy/CFyIcs5FiZt30csxGdfSSkfh6+IVZ71SaqDvzFW3oU19hFtI/4prb7CRkRolqZtGhgIeh+U0ojwTg39G+6wAn/CQVoxv/RulKxT3jQJf+mu6Gx+/k2s5jzsCezqb2hbZPqZIEE9kBnJ0HuQ4AAbFJ3ZdpSSDyF5V4RCVDrqyy1VNT0LlzQGJFYlF43uw1hs55YgN30XphCX3w0S1AKhxqi6fITVyrYpTuHNA0QH6KkXq0R35jW8ijiZknNu8RgTCOA8BDzAhLF7BtYBDZD7vej5OT3zIZL6aFkrt+D6IZJNXDZ2mGiDd5bf/AShAJXVHitrASkBexiUUo1UnVE0PQYAyYFITBc9yTay4bwHJRfcBoKROyKte4bW9bILxw4zypNdD7N7VvHWq+yS2/7CBvjj4VXgcBjZoemnYehD+4+yKtj5twJSGuF4mXpWIAWAZKDUPUDpSWV3DpALybbrSZUPPHiV5Nwhcs41iB4AgqPMEpy+V9U8CZ8CqwFfB14BdOHHOBPReIWacy0q4zQQyQFiXpyqZw8+j5U/puta8hOcYuePQoeIpn5u4a0f4iwo7SUAIlp3OSyjg2QdDBS1kIxX42RdsAV4AyAMqbuUXDlxkFYKgFa0zkTIumj2EZyhH9CTVP5AWPWYnn97N6kYqe8LTmtlOG/Q826isi+TcgZ343LD0trAtCaoumHffkywwPMAAnbeDUDhQZJTWHYfXgJpi5d37kFbA5Lr4mQdFNPlgOSq35AmVu71OHlnYsGNKGnLTzFqOMTerCKgd/DtHOcIbHYvJgdgRLcNHKY4uUU3YlUdNMd1OHq78XbrpXW0/uJPKCOEr704a0bNowRFB6Ru+anHCcp2sPfh0sbdWLPlwhL47hDxKUjph4i2/L7V6IwmsvkcP//qCVa+quHxEbLjGM2paJjAabrY9n733APHOCATCcrTJzgFoAtACbA1YAgIluxc9z8s69qeIQimq4ll4wnaXm7p/QBxC9bYXzj4KVrZDV2HoQzt5Lvu+4gagDDouSNwaODInkisAdqAUe6e5EbV9TPawiseg/5BLAT+P86tAgMBDsOTXwVmE7wFwTIAKPFklABVpNc/P8ook1Q/5hXdhiPLct48wamEEQ8lrXlCNA8gQpWR6W0ezPL4rAvQtr0EJ3wRQA2wCLsaKGrCZPcBRQNeo+Q93OK70F1u/iggAFgkWNLmxauJzroQJD3zC96JNV8nO27iTdcBBKDx7rdZBkmW61jTtYOMCrTx6jF+LcE6yCq4BbRPsFz7ISEnXn0O2A6lPo8z9O0lFCA1vSGprQB9eOZfUTpwxMAZyoYXoC+IPQz/5No9WJv7JHpOPyIgnZB9Aa/t4eRdDxXXfx+pggTvxynKrBmPkZ2GqAz2aDcwwYVlpPbsfnKuqOo+1XK56OpbCM8QrPilt6OVnZ7cUqp94Kd4g75jlmm7eoSUq2175ccrM3dPQxY4SLQrmp6CCYCOgrojQjOVjY/jZE1plbfMXVMeVLvl7AwYgl+R2SXXtiAUJBUMAQ6OkOy0nEuejNy9OIOw9OZutKH4+lu8/izXeS1W3vQrSptR/wBBsQ8nuh5GZ50n5lyHYwEPxTVPfUXNEBAgNIK6O668hcEE/ZBUgce6/Pfd8ztgfANJwPGSVD4IS20EjmIXjPyKs9Hz3DkTKERQPg4Og1MwBs0LTz8DUAhNawNBlTe8RHhLQf6FLsiDQ9r2OcggxJyrgAlgo9S6p9B1+GroZbzmIjN/DMQF9gp2KTyzE2O4ApQOmAAg/oLNBdlOLp/w4tbEKs+ByQDQAD3sJRYD1UdnXfQCdci+YuzdpuSOAmEc59YAenjF46Bl+JzrYbIuUu7NCNV5pL6fU3QHhAmj79uNy8MYLgPhge8BmjlALYmSd3pxXWB+IYD9K1qD056LzjgNUEAquz2oRV4s90uisjtkw0VPaj7N7KYEur0/Mr1lN9rEzr0G/YMuRsrOmC+sRSm6fog3QLYCFUdEqAjmS+DeHVe2wE3vITgYeUPg5PcTbejsc97ccnXrK6ymB7pu6Zn3YhbxC4Z9+S7AFid/0D/JRTZdYDmu7sGY02rGwdaFp9azcwd8eKXqlmdgD09yS0DmQTvUbS/h4Y/xuoKB9SCh6xDRIiofA9Vw9K0FCquwOjCbVxARGfLGif8fRineT+OPgQUAAAAASUVORK5CYII=\" 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align=\"left\" alt=\"image\"\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHere, L* measures the lightness of color, a* ranged from green to red, b* blue to yellow, C* chroma of the color and h\u0026deg; represents the brightness of the rose petals.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"antioxidants, antinutrient, bioactive compounds, color, molar ratio, rose petal, secondary metabolites, variability","lastPublishedDoi":"10.21203/rs.3.rs-3873110/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3873110/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRose (\u003cem\u003eRosa sp.\u003c/em\u003e) is one of the most important ornamentals which is commercialize for its aesthetic values, essential oils, cosmetic, perfume, pharmaceuticals and food industries in the world. It has wide range of variations that is mostly distinguished by petal color differences which is interlinked with the phytochemicals, secondary metabolites and antinutrient properties. Here, we explored the color, bioactive compounds and antinutritional profiling and their association to sort out the most promising rose genotypes. For this purpose, we employed both quantitative and qualitative evaluation by colorimetric, spectrophotometric and visual analyses following standard protocols. The experiment was laid out in randomized complete block design (RCBD) with three replications where ten rose accessions labelled R1, R2, R3, R4, R5, R6, R7, R8, R9 and R10 were used as plant materials. Results revealed in quantitative assessment, the maximum L*, a* and b* value was recorded from rose accessions R4, R6 and R10, respectively which is further confirmed with the visually observed color of the respective rose petals. Proximate composition analyses showed that the highest amount of carotenoid and β-carotene was found in R10 rose accession, anthocyanin and betacyanin in R7. Among the bioactive compounds, maximum tocopherol, phenolic and flavonoid content was recorded in R8, R6 and R3 while R1 showed the highest free radical scavenging potentiality with the lowest IC\u003csub\u003e50\u003c/sub\u003e (82.60 \u0026micro;g/ mL FW) compared to the others. Meanwhile, the enormous variation was observed among the studied rose genotypes regarding the antinutrient contents of tannin, alkaloid, saponin and phytate whereas some other antinutrient like steroids, coumarines, quinones, anthraquinone and phlobatanin were also figured out with their presence or absence following qualitative visualization strategies. Furthermore, according to the Principal Component Analysis (PCA), correlation matrix and heatmap dendogram and cluster analysis, the ten rose accessions were grouped into three clusters where, cluster-I composed of R3, R4, R5, R8, cluster-II: R9, R10 and cluster-III: R1, R2, R6, R7 where the rose accessions under cluster III and cluster II were mostly contributed in the total variations by the studied variables. Therefore, the rose accessions R9, R10 and R1, R2, R6, R7 might be potential valuable resources of bioactive compounds for utilization in cosmetics, food coloration, and drugs synthesis which have considerable health impact.\u003c/p\u003e","manuscriptTitle":"Color, Proximate Composition, Bioactive Compounds and Antinutrient Profiling of Rose","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-29 19:11:58","doi":"10.21203/rs.3.rs-3873110/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-29T17:35:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-25T15:39:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-25T02:42:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-25T02:00:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-01-17T14:12:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3dfd6663-2848-4b4d-9b69-fee8e1578433","owner":[],"postedDate":"January 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28397977,"name":"Biological sciences/Plant sciences"},{"id":28397978,"name":"Biological sciences/Ecology/Biodiversity"}],"tags":[],"updatedAt":"2024-09-23T16:07:47+00:00","versionOfRecord":{"articleIdentity":"rs-3873110","link":"https://doi.org/10.1038/s41598-024-72424-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-09-17 15:57:30","publishedOnDateReadable":"September 17th, 2024"},"versionCreatedAt":"2024-01-29 19:11:58","video":"","vorDoi":"10.1038/s41598-024-72424-w","vorDoiUrl":"https://doi.org/10.1038/s41598-024-72424-w","workflowStages":[]},"version":"v1","identity":"rs-3873110","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3873110","identity":"rs-3873110","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}