Valorization of Fig (Ficus carica Linn.) Waste Leaves: HPLC-QTOF-MS/MS-DPPH System For Online Screening And Identification of Antioxidant Compounds

Valorization of Fig (Ficus carica Linn.) 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Waste Leaves: HPLC-QTOF-MS/MS-DPPH System For Online Screening And Identification of Antioxidant Compounds Chunying Li, Meiting Yu, Shen Li, Xue Yang, Bin Qiao, Sen Shi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-804140/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Nov, 2021 Read the published version in Plants → Version 1 posted You are reading this latest preprint version Abstract Fig (Ficus carica Linn.) leaves are produced each year and often thrown away as wastes, resulting in a waste of resources. Fig waste leaves are rich in flavonoids, which have strong antioxidant activity, however, the antioxidant components are not clear. So as to take full advantage of fig waste leaves, antioxidant capacity of different extracts (petroleum ether, ethyl acetate and water) was evaluated by 1, 1-diphenyl-2-picrylhydrazyl (DPPH), 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic) acid (ABTS) and ferric-ion reducing antioxidant power (FRAP) methods. The results showed that flavonoids in ethyl acetate extraction had the highest content, 83.92 ± 0.01 mg/g, and maximum DPPH scavenging activity (IC 50 0.54 mg/mL), highest ABTS scavenging rate (80.28%), FRAP (3.46 mmol/g). Furthermore, HPLC-QTOF-MS/MS-DPPH method was developed for the first time to identify 11 flavonoids in fig waste leaves. This rapid and efficient method can not only be used for screening the antioxidant components in fig waste leaves, but also can be combined with mass spectrometry to identify the compounds with antioxidant capacity. There are three flavonoids with significant antioxidant capacity, which are 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin, isoschaftoside and rutin. The results confirmed that fig waste leaves contain a variety of antioxidant components, which contributed to increase the value of fig waste leaves as antioxidants. Environmental Policy Chemical Engineering Ficus carica Linn waste leaves Antioxidant HPLC-QTOF-MS/MS-DPPH Flavonoids Polyphenols Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Statement Of Novelty A large number of fig leaves are produced each year and often thrown away as wastes, resulting in a waste of resources. However, fig leaves are rich in flavonoids and polyphenols, which have strong antioxidant activity. HPLC-QTOF-MS/MS-DPPH method was used for online screening and identification of components with antioxidant activity from fig waste leaves for the first time. Chemical structures were identified and the antioxidant capacity were measured. This study provided a scientific and theoretical basis for the development and utilization of waste biomass from fig leaves. Introduction Fig ( Ficus carica Linn.) as one of the earliest cultivated fruit trees, belongs to the mulberry family (Moraceae). Figs are native to the Mediterranean coast, from Turkey to Afghanistan [ 1 ], mainly grow in some tropical and temperate regions, belonging to the subtropical larch family [ 2 ]. It was introduced into China from Persia in the Tang Dynasty. Because of its low requirements on soil conditions and strong roots, it was widely cultivated in the north and south, mainly distributed in Xinjiang, Fujian, Shandong and other places. Fig has not only a wide range of medicinal and nutritional value, but also has nourishing the stomach and clearing the intestines, reducing swelling and detoxification. It is often used in the treatment of anorexia, abdominal distension and abdominal pain, hemorrhoids and constipation, dyspepsia, insufficient milk, sore throat, cough and sputum [ 3 , 4 , 5 ]. To make the fig trees grow more vigorously, they are often been pruned. Therefore, a large number of abandoned branches and leaves will be produced every year, causing environmental pollution and waste of resources. However, the fig leaves were found to contain flavonoids, sugars, pectin, tannins, vitamin C (Vc) and trace elements [ 6 , 7 ]. Clinical studies had shown that fig leaves extract had anti-tumor, hypolipidemic, antioxidant, antibacterial, hypoglycemic and other activities [ 8 , 9 , 10 ]. Because the fig leaves contain a large number of flavonoids, they have a variety of pharmacological activities, which can prevent cardiovascular diseases, anti-osteoporosis, treatment of diarrhea, scavenging oxidative free radicals, lowering blood lipids, treatment of sore throat and immune regulation [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. It is reported that higher amount of flavonoids have been found in fig leaves [ 18 ], including rutin, quercetin, anthocyanin and so on. Anthocyanins enable to promote the apoptosis of cancer cells, slow down the proliferation of cancer cells and prevent the metastasis of cancer cells [ 19 ]. At the same time, it can effectively relieve visual fatigue and slow down the development of diabetic cataract [ 20 ]. Quercetin and rutin have protective effects on ischemic brain injury [ 21 ]. Flavonoids not only regulate the cardiovascular system by reducing capillary permeability, lipid and blood pressure, but also play an important role in anti-inflammatory and anti-immune activity by affecting cell mitosis, cell-cell interaction and cell secretion [ 22 , 23 ]. Therefore, making full use of fig waste leaves is an effective way to realize resource utilization. 1, 1-diphenyl-2-picrylhydrazyl (DPPH) is a very stable nitrogen-centered free radical that can trap other free radicals and has maximum absorption at 517 nm. It has a strong purple color and turns yellow after reacting with antioxidant species. This method was often used to evaluate the antioxidant activity of compounds or plant extracts. [ 24 ]. Nevertheless, in the evaluation of antioxidant activity of herbal extracts with complex components, the main drawback of this method is that it is impossible to know exactly which compounds in the complex mixture have antioxidant activity. Only after the separation and purification of a compound it can be known whether it has antioxidant activity. This method is time-consuming, laborious, and the results are not accurate [ 25 ]. Recently, HPLC-DPPH-DAD online screening of antioxidant systems is a fast and efficient method for exploring antioxidant compounds from natural resources [ 26 , 27 ] and used for screening and identification of antioxidants in fruit wine, tea, plants and so on [ 28 , 29 , 30 ]. In this study, HPLC-DPPH was used to screen out the antioxidant active components in different extracts of fig waste leaves. In order to further study the antioxidant chemical components, HPLC-DPPH-MS/MS was applied to identify and analyze the antioxidant active components for the first time. By this method, 11 flavonoids were found in the fig waste leaves. Compared with the traditional methods for screening natural antioxidant active components, this method can screen and identify the antioxidant active components in fig waste leaves rapidly and efficiently, so as to make full use of the fig resources. Materials And Methods Chemicals and materials Discarded fig leaves were picked from Chengshan Town, Rongcheng City, Shandong Province, China. And the fig leaves were dried at a shady place out of direct sunlight until the weight was remained the same. The dried leaves were smashed and sieved through a 60-mesh sieve for further test. All chemicals were of analytical grade, unless stated otherwise and were purchased from Sigma Aldrich (St. Louis, MO, USA). Standard solutions were stored at 4 °C. Instrumentation An Agilent 6530 Accurate-Mass QTOF-MS system was connected with HPLC system via an Agilent Jet Stream electrospray (ESI) interface and an Agilent 1260 HPLC with diode array detector (DAD) (Agilent Technologies, Santa Clara, CA, USA). Kq-100e Ultrasonic cleaning instrument (Kunshan Ultrasonic Instrument Co., LTD.) was used. Sample preparation The fig leaves wastes were dried at the temperature of 60 ℃ and then crushed through a 60-mesh screen. 10 g of dry powder was weighed and put into a triangular flask, 70% ethanol was added at the ratio of 1:10 (w/v), 200 W, 40 ℃, ultrasonic for 30 min, repeated twice, centrifugation at 6000 rpm for 10 min, filtrate was combined, concentration was performed to obtain the ethanol extract of fig leaves. An appropriate amount of distilled water was added to the ethanol extract to form a homogeneous suspension, which was extracted by adding petroleum ether and ethyl acetate in turn to be extracted by rotary evaporation at 60 ℃ to obtain the extracts. Total polyphenol content The total polyphenol contents in different solvent extracts were based on Folin-Ciocalteu method. The optimal reaction conditions of the system were as follows: test sample 0.1 mL, Folin-Ciocalteu reagent 0.1 mL and 60 g/L Na 2 CO 3 solution 0.8 mL, with minor modifications [31]. Mixture was incubated at room temperature and protected from light for 10 min. Absorbance of total polyphenol at 765 nm was determined by UV-Visible spectrometer. Total flavonoid content The content of total flavonoids in fig waste leaves was determined by NaNO 2 -Al(NO 3 ) 3 method [32]. Rutin was used as a standard. Content of total flavonoid was measured at 506 nm of wavelength. Determination of antioxidant capacities DPPH radical scavenging capacity A proper amount of DPPH sample was weighted and anhydrous ethanol was added for ultrasonic dissolution to obtain DPPH solution with the concentration of 0.06 mg/mL. 0.15 mL of DPPH solution from the stock was mixed with 0.17 mL of diluted sample. The reaction was kept from light for 30 min at room temperature. The detection wavelength was 517 nm. Each group of experiments is parallel for three times, and the calculation formula is as follows: ......(1) where W (%) represents DPPH radical scavenging rate. A k , A m and A n represent absorbance of DPPH solution, absorbance of extracts of different concentrations reacted with DPPH solution and absorbance of different concentrations of extracts reacted with anhydrous ethanol. 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic) acid (ABTS) radical scavenging capacity The mixture of 100 µL ABTS solution and oxidant solution was added at the volume ratio of 1:1 and was kept away from light at room temperature for 16 h. The ABTS working solution was obtained by diluting the ABTS solution with anhydrous ethanol. 20 µL of different concentrations of extract solution, different concentration of Vc solution and 180 µL ABTS working solution were mixed evenly in a 96-well plate. The absorbance was measure at 734 nm, and the experiments were repeated three times in each group. The scavenging capacity of ABTS free radicals is calculated by the following formula (2): .........(2) where W (%) refers to ABTS radical scavenging rate. A k , A m and A n refer to absorbance of ABTS working solution, absorbance of ABTS after reacting with sample and absorbance of sample solution mixed with anhydrous ethanol. Ferric-ion reducing antioxidant power (FRAP) FRAP was determined according to the method of Jin et al. [33]. Take 150 µl of appropriately diluted extract of fig waste leaves, add 3 mL of 2, 3, 5-triphenyl-2h-tetrazolium,chloride (TPTZ) working solution, which consists of acetic acid buffer (pH 3.6), 10 mmol/L TPTZ solution and 20 mmol/L FeCl 3 solution mixed in proportion (10:1:1) and reacted at 37 ℃ for 30 min. The detection wavelength was 593 nm. Establishment of the HPLC-QTOF-MS/MS-DPPH system HPLC-DAD-ESI-MS analysis HPLC-ion trap mass spectrometry with DAD was used to determine the components of fig waste leaves extract. The mobile phase was cosisted of 0.1% formic acid solution (A) and acetonitrile (B). The gradient elution conditions were as follows: 0–6 min, 15% B; 6–30 min, 15%–45% B; 30–40 min, 45%–60% B. The column was kept at 30 ℃ and detected at 330 nm. An Agilent 6530 Accurate-Mass QTOF-MS system was connected with HPLC system via an Agilent Jet Stream electrospray (ESI) interface (Agilent Technologies, Santa Clara, CA). The electrospray ion source is in negative ion mode, the scanning range of mass spectrometer is from m/z 100 to 1500, the ion source is set at 550 ℃, the ion source voltage (IS) -4500 V, the atomization gas pressure 55 psi. And the air curtain gas (CUR) pressure is 35 psi. The de-clustering voltage (DP) of the first-level scanning and the focusing voltage (CE) is 100 V and 10 V, respectively. The secondary mass spectrometry scan uses Product Ion-IDA mode to collect mass spectrum data, and the CID energy is set at -20, -40 and -60 V, respectively. Before injection, the CDS pump is used to correct the mass axis, so that the error of the quality axis is less than 2 ppm. Online HPLC-DPPH analysis Antioxidants in the fig waste leaves extract were screened by online HPLC-DPPH. The flow chart of online HPLC-DPPH screening system was shown in figure 1. This method takes into account the negative peaks produced by the reaction of antioxidants with DPPH radical. Separation was achieved on Agilent 1260 HPLC (Agilent Technologies infinity, Santa Clara, CA, USA). All HPLC-DPPH separation steps were carried out on a C 18 column (4.6 mm × 250 mm, 5 μm, Waters Technologies, USA). The flow rate of HPLC-separated analytes and 50 µg/mL DPPH solution was set at 0.7 mL/min and 0.5 mL/min, respectively. The column temperature was maintained at 35 °C, the detection wavelength was 330 nm, and inject volume was 10 μL. The online HPLC-DPPH analysis conditions were the same as mentioned above. The sample was reacted with DPPH solution in PEEK tube (10 m0.25 mm), determined at 521 nm, the absorption of the compound with antioxidant activity was reduced by pairing with single electron of DPPH with a negative peak. Results And Discussion Determination of total polyphenol content The total polyphenol content of different solvent extracts of fig leaves was shown in figure 2a. It was obvious that the ethyl acetate extract showed the highest content of polyphenol compounds, which was (1.72±0.01) mg/g. In contrast, the content of polyphenol compounds measured in water and petroleum ether extracts was significantly lower, which might be related to the low solubility of polyphenol in petroleum ether and water. Determination of total flavonoids content The total flavonoids content of different solvent extracts of fig leaves was shown in figure 2b. The content of total flavonoids in the extracts was mainly related to different extraction solvents. The content of total flavonoids in the extracts of different solvents was determined. Total flavonoids content in the ethyl acetate part was the highest, which was (83.92±0.01) mg/g, and that in the petroleum ether part was the lowest, which was (18.71±0.11) mg/g. Antioxidant capacity DPPH, ABTS and FRAP were used to evaluate the antioxidant capacity of extracts from fig waste leaves. All the extracts of fig leaves with three different solvents all had the ability to scavenge DPPH free radicals, and with the increase of extract concentration, the DPPH scavenging rate gradually increased. The scavenging ability of ethyl acetate extract varied greatly with concentration. As is known, the lower the IC 50 value, the higher the antioxidant activity of the antioxidants. The IC 50 value of ethyl acetate extract was 0.54 mg/mL, which did not exceed the scavenging ability of Vc on DPPH free radical, nevertheless, the difference was not significant (P>0.05). It can be seen from figure 3a that the scavenging ability of three extracts on DPPH free radical decreased in the following order: ethyl acetate phase > water phase > petroleum ether phase. This may be related to the fact that the ethyl acetate extract contained more flavonoids and polyphenol compounds. It can be seen from figure 3b that each fig leaves extract had the ability of scavenging ABTS free radicals, which was similar to that of DPPH free radical. The changing trend of sample scavenging ability was the same as that of sample concentration. The ethyl acetate extract had the strongest scavenging rate at different concentration of three extracts and the scavenging rate was 80.28% at the concentration of 2.5 mg/mL. The ABTS free radical scavenging activity decreased in the following order: ethyl acetate phase > water phase > petroleum ether phase, which also proved that the flavonoids of fig leaves had strong antioxidant activity. Flavonoids and polyphenols mostly have phenolic hydroxyl groups, which show moderate polarity and can bind with free radicals, showing strong antioxidant activity. When the total antioxidant capacity was measured by FRAP method, the FRAP value was represented by the concentration of FeSO 4 solution. The higher the concentration of extracts, the stronger the antioxidant activity of the substance. The total antioxidant capacity was positively correlated with the concentration of extracts. Among the three extracts, ethyl acetate phase showed the highest FRAP value, 3.46 mmol/g and the strongest reducing ability to ferric ion, which was significantly higher than that of water and petroleum ether phase. The ethyl acetate extract has a strong ferric-ion reducing ability, which is related to the polarity of the solvent. The greater the polarity, the stronger the reducing ability, however, the water extract had the weakest reducing ability, which might be due to the extraction of water-soluble chemical components with water as the extraction solvent, resulting in the reduced antioxidant activity of the extract. Flavonoid characterization of fig leaves by HPLC-DAD-ESI-MS Flavonoids from fig waste leaves were characterized by HPLC-DAD-ESI-MS, as is shown in figure 4, 11 negative peaks of ethyl acetate extract in fig leaves were observed at 517 nm. By scanning in negative ion mode, 11 compounds were analyzed by mass spectrometry. The larger the area of the negative peak, the stronger the antioxidant activity of the compound. The chemical structures of 11 compounds are elucidated in figure 5. Among them, 1, 6 and 7 are the main substances with high antioxidant activity. It is speculated that they are 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin, isoschaftoside and rutin, respectively. Under the condition of negative ions, the total ion flow diagram of flavonoids in fig leaves is shown in figure 6. Through the analysis of the information in the first-level mass spectrometry, it can be preliminarily inferred that the molecular weight of each compound is shown in Table 1. By comparing the fragmentation information of the target compounds in the secondary mass spectrometry and searching the computer standard mass spectrometry database, combining with the references, the experimental results were comprehensively analyzed [34]. Radical scavenging capacity of fig flavonoids by online HPLC-DPPH The isolated compound reacted with DPPH in post-column, and the antioxidants in fig leaves were screened. 11 components of fig leaves extract have negative peak can be observed in DPPH free radical detection spectrum at wavelength 517 nm (figure 4). Three main peaks (1, 6 and 7) were clearly observed as the main contributors of antioxidants. The results showed that there were abundant antioxidant substances scavenging DPPH free radical in fig leaves. When extracted with ethyl acetate, the negative peak had a better front shape, a stable baseline and a large signal noise ratio (SNR). Identification of flavonoid compounds The active components in ethyl acetate from fig leaves were identified according to other characteristics of fragments in the mass spectrometry. 11 flavonoids in fig leaves were identified and their chemical structures were determined. Table 1 presented the retention time, MS fragmentation and molecular formula of compounds detected by HPLC-QTOF-MS/MS analysis. The first-level and secondary mass spectrometry of 11 flavonoids were shown in figure 7. Compound 1: from the first-level mass spectrometry of compound 1, it can be found that there is an excimer ion peak at m/z 771.2027 in the negative ion mode. The main fragment ions were obtained by secondary scanning of the parent ion m/z 771.2027, which were 609.1530, 462.0838 and 301.0357, respectively. According to the mass spectrometry data in Table 1 and related literature [35], it was inferred that the compound is 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin. Compound 2: the m/z 365.0881 of the negative ion mode scan was a [M-H]- peak. The main fragments were 203.0352, 159.0454, 130.0422 by secondary mass spectrometry scanning of m/z 365.0881 parent ion. According to the fragmentation information combined with the literature [36], the compound was identified as 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside according to the mass spectrometry data in Table 1. Compound 3: the m/z 579.1366 scanning in negative ion mode was [M-H] - peak. The main fragments were 519.1194, 489.1083, 429.0856, 399.0748, 369.0635 and 339.0521 by the secondary mass spectrometry scanning of the parent ion m/z 579.1419. It was found to be luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside according to the mass spectrometry data in Table 1 and related literature [37]. Compound 4: in the first-level mass spectrometry of the compound, the m/z 563.1412 scanning in the negative ion mode of the compound was [M-H] - peak. The main secondary mass fragments were m/z 443.1001, 473.1115, 353.0670 and 383.0795 by the secondary mass spectrometry scanning of the parent ion m/z 563.1414. According to the mass spectrometric data in Table 1 and the information combined with the previous literature [38], the compound was presumed to be schaftoside. Compound 5: the m/z 447.0934 scanning in negative ion mode was [M-H] - peak. Through the secondary mass spectrometry scanning of the parent ion m/z 447.0937, the main secondary mass spectrometry fragments can be obtained as follows: 369.0615, 357.0622, 327.0511, 297.0397, 285.0396 and 133.0280. According to the mass spectrometric data in Table 1 and related literature [39], it was speculated that compound 5 was isoorientin. Compound 6: the m/z 563.1412 scanning in negative ion mode of the compound was [M-H] - peak. The main fragments were m/z 443.1001, 473.1115, 353.0670 and 383.0795 by the secondary mass spectrometry scanning of the parent ion m/z 563.1414. According to the mass spectrometric data in Table 1 and related literature [40], it was speculated that this compound was isoschaftoside. Compound 7: the m/z 609.1470 of negative ion mode scanning is [M-H] - peak. The main secondary mass spectrometry fragments were 301.0362, 151.0031, 257.0450 and 273.0477 by the secondary mass spectrometry scan of the parent ion m/z 609.1470. According to the mass spectrum data in Table 1 and related literature [41], the compound was presumed to be rutin. Compound 8: the negative ion mode scan m/z 577.1577 shows the [M-H] - peak. By the secondary mass spectrometry scanning of the parent ion m/z 577.1577, the main secondary mass spectrometry fragments were obtained as m/z 457.1164 and 293.0454. The compound was presumed to be 2''-O-rhamnosylvitexin according to the mass spectrum data in Table 1 and related literature [42]. Compound 9: scanning m/z 431.0989 in the negative ion mode of the compound showed [M-H] - peak. The main fragments of m/z 431.0981 were 283.0621, 311.0564 and 341.0673 by secondary mass spectrometry. According to the mass spectrum data in Table 1 and related literature [43], it could be speculated that the compound was isovitexin. Compound 10: scanning in negative ion mode at m/z 463.0890 showed [M-H] - peak. m/z 463.0890 was scanned by secondary mass spectrometry, and the main fragment ions were m/z 301.0386 and 151.0033. According to the mass spectrum data in Table 1 and earlier studies [44], the compound was presumed to be isoquercetin. Compound 11: scanning m/z 593.1524 in the negative ion mode of the compound showed [M-H] - peak. m/z 593.1576 was scanned by secondary mass spectrometry, and the main fragment ion was m/z 285.0403. The compound was presumed to be kaempferol-3-O-rutinoside according to the mass spectrum data in Table 1 and unified with the literature [45]. Conclusions In this study, online HPLC-QTOF-MS/MS-DPPH method was used for the first time to screen and identify 11 antioxidant active components in fig waste leaves, including 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin (1), 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside (2), luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside (3), schaftoside (4), isoorientin (5), isoschaftoside (6), rutin (7), 2''-O-rhamnosylvitexin (8), isovitexin (9), isoquercetin (10), kaempferol-3-O-rutinoside (11), respectively. The antioxidant capacities of different extracts were based on DPPH and ABTS free radical scavenging rate and FRAP reduction ability. The ethyl acetate extract had the strongest antioxidant capacity. Furthermore, through online HPLC-DPPH analysis, compounds (1), (6) and (7) were considered to be significant antioxidant activity. Therefore, online HPLC-QTOF-MS/MS-DPPH was an effective and rapid analysis method for determining the antioxidant capacity of fig waste leaves, which provided the data support for development and utilization of fig resources. Declarations A cknowlegement s The author thanks Rongcheng healthy group co., ltd for supplying the fig waste leaves. Funding This work was financially supported by the Fundamental Research Fund for Central Universities (2572019CZ01) and Heilongjiang Touyan Innovation Team Program (Tree Genetics and Breeding Innovation Team). Declarations Conflicts of Interest The authors have declared no confict of interest. Availability of data and material Not applicable Code availability Not applicable Authors’ Contributions Chunjian Zhao and Yujie Fu conceived the underlying ideas of the study, Chunying Li, Meiting Yu and Shen Li contributed to the practical aspects of the research work, Xue Yang, Bin Qiao and Sen Shi analyzed the data, and Chunying Li, Meiting Yu and Shen Li wrote the manuscript. References Jules, J.: The Fig: Horticultural Reviews. John Wiley & Sons Inc, New Jersey (2010) Zohary, D., Spiegel-Roy, P.: Beginnings of Fruit Growing in the Old World. Science. 187 , 319–327 (1975) Afsah-Hejri, L., Toudeshki, A., Homayouni, T., Mehrazi, S., Ghomlami Pareh, A., Gordon, P., Ehsani, R.: Potential of ozonated-air (OA) application to reduce the weight and volume loss in fresh figs (Ficus carica L.). 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Supplementary Files GraphicAbstract.pdf Cite Share Download PDF Status: Published Journal Publication published 20 Nov, 2021 Read the published version in Plants → Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-804140","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":49118678,"identity":"aaf857a4-7a89-49c7-9140-b50bf6afed26","order_by":0,"name":"Chunying Li","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chunying","middleName":"","lastName":"Li","suffix":""},{"id":49118679,"identity":"f65ab3de-5b00-49d9-9066-321361101759","order_by":1,"name":"Meiting Yu","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Meiting","middleName":"","lastName":"Yu","suffix":""},{"id":49118680,"identity":"bbe68d4f-641d-48e8-8086-5774029a57da","order_by":2,"name":"Shen Li","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shen","middleName":"","lastName":"Li","suffix":""},{"id":49118681,"identity":"13bfe125-6b0b-431c-87e9-9442ac8dd84b","order_by":3,"name":"Xue Yang","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xue","middleName":"","lastName":"Yang","suffix":""},{"id":49118682,"identity":"f62e241a-e2a3-4178-931d-b5f764915482","order_by":4,"name":"Bin Qiao","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Qiao","suffix":""},{"id":49118683,"identity":"d6d56ab6-a916-4fc4-8106-51d065c8e6c4","order_by":5,"name":"Sen Shi","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sen","middleName":"","lastName":"Shi","suffix":""},{"id":49118684,"identity":"3936331a-f1e0-4952-b04a-b63a5716dd4c","order_by":6,"name":"Chunjian Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAq0lEQVRIiWNgGAWjYHCCBAaJCgk5eRK1nLEwNmwgyR7GtopEhgPEqpZvP/D4g+U8iQTGBuaHj24QZUFPQpqE5DaJPHYGNmPjHGK0MEswpDEAtRQzNvCwSROlhU2CIfmD5ByJxIYDxGrhkWBIkJBsIEWLBA/QLxLHJIwNm4n1i3z7meTPEjV1cvLszQ8fE6UF6LQEYBAAATNxykGA/QDjB+JVj4JRMApGwUgEAE5fKMraKh7WAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-2827-1999","institution":"Northeast Forestry University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Chunjian","middleName":"","lastName":"Zhao","suffix":""},{"id":49118685,"identity":"939d0704-4997-4e57-901f-8a68faa0cd20","order_by":7,"name":"Yujie Fu","email":"","orcid":"","institution":"Northeast Forestry University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yujie","middleName":"","lastName":"Fu","suffix":""}],"badges":[],"createdAt":"2021-08-11 21:11:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-804140/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-804140/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.3390/plants10112532","type":"published","date":"2021-11-21T02:56:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":12989232,"identity":"308fc733-d26e-4418-8c23-d6d5055947d1","added_by":"auto","created_at":"2021-09-01 22:04:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83063,"visible":true,"origin":"","legend":"The flow chart of online HPLC-DPPH screening system.","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/0088f400e889475f26af1eda.png"},{"id":12989234,"identity":"7d1ca275-8ffd-4740-bf6c-99303cc37b75","added_by":"auto","created_at":"2021-09-01 22:04:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46904,"visible":true,"origin":"","legend":"Effect of different extraction solvent on the yield of total polyphenol and flavonoids. (a. polyphenol; b. flavonoids).","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/9eff63868bfcef2835e5ea5c.png"},{"id":12989235,"identity":"93b27fc8-4cce-4ddf-8593-56c7abc271d5","added_by":"auto","created_at":"2021-09-01 22:04:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":81373,"visible":true,"origin":"","legend":"Effect of different extraction solvent on antioxidant capacity. (a. scavenging capacity on DPPH radical; b. scavenging capacity on ABTS radical; c. ferric-ion reducing capacity).","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/5df85f19ec66e5f72fb23307.png"},{"id":12989508,"identity":"9f13270c-9859-4eb6-b4ea-5988a097574b","added_by":"auto","created_at":"2021-09-01 22:07:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":94690,"visible":true,"origin":"","legend":"Antioxidant components of ethyl acetate extract from fig leaves by online HPLC-DPPH. (1. 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin; 2. 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside; 3. luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside; 4. schaftoside; 5. isoorientin; 6. isoschaftoside; 7. rutin; 8. 2''-O-rhamnosylvitexin; 9. isovitexin; 10. isoquercetin; 11. kaempferol-3-O-rutinoside).","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/f1e59e43ba875396c1ae72cd.png"},{"id":12989236,"identity":"209eda50-3f30-4150-8598-718ee8906235","added_by":"auto","created_at":"2021-09-01 22:04:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":111279,"visible":true,"origin":"","legend":"Chemical structures of 11 compounds in fig leaves. (1. 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin; 2. 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside; 3. luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside; 4. schaftoside; 5. isoorientin; 6. isoschaftoside; 7. rutin; 8. 2''-O-rhamnosylvitexin; 9. isovitexin; 10. isoquercetin; 11. kaempferol-3-O-rutinoside).","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/7bd4d4e9cde3a8ceefea3876.png"},{"id":12989237,"identity":"03320dfd-11bb-4d72-abfc-e6e9c285b284","added_by":"auto","created_at":"2021-09-01 22:04:42","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":50464,"visible":true,"origin":"","legend":"Total ion flow chromatogram of sample extract. Peak 1-11 are identified in Table 1.","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/96aba64a255715ea084c0a40.png"},{"id":12989239,"identity":"523898a8-c769-4798-bf19-42bc3b1698de","added_by":"auto","created_at":"2021-09-01 22:04:42","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":152530,"visible":true,"origin":"","legend":"The mass spectrometry of flavonoids compounds. (a. 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin; b. 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside; c. luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside; d. schaftoside; e. isoorientin; f. isoschaftoside; g. rutin; h. 2''-O-rhamnosylvitexin; i. isovitexin; j. isoquercetin; k. kaempferol-3-O-rutinoside).","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/287b5bde1e96cb4808cfbe0d.png"},{"id":15760219,"identity":"d4429a8d-3cce-449a-8268-c0cc4e74a115","added_by":"auto","created_at":"2021-11-22 02:56:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1117173,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/8c91da8f-3103-4ef3-8c7b-b4ae2866de9f.pdf"},{"id":12989509,"identity":"af4b3083-344e-4073-91db-719ccc2709f1","added_by":"auto","created_at":"2021-09-01 22:07:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":40012,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-804140/v1/b0e213ff0c10ef16d598e635.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eValorization of Fig (\u003cem\u003eFicus carica \u003c/em\u003eLinn.) Waste Leaves: HPLC-QTOF-MS/MS-DPPH System For Online Screening And Identification of Antioxidant Compounds\u003c/p\u003e","fulltext":[{"header":"Statement Of Novelty","content":"\u003cp\u003eA large number of fig leaves are produced each year and often thrown away as wastes, resulting in a waste of resources. However, fig leaves are rich in flavonoids and polyphenols, which have strong antioxidant activity. HPLC-QTOF-MS/MS-DPPH method was used for online screening and identification of components with antioxidant activity from fig waste leaves for the first time. Chemical structures were identified and the antioxidant capacity were measured. This study provided a scientific and theoretical basis for the development and utilization of waste biomass from fig leaves.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eFig (\u003cem\u003eFicus carica\u003c/em\u003e Linn.) as one of the earliest cultivated fruit trees, belongs to the mulberry family (Moraceae). Figs are native to the Mediterranean coast, from Turkey to Afghanistan [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], mainly grow in some tropical and temperate regions, belonging to the subtropical larch family [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It was introduced into China from Persia in the Tang Dynasty. Because of its low requirements on soil conditions and strong roots, it was widely cultivated in the north and south, mainly distributed in Xinjiang, Fujian, Shandong and other places. Fig has not only a wide range of medicinal and nutritional value, but also has nourishing the stomach and clearing the intestines, reducing swelling and detoxification. It is often used in the treatment of anorexia, abdominal distension and abdominal pain, hemorrhoids and constipation, dyspepsia, insufficient milk, sore throat, cough and sputum [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo make the fig trees grow more vigorously, they are often been pruned. Therefore, a large number of abandoned branches and leaves will be produced every year, causing environmental pollution and waste of resources. However, the fig leaves were found to contain flavonoids, sugars, pectin, tannins, vitamin C (Vc) and trace elements [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Clinical studies had shown that fig leaves extract had anti-tumor, hypolipidemic, antioxidant, antibacterial, hypoglycemic and other activities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Because the fig leaves contain a large number of flavonoids, they have a variety of pharmacological activities, which can prevent cardiovascular diseases, anti-osteoporosis, treatment of diarrhea, scavenging oxidative free radicals, lowering blood lipids, treatment of sore throat and immune regulation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It is reported that higher amount of flavonoids have been found in fig leaves [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], including rutin, quercetin, anthocyanin and so on. Anthocyanins enable to promote the apoptosis of cancer cells, slow down the proliferation of cancer cells and prevent the metastasis of cancer cells [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. At the same time, it can effectively relieve visual fatigue and slow down the development of diabetic cataract [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Quercetin and rutin have protective effects on ischemic brain injury [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Flavonoids not only regulate the cardiovascular system by reducing capillary permeability, lipid and blood pressure, but also play an important role in anti-inflammatory and anti-immune activity by affecting cell mitosis, cell-cell interaction and cell secretion [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, making full use of fig waste leaves is an effective way to realize resource utilization.\u003c/p\u003e \u003cp\u003e1, 1-diphenyl-2-picrylhydrazyl (DPPH) is a very stable nitrogen-centered free radical that can trap other free radicals and has maximum absorption at 517 nm. It has a strong purple color and turns yellow after reacting with antioxidant species. This method was often used to evaluate the antioxidant activity of compounds or plant extracts. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Nevertheless, in the evaluation of antioxidant activity of herbal extracts with complex components, the main drawback of this method is that it is impossible to know exactly which compounds in the complex mixture have antioxidant activity. Only after the separation and purification of a compound it can be known whether it has antioxidant activity. This method is time-consuming, laborious, and the results are not accurate [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Recently, HPLC-DPPH-DAD online screening of antioxidant systems is a fast and efficient method for exploring antioxidant compounds from natural resources [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and used for screening and identification of antioxidants in fruit wine, tea, plants and so on [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, HPLC-DPPH was used to screen out the antioxidant active components in different extracts of fig waste leaves. In order to further study the antioxidant chemical components, HPLC-DPPH-MS/MS was applied to identify and analyze the antioxidant active components for the first time. By this method, 11 flavonoids were found in the fig waste leaves. Compared with the traditional methods for screening natural antioxidant active components, this method can screen and identify the antioxidant active components in fig waste leaves rapidly and efficiently, so as to make full use of the fig resources.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003eChemicals and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiscarded\u0026nbsp;fig\u0026nbsp;leaves were picked from\u0026nbsp;Chengshan Town, Rongcheng City, Shandong Province,\u0026nbsp;China.\u0026nbsp;And the fig leaves were dried at a shady place out of direct sunlight until the weight was remained the same.\u0026nbsp;The dried leaves were smashed and sieved through a 60-mesh sieve for further\u0026nbsp;test.\u0026nbsp;All chemicals\u0026nbsp;were of analytical grade, unless stated otherwise\u0026nbsp;and\u0026nbsp;were purchased from Sigma\u0026nbsp;Aldrich (St. Louis, MO, USA).\u0026nbsp;Standard solutions were stored at 4 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstrumentation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn Agilent 6530 Accurate-Mass QTOF-MS system was connected with HPLC system via an Agilent Jet Stream electrospray (ESI) interface and an Agilent 1260 HPLC with\u0026nbsp;diode array detector (DAD) (Agilent\u0026nbsp;Technologies,\u0026nbsp;Santa Clara, CA,\u0026nbsp;USA).\u0026nbsp;Kq-100e Ultrasonic cleaning instrument (Kunshan Ultrasonic Instrument Co., LTD.)\u0026nbsp;was used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;fig\u0026nbsp;leaves\u0026nbsp;wastes\u0026nbsp;were\u0026nbsp;dried at\u0026nbsp;the\u0026nbsp;temperature of 60\u0026nbsp;℃\u0026nbsp;and then crushed through a 60-mesh screen.\u0026nbsp;10 g of dry powder was weighed and put into a triangular flask,\u0026nbsp;70% ethanol was added at the ratio of 1:10 (w/v), 200 W, 40\u0026nbsp;℃, ultrasonic for\u0026nbsp;30 min, repeated twice, centrifugation at 6000 rpm\u0026nbsp;for 10 min, filtrate was combined, concentration was performed to obtain the ethanol extract of\u0026nbsp;fig\u0026nbsp;leaves.\u0026nbsp;An\u0026nbsp;appropriate\u0026nbsp;amount of distilled water was added to the ethanol extract to form a homogeneous suspension, which was extracted by adding petroleum ether and ethyl acetate in turn\u0026nbsp;to be extracted\u0026nbsp;by rotary evaporation at 60\u0026nbsp;℃\u0026nbsp;to obtain the extracts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTotal polyphenol content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total polyphenol contents\u0026nbsp;in different solvent extracts were\u0026nbsp;based on\u0026nbsp;Folin-Ciocalteu\u0026nbsp;method.\u0026nbsp;The optimal reaction conditions of the system were as follows: test sample 0.1 mL, Folin-Ciocalteu reagent 0.1 mL and 60 g/L Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u0026nbsp;\u003c/sub\u003esolution 0.8 mL, with minor modifications [31].\u0026nbsp;Mixture was incubated at room temperature and protected from light for 10 min.\u0026nbsp;Absorbance\u0026nbsp;of total polyphenol\u0026nbsp;at 765 nm was determined\u0026nbsp;by UV-Visible spectrometer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTotal flavonoid content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe content of total flavonoids in\u0026nbsp;fig\u0026nbsp;waste\u0026nbsp;leaves\u0026nbsp;was determined by NaNO\u003csub\u003e2\u003c/sub\u003e-Al(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e method\u0026nbsp;[32].\u0026nbsp;Rutin was used\u0026nbsp;as\u0026nbsp;a standard. Content of total flavonoid\u0026nbsp;was measured at 506\u0026nbsp;nm\u0026nbsp;of\u0026nbsp;wavelength.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of antioxidant capacities\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDPPH radical scavenging capacity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA proper amount of DPPH sample was weighted and anhydrous ethanol was added for ultrasonic dissolution to obtain DPPH solution with the concentration of 0.06 mg/mL. 0.15 mL of DPPH solution from the stock was mixed with 0.17 mL of diluted sample. The reaction was kept from light for 30 min at room temperature. The detection wavelength was 517 nm. Each group of experiments is parallel for three times, and the calculation formula is as follows:\u003c/p\u003e\n\u003cp style=\"margin:0cm;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:DengXian;text-indent:20.0pt;line-height:150%;\"\u003e\u003cspan style='font-size:13px;line-height:150%;font-family:\"Times New Roman\",serif;background:white;'\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/span\u003e\u003cbr\u003e......(1)\u003c/p\u003e\n\u003cp\u003ewhere W (%) represents DPPH radical scavenging rate. A\u003csub\u003ek\u003c/sub\u003e, A\u003csub\u003em\u003c/sub\u003e and A\u003csub\u003en\u003c/sub\u003e represent absorbance of DPPH solution, absorbance of extracts of different concentrations reacted with DPPH solution and absorbance of different concentrations of extracts reacted with anhydrous ethanol.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2,2\u0026rsquo;-azino-bis(3-ethylbenzothiazoline-6-sulfonic) acid\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(ABTS) radical scavenging capacity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mixture of 100 \u0026micro;L ABTS solution and oxidant solution was added at the volume ratio of 1:1 and was kept away from light at room temperature for 16 h. The ABTS working solution was obtained by diluting the ABTS solution with anhydrous ethanol. 20 \u0026micro;L of different concentrations of extract solution, different concentration of Vc solution and 180 \u0026micro;L ABTS working solution were mixed evenly in a 96-well plate. The absorbance was measure at 734 nm, and the experiments were repeated three times in each group. The scavenging capacity of ABTS free radicals is calculated by the following formula (2):\u003cbr\u003e\u003cbr\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e.........(2)\u003c/p\u003e\n\u003cp\u003ewhere W (%) refers to ABTS radical scavenging rate. A\u003csub\u003ek\u003c/sub\u003e, A\u003csub\u003em\u003c/sub\u003e and A\u003csub\u003en\u003c/sub\u003e refer to absorbance of ABTS working solution, absorbance of ABTS after reacting with sample and absorbance of sample solution mixed with anhydrous ethanol.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFerric-ion reducing antioxidant power (FRAP)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFRAP was determined according to the method of Jin et al. [33]. Take 150 \u0026micro;l of appropriately diluted\u0026nbsp;extract of\u0026nbsp;fig waste leaves, add 3 mL of\u0026nbsp;2, 3, 5-triphenyl-2h-tetrazolium,chloride (TPTZ) working solution,\u0026nbsp;which consists of acetic acid buffer (pH 3.6), 10 mmol/L TPTZ solution and 20 mmol/L FeCl\u003csub\u003e3\u003c/sub\u003e solution mixed in proportion (10:1:1) and reacted at 37 ℃ for 30 min. The detection wavelength was 593 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of the HPLC-QTOF-MS/MS-DPPH system\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHPLC-DAD-ESI-MS analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHPLC-ion trap mass spectrometry with DAD was used to determine the components of fig waste leaves extract. The mobile phase was cosisted of 0.1% formic acid\u0026nbsp;solution (A) and acetonitrile (B). The gradient elution conditions were as follows: 0\u0026ndash;6 min, 15% B; 6\u0026ndash;30 min, 15%\u0026ndash;45% B; 30\u0026ndash;40 min, 45%\u0026ndash;60% B. The column was kept at 30\u0026nbsp;℃\u0026nbsp;and detected at 330 nm. An Agilent 6530 Accurate-Mass QTOF-MS system was connected with HPLC system via an Agilent Jet Stream electrospray (ESI) interface (Agilent Technologies, Santa Clara, CA). The electrospray ion source is in negative ion mode, the scanning range of mass spectrometer is from m/z 100 to 1500, the ion source is set at 550\u0026nbsp;℃,\u0026nbsp;the ion source voltage (IS) -4500 V, the atomization gas pressure 55 psi. And the air curtain gas (CUR) pressure is 35 psi. The de-clustering voltage (DP) of the first-level scanning and the focusing voltage (CE) is 100 V and 10 V, respectively. The secondary mass spectrometry scan uses Product Ion-IDA mode to collect mass spectrum data, and the CID energy is set at -20, -40 and -60 V, respectively. Before injection, the CDS pump is used to correct the mass axis, so that the error of the quality axis is less than 2 ppm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOnline HPLC-DPPH analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntioxidants in the fig waste leaves extract were screened by online HPLC-DPPH.\u0026nbsp;The flow chart\u0026nbsp;of\u0026nbsp;online HPLC-DPPH screening system\u0026nbsp;was shown in\u0026nbsp;figure\u0026nbsp;1.\u0026nbsp;This method takes into account the\u0026nbsp;negative peaks produced by the reaction of antioxidants with DPPH radical. Separation was achieved on Agilent 1260 HPLC (Agilent Technologies infinity, Santa Clara, CA, USA). All HPLC-DPPH separation steps were carried out on a C\u003csub\u003e18\u003c/sub\u003e column (4.6 mm \u0026times; 250 mm, 5 \u0026mu;m, Waters Technologies, USA). The flow rate of HPLC-separated analytes and 50 \u0026micro;g/mL DPPH solution was set at 0.7 mL/min and 0.5 mL/min, respectively. The column temperature was maintained at 35 \u0026deg;C, the detection wavelength was 330 nm, and inject volume was 10 \u0026mu;L. The online HPLC-DPPH analysis conditions were the same as mentioned above. The sample was reacted with DPPH solution in PEEK tube (10 m0.25 mm), determined at 521 nm, the absorption of the compound with antioxidant activity was reduced by pairing with single electron of DPPH with a negative peak.\u003c/p\u003e"},{"header":"Results And Discussion","content":"\u003cp\u003e\u003cstrong\u003eDetermination of total polyphenol content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total polyphenol content of different solvent extracts of\u0026nbsp;fig\u0026nbsp;leaves was shown in\u0026nbsp;figure 2a. It was obvious that the ethyl acetate\u0026nbsp;extract showed the highest content of polyphenol compounds, which was (1.72\u0026plusmn;0.01)\u0026nbsp;mg/g. In contrast, the content of\u0026nbsp;polyphenol\u0026nbsp;compounds\u0026nbsp;measured in water and petroleum ether extracts was significantly lower, which might be related to the low solubility of polyphenol in petroleum ether and water.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of total flavonoids content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total\u0026nbsp;flavonoids\u0026nbsp;content of different solvent extracts of\u0026nbsp;fig\u0026nbsp;leaves was shown in\u0026nbsp;figure 2b.\u0026nbsp;The content of total flavonoids in the extracts was mainly related to different extraction solvents. The content of total flavonoids in the extracts of different solvents was determined.\u0026nbsp;Total flavonoids content\u0026nbsp;in\u0026nbsp;the ethyl acetate\u0026nbsp;part was the highest,\u0026nbsp;which was (83.92\u0026plusmn;0.01) mg/g, and\u0026nbsp;that\u0026nbsp;in\u0026nbsp;the petroleum ether\u0026nbsp;part was the\u0026nbsp;lowest, which was\u0026nbsp;(18.71\u0026plusmn;0.11)\u0026nbsp;mg/g.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntioxidant capacity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDPPH, ABTS and FRAP were used to evaluate the antioxidant capacity of extracts from fig waste leaves. All the extracts of fig leaves with three different solvents all had the ability to scavenge DPPH free radicals, and with the increase of extract concentration, the DPPH scavenging rate gradually increased. The scavenging ability of ethyl acetate extract varied greatly with concentration. As is known, the lower the IC\u003csub\u003e50\u003c/sub\u003e value, the higher the antioxidant activity of the antioxidants. The IC\u003csub\u003e50\u003c/sub\u003e value of ethyl acetate extract was 0.54 mg/mL, which did not exceed the scavenging ability of Vc on DPPH free radical, nevertheless, the difference was not significant (P\u0026gt;0.05). It can be seen from figure 3a that the scavenging ability of three extracts on DPPH free radical decreased in the following order: ethyl acetate phase \u0026gt; water phase \u0026gt; petroleum ether phase. This may be related to the fact that the ethyl acetate extract contained more flavonoids and polyphenol compounds.\u003c/p\u003e\n\u003cp\u003eIt can be seen from figure 3b that each fig leaves extract had the ability of scavenging ABTS free radicals, which was similar to that of DPPH free radical. The changing trend of sample scavenging ability was the same as that of sample concentration. The ethyl acetate extract had the strongest scavenging rate at different concentration of three extracts and the scavenging rate was 80.28% at the concentration of 2.5 mg/mL. The ABTS free radical scavenging activity decreased in the following order: ethyl acetate phase \u0026gt; water phase \u0026gt; petroleum ether phase, which also proved that the flavonoids of fig leaves had strong antioxidant activity. Flavonoids and polyphenols mostly have phenolic hydroxyl groups, which show moderate polarity and can bind with free radicals, showing strong antioxidant activity.\u003c/p\u003e\n\u003cp\u003eWhen the total antioxidant capacity was measured by FRAP method, the FRAP value was represented by the concentration of FeSO\u003csub\u003e4\u003c/sub\u003e solution. The higher the concentration of extracts, the stronger the antioxidant activity of the substance. The total antioxidant capacity was positively correlated with the concentration of extracts. Among the three extracts, ethyl acetate phase showed the highest FRAP value, 3.46 mmol/g and the strongest reducing ability to ferric ion, which was significantly higher than that of water and petroleum ether phase. The ethyl acetate extract has a strong ferric-ion reducing ability, which is related to the polarity of the solvent. The greater the polarity, the stronger the reducing ability, however, the water extract had the weakest reducing ability, which might be due to the extraction of water-soluble chemical components with water as the extraction solvent, resulting in the reduced antioxidant activity of the extract.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlavonoid characterization of fig leaves by HPLC-DAD-ESI-MS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlavonoids from fig waste leaves were characterized by HPLC-DAD-ESI-MS, as is shown in figure\u0026nbsp;4, 11 negative peaks of ethyl acetate extract in fig leaves were observed at 517 nm. By scanning in negative ion mode, 11 compounds were analyzed by mass spectrometry. The larger the area of the negative peak, the stronger the antioxidant activity of the compound.\u0026nbsp;The chemical structures of 11 compounds are elucidated in figure 5.\u0026nbsp;Among them, 1, 6 and 7 are the main substances with high antioxidant activity.\u0026nbsp;It is speculated that they are\u0026nbsp;3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin, isoschaftoside and rutin, respectively.\u003c/p\u003e\n\u003cp\u003eUnder the condition of negative ions, the total ion flow diagram of flavonoids in fig leaves is shown in figure\u0026nbsp;6.\u0026nbsp;Through the analysis of the information in the first-level mass\u0026nbsp;spectrometry, it can be preliminarily inferred that the molecular weight of each compound is shown in Table\u0026nbsp;1. By comparing the fragmentation information of the target compounds in the secondary mass spectrometry and searching the computer standard mass spectrometry database, combining with the references, the experimental results were comprehensively analyzed\u0026nbsp;[34].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRadical scavenging capacity of fig flavonoids by online HPLC-DPPH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe isolated compound reacted with DPPH in post-column, and the antioxidants in fig leaves were screened. 11 components of fig leaves extract have negative peak can be observed in DPPH free radical detection spectrum at wavelength 517 nm (figure 4). Three main peaks (1, 6 and 7) were clearly observed as the main contributors of antioxidants.\u0026nbsp;The results showed that there were abundant antioxidant substances scavenging DPPH free radical in\u0026nbsp;fig\u0026nbsp;leaves. When extracted with\u0026nbsp;ethyl acetate, the negative peak had a better front shape, a stable baseline and a large\u0026nbsp;signal noise ratio (SNR).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of flavonoid compounds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe active components in ethyl acetate from fig leaves were identified according to other characteristics of fragments in the mass spectrometry. 11 flavonoids in fig leaves were identified and their chemical structures were determined. Table 1 presented the retention time, MS fragmentation and molecular formula of compounds detected by HPLC-QTOF-MS/MS analysis. The first-level and secondary mass spectrometry of 11 flavonoids were shown in figure 7.\u003c/p\u003e\n\u003cp\u003eCompound 1: from the first-level mass\u0026nbsp;spectrometry\u0026nbsp;of compound 1, it can be found that there is an excimer ion peak at m/z 771.2027 in the negative ion mode. The main fragment ions were obtained by secondary scanning of the parent ion m/z 771.2027, which were 609.1530, 462.0838 and 301.0357, respectively. According to the mass\u0026nbsp;spectrometry\u0026nbsp;data in Table 1 and related literature [35], it was inferred that the compound is 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin.\u003c/p\u003e\n\u003cp\u003eCompound 2: the m/z 365.0881 of the negative ion mode scan was a [M-H]- peak. The main fragments were 203.0352, 159.0454, 130.0422 by secondary mass spectrometry scanning of m/z 365.0881 parent ion. According to the fragmentation information combined with the literature [36], the compound was identified as 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside according to the mass spectrometry data in Table 1.\u003c/p\u003e\n\u003cp\u003eCompound 3: the m/z 579.1366 scanning in negative ion mode was [M-H]\u003csup\u003e-\u003c/sup\u003e peak. The main fragments were 519.1194, 489.1083, 429.0856, 399.0748, 369.0635 and 339.0521 by the secondary mass spectrometry scanning of the parent ion m/z 579.1419. It was found to be luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside according to the mass spectrometry data in Table 1 and related literature [37].\u003c/p\u003e\n\u003cp\u003eCompound 4: in the first-level mass\u0026nbsp;spectrometry\u0026nbsp;of the compound, the m/z 563.1412 scanning in the negative ion mode of the compound was [M-H]\u003csup\u003e-\u003c/sup\u003e peak. The main secondary mass fragments were m/z 443.1001, 473.1115, 353.0670 and 383.0795 by the secondary mass spectrometry scanning of the parent ion m/z 563.1414. According to the mass spectrometric data in Table 1 and the information combined with the previous literature [38], the compound was presumed to be schaftoside.\u003c/p\u003e\n\u003cp\u003eCompound 5: the m/z 447.0934 scanning in negative ion mode was [M-H]\u003csup\u003e-\u003c/sup\u003e peak. Through the secondary mass spectrometry scanning of the parent ion m/z 447.0937, the main secondary mass spectrometry fragments can be obtained as follows: 369.0615, 357.0622, 327.0511, 297.0397, 285.0396 and 133.0280. According to the mass spectrometric data in Table 1 and related literature [39], it was speculated that compound 5 was isoorientin.\u003c/p\u003e\n\u003cp\u003eCompound\u0026nbsp;6:\u0026nbsp;the m/z 563.1412\u0026nbsp;scanning in negative ion mode of the compound was [M-H]\u003csup\u003e-\u003c/sup\u003e peak.\u0026nbsp;The main\u0026nbsp;fragments were\u0026nbsp;m/z\u0026nbsp;443.1001, 473.1115, 353.0670 and 383.0795 by the secondary\u0026nbsp;mass spectrometry\u0026nbsp;scanning of the parent ion\u0026nbsp;m/z\u0026nbsp;563.1414.\u0026nbsp;According to the mass spectrometric data in Table\u0026nbsp;1\u0026nbsp;and related literature\u0026nbsp;[40], it was speculated that this compound was\u0026nbsp;isoschaftoside.\u003c/p\u003e\n\u003cp\u003eCompound\u0026nbsp;7:\u0026nbsp;the m/z 609.1470 of negative ion mode scanning is [M-H]\u003csup\u003e-\u003c/sup\u003e peak.\u0026nbsp;The main secondary\u0026nbsp;mass spectrometry\u0026nbsp;fragments were 301.0362, 151.0031, 257.0450 and 273.0477 by the secondary\u0026nbsp;mass spectrometry\u0026nbsp;scan of the parent ion\u0026nbsp;m/z\u0026nbsp;609.1470.\u0026nbsp;According to the mass spectrum data in Table\u0026nbsp;1 and\u0026nbsp;related literature\u0026nbsp;[41],\u0026nbsp;the compound was presumed to be rutin.\u003c/p\u003e\n\u003cp\u003eCompound\u0026nbsp;8:\u0026nbsp;the negative ion mode scan m/z 577.1577 shows the [M-H]\u003csup\u003e-\u003c/sup\u003e peak.\u0026nbsp;By the secondary mass spectrometry scanning of the parent ion\u0026nbsp;m/z\u0026nbsp;577.1577, the main secondary mass spectrometry fragments were obtained as\u0026nbsp;m/z\u0026nbsp;457.1164 and 293.0454.\u0026nbsp;The compound was presumed to be\u0026nbsp;2\u0026apos;\u0026apos;-O-rhamnosylvitexin according to the mass spectrum data in Table\u0026nbsp;1 and related literature [42].\u003c/p\u003e\n\u003cp\u003eCompound\u0026nbsp;9:\u0026nbsp;scanning\u0026nbsp;m/z\u0026nbsp;431.0989\u0026nbsp;in the negative ion mode of the compound showed [M-H]\u003csup\u003e-\u003c/sup\u003e peak.\u0026nbsp;The main fragments of m/z 431.0981 were 283.0621, 311.0564 and 341.0673 by\u0026nbsp;secondary\u0026nbsp;mass spectrometry.\u0026nbsp;According to the\u0026nbsp;mass spectrum data\u0026nbsp;in Table\u0026nbsp;1\u0026nbsp;and related literature\u0026nbsp;[43], it could be\u0026nbsp;speculated that the compound was isovitexin.\u003c/p\u003e\n\u003cp\u003eCompound 10:\u0026nbsp;scanning\u0026nbsp;in negative ion mode at m/z 463.0890 showed [M-H]\u003csup\u003e-\u003c/sup\u003e peak.\u0026nbsp;m/z\u0026nbsp;463.0890 was scanned by secondary mass spectrometry, and the main fragment ions were\u0026nbsp;m/z\u0026nbsp;301.0386 and 151.0033.\u0026nbsp;According to the mass spectrum data in Table\u0026nbsp;1\u0026nbsp;and earlier studies\u0026nbsp;[44],\u0026nbsp;the compound was presumed to be isoquercetin.\u003c/p\u003e\n\u003cp\u003eCompound 11: scanning m/z 593.1524 in the negative ion mode of the compound showed [M-H]\u003csup\u003e-\u0026nbsp;\u003c/sup\u003epeak. m/z 593.1576 was scanned by secondary mass spectrometry, and the main fragment ion was m/z 285.0403. The compound was presumed to be kaempferol-3-O-rutinoside according to the mass spectrum data in Table 1 and unified with the literature [45].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, online HPLC-QTOF-MS/MS-DPPH method was used for the first time to screen and identify 11 antioxidant active components in fig waste leaves, including 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin (1), 2-carboxyl-1, 4-naphthohydroquinone-4-O-glucopyranoside (2), luteolin 6-C-glucopyranoside, 8-C-arabinopyranoside (3), schaftoside (4), isoorientin (5), isoschaftoside (6), rutin (7), 2''-O-rhamnosylvitexin (8), isovitexin (9), isoquercetin (10), kaempferol-3-O-rutinoside (11), respectively. The antioxidant capacities of different extracts were based on DPPH and ABTS free radical scavenging rate and FRAP reduction ability. The ethyl acetate extract had the strongest antioxidant capacity. Furthermore, through online HPLC-DPPH analysis, compounds (1), (6) and (7) were considered to be significant antioxidant activity. Therefore, online HPLC-QTOF-MS/MS-DPPH was an effective and rapid analysis method for determining the antioxidant capacity of fig waste leaves, which provided the data support for development and utilization of fig resources.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003ecknowlegement\u003c/strong\u003e\u003cstrong\u003es\u0026nbsp;\u003c/strong\u003eThe author\u0026nbsp;thanks Rongcheng healthy group co., ltd for supplying the fig waste leaves.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was financially supported by the Fundamental Research Fund for Central Universities (2572019CZ01) and Heilongjiang Touyan Innovation Team Program (Tree Genetics and Breeding Innovation Team).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e The authors have declared no confict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u0026nbsp;\u003c/strong\u003eChunjian Zhao and Yujie Fu conceived the underlying ideas of the study, Chunying Li, Meiting Yu and Shen Li contributed to the practical aspects of the research work, Xue Yang,\u0026nbsp;Bin Qiao\u0026nbsp;and\u0026nbsp;Sen Shi\u0026nbsp;analyzed the data, and Chunying Li, Meiting Yu and Shen Li wrote the manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eJules, J.: The Fig: Horticultural Reviews. 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Technol. 116217 (2020)\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eWang, Y., Tang, C., Zhang, H.: Hepatoprotective effects of kaempferol 3-O-rutinoside and kaempferol 3-O-glucoside from Carthamus tinctorius L. on CCl4-induced oxidative liver injury in mice. J. Food Drug Anal. \u003cstrong\u003e23\u003c/strong\u003e, 310\u0026ndash;317 (2015)\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTab.1\u003c/strong\u003e Flavonoids identified in the fig leaves extracts using HPLC-QTOF-MS/MS.\u003cbr\u003e\u003cimg 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Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ficus carica Linn, waste leaves, Antioxidant, HPLC-QTOF-MS/MS-DPPH, Flavonoids, Polyphenols","lastPublishedDoi":"10.21203/rs.3.rs-804140/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-804140/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFig (Ficus carica Linn.) leaves are produced each year and often thrown away as wastes, resulting in a waste of resources. Fig waste leaves are rich in flavonoids, which have strong antioxidant activity, however, the antioxidant components are not clear. So as to take full advantage of fig waste leaves, antioxidant capacity of different extracts (petroleum ether, ethyl acetate and water) was evaluated by 1, 1-diphenyl-2-picrylhydrazyl (DPPH), 2,2\u0026rsquo;-azino-bis(3-ethylbenzothiazoline-6-sulfonic) acid (ABTS) and ferric-ion reducing antioxidant power (FRAP) methods. The results showed that flavonoids in ethyl acetate extraction had the highest content, 83.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 mg/g, and maximum DPPH scavenging activity (IC\u003csub\u003e50\u003c/sub\u003e 0.54 mg/mL), highest ABTS scavenging rate (80.28%), FRAP (3.46 mmol/g). Furthermore, HPLC-QTOF-MS/MS-DPPH method was developed for the first time to identify 11 flavonoids in fig waste leaves. This rapid and efficient method can not only be used for screening the antioxidant components in fig waste leaves, but also can be combined with mass spectrometry to identify the compounds with antioxidant capacity. There are three flavonoids with significant antioxidant capacity, which are 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin, isoschaftoside and rutin. The results confirmed that fig waste leaves contain a variety of antioxidant components, which contributed to increase the value of fig waste leaves as antioxidants.\u003c/p\u003e","manuscriptTitle":"Valorization of Fig (Ficus carica Linn.) Waste Leaves: HPLC-QTOF-MS/MS-DPPH System For Online Screening And Identification of Antioxidant Compounds","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-01 22:04:40","doi":"10.21203/rs.3.rs-804140/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"80b82da5-5455-473d-b44f-25dab5da13cd","owner":[],"postedDate":"September 1st, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":6892487,"name":"Environmental Policy"},{"id":6892488,"name":"Chemical Engineering"}],"tags":[],"updatedAt":"2021-11-22T02:56:03+00:00","versionOfRecord":{"articleIdentity":"rs-804140","link":"https://doi.org/10.3390/plants10112532","journal":{"identity":"plants","isVorOnly":true,"title":"Plants"},"publishedOn":"2021-11-21 02:56:03","publishedOnDateReadable":"November 21st, 2021"},"versionCreatedAt":"2021-09-01 22:04:40","video":"","vorDoi":"10.3390/plants10112532","vorDoiUrl":"https://doi.org/10.3390/plants10112532","workflowStages":[]},"version":"v1","identity":"rs-804140","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-804140","identity":"rs-804140","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}