Adjusting sowing date to enhance roselle performance and water productivity under water deficiency stress

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A. Ahmed, Alia Amer, S. M. Abolmaaty, Karam Elzopy, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6185764/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Climate change, especially water stress, poses a threat to food production and increases the occurrence of famines worldwide. Adjusting sowing dates to enhance irrigation water productivity is among the adaptation strategies to mitigate the effects of water deficiency stress on crop yields. In this context, a field experiment was conducted during 2021 and 2022 seasons at the AL-Busili Experimental Farm of the Central Laboratory for Agricultural Climate, Agricultural Research Center in Egypt, to assess the effects of sowing dates (T1: May 19, T2: June 19, and T3: July 19) and irrigation rates (I1: 100%, I2: 75%, and I3: 50% of potential crop evapotranspiration “ETc”) on the performance and water productivity of roselle ( Hibiscus sabdariffa L.). The treatments were arranged in a split-plot design with three replications. The results indicated that regular irrigation (I1 at 100% ETc) under the mid-sowing date T2 (June 19) significantly (p ≤ 0.05) increased plant height, branch number, fruit number per plant, and the dry weight of sepals per plant. Adopting I2 or I3 on June 19 enhanced anthocyanin content (AC%). Notably, the late sowing date on 19th July, coupled with the severe water stress (I3, 50% ETc), yielded the uppermost water productivity (1.917 and 1.922 kg/m 3 ). Based on these findings, it could be concluded that the late sowing date can be a viable management strategy in Egypt with limited water availability in terms of water productivity of harvested roselle fruits. Anthocyanin Hibiscus sabdariffa planting dates productivity water saving Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Roselle ( Hibiscus sabdariffa L. ) is an annual summer plant from the family Malvaceae, commonly referred to as "Karkade" in most Arab countries, including Egypt [ 1 ]. Egypt is considered the country where roselle originated [ 2 ]. It is one of the herbal drugs; it is rich in vitamin C, organic acids (tartaric, citric, malic, and oxalic acids), and two types of anthocyanin, namely gossypetin (cyanidin) and hibiscin (delphinidin) [ 3 ]. Numerous environmental agronomic parameters impact roselle plant growth, yield, and quality [ 4 ]. The biggest challenge to obtaining good agricultural production globally is drought stress. Moreover, increasing crop yields and conserving irrigation water are two connected and significant worldwide challenges. A few efficient methods for using scarce water resources are choosing the right planting date and managing irrigation [ 5 ]. Agronomic measures like sowing timing enhance high yield by promoting plant development and growth, improving land economics, and ensuring the plant's vulnerable growth stage aligns with environmental conditions [ 6 ]. Roselle is a short-day plant that needs a photoperiod of 12 to 12.5 hours to bloom. Long days during the wrong stage of development lead to yield loss [ 7 ]. The sown roselle’s relative earliness is caused by photosensitivity and temperature. Such plants might bloom early under conditions of short levels of sunlight and may not bloom when the sunlight interval exceeds 11 hours [ 8 ]. H. sabdariffa L. plants, which were sown on 15th April, had significant increases in all growth characteristics [ 9 ]. Hibiscus planting time substantially impacts the wet weight of the bush, the wet/dry weights of the boll, 1000 seed weight, total performance, and the harvested seed. The periods of planting on 9th March and 30th April caused a decrease in the weight of the bush and bolls [ 10 ]. The roselle planted on 15th April improved and yielded more leaves and branches, taller plants, and heavier leaf DW per plant compared to the 1st May, 15th May, and 1st June, respectively. In contrast, the earliest day of sowing (15th April) demonstrated greater values of roselle yield components with substantial variations compared to other dates [ 11 ]. Early dates of planting yielded the greatest number of branches, plant heights, dry and fresh weights of plants, seeds, and sepals, increased total carbohydrates percent, nutrient contents, anthocyanin, and acidity in sepals, as well as fixed oil in seeds [ 12 ]. The planting date shift from mid-May to mid-July resulted in a 60-percent drop in flower yield and a 58-percent decrease in the yield of calyxes [ 7 ]. On the other hand, water stress, a widespread environmental issue, negatively impacts crop yield, quality, and biomass production [ 13 ]. Plants respond with strategies like essential and auxiliary reactions to cope with temporary stress, but prolonged stress can negatively impact growth and yield [ 14 – 16 ]. Furthermore, saving irrigation water and improving crop yields are two related and important global issues [ 6 ]. In this concern, it has been stated that extending the period between drought and irrigation conditions led to a reduction in roselle components and yield but an increase in active calyces, including total phenols and vitamin C [ 17 ]. Irrigation periods affect plant growth as stem diameters and plant height as well as carbohydrate production and photosynthesis. Furthermore, increased growth levels contributed to making use of growth factors such as nutrients, water, and light, thereby increasing roselle growth. Moreover, Rah Khosravani et al.[ 18 ] and Seghatoleslami et al.[ 19 ] illustrated that irrigation water rates don't significantly affect roselle plant growth but affect chlorophyll content in leaves. In addition, sowing dates affect calyx water use efficacy, seed oil content, antioxidant activity, calyx yield, and biological yield. In contrast, the interaction between irrigation periods and sowing date treatments did not significantly affect any trait [ 6 ]. El-Dissoky et al.[ 20 ] found that the increase of calyx yield for roselle is affected by irrigation frequency and mild drought stress. The results of Silakhoor et al.[ 6 ] highlighted that water stress has decreased the number of flowers and calyx since the flowering stage entails multiple processes prone to stress conditions. Additionally, roselle’s total anthocyanin content was significantly affected under mild and severe drought stress [ 6 ]. Therefore, the objectives of the current study were to determine the impact of different sowing dates on roselle performance and water productivity under water-deficiency stress. Materials and methods Experimental site Through the two summer seasons of 2021 and 2022, an experimental study was established in a split-plot design with three replicates, the sowing dates (T1; May 19, T2; June 19, and T3; July 19) as main plots and irrigation rates (I1; 100%, I2; 75%, and I3; 50% of crop evapotranspiration “ETc”) as sub-plots. The experiment was conducted at the AL-Busili Experimental Farm of the Central Laboratory for Agricultural Climate, Agricultural Research Center, Rashid City, Beheira Governorate, Egypt, 31°27'15" N, 30°23'23” E. The soil’s physical and chemical analysis (Table 1 ) was carried out by taking a sample of the soil at a 0–30 cm depth before planting, according to Cottenie et al. [ 21 ] and Kult et al. [ 22 ]. Table 1 Soil mechanical and chemical analysis of the experimental site Soil texture Sandy loam Clay (%) Silt (%) Sand (%) Organic matter (%) CaCO 3 (%) Field capacity (%) Wilting point (%) Bulk density gcm -3 6.48 10.00 83.52 0.76 3.26 16.8 7.7 1.2 Available nutrients (mg/kg soil) Soluble Cations (meq/l) Soluble Anions (meg/l) pH EC (dS/m) N P K Ca 2+ Mg 2+ Na + K + Cl - HCO3 - SO4 2- 30.86 5.20 200 3.35 5.0 10.09 0.86 7.2 2.4 9.7 7.78 1.93 Meteorological data The daily meteorological values during the experimental period were gathered from the CLAC automated weather station located at the experimental site, as depicted in Fig. 1 . The reference evapotranspiration (ET o , mm/day) was determined using the method of Penman-Monteith (PM) [ 23 ]. Field experiments Inland preparation, the soil was well plowed, where compost as organic fertilizers at a rate of 20 m 3 fed -1 and calcium super phosphate (15.5% P 2 O 5 ) at 300 kg/fed (1feddan ≈ 0.42 hectare) were added. Roselle seeds ( H. sabdariffa L. cv. Sabahia 17 dark) were provided by the Medicinal and Aromatic Plants Research Department, Horticulture Research Institute, Agricultural Research Center, Giza, Egypt. The experiment comprised nine treatments, and each experimental plot was 2×1.0 m (3 m 2 ) and had two rows, 50 cm apart and 50 cm between the plant holes. Then, the treatments were replicated three times in a total of 27 plots, and each replicate encompassed ten plants. Seeds were sown on May 19, T 1 (early), June 19, T 2 (mid), and July 19, T 3 (late) in both seasons. Three weeks after the seeds were sown, plants were thinned to one plant/hole. Beginning in the third week following seeding, the plants received the recommended dosage of nitrogen, phosphorus, and potassium fertilizers, which were added at a rate of 200 kg/fed as ammonium sulfate (20.5% N), 150 kg/fed as potassium sulfate (48% K 2 O), and 25 L/ fed as phosphoric acid (85% H 3 PO 4 ) through fertigation. A drip irrigation system was used to apply irrigation water stress treatments (I1; 100% ETc “regular”, I2; 75% ETc “mild”, and I3; 50% ETc “severe”) every three days. The conveying pipeline system consists of a 63 mm PVC main line connected to a 50.8 mm PVC sub-main line. It was a surface drip system with a 50-hp irrigation pump coupled to sand and screen filters. The sub-main line is connected to the 16 mm-diameter drip lateral lines. With built-in emitters with a 2 L/h discharge rate placed 0.3 m apart on the lateral lines, each 20 m long lateral line is separated 0.7 m apart on the sub-main. Small amounts of soluble water fertilizers were injected via a tank attached to the drip irrigation system. Other agricultural practices, including the use of insecticides, hoeing, and weeding, were all promptly applied to improve crop development according to the Ministry of Agriculture and Land Reclamation recommendations. Crop irrigation water calculation Levels of irrigation were estimated, while manual valves were used to regulate irrigation for each experimental plot. Food and Agricultural Organization (FAO) Penman-Monteith (PM) procedure, the FAO 56 method was utilized to estimate the total quantity of irrigation water [ 23 ]. The first step entailed the calculation of reference evapotranspiration (ETo) as follows: $$\:{\varvec{E}\varvec{T}}_{\varvec{o}}=\frac{0.408\varDelta\:\left({\varvec{R}}_{\varvec{n}}-\varvec{G}\right)+\varvec{\gamma\:}\frac{900}{\varvec{T}+273}{\varvec{u}}_{2}({\varvec{e}}_{\varvec{s}}-{\varvec{e}}_{\varvec{a}})}{\varDelta\:+\varvec{\gamma\:}(1+0.34{\varvec{u}}_{2})}\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)$$ where: ET o = Daily reference evapotranspiration [mm d -1 ]. R n =Net radiation at the crop surface (MJ m -2 d -1 ). G = Soil heat flux density (MJ m -2 d -1 ), T = Mean daily air temperature at 2 m height (°C), U 2 = Wind speed at 2 m height (m s -1 ), e s = Saturation vapor pressure (kPa), e a = Actual vapor pressure (kPa), Δ = The slope of the vapor pressure curve (kPa °C -1 ), γ = The psychometric constant (kPa °C -1 ). The second step was to determine crop evapotranspiration (ETc) values according to Doorenbos and Pruitt[ 24 ] ETc = ET o × Kc mm.d -1 (2) where: ET o = Evapotranspiration rate from an excessive surface of green cover of uniform height (8 to 15 cm), entirely shading the ground, actively growing, with no water shortage, Kc = Crop coefficient, crop coefficient values were used (between 0.4 to 1.2). Leaching requirements were determined according to (Allen et al. [ 23 ] as follows. $$\:\varvec{L}\varvec{R}=\left(\frac{\varvec{E}\varvec{C}\varvec{i}\varvec{w}}{\varvec{E}\varvec{C}\varvec{d}}\right)\times\:100\:\:\:\varvec{\%}\:\:\:\:\:\:\:\:\:\:\:\:\:\left(3\right)$$ where: LR = leaching requirements, ECiw = Electrical conductivity of irrigation water (0.36 dS/m), ECd = Electrical conductivity of drainage water 1.7 dS/m – maize salinity threshold. Therefore, the LR of the current study was 21.17%. Water requirements (WR) were determined based on the following equation: $$\:\varvec{W}\varvec{R}=\varvec{E}\varvec{T}\varvec{c}\left(1+\frac{\varvec{L}\varvec{R}}{100}\right)\:\:\:\:\:\:\:\varvec{m}\varvec{m}.{\varvec{d}}^{-1}\:\:\:\:\:\:\:\:\:\:\:\:\left(4\right)$$ The irrigation requirement (IR) was determined as follows: $$\:\varvec{I}\varvec{R}=\frac{\varvec{W}\varvec{R}\times\:4200\times\:100}{1000\times\:\varvec{E}\varvec{a}}\:\:\:\:{\varvec{m}}^{3}.{\varvec{f}\varvec{e}\varvec{d}}^{-1}.{\varvec{d}}^{-1}\:\:\:\:\:\:\:\:\:\:\left(5\right)$$ where: Ea = The irrigation system's efficiency (assumed 85% of the total applied water). The water flow meter for all treatments determined the total quantity of irrigation water. depicts the seasonal irrigation quantities for roselle under varying irrigation treatments at the AL-Busili site for the three sowing dates during the two seasons. The plants were irrigated with 2 l/h capacity drippers utilizing the fertigation technique. Irrigation water productivity (WP) The irrigation water productivity (kg/m 3 ) of roselle was calculated according to the equation accessible by Zhang [ 25 ] as follows: $$\:{WP}_{I}=\frac{Crop\:Yeild\:(kg\:.{fed}^{-1})}{Applied\:Water\:({m}^{3}.{fed}^{-1})}\:\:\:\:\:\:\:\:\:\left(6\right)$$ Recorded Data At the end of each season, roselle fruits were harvested on the 15th of November, 15th of December, and 15th of January for each sowing date. Ten plants were randomly taken from each plot, and plant height (cm), no. of branches/plant, no. of fruit/plant, the weight of the dry sepals (g/plant), dry weight of plant (g), stem diameter (cm), roots dry weight (g/plant), seed yield/plant (g), and fresh fruit yield (ton/fed) were determined. The available macronutrient percentage, including N, K, and P, was assessed in the roselle dry herb based on the methods defined by Nessler's method [ 26 , 27 ]. Total chlorophyll was determined in leaves using SPAD-502, Konica, Minolta. Statistical analysis The general linear model (GLM) algorithm of the SAS 9.2 program for Windows was used to conduct an analysis of variance (ANOVA) on all analyzed parameters. The data were assessed statistically utilizing Fisher's least significant difference (LSD) test at a (P \(\:\le\:\) 0.05). Boxplots were developed to demonstrate the disparity between sowing date and irrigation rates, whereas Pearson correlation coefficients were utilized for assessing the correlation among traits. In the R project (version 3.4.5), the ggplot2 package was utilized for drawing a boxplot. Results Vegetative growth ANOVA for the impact of sowing date and irrigation treatments, as well as their interaction, are displayed in Table 2. During the 2021 and 2022 seasons, the results revealed that sowing date and irrigation treatments had a significant effect at 5% (P ≤ 0.05) on all studied parameters, including plant height, number of branches per plant, the number of fruits per plant, plant dry weight (g), root dry weight (g/plant), stem diameter (mm), sepals dry weight (g/plant), and seed yield (g/plant). A marked (P ≤ 0.05) correlation was detected between the sowing dates and the irrigation treatments, revealing an association with plant height, branch number/plant, plant dry weight, root dry weight, and stem diameter only in season two. Plant dry weight (g/plant) and root dry weight (g/plant) were significantly affected by the interaction between sowing date and irrigation rates in both seasons. However, plant height (cm), branch number/plant, and sepals dry weight (g/plant) were only affected in the 1st season. While the number of fruits/plants and stem diameter (mm) were only affected in the 2nd season. Moreover, as seen in (Fig. 2), the mean data of 2 seasons revealed that (T2) with (I1) had the highest value of plant height (PH, 253.17 cm), stem diameter (SD, 20.01), fruit number/plant (FN, 100.30), branch number/plant (BN, 25.74), plant dry weight (PDW, 2210.89 g/plant), root dry weight (RDW, 0.74 g/plant), seed yield (SYP, 32.51 g/plant), and sepals (SDWP, 18.32 g/plant). Whereas adopting a late sowing date (T3) with severe water stress (I3; 50% ETc) yielded the lowest values for the same parameters. Table 2 Analysis of variance results for different traits of roselle under varying sowing dates and irrigation rates ns, **, *** indicate non-significance, significance at 5% (P 0.05), R 2 coefficient of determination; RMSE, root mean square error; CV, coefficient of variation. Source of variance Plant height (cm) Branch Number / plant Number of fruits /plant Plant dry weight (g/ plant) 2021 2022 2021 2022 2021 2022 2021 2022 Sowing date (T) *** ** *** *** * *** *** *** Irrigation rates (I) *** *** *** *** ** *** *** *** T X I ** ns ** ns ns *** *** *** CV 2.180 3.088 2.745 3.634 8.997 3.503 1.783 1.67 R 2 0.987 0.960 0.976 0.954 0.841 0.956 0.990 0.986 RMSE 4.721 6.627 0.565 0.836 7.452 3.058 33.408 31.28 Stem diameter (mm) Roots dry weight (g/ plant) Sepals dry weight (g/ plant) Seed yield (g/ plant) Sowing date (T) ns ** *** *** *** *** * ns Irrigation rates (I) ns *** *** *** *** *** *** ** T X I ns * ** *** *** ns ns ns CV 9.819 2.776 2.364 1.77 1.79 3.60 2.80 6.58 R 2 0.709 0.967 0.984 0.984 0.984 0.963 0.955 0.791 RMSE 1.770 0.515 0.015 0.011 0.277 0.562 0.811 1.929 ns, **, *** indicate non-significance, significance at 5% (P 0.05), R 2 coefficient of determination; RMSE, root mean square error; CV, coefficient of variation. Fruits yield (FW, ton/fed) In the first season, under the well-watered condition (I1;100% ETc), an increase from 3.62 ton/fed to 3.73 ton/fed in roselle fruit yield was registered with delayed the sowing date from 19th May to 19th June by 3.08% while it significantly decreased to 2.83 ton/fed by 21.84% when the sowing date was delayed to July 19th (Fig. 3). Furthermore, under the sever water stress (I3;50% ETc), the delayed sowing date from 19th May to 19th June, the roselle fresh yield per ton was increased by 3.97%, where it decreased to 17.95% when delayed to 19th July. It would be noticed that the second season reported the same trend of the first season (Fig. 3). Anthocyanin content A non-significant difference in anthocyanin content was observed based on sowing dates. In contrast, the irrigation rates of 75% ETc and 50% ETc were equally significant, as shown in Table 3, which indicated that maximum values were 44.87 mg/g d.w. in the first season on May 19th, and 49.015 mg/g d.w. in the second season on June 19th. The relative increases in anthocyanin content were 5.80% and 5.60% for the first and second seasons, respectively, when comparing the May sowing date to the July sowing date. Additionally, the relative increases were 2.86% and 9.02% in the first and second seasons, respectively, for the June sowing date compared to the July sowing date. Furthermore, irrigation showed a significant increase in anthocyanin content (mg/g d.w.) in both seasons. The maximum anthocyanin content was 45.815 mg/g d.w. in the first season and 49.68 mg/g d.w. in the second season, influenced by the irrigation level at 75% ETc compared to other levels. When comparing irrigation at 75% ETc to 100% ETc in the first and second seasons, the relative increases were 12.53% and 10.98%. Conversely, the relative increases for irrigation at 50% ETc in the first and second seasons compared to irrigation at 100% ETc were 14.42% and 14.34%, respectively. The interaction between irrigation rates and sowing dates resulted in substantial variations in anthocyanin contents. The maximum anthocyanin content of 47.59 mg/g F.W. was observed with the dates (T2) and (I2) during the first growing season. Additionally, the results indicated that anthocyanin contents could be enhanced by coordinating (T2) with (I2) during the second growing season (Table 3). Table 3 Anthocyanin content (mg / g d.w.) in roselle sepals as affected by sowing date and irrigation rates Treatments Sowing date (T1) Irrigation rates (I) Season 2021 Season 2022 T1 T2 T3 Mean T1 T2 T3 Mean I1 45.04 42.02 33.06 40.04 b 48.40 45.63 36.60 43.54 b I2 44.12 47.59 43.45 45.058 a 48.99 52.69 46.96 49.55 a I3 45.45 45.40 46.58 45.814 a 45.03 48.72 51.32 48.35 a Mean 44.87 a 43.63 a 42.42 a 47.48 a 49.02 a 44.96 a LSD 0.05 T = 4.43 I = 1.82 T = 4.94 I = 3.53 T x I = 3.14 *** T x I = 6.11 ** Different lowercase letters indicate statistically significant differences between treatments (p \(\:\le\:\) 0.05), as revealed by the least significant difference (Fisher’s LSD) test. Where. T1= 19th May, T2= 19th June, T3=19th July, I 1 = 100% ETc, I 2 = 75% ETc, I 3 = 50% ETc. Macronutrient content Concerning the interactive impact of the sowing dates and various irrigation rates on the available macronutrient content in leaves of roselle, the mean data of both seasons in Fig. (4) reflected that the irrigation level was at 100% ETc under the sowing date on the 19th of May (T1) and 19th of June (T2) and demonstrated the superiority of the N%, P%, and K% in leaves as compared with other treatments. Moreover, as shown in Fig. (4), no significant differences were registered in the N%, P%, and K% between I1 and I2 during T2 of sowing date. Total chlorophyll The mean effects of sowing date and irrigation rates on total chlorophyll (mg/g f.w.) are presented in Fig. 5. Generally, there was a non-significant difference in the total chlorophyll content at the I1 (100% ETc) and I2 (75% ETc) under the dates of T1 and T3. On the other hand, the results presented that the adoption of sowing date (T2) directed to an increase in total chlorophyll content (0.85 mg/g f.w.) under I1 treatment, although this increase was significantly equal to the application of T1 + I1 (0.87 mg/g f.w.) and T3 + I1. (0.83 mg/g f.w.). Correlation between studied traits The Pearson’s correlation coefficients for different attributes examined under varying sowing dates and irrigation rates are presented in Fig. 6. Data revealed that the association between root dry weight and plant dry weight was substantially positive. The plant height (PH) revealed a strong positive correlation with plant dry weight (PDW), root dry weight (RDW), sepals dry weight per plant (SDWP), and nitrogen content (N). Likewise, branch number/plant (BN) expressed a positive correlation with PDW, RDW, stem diameter (SD), seed yield per plant (SYP), and SDWP. Also, sepals’ dry weight per plant had a positive correlation with nitrogen content. Nonetheless, anthocyanin (Anc) or chlorophyll (Chloro) content exhibited a substantially negative association with PH, FN, BN, PDW, RDW, SD, SYP, and SDWP. Determining the correlation between yield traits is necessary as it directly contributes to enhancing yield traits. The direct selection of these attributes might enhance the selection efficiency of yield. The correlation between irrigation rates and sowing date The hierarchical clustering effectively identified the link between combinations of sowing dates and irrigation rates (12 combinations) based on their yield and growth performance parameters (Fig. 7). Two main clusters were characterized concerning the association between sowing dates and irrigation rates. The combination treatments of A (T2 + I1), B (T1 + I1), and C (T2 + I2) generated the first cluster. B and C treatments were the closest sub-clusters. Treatment A yielded the greatest values for most traits in this group. For treatment B, most traits, except SYP, FN, P, Chloro, and Anc, demonstrated high performance. Conversely, treatment C demonstrated the highest positive impacts on PH, BN, SD, SYP, and FN, followed by SDWP, RDW, N, and K, whereas chloro content was negatively impacted by this treatment. The second cluster consisted of treatments D (T3 + I3), E (T2 + I3), F (T3 + I1), G (T3 + I2), H (T1 + I2), and I (T1 + I3), with treatments F and G or H and I being the closest sub-clusters. The combinations of sowing dates and irrigation rates in the second cluster demonstrated an opposite pattern to the first cluster combinations. All examined traits were adversely affected except for the anthocyanin content, indicating diminished overall performance, particularly for the control treatment, which had the lowest value for all assessed parameters. Principal component analysis PCA was carried out to determine the association between the examined treatments and traits (Fig. 8). The two PCs are responsible for 91.85% of the variance. F1 seemed to be linked to the T1I2, T2I1, T2I2, and T1I1 on the positive side to T3I1, T3I2, T1I3, T2I3, and T3I3 on the negative side, which illustrates 81.05% of the variability, whereas F2 contributed to 10.8% of the variation (Fig. 8). The angles between trait vectors demonstrated the relationship between the investigated characteristics. Vectors with large angles (about 180 degrees) exhibit a negative correlation, while contiguous vectors exhibit a significant positive correlation. A high positive correlation was found between anthocyanin and chlorophyll content and all of its characteristics. Due to the simplicity of their measurement, the closeness of FN, SYP, and SD to anthocyanin content indicates their significance in indirect selection (Fig. 8). Applied irrigation water The applied irrigation water varied among different sowing dates and irrigation rates (Fig. 9). The applied irrigation water values for roselle fluctuated between 1259 and 4657.32 m 3 /fed in 2021 and 1405.86 to 4779.19 m 3 /fed in 2022. The early-sown plants at T1 recorded the highest irrigation demand as the crop coefficient reached its maximum values during July and August, when Tmin, Tmax, and ETo values were maximum (Fig. 1). While delaying sowing dates at T3 treatments registered the lowest applied irrigation water when periods of peak climatic factors coincided with low crop coefficient values. As a result of changes in the meteorological components, the results also revealed that the applied water had higher values in the second season than in the first season. Irrigation water productivity (WP I , kg/m 3 ) In both seasons, the maximum irrigation water productivity for fresh sepals (1.917 and 1.922 kg/m 3 , respectively) was obtained with severe water stress (I3; 50% ETc) at the late sowing date (T3; 19th July). It was higher by 32.22% and 9.66% (1st season) 36.50% and 15.60% (2nd season) than the first (early) and second (mild sowing dates, respectively, under the same condition of irrigation (50% ETc).On the other hand, the lowest values of irrigation water productivity (0.776 and 0.738 kg/m 3 ) were observed with the well-watered treatment (I1; 100% ETc) at the early sowing date (T1; 19th May) in both seasons, respectively. In this case, severe water stress was found to be the optimal irrigation regime in terms of the WP I based on the yield of roselle sepals and the quantity of irrigation (Fig. 10). It is reasonably known that the WP I increases when the applied water amount decreases; nonetheless, the crop yield could be reduced. Examining all the efficiency results of irrigation with the crop yields, it was found that WP I of 1.917 and 1.922 kg/m 3 matched the yield of 2.48 and 2.70 ton/fed. Discussion The current experiment was conducted to determine the optimal sowing date and irrigation rates for improved roselle productivity and water use efficiency. This result may be due to the effect of the day and night temperature, daylight intensity, and photoperiods. In addition, these results are probably because the sowing dates in June led to the high growing period and irrigation rates received during the growing periods. An adequate supply of moisture would eventually boost the growth rate as well as timely maturity, hence a higher productivity of the roselle. These results are in agreement with El-Bakhshwan and El-Kouny [ 28 ], who indicated that the plant height (cm), number of branches/plant, and number of fruit decreased in the roselle sown in July compared with the roselle sown in June. El-Bakhshwan and El-Kouny [ 28 ] found that all parameters of hibiscus growth were significantly increased as affected by irrigation water level (1000 m 3 ) and the sowing period in June. Moreover, our findings align with Barzgaran [ 29 ] results on H. Sabdariffa, who confirmed that planting time has a greater influence on the performance of other agronomic features. The outcome indicates that delaying the planting of this crop would be optimal (19th June). The date of planting on 19th June corresponded to the greatest values of the examined parameters. Khattak et al. [ 12 ] discovered the same pattern in roselle plants. It was observed that the maximum increase in anthocyanin content was observed when the sowing date 19 of June was adopted with the implementation of I 2 (75%ETc) and I 3 (50% ETc). Drought stress enhanced the overall anthocyanin content of roselle to minimize excess light availability and provide beneficial protection to leaves without significantly affecting photosynthetic efficiency, as reported in numerous articles [ 30 , 31 ]. This demonstrates a way to control light absorption and lessen damage caused by photooxidation. According to reports, anthocyanin can prevent extra high-energy quanta from damaging chloroplasts and scavenging reactive oxygen species, hence reducing photo-oxidative damage in leaves (He et al., 2020). Moreover, the impact that drought stress has on TAC is consistent with the findings of[ 32 , 33 ] on roselle, which reported that enhanced secondary metabolism has been linked to improvements in the plants' qualitative traits, like anthocyanins, under simultaneous drought stress. These results are in agreement with [ 6 , 9 , 34 ]. On the other hand, the results showed that the accumulation of N, P, K, and total chlorophyll in roselle leaves reached its highest values when T2 (19 June) was combined with I 1 (100% ETc) and I 2 (75% ETc), while the lowest values were detected when roselle seeds were sown on 19th of July with I 3 (50% ETc). The authors postulate that extreme heat and evaporation conditions begin to impair plant growth on July 19. Plants respond to these conditions by increasing their uptake and storage of K as a defensive mechanism. K contains several qualities that can enhance temperature and plant water status beneath water. The results are in line with [ 6 , 12 , 35 ] on Hibiscus sabdariffa , and [ 36 – 38 ] on Foeniculum vulgare. Conclusions Based on the current study, planting time and irrigation rates significantly impacted the roselle crop productivity. Delayed planting dates to 19 June under irrigation rates of 100% ETc (I 1 ) increased plant height, the number of branches per plant, the number of fruits per plant, plant dry weight, No. of fruit/plant, number of branches per plant, stem diameter, sepals yield (d.w/plant), seed yield/plant, root dry weight per plant of roselle, and anthocyanin content. The highest irrigation water productivity was obtained with delayed planting dates to 19 July under 50% ETc irrigation level (I 3 ). In conclusion, the late sowing date can be a viable management strategy in Egypt with limited water availability in terms of water productivity of harvested roselle fruits. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and material All data generated or analyzed during this study are included in this published article. Competing Interest All the authors declared that they have no competing interests. Clinical trial number Not applicable Funding This research received no external funding. Author contributions Conceptualization and design of the work, M.A.A.A. and E.A.S; methodology, M. A. A. A., A.A. and E.A.S; software, K.A.E., E.A.A. and M.A.A.A; formal analysis, A.A., K.A.E., M.A.A.A., S.M.A. and E.A.S; investigation, M.A.A.A., E.A.S.; resources, M.A.A.A., E.A.S.; writing—original draft preparation, M. A.A.A., A.A. and E.A.S; writing—review and editing, E.A.A., K.A.E., and S.M.A.. All authors provided critical feedback and helped shape the research, analysis, and manuscript. Also, all authors discussed the results and contributed to the final manuscript. All authors read and approved the final manuscript. References Mohamed R, Fernandez J, Pineda M, Aguilar M. Roselle (Hibiscus sabdariffa) seed oil is a rich source of γ‐tocopherol. J Food Sci. 2007;72:S207–11. Ismail A, Ikram EHK, Nazri HSM. Roselle (Hibiscus sabdariffa L.) seeds nutritional composition protein quality and health benefits. Food. 2008;2:1–16. Hassan FAS. Response of Hibiscus sabdariffa L. plant to some biofertilization treatments. 2009. Xu H, Wang X, Zhao C, Zhang X. Responses of ecosystem water use efficiency to meteorological drought under different biomes and drought magnitudes in northern China. Agric For Meteorol. 2019;278:107660. Keshavarz Mirzamohammadi H, Modarres-Sanavy SAM, Sefidkon F, Mokhtassi-Bidgoli A, Mirjalili MH. Irrigation and fertilizer treatments affecting rosmarinic acid accumulation, total phenolic content, antioxidant potential and correlation between them in peppermint (Mentha piperita L.). Irrig Sci. 2021;39:671–83. Zand-Silakhoor A, Madani H, Sharifabad HH, Mahmoudi M, Nourmohammadi G. Influence of different irrigation regimes and planting times on the quality and quantity of calyx, seed oil content and water use efficiency of roselle (Hibiscus sabdariffa L.). Grasas y Aceites. 2022;73:e472–e472. Ghayour M, Taherian M, Baghban S, Khavari S. Effect of early planting dates and different treatments of seed priming on germination and seedling establishment of roselle (Hibiscus sabdariffa). Iranian Journal of Seed Research. 2020;6:95–109. Butler TJ, Evers GW, Hussey MA, Ringer LJ. Flowering in crimson clover as affected by planting date. Crop Sci. 2002;42:242–7. Attia EM, Khater RM. Effect of different planting dates and organic fertilizers treatments on growth and yield of Hibiscus sabdariffa L. plants. Egyptian Journal of Desert Research. 2015;65:153–70. Behzadi M, Emamipour Y, Koduri MR, Sardoei AS. The effect of planting time on performance of Roselle (Hibiscus sabdariffa) to use in urban green space. Journal of Mddle east Applied Science and Technology. 2014;24:156–9. Ali HKM, Awad AE, Abdelkader MA. Improving growth and yield of Roselle (Hibiscus sabdariffa L.) plants by using tyrosine and glutamine acids under different sowing dates. Zagazig Journal of Agricultural Research. 2020;47:1165–74. Khattak AM, Sajid M, Sarwar HZ, Rab A, Ahmad M, Khan MA. Effect of Sowing Time and Plant Density on the Growth and Production of Roselle (Hibiscus sabdariffa). Int J Agric Biol. 2016;18:1219–24. Laskari M, Menexes G, Kalfas I, Gatzolis I, Dordas C. Water stress effects on the morphological, physiological characteristics of maize (Zea mays L.), and on environmental cost. Agronomy. 2022;12:2386. Seleiman MF, Al-Suhaibani N, Ali N, Akmal M, Alotaibi M, Refay Y, et al. Drought stress impacts on plants and different approaches to alleviate its adverse effects. Plants. 2021;10:259. Haggag Wafaa M, Tawfik MM, Abouziena HF, Abd El Wahed MSA, Ali RR. Erhöhung der Weizenproduktion unter aridem Klimastress durch Bio-Elicitoren. Gesunde Pflanzen. 2017;69:149–58. He M, He C-Q, Ding N-Z. Abiotic stresses: general defenses of land plants and chances for engineering multistress tolerance. Front Plant Sci. 2018;9:1771. Hewidy M, Elsayed MLM, Sultan E. Water schedule of roselle (Hibiscus sabdariffa L.) under organic fertilization. Egyptian journal of Horticulture. 2018;45:53–64. Rah Khosravani AT, Mansourifar C, Modarres Sanavy SAM, Asilan KS, Keshavarz H. Effects of sowing date on physiological characteristics, yield and yield components for different maize (Zea mays L.) hybrids. Not Sci Biol. 2017;9:143–7. Seghatoleslami MJ, Mousavi SG, Barzgaran T. Effect of irrigation and planting date on morpho-physiological traits and yield of Roselle (Hibiscus sabdariffa). 2013. El-Dissoky R, Attia AM, Awad AM. Managing Roselle Plant (Hibiscus sabdariffa L.) Requirements of Fertilizers and Irrigation Grown under Upper Egypt Conditions. Journal of Soil Sciences and Agricultural Engineering. 2020;11:693–700. Cottenie A, Verloo M, Kiekens L, Velghe G, Camerlynck R. Chemical analysis of plants and soils. Lab Agroch State Univ Gent, Belgium. 1982;63:44–5. Klute A, Page AL. Methods of soil analysis. American Society of Agronomy. Agronomy Monograph. 1986;9. Allen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome. 1998;300:D05109. Doorenbos J, Pruitt WO. Crop water requirements. FAO irrigation and drainage paper 24. Land and Water Development Division, FAO, Rome. 1977;144. Zhang C-H. Compound decision theory and empirical Bayes methods. Ann Stat. 2003;:379–90. Chapman HD, Pratt PE, Parker F. Methods of analysis for soils, plants and waters. Univ. of Calif. Div Agric Sci Priced Pub. 1978;4034:50–169. Jackson ML. Soil Chemical Analysis,(2nd Indian Print) Prentice-Hall of India Pvt. Ltd New Delhi. 1973;38:336. El-Bakhshwan MH, El-Kouny H. Impact of irrigation intervals, planting time and density on hibiscus yield. Misr Journal of Agricultural Engineering. 2018;35:485–500. Barzgaran T. Effects of irrigation and planting date on agronomic traits and yield of roselle. Unpublished M Sc thesis, Dept of Agriculture, Islamic Azad Univ Birjand Branch, Iran 111pp. 2011. Cirillo V, D’Amelia V, Esposito M, Amitrano C, Carillo P, Carputo D, et al. Anthocyanins are key regulators of drought stress tolerance in tobacco. Biology (Basel). 2021;10:139. An J, Zhang X, Bi S, You C, Wang X, Hao Y. The ERF transcription factor MdERF38 promotes drought stress‐induced anthocyanin biosynthesis in apple. The Plant Journal. 2020;101:573–89. Fallahi H-R, Ghorbany M, Aghhavani-Shajari M, Samadzadeh A, Asadian AH. Qualitative response of roselle to planting methods, humic acid application, mycorrhizal inoculation and irrigation management. J Crop Improv. 2017;31:192–208. Hinojosa-Gómez J, San Martín-Hernández C, Heredia JB, León-Félix J, Osuna-Enciso T, Muy-Rangel MD. Anthocyanin induction by drought stress in the calyx of roselle cultivars. Molecules. 2020;25:1555. Khalil SE, Yousef RMM. Study the effect of irrigation water regime and fertilizers on growth, yield and some fruit quality of Hibiscus sabdariffa L. Int J Adv Res (Indore). 2014;2:738–50. Futuless KN, Kwaga YM, Clement T, ANEJA KR, JOSHI R, SHARMA C, et al. Effect of sowing date on calyx yield and yield components of roselle (Hibiscus Sabdariffa L.) in Nothern Guinea Savanna. New York Science Journal. 2010;3:1–4. Sanjeet Bagari SB, Singh PP, Naruka IS, Rathore SS, Shaktawat RPS. Effect of date of sowing and nitrogen levels on growth, yield and quality of fennel. 2010. El-Khayat ASM, Gouda HAH. Effect of sowing date and potassium fertilization on growth, yield and chemical composition of Foeniculum vulgare Mill plants. 2005. El-Wahab MAA, Mehasen HRA. Effect of locations and sowing date on (Foeniculum vulgare Mill.) Indian fennel type under Upper Egypt conditions. 2009 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Apr, 2026 Reviews received at journal 06 Apr, 2026 Reviewers agreed at journal 03 Apr, 2026 Reviewers agreed at journal 16 Mar, 2026 Reviewers agreed at journal 20 Apr, 2025 Reviews received at journal 11 Apr, 2025 Reviewers agreed at journal 06 Apr, 2025 Reviewers invited by journal 06 Apr, 2025 Editor invited by journal 12 Mar, 2025 Editor assigned by journal 12 Mar, 2025 Submission checks completed at journal 12 Mar, 2025 First submitted to journal 08 Mar, 2025 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-6185764","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":428099591,"identity":"5cd200e7-5313-4fc3-b134-16cb0f00011f","order_by":0,"name":"Mohamed A. A. Ahmed","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"A. A.","lastName":"Ahmed","suffix":""},{"id":428099592,"identity":"cfb02e7e-04cf-4bf6-811c-0a3b35e96de3","order_by":1,"name":"Alia Amer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDACdsYGMM0P5fMQ1sIM1SLZQLwWKG1wgFh38TczN374mWOTb3z87MMPDH/sZBjY2y/g1SJxmLFZsndbmuW2M+nGEoxtyTwMPGcK8FtzmLFBgnfbYQOzA2lsDIwNB3gYJHIS8OqQB9ry8++2/wbG/c/YGBj+ALXIv8GvxeAwY5s077YDBgYSQFsY2EC2sB/Aq8UQqMVadluygcSNZ8wSiUC/sPHk4PeK3PH2xzffbrMz4O9PY/zw4Y+dPT/78Qf49aAAkCfYGHgMSNACAeyk2DIKRsEoGAUjAAAAQ5I/IGQEjjMAAAAASUVORK5CYII=","orcid":"","institution":"Agricultural Research Centre","correspondingAuthor":true,"prefix":"","firstName":"Alia","middleName":"","lastName":"Amer","suffix":""},{"id":428099598,"identity":"28212631-e171-4139-8bf3-d67a04216d9a","order_by":2,"name":"S. M. Abolmaaty","email":"","orcid":"","institution":"Agricultural Research Centre","correspondingAuthor":false,"prefix":"","firstName":"S.","middleName":"M.","lastName":"Abolmaaty","suffix":""},{"id":428099599,"identity":"19a63077-2a87-4941-9622-65cf4a893e9c","order_by":3,"name":"Karam Elzopy","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Karam","middleName":"","lastName":"Elzopy","suffix":""},{"id":428099600,"identity":"761b6cdd-6d7a-471e-9f0f-7ac4fb7b6fc8","order_by":4,"name":"Ekramy Atef","email":"","orcid":"","institution":"Alexandria University","correspondingAuthor":false,"prefix":"","firstName":"Ekramy","middleName":"","lastName":"Atef","suffix":""},{"id":428099601,"identity":"f565a4ca-ae1a-44ea-a7ab-d408ed8811f3","order_by":5,"name":"Engy Sultan","email":"","orcid":"","institution":"Agricultural Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Engy","middleName":"","lastName":"Sultan","suffix":""}],"badges":[],"createdAt":"2025-03-08 20:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6185764/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6185764/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78541012,"identity":"9df46dbb-d9fb-4c43-9a8c-eccde866824c","added_by":"auto","created_at":"2025-03-14 16:04:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":462474,"visible":true,"origin":"","legend":"\u003cp\u003eWeather data for the study area in 2021 and 2022, growing seasons\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/e9279c5e2b5227f44fa7b4f6.png"},{"id":78543168,"identity":"6d3b986a-99ba-49f7-be86-606182922eca","added_by":"auto","created_at":"2025-03-14 16:36:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":281619,"visible":true,"origin":"","legend":"\u003cp\u003eRoselle vegetative growth as affected by varying sowing dates (1T1:19\u003csup\u003eth\u003c/sup\u003e May, T2:19\u003csup\u003eth\u003c/sup\u003e June, and T3:19\u003csup\u003eth\u003c/sup\u003e July) and irrigation rates (I1:100% ETc; I2: 75% ETc, and I3: 50 % ETc). Plant height (PH); Stem diameter (SD), Number of fruits /plant (FN), Number of branches/ plant (BN), Plant dry weight (PDW), Roots dry weight (RDW), Seed yield/plant (SYP), sepals dry weight/plant (SDWP)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/71f04bb61ad3871caec1953f.png"},{"id":78541014,"identity":"e9a8d5ca-5868-4117-be70-90ba4ce9f62f","added_by":"auto","created_at":"2025-03-14 16:04:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":146509,"visible":true,"origin":"","legend":"\u003cp\u003eRoselle fruits yield (FW, ton/fed) as affected by varying sowing dates (1T1:19\u003csup\u003eth\u003c/sup\u003e May, T2:19\u003csup\u003eth\u003c/sup\u003e June, and T3:19\u003csup\u003eth\u003c/sup\u003e July) and irrigation rates (I1:100% ETc; I2: 75% ETc, and I3: 50 % ETc). Plant height (PH); Stem diameter (SD), Number of fruits /plant (FN), Number of branches/ plant (BN), Plant dry weight (PDW), Roots dry weight (RDW), Seed yield/plant (SYP), sepals dry weight/plant (SDWP)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/b5ae2e9581d85ca79765de12.png"},{"id":78541017,"identity":"523364af-5258-4e0f-9b6c-e35b82fe3d68","added_by":"auto","created_at":"2025-03-14 16:04:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":152078,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of sowing date and irrigation rates on available macronutrients content (%) in roselle leaves. Where: T1= 19\u003csup\u003eth\u003c/sup\u003e May, T2= 19\u003csup\u003eth\u003c/sup\u003e June, T3=19\u003csup\u003eth\u003c/sup\u003e July, I\u003csub\u003e1\u003c/sub\u003e= 100% ETc, I\u003csub\u003e2\u003c/sub\u003e= 75% ETc, I\u003csub\u003e3\u003c/sub\u003e= 50% ETc.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/30bcdb09ab9dfc56aa2dbdaa.png"},{"id":78542072,"identity":"a41a7dde-489c-4e48-b6fe-6d069575adcb","added_by":"auto","created_at":"2025-03-14 16:12:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":142244,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of sowing date and irrigation rates on total chlorophyll (mg/g f.w.) in roselle leaves. Where: T1= 19\u003csup\u003eth\u003c/sup\u003e May, T2= 19\u003csup\u003eth\u003c/sup\u003e June, T3=19\u003csup\u003eth\u003c/sup\u003e July, I\u003csub\u003e1\u003c/sub\u003e= 100% ETc, I\u003csub\u003e2\u003c/sub\u003e= 75% ETc, I\u003csub\u003e3\u003c/sub\u003e= 50% ETc.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/3ee7ac7cea94b3543d5181c3.png"},{"id":78541015,"identity":"343e4b8d-6450-4a1f-bb79-cbcfb4502b3e","added_by":"auto","created_at":"2025-03-14 16:04:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":248406,"visible":true,"origin":"","legend":"\u003cp\u003ePearson’s correlation coefficients for seven attributes examined under varying sowing dates and irrigation rates (Combined analysis of two successive seasons of 2021 and 2022). Plant height (PH); Number of fruits /plant (FN), Number of branches/ plant (BN), Plant dry weight (PDW), Roots dry weight (RDW), Stem diameter (SD), Seed yield/plant (SYP), sepals dry weight/plant (SDWP); Anthocyanin content (Anc), chlorophyll content (Chloro), Nitrogen content (N), Phosphor content (P), and Potassium content (K). A positive correlation is represented by the blue color, whereas a negative correlation is depicted by the red color\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/c3d2695b26f51aee882f63f0.png"},{"id":78542079,"identity":"7d86ddf8-71a8-4c8c-b195-e57a950e0aec","added_by":"auto","created_at":"2025-03-14 16:12:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":54289,"visible":true,"origin":"","legend":"\u003cp\u003eClustering analysis of the interrelationships between examined traits, sowing date, and irrigation rates treatments. In the ballots, the hierarchical clustering analysis with the Euclidean distance using the principal component scores and Ward’s technique as the process of linkage was used. Plant height (PH); Number of fruits /plant (FN), Number of branches/ plant (BN), Plant dry weight (PDW), Roots dry weight (RDW), Stem diameter (SD), Seed yield/plant (SYP), sepals dry weight/plant (SDWP); Anthocyanin content (Anc), chlorophyll content (Chloro), Nitrogen content (N), Phosphor content (P), and Potassium content (K). Where: T\u003csub\u003e1\u003c/sub\u003e= 19\u003csup\u003eth\u003c/sup\u003e May, T\u003csub\u003e2\u003c/sub\u003e= 19\u003csup\u003eth\u003c/sup\u003e June, T\u003csub\u003e3\u003c/sub\u003e=19\u003csup\u003eth\u003c/sup\u003e July, I\u003csub\u003e1\u003c/sub\u003e= 100% ETc, I\u003csub\u003e2\u003c/sub\u003e= 75% ETc, I\u003csub\u003e3\u003c/sub\u003e= 50% ETc.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/fa3caf780d02eeb6c351367d.png"},{"id":78541025,"identity":"8c3d0f02-c545-4708-a0e2-242617720630","added_by":"auto","created_at":"2025-03-14 16:04:34","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":101839,"visible":true,"origin":"","legend":"\u003cp\u003ePCA analysis of the correlations between traits based on the sowing dates and levels of irrigation within two years. Diagrams are defined by the first two axes of the PCA of the different variables (n = 3); Axis1 (illustrating 81.05% of variance) and Axis2 (illustrating 10.80% of variance). Where Plant height (PH); Number of fruits /plant (FN), Number of branches/ plant (BN), Plant dry weight (PDW), Roots dry weight (RDW), Stem diameter (SD), Seed yield/plant (SYP), sepals dry weight/plant (SDWP); Anthocyanin content (Anc), chlorophyll content (Chloro), Nitrogen content (N), Phosphor content (P), and Potassium content (K)\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/ee64be500795c15a1424ea83.png"},{"id":78542085,"identity":"8f1923d6-c13c-44b7-b097-662e9d7bb72e","added_by":"auto","created_at":"2025-03-14 16:12:35","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":155290,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal irrigation quantities of roselle under various sowing dates at the AL-Busili site\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/b95a66b6b49061b913049cef.png"},{"id":78542260,"identity":"79d411f7-b3be-41f8-bf28-0351cdc1547d","added_by":"auto","created_at":"2025-03-14 16:20:34","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":132407,"visible":true,"origin":"","legend":"\u003cp\u003eIrrigation water productivity (kg/m\u003csup\u003e3\u003c/sup\u003e) of both growing seasons of roselle as impacted by different sowing dates and irrigation rates. Where: T1= 19\u003csup\u003eth\u003c/sup\u003e May, T2= 19\u003csup\u003eth\u003c/sup\u003e June, T3=19\u003csup\u003eth\u003c/sup\u003e July, I\u003csub\u003e1\u003c/sub\u003e= 100% ETc, I\u003csub\u003e2\u003c/sub\u003e= 75% ETc, I\u003csub\u003e3\u003c/sub\u003e= 50% ETc\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/394cff3d2de8d4e87b41b1a4.png"},{"id":78543170,"identity":"f932b114-55c7-4474-a403-2293072eba27","added_by":"auto","created_at":"2025-03-14 16:36:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2530058,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6185764/v1/04196227-2b16-47f5-a58b-8966c70545b2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adjusting sowing date to enhance roselle performance and water productivity under water deficiency stress","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRoselle (\u003cem\u003eHibiscus sabdariffa L.\u003c/em\u003e) is an annual summer plant from the family Malvaceae, commonly referred to as \"Karkade\" in most Arab countries, including Egypt [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Egypt is considered the country where roselle originated [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is one of the herbal drugs; it is rich in vitamin C, organic acids (tartaric, citric, malic, and oxalic acids), and two types of anthocyanin, namely gossypetin (cyanidin) and hibiscin (delphinidin) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Numerous environmental agronomic parameters impact roselle plant growth, yield, and quality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The biggest challenge to obtaining good agricultural production globally is drought stress. Moreover, increasing crop yields and conserving irrigation water are two connected and significant worldwide challenges. A few efficient methods for using scarce water resources are choosing the right planting date and managing irrigation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgronomic measures like sowing timing enhance high yield by promoting plant development and growth, improving land economics, and ensuring the plant's vulnerable growth stage aligns with environmental conditions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Roselle is a short-day plant that needs a photoperiod of 12 to 12.5 hours to bloom. Long days during the wrong stage of development lead to yield loss [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The sown roselle\u0026rsquo;s relative earliness is caused by photosensitivity and temperature. Such plants might bloom early under conditions of short levels of sunlight and may not bloom when the sunlight interval exceeds 11 hours [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. \u003cem\u003eH. sabdariffa\u003c/em\u003e L. plants, which were sown on 15th April, had significant increases in all growth characteristics [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Hibiscus planting time substantially impacts the wet weight of the bush, the wet/dry weights of the boll, 1000 seed weight, total performance, and the harvested seed. The periods of planting on 9th March and 30th April caused a decrease in the weight of the bush and bolls [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The roselle planted on 15th April improved and yielded more leaves and branches, taller plants, and heavier leaf DW per plant compared to the 1st May, 15th May, and 1st June, respectively. In contrast, the earliest day of sowing (15th April) demonstrated greater values of roselle yield components with substantial variations compared to other dates [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Early dates of planting yielded the greatest number of branches, plant heights, dry and fresh weights of plants, seeds, and sepals, increased total carbohydrates percent, nutrient contents, anthocyanin, and acidity in sepals, as well as fixed oil in seeds [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The planting date shift from mid-May to mid-July resulted in a 60-percent drop in flower yield and a 58-percent decrease in the yield of calyxes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, water stress, a widespread environmental issue, negatively impacts crop yield, quality, and biomass production [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Plants respond with strategies like essential and auxiliary reactions to cope with temporary stress, but prolonged stress can negatively impact growth and yield [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, saving irrigation water and improving crop yields are two related and important global issues [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In this concern, it has been stated that extending the period between drought and irrigation conditions led to a reduction in roselle components and yield but an increase in active calyces, including total phenols and vitamin C [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Irrigation periods affect plant growth as stem diameters and plant height as well as carbohydrate production and photosynthesis. Furthermore, increased growth levels contributed to making use of growth factors such as nutrients, water, and light, thereby increasing roselle growth. Moreover, Rah Khosravani et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and Seghatoleslami et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] illustrated that irrigation water rates don't significantly affect roselle plant growth but affect chlorophyll content in leaves. In addition, sowing dates affect calyx water use efficacy, seed oil content, antioxidant activity, calyx yield, and biological yield. In contrast, the interaction between irrigation periods and sowing date treatments did not significantly affect any trait [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. El-Dissoky et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found that the increase of calyx yield for roselle is affected by irrigation frequency and mild drought stress. The results of Silakhoor et al.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] highlighted that water stress has decreased the number of flowers and calyx since the flowering stage entails multiple processes prone to stress conditions. Additionally, roselle\u0026rsquo;s total anthocyanin content was significantly affected under mild and severe drought stress [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, the objectives of the current study were to determine the impact of different sowing dates on roselle performance and water productivity under water-deficiency stress.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental site\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThrough the two summer seasons of 2021 and 2022, an experimental study was established in a split-plot design with three replicates, the sowing dates (T1; May 19, T2; June 19, and T3; July 19) as main plots and irrigation rates (I1; 100%, I2; 75%, and I3; 50% of crop evapotranspiration \u0026ldquo;ETc\u0026rdquo;) as sub-plots. The experiment was conducted at the AL-Busili Experimental Farm of the Central Laboratory for Agricultural Climate, Agricultural Research Center, Rashid City, Beheira Governorate, Egypt, 31\u0026deg;27'15\" N, 30\u0026deg;23'23\u0026rdquo; E. The soil\u0026rsquo;s physical and chemical analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was carried out by taking a sample of the soil at a 0\u0026ndash;30 cm depth before planting, according to Cottenie et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and Kult et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSoil mechanical and chemical analysis of the experimental site\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eSoil texture\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eSandy loam\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eClay\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSilt\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSand (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eOrganic matter\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCaCO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eField capacity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eWilting point (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eBulk density\u003c/p\u003e \u003cp\u003egcm\u003csup\u003e-3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e6.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAvailable nutrients\u003c/p\u003e \u003cp\u003e(mg/kg soil)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eSoluble Cations\u003c/p\u003e \u003cp\u003e(meq/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eSoluble Anions\u003c/p\u003e \u003cp\u003e(meg/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEC (dS/m)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCa\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMg\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eK\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCl\u003csup\u003e-\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHCO3\u003csup\u003e-\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSO4\u003csup\u003e2-\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeteorological data\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe daily meteorological values during the experimental period were gathered from the CLAC automated weather station located at the experimental site, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The reference evapotranspiration (ET\u003csub\u003eo\u003c/sub\u003e, mm/day) was determined using the method of Penman-Monteith (PM) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eField experiments\u003c/h3\u003e\n\u003cp\u003eInland preparation, the soil was well plowed, where compost as organic fertilizers at a rate of 20 m\u003csup\u003e3\u003c/sup\u003efed\u003csup\u003e-1\u003c/sup\u003e and calcium super phosphate (15.5% P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e) at 300 kg/fed (1feddan\u0026thinsp;\u0026asymp;\u0026thinsp;0.42 hectare) were added. Roselle seeds (\u003cem\u003eH. sabdariffa\u003c/em\u003e L. cv. Sabahia 17 dark) were provided by the Medicinal and Aromatic Plants Research Department, Horticulture Research Institute, Agricultural Research Center, Giza, Egypt. The experiment comprised nine treatments, and each experimental plot was 2\u0026times;1.0 m (3 m\u003csup\u003e2\u003c/sup\u003e) and had two rows, 50 cm apart and 50 cm between the plant holes. Then, the treatments were replicated three times in a total of 27 plots, and each replicate encompassed ten plants. Seeds were sown on May 19, T\u003csub\u003e1\u003c/sub\u003e (early), June 19, T\u003csub\u003e2\u003c/sub\u003e (mid), and July 19, T\u003csub\u003e3\u003c/sub\u003e (late) in both seasons. Three weeks after the seeds were sown, plants were thinned to one plant/hole. Beginning in the third week following seeding, the plants received the recommended dosage of nitrogen, phosphorus, and potassium fertilizers, which were added at a rate of 200 kg/fed as ammonium sulfate (20.5% N), 150 kg/fed as potassium sulfate (48% K\u003csub\u003e2\u003c/sub\u003eO), and 25 L/ fed as phosphoric acid (85% H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e) through fertigation. A drip irrigation system was used to apply irrigation water stress treatments (I1; 100% ETc \u0026ldquo;regular\u0026rdquo;, I2; 75% ETc \u0026ldquo;mild\u0026rdquo;, and I3; 50% ETc \u0026ldquo;severe\u0026rdquo;) every three days. The conveying pipeline system consists of a 63 mm PVC main line connected to a 50.8 mm PVC sub-main line. It was a surface drip system with a 50-hp irrigation pump coupled to sand and screen filters. The sub-main line is connected to the 16 mm-diameter drip lateral lines. With built-in emitters with a 2 L/h discharge rate placed 0.3 m apart on the lateral lines, each 20 m long lateral line is separated 0.7 m apart on the sub-main. Small amounts of soluble water fertilizers were injected via a tank attached to the drip irrigation system. Other agricultural practices, including the use of insecticides, hoeing, and weeding, were all promptly applied to improve crop development according to the Ministry of Agriculture and Land Reclamation recommendations.\u003c/p\u003e\n\u003ch3\u003eCrop irrigation water calculation\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eLevels of irrigation were estimated, while manual valves were used to regulate irrigation for each experimental plot. Food and Agricultural Organization (FAO) Penman-Monteith (PM) procedure, the FAO 56 method was utilized to estimate the total quantity of irrigation water [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The first step entailed the calculation of reference evapotranspiration (ETo) as follows:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equa\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{E}\\varvec{T}}_{\\varvec{o}}=\\frac{0.408\\varDelta\\:\\left({\\varvec{R}}_{\\varvec{n}}-\\varvec{G}\\right)+\\varvec{\\gamma\\:}\\frac{900}{\\varvec{T}+273}{\\varvec{u}}_{2}({\\varvec{e}}_{\\varvec{s}}-{\\varvec{e}}_{\\varvec{a}})}{\\varDelta\\:+\\varvec{\\gamma\\:}(1+0.34{\\varvec{u}}_{2})}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ewhere: ET\u003csub\u003eo\u003c/sub\u003e = Daily reference evapotranspiration [mm d\u003csup\u003e-1\u003c/sup\u003e]. R\u003csub\u003en\u003c/sub\u003e =Net radiation at the crop surface (MJ m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e). G\u0026thinsp;=\u0026thinsp;Soil heat flux density (MJ m\u003csup\u003e-2\u003c/sup\u003e d\u003csup\u003e-1\u003c/sup\u003e), T\u0026thinsp;=\u0026thinsp;Mean daily air temperature at 2 m height (\u0026deg;C), U\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Wind speed at 2 m height (m s\u003csup\u003e-1\u003c/sup\u003e), e\u003csub\u003es\u003c/sub\u003e = Saturation vapor pressure (kPa), e\u003csub\u003ea\u003c/sub\u003e = Actual vapor pressure (kPa), Δ\u0026thinsp;=\u0026thinsp;The slope of the vapor pressure curve (kPa \u0026deg;C\u003csup\u003e-1\u003c/sup\u003e), γ\u0026thinsp;=\u0026thinsp;The psychometric constant (kPa \u0026deg;C\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe second step was to determine crop evapotranspiration (ETc) values according to Doorenbos and Pruitt[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e \u003cem\u003eETc\u0026thinsp;=\u0026thinsp;ET\u003c/em\u003e \u003csub\u003e \u003cem\u003eo\u003c/em\u003e \u003c/sub\u003e \u003cem\u003e\u0026times; Kc mm.d\u003c/em\u003e\u003csup\u003e\u003cem\u003e-1\u003c/em\u003e\u003c/sup\u003e \u003cb\u003e(2)\u003c/b\u003e\u003c/p\u003e \u003cp\u003ewhere: ET\u003csub\u003eo\u003c/sub\u003e = Evapotranspiration rate from an excessive surface of green cover of uniform height (8 to 15 cm), entirely shading the ground, actively growing, with no water shortage, Kc\u0026thinsp;=\u0026thinsp;Crop coefficient, crop coefficient values were used (between 0.4 to 1.2).\u003c/p\u003e \u003cp\u003eLeaching requirements were determined according to (Allen et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] as follows.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equb\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{L}\\varvec{R}=\\left(\\frac{\\varvec{E}\\varvec{C}\\varvec{i}\\varvec{w}}{\\varvec{E}\\varvec{C}\\varvec{d}}\\right)\\times\\:100\\:\\:\\:\\varvec{\\%}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(3\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ewhere: LR\u0026thinsp;=\u0026thinsp;leaching requirements, ECiw\u0026thinsp;=\u0026thinsp;Electrical conductivity of irrigation water (0.36 dS/m), ECd\u0026thinsp;=\u0026thinsp;Electrical conductivity of drainage water 1.7 dS/m \u0026ndash; maize salinity threshold. Therefore, the LR of the current study was 21.17%.\u003c/p\u003e \u003cp\u003eWater requirements (WR) were determined based on the following equation:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equc\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{W}\\varvec{R}=\\varvec{E}\\varvec{T}\\varvec{c}\\left(1+\\frac{\\varvec{L}\\varvec{R}}{100}\\right)\\:\\:\\:\\:\\:\\:\\:\\varvec{m}\\varvec{m}.{\\varvec{d}}^{-1}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(4\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe irrigation requirement (IR) was determined as follows:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equd\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{I}\\varvec{R}=\\frac{\\varvec{W}\\varvec{R}\\times\\:4200\\times\\:100}{1000\\times\\:\\varvec{E}\\varvec{a}}\\:\\:\\:\\:{\\varvec{m}}^{3}.{\\varvec{f}\\varvec{e}\\varvec{d}}^{-1}.{\\varvec{d}}^{-1}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(5\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ewhere: Ea\u0026thinsp;=\u0026thinsp;The irrigation system's efficiency (assumed 85% of the total applied water).\u003c/p\u003e \u003cp\u003eThe water flow meter for all treatments determined the total quantity of irrigation water. depicts the seasonal irrigation quantities for roselle under varying irrigation treatments at the AL-Busili site for the three sowing dates during the two seasons. The plants were irrigated with 2 l/h capacity drippers utilizing the fertigation technique.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eIrrigation water productivity (WP)\u003c/h3\u003e\n\u003cp\u003eThe irrigation water productivity (kg/m\u003csup\u003e3\u003c/sup\u003e) of roselle was calculated according to the equation accessible by Zhang [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] as follows:\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e\n$$\\:{WP}_{I}=\\frac{Crop\\:Yeild\\:(kg\\:.{fed}^{-1})}{Applied\\:Water\\:({m}^{3}.{fed}^{-1})}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(6\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRecorded Data\u003c/h2\u003e \u003cp\u003eAt the end of each season, roselle fruits were harvested on the 15th of November, 15th of December, and 15th of January for each sowing date. Ten plants were randomly taken from each plot, and plant height (cm), no. of branches/plant, no. of fruit/plant, the weight of the dry sepals (g/plant), dry weight of plant (g), stem diameter (cm), roots dry weight (g/plant), seed yield/plant (g), and fresh fruit yield (ton/fed) were determined. The available macronutrient percentage, including N, K, and P, was assessed in the roselle dry herb based on the methods defined by Nessler's method [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Total chlorophyll was determined in leaves using SPAD-502, Konica, Minolta.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe general linear model (GLM) algorithm of the SAS 9.2 program for Windows was used to conduct an analysis of variance (ANOVA) on all analyzed parameters. The data were assessed statistically utilizing Fisher's least significant difference (LSD) test at a (P\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e0.05). Boxplots were developed to demonstrate the disparity between sowing date and irrigation rates, whereas Pearson correlation coefficients were utilized for assessing the correlation among traits. In the R project (version 3.4.5), the ggplot2 package was utilized for drawing a boxplot.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eVegetative growth\u003c/h2\u003e\n \u003cp\u003eANOVA for the impact of sowing date and irrigation treatments, as well as their interaction, are displayed in Table 2. During the 2021 and 2022 seasons, the results revealed that sowing date and irrigation treatments had a significant effect at 5% (P\u0026thinsp;\u0026le;\u0026thinsp;0.05) on all studied parameters, including plant height, number of branches per plant, the number of fruits per plant, plant dry weight (g), root dry weight (g/plant), stem diameter (mm), sepals dry weight (g/plant), and seed yield (g/plant). A marked (P\u0026thinsp;\u0026le;\u0026thinsp;0.05) correlation was detected between the sowing dates and the irrigation treatments, revealing an association with plant height, branch number/plant, plant dry weight, root dry weight, and stem diameter only in season two. Plant dry weight (g/plant) and root dry weight (g/plant) were significantly affected by the interaction between sowing date and irrigation rates in both seasons. However, plant height (cm), branch number/plant, and sepals dry weight (g/plant) were only affected in the 1st season. While the number of fruits/plants and stem diameter (mm) were only affected in the 2nd season.\u003c/p\u003e\n \u003cp\u003eMoreover, as seen in (Fig. 2), the mean data of 2 seasons revealed that (T2) with (I1) had the highest value of plant height (PH, 253.17 cm), stem diameter (SD, 20.01), fruit number/plant (FN, 100.30), branch number/plant (BN, 25.74), plant dry weight (PDW, 2210.89 g/plant), root dry weight (RDW, 0.74 g/plant), seed yield (SYP, 32.51 g/plant), and sepals (SDWP, 18.32 g/plant). Whereas adopting a late sowing date (T3) with severe water stress (I3; 50% ETc) yielded the lowest values for the same parameters.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAnalysis of variance results for different traits of roselle under varying sowing dates and irrigation rates ns, **, *** indicate non-significance, significance at 5% (P 0.05), R\u003csup\u003e2\u003c/sup\u003e coefficient of determination; RMSE, root mean square error; CV, coefficient of variation.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSource of variance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePlant height\u003c/p\u003e\n \u003cp\u003e(cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBranch Number / plant\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNumber of fruits /plant\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePlant dry weight\u003c/p\u003e\n \u003cp\u003e(g/ plant)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSowing date (T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrrigation rates (I)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT X I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStem diameter\u003c/p\u003e\n \u003cp\u003e(mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRoots dry weight\u003c/p\u003e\n \u003cp\u003e(g/ plant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSepals dry weight\u003c/p\u003e\n \u003cp\u003e(g/ plant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSeed yield\u003c/p\u003e\n \u003cp\u003e(g/ plant)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSowing date (T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrrigation rates (I)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT X I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003ens, **, *** indicate non-significance, significance at 5% (P\u0026nbsp;0.05), R\u003csup\u003e2\u003c/sup\u003e coefficient of determination; RMSE, root mean square error; CV, coefficient of variation.\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eFruits yield (FW, ton/fed)\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eIn the first season, under the well-watered condition (I1;100% ETc), an increase from 3.62 ton/fed to 3.73 ton/fed in roselle fruit yield was registered with delayed the sowing date from 19th May to 19th June by 3.08% while it significantly decreased to 2.83 ton/fed by 21.84% when the sowing date was delayed to July 19th (Fig. 3). Furthermore, under the sever water stress (I3;50% ETc), the delayed sowing date from 19th May to 19th June, the roselle fresh yield per ton was increased by 3.97%, where it decreased to 17.95% when delayed to 19th July. It would be noticed that the second season reported the same trend of the first season (Fig. 3).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eAnthocyanin content\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eA non-significant difference in anthocyanin content was observed based on sowing dates. In contrast, the irrigation rates of 75% ETc and 50% ETc were equally significant, as shown in Table 3, which indicated that maximum values were 44.87 mg/g d.w. in the first season on May 19th, and 49.015 mg/g d.w. in the second season on June 19th. The relative increases in anthocyanin content were 5.80% and 5.60% for the first and second seasons, respectively, when comparing the May sowing date to the July sowing date. Additionally, the relative increases were 2.86% and 9.02% in the first and second seasons, respectively, for the June sowing date compared to the July sowing date. Furthermore, irrigation showed a significant increase in anthocyanin content (mg/g d.w.) in both seasons. The maximum anthocyanin content was 45.815 mg/g d.w. in the first season and 49.68 mg/g d.w. in the second season, influenced by the irrigation level at 75% ETc compared to other levels. When comparing irrigation at 75% ETc to 100% ETc in the first and second seasons, the relative increases were 12.53% and 10.98%. Conversely, the relative increases for irrigation at 50% ETc in the first and second seasons compared to irrigation at 100% ETc were 14.42% and 14.34%, respectively. The interaction between irrigation rates and sowing dates resulted in substantial variations in anthocyanin contents. The maximum anthocyanin content of 47.59 mg/g F.W. was observed with the dates (T2) and (I2) during the first growing season. Additionally, the results indicated that anthocyanin contents could be enhanced by coordinating (T2) with (I2) during the second growing season (Table 3).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAnthocyanin content (mg / g d.w.) in roselle sepals as affected by sowing date and irrigation rates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTreatments\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eSowing date (T1)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eIrrigation rates (I)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eSeason 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eSeason 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.04 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.54 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.058 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.55 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.814 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.35 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.87 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.63 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.42 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.48 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.02 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.96 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eLSD\u003csub\u003e0.05\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eT\u0026thinsp;=\u0026thinsp;4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eI\u0026thinsp;=\u0026thinsp;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eT\u0026thinsp;=\u0026thinsp;4.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eI\u0026thinsp;=\u0026thinsp;3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eT x I\u0026thinsp;=\u0026thinsp;3.14\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eT x I\u0026thinsp;=\u0026thinsp;6.11\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDifferent lowercase letters indicate statistically significant differences between treatments (p \\(\\:\\le\\:\\) 0.05), as revealed by the least significant difference (Fisher\u0026rsquo;s LSD) test. Where. T1= 19th May, T2= 19th June, T3=19th July, I\u003csub\u003e1\u003c/sub\u003e= 100% ETc, I\u003csub\u003e2\u003c/sub\u003e= 75% ETc, I\u003csub\u003e3\u003c/sub\u003e= 50% ETc.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eMacronutrient content\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eConcerning the interactive impact of the sowing dates and various irrigation rates on the available macronutrient content in leaves of roselle, the mean data of both seasons in Fig.\u0026nbsp;(4) reflected that the irrigation level was at 100% ETc under the sowing date on the 19th of May (T1) and 19th of June (T2) and demonstrated the superiority of the N%, P%, and K% in leaves as compared with other treatments. Moreover, as shown in Fig.\u0026nbsp;(4), no significant differences were registered in the N%, P%, and K% between I1 and I2 during T2 of sowing date.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eTotal chlorophyll\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe mean effects of sowing date and irrigation rates on total chlorophyll (mg/g f.w.) are presented in Fig. 5. Generally, there was a non-significant difference in the total chlorophyll content at the I1 (100% ETc) and I2 (75% ETc) under the dates of T1 and T3. On the other hand, the results presented that the adoption of sowing date (T2) directed to an increase in total chlorophyll content (0.85 mg/g f.w.) under I1 treatment, although this increase was significantly equal to the application of T1\u0026thinsp;+\u0026thinsp;I1 (0.87 mg/g f.w.) and T3\u0026thinsp;+\u0026thinsp;I1. (0.83 mg/g f.w.).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eCorrelation between studied traits\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe Pearson\u0026rsquo;s correlation coefficients for different attributes examined under varying sowing dates and irrigation rates are presented in Fig. 6. Data revealed that the association between root dry weight and plant dry weight was substantially positive. The plant height (PH) revealed a strong positive correlation with plant dry weight (PDW), root dry weight (RDW), sepals dry weight per plant (SDWP), and nitrogen content (N). Likewise, branch number/plant (BN) expressed a positive correlation with PDW, RDW, stem diameter (SD), seed yield per plant (SYP), and SDWP. Also, sepals\u0026rsquo; dry weight per plant had a positive correlation with nitrogen content. Nonetheless, anthocyanin (Anc) or chlorophyll (Chloro) content exhibited a substantially negative association with PH, FN, BN, PDW, RDW, SD, SYP, and SDWP. Determining the correlation between yield traits is necessary as it directly contributes to enhancing yield traits. The direct selection of these attributes might enhance the selection efficiency of yield.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eThe correlation between irrigation rates and sowing date\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe hierarchical clustering effectively identified the link between combinations of sowing dates and irrigation rates (12 combinations) based on their yield and growth performance parameters (Fig. 7). Two main clusters were characterized concerning the association between sowing dates and irrigation rates. The combination treatments of A (T2\u0026thinsp;+\u0026thinsp;I1), B (T1\u0026thinsp;+\u0026thinsp;I1), and C (T2\u0026thinsp;+\u0026thinsp;I2) generated the first cluster. B and C treatments were the closest sub-clusters. Treatment A yielded the greatest values for most traits in this group. For treatment B, most traits, except SYP, FN, P, Chloro, and Anc, demonstrated high performance. Conversely, treatment C demonstrated the highest positive impacts on PH, BN, SD, SYP, and FN, followed by SDWP, RDW, N, and K, whereas chloro content was negatively impacted by this treatment. The second cluster consisted of treatments D (T3\u0026thinsp;+\u0026thinsp;I3), E (T2\u0026thinsp;+\u0026thinsp;I3), F (T3\u0026thinsp;+\u0026thinsp;I1), G (T3\u0026thinsp;+\u0026thinsp;I2), H (T1\u0026thinsp;+\u0026thinsp;I2), and I (T1\u0026thinsp;+\u0026thinsp;I3), with treatments F and G or H and I being the closest sub-clusters. The combinations of sowing dates and irrigation rates in the second cluster demonstrated an opposite pattern to the first cluster combinations. All examined traits were adversely affected except for the anthocyanin content, indicating diminished overall performance, particularly for the control treatment, which had the lowest value for all assessed parameters.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \u003ch2\u003ePrincipal component analysis\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003ePCA was carried out to determine the association between the examined treatments and traits (Fig. 8). The two PCs are responsible for 91.85% of the variance. F1 seemed to be linked to the T1I2, T2I1, T2I2, and T1I1 on the positive side to T3I1, T3I2, T1I3, T2I3, and T3I3 on the negative side, which illustrates 81.05% of the variability, whereas F2 contributed to 10.8% of the variation (Fig. 8). The angles between trait vectors demonstrated the relationship between the investigated characteristics. Vectors with large angles (about 180 degrees) exhibit a negative correlation, while contiguous vectors exhibit a significant positive correlation. A high positive correlation was found between anthocyanin and chlorophyll content and all of its characteristics. Due to the simplicity of their measurement, the closeness of FN, SYP, and SD to anthocyanin content indicates their significance in indirect selection (Fig. 8).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\"\u003e\n \u003ch2\u003eApplied irrigation water\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe applied irrigation water varied among different sowing dates and irrigation rates (Fig. 9). The applied irrigation water values for roselle fluctuated between 1259 and 4657.32 m\u003csup\u003e3\u003c/sup\u003e/fed in 2021 and 1405.86 to 4779.19 m\u003csup\u003e3\u003c/sup\u003e/fed in 2022. The early-sown plants at T1 recorded the highest irrigation demand as the crop coefficient reached its maximum values during July and August, when Tmin, Tmax, and ETo values were maximum (Fig. 1). While delaying sowing dates at T3 treatments registered the lowest applied irrigation water when periods of peak climatic factors coincided with low crop coefficient values. As a result of changes in the meteorological components, the results also revealed that the applied water had higher values in the second season than in the first season.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\"\u003e\n \u003ch2\u003eIrrigation water productivity (WP\u003csub\u003eI\u003c/sub\u003e, kg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/h2\u003e\n \u003cp\u003eIn both seasons, the maximum irrigation water productivity for fresh sepals (1.917 and 1.922 kg/m\u003csup\u003e3\u003c/sup\u003e, respectively) was obtained with severe water stress (I3; 50% ETc) at the late sowing date (T3; 19th July). It was higher by 32.22% and 9.66% (1st season) 36.50% and 15.60% (2nd season) than the first (early) and second (mild sowing dates, respectively, under the same condition of irrigation (50% ETc).On the other hand, the lowest values of irrigation water productivity (0.776 and 0.738 kg/m\u003csup\u003e3\u003c/sup\u003e) were observed with the well-watered treatment (I1; 100% ETc) at the early sowing date (T1; 19th May) in both seasons, respectively. In this case, severe water stress was found to be the optimal irrigation regime in terms of the WP\u003csub\u003eI\u003c/sub\u003e based on the yield of roselle sepals and the quantity of irrigation (Fig. 10). It is reasonably known that the WP\u003csub\u003eI\u003c/sub\u003e increases when the applied water amount decreases; nonetheless, the crop yield could be reduced. Examining all the efficiency results of irrigation with the crop yields, it was found that WP\u003csub\u003eI\u003c/sub\u003e of 1.917 and 1.922 kg/m\u003csup\u003e3\u003c/sup\u003e matched the yield of 2.48 and 2.70 ton/fed.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe current experiment was conducted to determine the optimal sowing date and irrigation rates for improved roselle productivity and water use efficiency. This result may be due to the effect of the day and night temperature, daylight intensity, and photoperiods. In addition, these results are probably because the sowing dates in June led to the high growing period and irrigation rates received during the growing periods. An adequate supply of moisture would eventually boost the growth rate as well as timely maturity, hence a higher productivity of the roselle. These results are in agreement with El-Bakhshwan and El-Kouny [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], who indicated that the plant height (cm), number of branches/plant, and number of fruit decreased in the roselle sown in July compared with the roselle sown in June. El-Bakhshwan and El-Kouny [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] found that all parameters of hibiscus growth were significantly increased as affected by irrigation water level (1000 m\u003csup\u003e3\u003c/sup\u003e) and the sowing period in June. Moreover, our findings align with Barzgaran [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] results on H. Sabdariffa, who confirmed that planting time has a greater influence on the performance of other agronomic features. The outcome indicates that delaying the planting of this crop would be optimal (19th June). The date of planting on 19th June corresponded to the greatest values of the examined parameters. Khattak et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] discovered the same pattern in roselle plants.\u003c/p\u003e \u003cp\u003eIt was observed that the maximum increase in anthocyanin content was observed when the sowing date 19 of June was adopted with the implementation of I\u003csub\u003e2\u003c/sub\u003e (75%ETc) and I\u003csub\u003e3\u003c/sub\u003e (50% ETc). Drought stress enhanced the overall anthocyanin content of roselle to minimize excess light availability and provide beneficial protection to leaves without significantly affecting photosynthetic efficiency, as reported in numerous articles [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This demonstrates a way to control light absorption and lessen damage caused by photooxidation. According to reports, anthocyanin can prevent extra high-energy quanta from damaging chloroplasts and scavenging reactive oxygen species, hence reducing photo-oxidative damage in leaves (He et al., 2020). Moreover, the impact that drought stress has on TAC is consistent with the findings of[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] on roselle, which reported that enhanced secondary metabolism has been linked to improvements in the plants' qualitative traits, like anthocyanins, under simultaneous drought stress. These results are in agreement with [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, the results showed that the accumulation of N, P, K, and total chlorophyll in roselle leaves reached its highest values when T2 (19 June) was combined with I\u003csub\u003e1\u003c/sub\u003e (100% ETc) and I\u003csub\u003e2\u003c/sub\u003e (75% ETc), while the lowest values were detected when roselle seeds were sown on 19th of July with I\u003csub\u003e3\u003c/sub\u003e (50% ETc). The authors postulate that extreme heat and evaporation conditions begin to impair plant growth on July 19. Plants respond to these conditions by increasing their uptake and storage of K as a defensive mechanism. K contains several qualities that can enhance temperature and plant water status beneath water. The results are in line with [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] on \u003cem\u003eHibiscus sabdariffa\u003c/em\u003e, and [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] on \u003cem\u003eFoeniculum vulgare.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the current study, planting time and irrigation rates significantly impacted the roselle crop productivity. Delayed planting dates to 19 June under irrigation rates of 100% ETc (I\u003csub\u003e1\u003c/sub\u003e) increased plant height, the number of branches per plant, the number of fruits per plant, plant dry weight, No. of fruit/plant, number of branches per plant, stem diameter, sepals yield (d.w/plant), seed yield/plant, root dry weight per plant of roselle, and anthocyanin content. The highest irrigation water productivity was obtained with delayed planting dates to 19 July under 50% ETc irrigation level (I\u003csub\u003e3\u003c/sub\u003e). In conclusion, the late sowing date can be a viable management strategy in Egypt with limited water availability in terms of water productivity of harvested roselle fruits.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All the authors declared that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization and design of the work, M.A.A.A. and E.A.S; methodology, M. A. A. A., A.A. and E.A.S; software, K.A.E., E.A.A. and M.A.A.A; formal analysis, A.A., K.A.E., M.A.A.A., S.M.A. and E.A.S; investigation, M.A.A.A., E.A.S.; resources, M.A.A.A., E.A.S.; writing\u0026mdash;original draft preparation, M. A.A.A., A.A. and E.A.S; writing\u0026mdash;review and editing, E.A.A., K.A.E., and S.M.A.. All authors provided critical feedback and helped shape the research, analysis, and manuscript. Also, all authors discussed the results and contributed to the final manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMohamed R, Fernandez J, Pineda M, Aguilar M. Roselle (Hibiscus sabdariffa) seed oil is a rich source of \u0026gamma;‐tocopherol. J Food Sci. 2007;72:S207\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eIsmail A, Ikram EHK, Nazri HSM. Roselle (Hibiscus sabdariffa L.) seeds nutritional composition protein quality and health benefits. 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Effects of sowing date on physiological characteristics, yield and yield components for different maize (Zea mays L.) hybrids. Not Sci Biol. 2017;9:143\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eSeghatoleslami MJ, Mousavi SG, Barzgaran T. Effect of irrigation and planting date on morpho-physiological traits and yield of Roselle (Hibiscus sabdariffa). 2013.\u003c/li\u003e\n\u003cli\u003eEl-Dissoky R, Attia AM, Awad AM. Managing Roselle Plant (Hibiscus sabdariffa L.) Requirements of Fertilizers and Irrigation Grown under Upper Egypt Conditions. Journal of Soil Sciences and Agricultural Engineering. 2020;11:693\u0026ndash;700.\u003c/li\u003e\n\u003cli\u003eCottenie A, Verloo M, Kiekens L, Velghe G, Camerlynck R. Chemical analysis of plants and soils. Lab Agroch State Univ Gent, Belgium. 1982;63:44\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eKlute A, Page AL. Methods of soil analysis. American Society of Agronomy. Agronomy Monograph. 1986;9.\u003c/li\u003e\n\u003cli\u003eAllen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome. 1998;300:D05109.\u003c/li\u003e\n\u003cli\u003eDoorenbos J, Pruitt WO. Crop water requirements. FAO irrigation and drainage paper 24. Land and Water Development Division, FAO, Rome. 1977;144.\u003c/li\u003e\n\u003cli\u003eZhang C-H. Compound decision theory and empirical Bayes methods. Ann Stat. 2003;:379\u0026ndash;90.\u003c/li\u003e\n\u003cli\u003eChapman HD, Pratt PE, Parker F. Methods of analysis for soils, plants and waters. Univ. of Calif. Div Agric Sci Priced Pub. 1978;4034:50\u0026ndash;169.\u003c/li\u003e\n\u003cli\u003eJackson ML. Soil Chemical Analysis,(2nd Indian Print) Prentice-Hall of India Pvt. Ltd New Delhi. 1973;38:336.\u003c/li\u003e\n\u003cli\u003eEl-Bakhshwan MH, El-Kouny H. Impact of irrigation intervals, planting time and density on hibiscus yield. 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J Crop Improv. 2017;31:192\u0026ndash;208.\u003c/li\u003e\n\u003cli\u003eHinojosa-G\u0026oacute;mez J, San Mart\u0026iacute;n-Hern\u0026aacute;ndez C, Heredia JB, Le\u0026oacute;n-F\u0026eacute;lix J, Osuna-Enciso T, Muy-Rangel MD. Anthocyanin induction by drought stress in the calyx of roselle cultivars. Molecules. 2020;25:1555.\u003c/li\u003e\n\u003cli\u003eKhalil SE, Yousef RMM. Study the effect of irrigation water regime and fertilizers on growth, yield and some fruit quality of Hibiscus sabdariffa L. Int J Adv Res (Indore). 2014;2:738\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eFutuless KN, Kwaga YM, Clement T, ANEJA KR, JOSHI R, SHARMA C, et al. Effect of sowing date on calyx yield and yield components of roselle (Hibiscus Sabdariffa L.) in Nothern Guinea Savanna. New York Science Journal. 2010;3:1\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eSanjeet Bagari SB, Singh PP, Naruka IS, Rathore SS, Shaktawat RPS. Effect of date of sowing and nitrogen levels on growth, yield and quality of fennel. 2010.\u003c/li\u003e\n\u003cli\u003eEl-Khayat ASM, Gouda HAH. Effect of sowing date and potassium fertilization on growth, yield and chemical composition of Foeniculum vulgare Mill plants. 2005.\u003c/li\u003e\n\u003cli\u003eEl-Wahab MAA, Mehasen HRA. Effect of locations and sowing date on (Foeniculum vulgare Mill.) Indian fennel type under Upper Egypt conditions. 2009\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anthocyanin, Hibiscus sabdariffa, planting dates, productivity, water saving","lastPublishedDoi":"10.21203/rs.3.rs-6185764/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6185764/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change, especially water stress, poses a threat to food production and increases the occurrence of famines worldwide. Adjusting sowing dates to enhance irrigation water productivity is among the adaptation strategies to mitigate the effects of water deficiency stress on crop yields. In this context, a field experiment was conducted during 2021 and 2022 seasons at the AL-Busili Experimental Farm of the Central Laboratory for Agricultural Climate, Agricultural Research Center in Egypt, to assess the effects of sowing dates (T1: May 19, T2: June 19, and T3: July 19) and irrigation rates (I1: 100%, I2: 75%, and I3: 50% of potential crop evapotranspiration \u0026ldquo;ETc\u0026rdquo;) on the performance \u003cem\u003eand\u003c/em\u003e water productivity of roselle (\u003cem\u003eHibiscus sabdariffa\u003c/em\u003e L.). The treatments were arranged in a split-plot design with three replications. The results indicated that regular irrigation (I1 at 100% ETc) under the mid-sowing date T2 (June 19) significantly (p\u0026thinsp;\u0026le;\u0026thinsp;0.05) increased plant height, branch number, fruit number per plant, and the dry weight of sepals per plant. Adopting I2 or I3 on June 19 enhanced anthocyanin content (AC%). Notably, the late sowing date on 19th July, coupled with the severe water stress (I3, 50% ETc), yielded the uppermost water productivity (1.917 and 1.922 kg/m\u003csup\u003e3\u003c/sup\u003e). Based on these findings, it could be concluded that the late sowing date can be a viable management strategy in Egypt with limited water availability in terms of water productivity of harvested roselle fruits.\u003c/p\u003e","manuscriptTitle":"Adjusting sowing date to enhance roselle performance and water productivity under water deficiency stress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-14 16:04:29","doi":"10.21203/rs.3.rs-6185764/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-07T03:59:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-06T09:37:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39931363215279044480933375581630538159","date":"2026-04-03T07:38:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227499197530906047066162722795962316922","date":"2026-03-16T09:30:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78766713785897624839550953587167144460","date":"2025-04-20T06:07:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-11T19:23:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"34911551828595262760631107561758915536","date":"2025-04-06T15:12:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-06T13:24:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-13T03:16:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-12T10:26:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-12T10:22:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-03-08T20:03:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d7f3b04e-c75d-4538-b21a-34c74c31c8c6","owner":[],"postedDate":"March 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T02:53:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-14 16:04:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6185764","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6185764","identity":"rs-6185764","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}