Adaptation under Integrating Seasonal and AQUACROP Simulations to Evaluate Soil Moisture and Drip Irrigation Effects on Tomato Production in Southern Ethiopia

Adaptation under Integrating Seasonal and AQUACROP Simulations to Evaluate Soil Moisture and Drip Irrigation Effects on Tomato Production in Southern Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Adaptation under Integrating Seasonal and AQUACROP Simulations to Evaluate Soil Moisture and Drip Irrigation Effects on Tomato Production in Southern Ethiopia Babur Tesfaye Yersaw This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7945516/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Seasonal variation analysis revealed slight differences in crop growth and model performance between the calibration (Season 1) and validation (Season 2) periods. The simulated and observed results showed that biomass (BM) and dry yield (DY) exhibited minor seasonal reductions, while soil water content (SWC) and water productivity (WPET) showed modest increases. Specifically, biomass decreased by 1.6%, from 8.788 t ha⁻¹ in Season 1 to 8.650 t ha⁻¹ in Season 2, whereas dry yield declined by 1.9%, from 5.458 to 5.357 t ha⁻¹. These slight decreases are mainly attributed to higher mean air temperature and reduced mid-season rainfall during the validation period, which increased crop water stress and evapotranspiration demand under deficit irrigation treatments. In contrast, the mean soil water content increased by 1.3%, from 276.1 mm in Season 1 to 279.6 mm in Season 2, likely due to enhanced late-season rainfall and improved soil moisture retention under full irrigation. The most notable seasonal improvement was observed in water productivity, which increased by 10.0%, from 1.65 to 1.81 kg m⁻³, indicating more efficient water use and higher transpiration efficiency during the slightly drier validation season. Overall, AquaCrop demonstrated stable performance across both seasons, effectively capturing the temporal variability in crop growth and soil moisture dynamics. Although small fluctuations occurred due to climatic variability, the model maintained strong correlations for canopy cover (r ≥ 0.96), biomass (r ≥ 0.98), and soil water content (r ≥ 0.94), confirming its reliability for simulating seasonal crop responses under different irrigation regimes. Aquacrop Climate change Seasonal adaptation Water productivity Yield Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. INTRODUCTİON Climate change significantly impacts agriculture, affecting crop yields, water availability, and the livelihoods of farming communities. The increasing frequency of extreme weather events, altered precipitation patterns, and rising temperatures disrupt agricultural systems, leading to food insecurity and economic challenges, particularly in developing nations (Majeed et al ., 2023). Water scarcity is a critical global problem which is caused by climate change, especially in arid and semi-arid regions, where the availability of this vital resource is severely limited. This issue is acutely felt in Ethiopia, where water scarcity not only threatens the livelihoods of millions but also undermines agricultural productivity and food security (Gorjian et al. , 2021). The situation is further aggravated by the impacts of climate change, which disrupts traditional rainfall patterns and exacerbates water shortages (Pawlak and Małgorzata, 2020). As the global population continues to increase, the demand for food production intensifies; necessitating innovative solutions to optimize water use in agriculture and ensure sustainable development (Christoforidou et al ., 2022). To address the pressing issue of water scarcity, innovations in efficient irrigation technologies are transforming water management in agriculture (Choudhary, 2024; Mallareddy et al ., 2023). These advancements focus on maximizing water use efficiency, minimizing wastage, and optimizing crop yields while reducing the environmental impact of irrigation practices. With developments such as precision irrigation systems, sensor-based technologies, and smart water management solutions, these strategies present promising approaches for promoting sustainable agriculture in a world facing water scarcity. Drip irrigation is an efficient irrigation method that delivers water directly to the root zone of plants using a system of pipes, tubing, and emitters. Unlike traditional surface irrigation and sprinkler irrigation, which distributes water uniformly across an entire field, drip irrigation applies water precisely where needed, reducing evaporation, runoff, and soil erosion (Santosh et al., 2022 ). This targeted approach enables precise water control, leading to significant water savings and enhanced crop yields. A key advantage of drip irrigation is its adaptability to various terrains and crop layouts. It can be implemented in fields, greenhouses, and on uneven or sloping land where traditional irrigation methods may not be practical. Drip irrigation is particularly effective for row crops, orchards, vineyards, and high-value specialty crops, where precise water delivery is crucial for optimal growth and yields (Santosh et al., 2022 ; Yersaw et al ., 2024). Under climate change projections, modeling tool can be effectively utilized to simulate crop growth and water productivity. From those modeling tools, the Aqua Crop Model under stage-wise deficit irrigation scenarios could be effective in estimation of the yield and water productivity (Wale et al., 2022 ). The significance of this research was advancement of scientific knowledge by addressing a gap in understanding the applicability of crop models in water-limited environments under deficit drip irrigation system, particularly in regions where tomato cultivation plays a significant role in agricultural livelihoods. Moreover, the study provides practical recommendations for farmers, policymakers, and agricultural stakeholders in Southern Ethiopia, aiding in the development of sustainable water management practices and enhancing agricultural productivity in the region by conducting field experiments (Raes et al ., 2022). In addition to adopting advanced irrigation technologies, implementing effective irrigation scheduling is essential for optimizing water application (Jones, 2004). This method involves accurately measuring soil moisture levels to determine the precise timing and quantity of irrigation needed (Zhe et al ., 2020). Recent advancements in dielectric sensor technology have made it feasible to monitor soil moisture levels more accurately and affordably, thereby facilitating improved irrigation management practices. By employing techniques such as deficit irrigation, which allows for controlled moisture stress during specific growth stages, farmers can enhance crop yields while conserving water resources. Deficit irrigation represents a promising approach to minimizing water usage without significantly compromising crop yields. This method strategically subjects crops to moisture stress during certain growth phases, allowing for the conservation of water resources that can be redirected to irrigate additional land. Stage-wise deficit irrigation (SWDI) has emerged as a crucial strategy in modern agricultural water management, particularly in the context of increasing water scarcity and the need for sustainable farming practices. This technique involves applying irrigation water at levels below the full crop requirements, optimized according to the crop's critical growth stages. Research indicates that plants respond differently to water stress during various phonological phases; for instance, sensitive stages such as flowering and fruit development are particularly crucial for maximizing yields (Cheng et al. , 2021). By strategically timing water applications, stage wise deficit irrigation (SWDI) can significantly enhance water use efficiency while maintaining acceptable yield levels, thereby reducing both water input and costs under limited resource conditions (Lu et al ., 2021). Furthermore, recent studies have demonstrated that stage wise deficit irrigation (SWDI) not only supports the economic viability of farming in arid regions but also contributes to improved crop resilience against climate variability, promoting sustainable agriculture (Zhang et al ., 2024). Research indicates that this practice can be effective across various climates and agronomic conditions, optimizing water use efficiency while maintaining satisfactory yields (Laita et al., 2024 ; Yufeng et al ., 2021; Fitsum et al., 2023 ; Aziz et al ., 2022; Asmamaw et al ., 2021; Eshete et al ., 2022). However, the effectiveness of deficit irrigation can vary based on numerous factors, including soil types, tomato cultivars, capacity of watering and local climatic conditions (Chand et al ., 2020; Kusumiyati et al ., 2023; Rempelos et al ., 2023). This practice has been implemented across various regions, climates, and agronomic management systems, demonstrating notable effects on yield and water use efficiency (Chand et al ., 2020; Kusumiyati et al ., 2023; Rempelos et al ., 2023). While numerous studies have primarily examined the impacts of deficit irrigation at different levels, focusing on specific factors such as tomato cultivars (Vasile et al ., 2020), soil types (Chand et al ., 2020; Kusumiyati et al ., 2023; Rempelos et al ., 2023; Vasile et al ., 2020), irrigation scheduling types (França et al ., 2024; Yersaw and Lohani, 2022), soil texture (Lu et al ., 2021) and local climate conditions (Rempelos et al ., 2023), these factors have been shown to significantly influence yield outcomes. However, the effects of deficit irrigation can vary considerably depending on the specific soil types, tomato varieties, and climatic characteristics present in a given area (Lu et al ., 2021; Yersaw and Lohani, 2022). Furthermore, certain investigations have explored the implications of deficit irrigation without adopting stage-based approaches, which often hinders the identification of optimal deficit irrigation levels (Cheng et al ., 2022; Burato et al ., 2024; Li et al ., 2022). Consequently, this study aims to identify the optimal deficit irrigation levels by combining irrigation scheduling system under stage wise deficit drip irrigation framework to enhance both yield and water use efficiency for tomato cultivation in the climatic conditions of Arba Minch. By addressing these research gaps, future studies can contribute to the development of more effective water management practices that enhance agricultural productivity in water-scarce regions, ultimately supporting sustainable food production in the face of ongoing climate challenges. 2. MATERİALS AND METHODS 2.1. Location, and climate characteristics of the experimental site The field experiment was conducted in the south western part of SNNP regional state at Arba Minch Demonstration farm located 500 km south of Addis Ababa during the period of January to April (season 1) from dry season, and June to September (round 2) from wet season. Geographically it is located at 37°20'00'' − 37°38'40''E longitude, 5°45'00'' to 6°10'00''N latitude. The catchment topography of elevation is ranging from 1105 to 3486 m above sea level (Fig. 1 ). From the analysis of thirty-two years of data from 1990 to 2020, showed that, the average minimum and maximum temperature were 17.40°C and 30.63°C. Average annual precipitation is 885.2 mm, necessitating supplemental irrigation during the dry months of January to March and June to August. The rainfall pattern (Fig. 2 ) indicates that irrigation was required during dry seasons from January to March and June to August. The source of irrigation water used in the study area was a canal from Kulfo River which is discharged to Lake Chamo. 2.2. Soil properties of the study area The soil characteristics of the experimental field are presented in Table 1 . The soil properties in the study were soil texture, field capacity, permanent wilting point, and bulk density at every 0.25m for total soil layer of 0.75m. Soil texture is determined by using USDA textural triangle method after obtaining soil particle distribution result from the hydrometer (sedimentation test) analysis. Pressure plate and Pressure membrane apparatus were be used for the determination of soil moisture content at field capacity (FC) and permanent wilting point (PWP) at the suction of -1/3 bar and − 15 bar, respectively. The average percentage of clay, silt, and sand of the field were 45.78, 33.54, and 20.61% respectively. The dominant soil texture based on sedimentation test and the USDA textural triangle was clay soil throughout the soil profile. The average bulk density ( pd) , field capacity (FC), and permanent wilting point (PWP) of the experimental field were 1.11 g/cm 3 , 38.85% and 25.25%, respectively. Table 1 Soil physiochemical properties of the study area Soil properties Soil Layer (cm) Average 0–25 25–50 50–75 Clay (%) 51.17 43.17 43.00 45.78 Silt (%) 32.60 34.01 34.00 33.54 Sand (%) 16.00 22.83 22.99 20.61 Soil Texture Clay Clay Clay Clay Bulk density (g/cm 3 ) 1.12 1.15 1.02 1.10 FC (%) 39.46 38.88 38.21 38.85 WP (%) 26.12 25.22 24.40 25.25 TAW (mm/m) 133.40 136.60 138.10 136.0 PH 5.70 6.34 6.59 6.21 ECs(dS/m) 0.32 0.35 0.35 0.34 2.3. Treatments design and settings The experiment used a random design with three irrigation levels of 75, 50, 25% of full irrigation including full irrigation as a control applied at four stages of vegetative, flowering, yield formation, and ripening) as shown in Table 2 . Table 2 Experimental treatment design Treatment Treatment tag Treatment description T1 100 V 100 F 100 YF 100 R (FI) 100%ETa (Full irrigation at all stages) T2 75 V 100 F 100 YF 100 R 75%FI at vegetative and FI at remaining stages T3 100 V 75 F 100 YF 100 R 75%FI at flowering and FI at remaining stages T4 100 V 100 F 75 YF 100 R 75%FI at yield formation and FI at remaining stages T5 100 V 100 F 100 YF 75 R 75%FI ripening and FI at remaining stages T6 50 V 100 F 100 YF 100 R 50%FI at vegetative and FI at remaining stages T7 100 V 50 F 100 YF 100 R 50%FI at flowering and FI at remaining stages T8 100 V 100 F 50 YF 100 R 50%FI at yield formation and FI at remaining stages T9 100 V 100 F 100 YF 50 R 50%FI at ripening and FI at remaining stages T10 25 V 100 F 100 YF 100 R 25%FI at vegetative and FI at remaining stages T11 100 V 25 F 100 YF 100 R 25%FI at flowering and FI at remaining stages T12 100 V 100 F 25 YF 100 R 25%FI at yield formation and FI at remaining stages T13 100 V 100 F 100 YF 25 R 25%FI at ripening and FI at remaining stages N.B: T = Treatment, V = Vegetative, F = Flowering, YF = Yield formation, R = Ripening, ETa = Actual Evapotranspiration, and R = Remaining. Roma Vf tomato crop variety were transplanted with row and plant spacing of 40 cm (Cheng et al ., 2022). Each plot has four furrows and ten plants measuring 4 m length by 1.6 m width (6.4 m 2 ). The distance between treatments and replication was 0.5 m to avoid the influence of irrigation water from one plot to the next. The experimental field has a total area of 397.9 m 2 (width ×length = 23 m x 17. 3m). The experiment is laid out in random complete block design with three replications as shown in Fig. 3 . Full irrigation (FI) refers to the practice of providing crops with the entire amount of water they need to reach their full potential for growth, yield, and development throughout the growing season. This approach aims to meet the water requirements of plants by applying the exact amount of water lost through evapotranspiration (ET), which is the combined loss of water through evaporation from the soil and transpiration from plants. 2.4. Irrigation scheduling The total available water (TAW) of the experimental field was determined by using Eq. 1 (Allen et al ., 1998). T \(\:\text{A}\text{W}=\left(\frac{\left(\text{F}\text{C}-\text{P}\text{W}\text{P}\right)Pd\text{*}\text{D}\text{r}}{100}\right)\text{*}\frac{1}{\text{P}\text{w}}\) ………………………………………………. (1) Where, TAW = Total available water (mm); FC = Field Capacity (%); PWP = Permanent wilting point (%); Pd = Bulk density (g/cm 3 ); Dr = Root depth (cm); Pw = Density of water (g/cm 3 ). Bulk density was determined by taking undisturbed soil sample using a core-sampler from six representative places in the trial plot at three different depths (0–25 cm, 25–50 cm, and 50–75 cm). The sampled soil was oven-dried at 105°C for 24 h and weighed to determine the dry weight fraction. Then, bulk density was calculated as the ratio of dry weight of the soil to known cylindrical core sampler volume using Eq. 2 (Hillel, 2004). $$\:pd=\frac{\text{M}\text{c}}{\text{V}\text{t}}$$ 2 …………………………………………………………………….. Where, Pd = Bulk Density (g/cm 3 ); Mc = Dry Weight of Soil (g); and Vt = Volume of core sampler (cm 3 ). The current soil moisture is measured by Time domain reflector meter (TDR) which has some soil moisture uncertainty. Therefore, it requires calibration to change it into gravimetrical soil moisture. The irrigation date was determined by waiting the current soil moisture reaches at management allowed deficit (MAD) of tomato crop (p = 40%) expressed in Eq. (3) (Allen et al ., 1998). RAM \(\:=\left(\frac{\left(\text{F}\text{C}-\text{P}\text{W}\text{P}\right)\text{P}\text{b}\text{*}\text{D}\text{r}}{100}\right)\text{*}\frac{1}{\text{P}\text{w}}\) *p = TAW*p = 40%TAW ……………………. (3) Where, RAM = Readily available moisture (mm), and p = Depletion level (%). The irrigation was applied at which the current soil moisture (Ɵi) reaches to readily available moisture (RAM) for full irrigation application and the other treatments gain irrigation based on the deficit irrigation levels of 75%, 50%, and 25% varied with growth stages. The irrigation depth were applied back to the filed capacity by measured the root depth at each irrigation time using Eq. 4 , and converted to volume using Eq. 5 (Borena, and Seyoum, 2021; Yerli et al ., 2023). $$\:\text{E}\text{T}\text{a}\:=\:\frac{\left(\text{Ɵ}\text{F}\text{C}-\text{Ɵ}\text{i}\right)\text{*}Pb\text{*}\text{D}\text{r}\text{*}\text{D}\text{w}}{10}$$ 4 ……………………………………………………. $$\:\text{V}=\text{E}\text{T}\text{a}\text{*}\text{A}$$ 5 ………………………………………………………………….. Where, ETa = Actual crop evapotranspiration (mm), ƟFC = Moisture retained at field capacity (%), Ɵi = Current moisture before irrigation (%), Pd = Bulk density (g/cm 3 ), Dr = Root depth (cm), Dw = Wetting fraction, V = Volume (L) and A = Area of plot (6.4m 2 ). The wetting fraction used in this study was 0.3 (30%) taken from FAO (Allen et al ., 1998), the surface wetting fraction for drip irrigation ranged between 0.30–0.40. 2.5. Water Application System A gravity drip system was used to supply irrigation water to the experimental plots. Drip system consists of Polyvinyl Chloride main lines, and drip laterals. The plots were leveled manually to create uniform plots within the given treatment. There are 39 plots with four laterals per plot. Hence, each plot consisted of four drip lateral lines which had 4m length and consists of 10 emitters (holes). The number of emitters per plant was kept at one and with 1.2 l/hr flow rate fixed for all treatments determined from measuring and calibrated by measuring cylinder. A barrel (drum) of 300 liter capacity is mounted on a stand at a head up to 1.25 m above the ground level. The flow rate was determined by calibration by increasing and decreasing the head of the barrel (drum) at each treatment. The barrel top was covered in order to prevent evaporation loss. One 40 mm diameter size of main line and five lateral line which had diameter of 10 mm used. Operating duration of each treatment varied according to irrigation schedules (irrigation level) and calculated using Eq. 6 (Doorenbos, and Pruitt, 1975 ). $$\:\text{T}=\frac{\text{G}\text{I}\text{R}\text{*}\text{R}\text{s}\text{*}\text{P}\text{s}\text{*}\text{N}}{\text{q}\text{e}}=\frac{V}{qe}\:$$ 6 ……………………………………………………………… Where, Rs = Plant row spacing (cm), Ps = Plant spacing (cm), N = number of dripper present at each treatment (N = 40), and qe = Emitter flow rate (l/hr). 2.6. Method of Crop data collection 2.6.1. Ethics and consent to participate Tomato seeds and plant materials used in this study were cultivated in accordance with Ethiopian national agricultural guidelines. 2.6.2. Plant Materials Tomato seeds used in this study were obtained from the Arba Minch University Demonstration Farm, Southern Ethiopia. Field trials were conducted at the experimental farm of Arba Minch University, located at 6°03′ N, 37°34′ E. 2.6.3. Crop data collected The leaf length (cm) and leaf width (cm) of plants from each treatment were measured using tape mete every 10 days. The leaf area (A) (Eq. 7 ), leaf area index (LAI) (Eq. 8 ) and the canopy cover (CC) (Eq. 9 ) were calculated from the leaf length and leaf width. The total leaf area (cm 2 ) for tomato leaves was calculated using a relationship based on (Schwarz and Kläring, 2006) using Eq. 7 . The leaf area index was obtained by the ratio of total leaf area of the crop per unit of ground area using Eq. 8 . Canopy cover (CC, %) was converted by the LAI data using Eq. 9 (Raes, 2017). $$\:\text{A}=0.2695\text{*}{\text{L}}^{0.4759}\text{*}{\text{W}}^{1.4184}$$ 7 ………………………………………………… $$\:\text{L}\text{A}\text{I}=\frac{\text{M}\text{e}\text{a}\text{s}\text{u}\text{r}\text{e}\text{d}\:\text{l}\text{e}\text{a}\text{f}\:\text{a}\text{r}\text{e}\text{a}\:\text{p}\text{e}\text{r}\:\text{p}\text{l}\text{a}\text{n}\text{t}\:{\text{c}\text{m}}^{2}}{100\text{*}100}\text{*}\frac{\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{p}\text{l}\text{a}\text{n}\text{t}\text{s}}{{\text{m}}^{2}}$$ 8 ………………………...… $$\:CC=1.005*{⌈1-Exp\left(-0.6LAI\right)⌉}^{1.2}$$ 9 …………………………………………. Fresh yield (ton/ha), and weight of single fruit were measured at the harvest time and measured by sensitive balance. Above ground biomass (BM), and dry yield (DY) data samples were taken out at the harvest time for each treatment. The dry biomass of each sample was determined by weighing it after it had been held in an oven for 48 hours at 65°C and the harvest index (HI) was the ratio of dry yield and above ground biomass as shown in Eq. 10 (Yersaw et al ., 2024; Raes Dirk, 2017 ; Raes, 2023). $$\:\text{H}\text{I}=\:\left(\frac{\text{D}\text{Y}}{\text{B}\text{M}}\right)\text{*}100$$ 10 ………………………………………………………..…..… 2.7. Identification of Optimum Deficit Irrigation 2.7.1. Water productivity, irrigation water use efficiency, and Water use efficiency Water productivity (WP ET ) is the ratio of dry yield (Yd) per crop transpired [35–36] as shown in Eq. 11 , irrigation water-use efficiency (IWUE, kg/m 3 ) was calculated as the marketable fruit yield (kg/ha) obtained per unit volume of seasonal irrigation water applied (m 3 /ha) as shown in Eq. 12 (Kuscu Hayrettin, Ahmet Turhan, Nese Ozmen, Pinar Aydinol, and Ali Osman Demir, 2014)[40] and Water use efficiency (WUE) was the ratio of fresh yield per unit volume of seasonal evapotranspiration (ET) as shown in Eq. 13 (Raes, 2017; Raes, 2023). $$\:{\text{W}\text{P}}_{\text{E}\text{T}}=\frac{\text{Y}\text{d}}{\text{E}\text{T}}$$ 11 ………………………………………………………………………….. IWUE \(\:=\frac{\text{F}\text{Y}}{\text{E}\text{T}\text{a}}\) ………………………………………………………………………… (12) $$\:\text{W}\text{U}\text{E}=\frac{\text{F}\text{Y}}{\text{E}\text{T}}$$ 13 ………………………………………………………………………..… Where; WP ET = Water productivity (kg/m 3 ), Yd = Dry yield (ton/ha), ET = Evapotranspiration (mm), IWUE = Irrigation water use efficiency (Kg/m 3 ), FY = Fresh yield (t/ha), and ETa = Actual Evapotranspiration (mm), and WUE = Water Use Efficiency (Kg/m 3 ). The amount of water saved (WS) per hectare can be obtained by subtracting the amount of water consumption of particular deficit irrigation from the full irrigation requirement using Eq. 14 (Hassene, and Seid 2017). Additional fresh yield estimated at deficit irrigation levels from water saved can be estimated by the ratio of the multiplication of the fresh yield gain and water saved with the actual evapotranspiration at corresponding treatments using Eq. 15 (Yersaw and Lohani, 2022). The fresh yield increments can be calculated by subtracting the total fresh yield of each treatment from full irrigation by using Eq. 16 (Yerli et al ., 2023); (Hassene, and Seid, 2017). $$\:\text{W}\text{S}=\frac{(\text{E}\text{T}\text{a}\:\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}-\text{E}\text{T}\text{a}\:\text{f}\text{r}\text{o}\text{m}\:\text{d}\text{e}\text{f}\text{i}\text{c}\text{i}\text{t}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}\:\text{l}\text{e}\text{v}\text{e}\text{l})\text{*}100}{\text{E}\text{T}\text{a}\:\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}}$$ 14 ….……….……. $$\:\:\text{F}\text{Y}\text{W}\text{S}=\frac{\text{F}\text{Y}\text{*}\text{W}\text{S}}{\text{E}\text{T}\text{a}\:\text{f}\text{r}\text{o}\text{m}\:\text{d}\text{e}\text{f}\text{i}\text{c}\text{i}\text{t}\:\text{l}\text{e}\text{v}\text{e}\text{l}\text{s}}$$ 15 ……………………………..……..…………… $$\:\text{F}\text{Y}\frac{\text{i}\text{n}\text{c}\text{r}\text{e}\text{m}\text{e}\text{n}\text{t}}{\text{d}\text{e}\text{c}\text{r}\text{e}\text{m}\text{e}\text{n}\text{t}}=\:\left(\frac{\text{T}\text{F}\text{Y}\:\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}-\:\text{T}\text{F}\text{Y}\:\text{f}\text{r}\text{o}\text{m}\:\text{d}\text{e}\text{f}\text{i}\text{c}\text{i}\text{t}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}\:}{\text{T}\text{F}\text{Y}\:\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}}\right)*100$$ 16 ………. Where, WS = Water saved (%), ETa = Actual evapotranspiration (mm), FYWS = Fresh yield from water saved (ton/ha), FY = Fresh Yield (ton/ha), and TFY = Total fresh yield (ton/ha). The increment/decrement percentage of evapotranspiration water productivity, water use efficiency, and irrigation water use efficiency can be calculated by using Eq. 17–19 13 (Raes, 2017; Raes, 2023). \(\:{\text{W}\text{P}}_{\text{E}\text{T}}\) Increment/decrement = \(\:\left(\frac{{\text{W}\text{P}}_{\text{E}\text{T}\:\:}\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}}{{\text{W}\text{P}}_{\text{E}\text{T}}\:\:\text{f}\text{r}\text{o}\text{m}\:\text{d}\text{e}\text{f}\text{i}\text{c}\text{i}\text{t}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}\:\text{l}\text{e}\text{v}\text{e}\text{l}}\right)*100\) ……………… (17) \(\:\text{W}\text{U}\text{E}\:\text{I}\text{n}\text{c}\text{r}\text{e}\text{m}\text{e}\text{n}\text{t}/\text{d}\text{e}\text{c}\text{r}\text{e}\text{m}\text{e}\text{n}\text{t}\) = \(\:\left(\frac{\text{W}\text{U}\text{E}\:\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}}{\text{W}\text{U}\text{E}\:\:\text{f}\text{r}\text{o}\text{m}\:\text{d}\text{e}\text{f}\text{i}\text{c}\text{i}\text{t}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}\:\text{l}\text{e}\text{v}\text{e}\text{l}}\right)*100\) ……,……… (18) \(\:\text{I}\text{W}\text{U}\text{E}\:\text{I}\text{n}\text{c}\text{r}\text{e}\text{m}\text{e}\text{n}\text{t}/\text{d}\text{e}\text{c}\text{r}\text{e}\text{m}\text{e}\text{n}\text{t}\) = \(\:\left(\frac{\text{I}\text{W}\text{U}\text{E}\:\text{f}\text{r}\text{o}\text{m}\:\text{f}\text{u}\text{l}\text{l}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}}{\text{I}\text{W}\text{U}\text{E}\:\:\text{f}\text{r}\text{o}\text{m}\:\text{d}\text{e}\text{f}\text{i}\text{c}\text{i}\text{t}\:\text{i}\text{r}\text{r}\text{i}\text{g}\text{a}\text{t}\text{i}\text{o}\text{n}\:\text{l}\text{e}\text{v}\text{e}\text{l}}\right)*100\) …………… (19) Where, WP ET = Evapotranspiration water productivity (%), WUE = Water use efficiency (%), IWUE = Irrigation water use efficiency (%). 2.8. Statistical Analysis The collected data were statistically analyzed using SAS software using a procedure of general linear model for the variance analysis. Mean comparisons were executed using the least significant difference (LSD) of 1% and the graph was illustrated using Origin lab pro 2024. 3. RESULTS AND DİSCUSSİONS 3.1. Actual evapotranspiration, evapotranspiration, and gross depth of irrigation water applied Table 3 presents the irrigation water amounts applied to the experimental treatments, along with the gross irrigation and seasonal evapotranspiration values for the study period. The actual evapotranspiration (ETa) for the full irrigation application during the vegetative, flowering, yield formation, and ripening stages was 17.8, 62.7, 134.5, and 45 mm for season 1. For season 2, the actual evapotranspiration (ETa) for the vegetative, flowering, yield formation, and ripening stages values were 14.5, 63.9, 104.5, and 45 mm, respectively. The smallest irrigation depths required were observed at vegetative stage, increased up to the yield formation growth stage, and decreased at ripening growth stage at all irrigation levels. Like any other crops, tomato crop require relatively large amount of water during mid-stage (yield formation) followed by ripening growth stage. The obtained result in agreement to the result reported by Lu et al ., (2019), who suggested that, the irrigation requirement of tomato crop was low at the vegetative stage, increased during flowering stage, reached maximum at yield formation stage and slightly declined during harvesting stage. This is also supported by Dirirsa et al ., (2017), who suggested high amount of irrigation depth was applied at mid (yield formation) stage to substitute the evaporation rate due to the presence of high canopy cover which increases the evaporation rate of leaf. The average seasonal actual evapotranspiration (ETa), gross irrigation, and evapotranspiration, varied between 171–244, 180–257, and 245-327mm, respectively. The highest seasonal ETa was recorded in the full irrigation application, clearly owing to favorable soil moisture during the growing period, whereas the lowest seasonal ETa was recorded in T12, with a prolonged water deficit after the vegetative period recorded in the application of 100 V 100 F 25 YF 100 R with a prolonged water deficit. The estimated ET values for tomato at full irrigation application was 341 mm at season 1 and 312 mm for the same treatment at season 2 with average value of 327mm. This value is in consistent with in the ranges of 237.5-514.4 mm (Hong et al ., 2022), 215–841 mm for tomato crop (Mukherjee et al., 2010 ). In contradict; this value was less than in ranges of the water requirement of tomato (400-600mm) (Allen et al ., 1998) depending on the climate and the total length of the growing period. The variation may be due to, climate, water supply, soil, and topography, temperature, precipitation, humidity, wind movement and growing-season length, which have the greatest effect on evapotranspiration (Ndiaye et al ., 2020). Table 3 Stage wise actual gross irrigation and evapotranspiration depth applied (mm). Stage Season 1 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 V 18 13 18 18 18 9 18 18 18 5 18 18 18 F 63 59 51 63 63 55 39 63 63 51 28 63 63 YF 135 135 127 108 135 135 120 82 135 135 113 56 135 R 45 45 45 45 34 45 45 45 23 45 45 45 11 ETa (mm) 260 252 241 234 249 243 222 207 237 235 203 181 226 ET (mm) 341 333 322 290 305 298 287 269 302 300 268 246 291 Stage Season 2 V 15 11 15 15 15 7 15 15 15 4 15 15 15 F 64 60 52 64 64 56 40 64 64 52 28 64 64 YF 105 105 101 82 105 105 97 60 105 105 94 37 105 R 45 45 45 45 34 45 45 45 23 45 45 45 11 ETa (mm) 228 220 212 205 217 213 197 183 205 205 181 160 194 ET (mm) 312 304 296 289 301 297 281 265 289 289 265 244 278 Average ETa 244 236 227 220 233 228 210 195 221 220 192 171 210 Average ET 327 319 309 290 303 298 284 267 296 295 267 245 285 N.B V = Vegetative, F = Flowering, YF = Yield formation, R = Ripening, ETa = Actual evapotranspiration, GIR = Gross irrigation requirement, and ET = Evapotranspiration. 3.2. Calibration of Aqua-Crop The observed and simulated dry yield (DY), biomass (BM), soil water content (SWC) and water productivity (WP ET ) of the Aqua-crop model, focused on the performance of calibration and validation, are presented in Table 4 . Calibration was performed for all deficit irrigation treatments under conditions of water stress only (no nutrient or salinity stress). During calibration, observed biomass ranged from 7.578 to 8.788 t/ha, while simulated biomass ranged from 7.280 to 9.129 t/ha, with deviations between + 3.74% and − 4.09%. For dry yield during the same period, observed values ranged from 4.131 to 5.458 t/ha, and simulated values ranged from 3.987 to 5.751 t/ha, with errors between + 5.37% and − 3.49%. The model also showed reasonable calibration for SWC, with observed values between 270.9 and 281.2 mm and simulated values between 268.0 and 285.6 mm, resulting in deviations from − 2.05% to + 1.58%. The highest BM, DY, and WPET were observed under full irrigation (FI), while the lowest values were associated with the I25YF×100R treatment (25% irrigation at yield formation and full irrigation for the remaining stages). Generally, BM, DY, and WPET decreased with decreasing water application depth. This trend aligns with findings from Yersaw & Lohani (2022) and Banjaw et al . (2017), who reported reductions in biomass and yield with increasing deficit irrigation levels. Similarly, Wang et al . (2011) observed a negative impact of increased water stress on biomass and dry yield compared to full irrigation. The Aquacrop performance on canopy covers was shown in Table 5 . Based on the performance classification by Raes et al. (2022), the model demonstrated good calibration for CC, achieving r ≥ 0.96, 2.9%≤RMSE ≤ 8.0%, 7.5%≤NRMSE ≤ 21.1%, 0.91 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. Specifically, under full irrigation (FI), the model yielded values of r = 1.00, RMSE = 4.3%, NRMSE = 11.1%, EF = 0.98, and d = 1.00. In contrast, under high deficit irrigation (DI), the performance metrics were r = 0.96, RMSE = 8.0%, NRMSE = 21.1%, EF = 0.91, and d = 0.98, indicating a performance range from well to excellent. The model also performed well on BM with r ≥ 0.99 (very good), 0.3t/ha ≤ RMSE ≤ 0.8t/ha (very good), 8.3% ≤ NRMSE ≤ 25.2% (very good and moderate good), 0.92 ≤ EF ≤ 0.99 (very good), and 0.98 ≤ d ≤ 1.00 (very good). The AquaCrop model's performance in simulating soil water content (SWC), which ranged from moderate to good based on various statistical indicators. Correlation coefficients (0.54 ≤ r ≤ 0.82) suggested a moderate to good relationship between simulated and observed values. The Root Mean Square Error (3.60 mm ≤ RMSE ≤ 24.4 mm) and Normalized Root Mean Square Error (1.30%≤NRMSE ≤ 9.00%) indicated very good to moderate good model accuracy. However, the Nash-Sutcliffe Efficiency (− 4.18 ≤ EF ≤ 0.00) indicated poor model efficiency. The index of agreement (0.66 ≤ d ≤ 0.81) suggested good to moderate good agreement between the simulated and observed SWC. Table 4 Aquacrop calibration performance values Treatments Canopy cover Biomass ( Soil water content r RMSE (%) NRMSE (%) EF d r RMSE (t/ha) NRMSE (%) EF d r RMSE (mm) NRMSE (%) EF d T1 1.00 4.3 11.1 0.98 1.00 1.00 0.3 10.6 0.99 1.00 0.75 6.60 2.30 -1.40 0.70 T2 0.99 4.1 10.8 0.98 1.00 1.00 0.3 10.4 0.99 1.00 0.79 5.30 1.90 -0.24 0.78 T3 0.99 4.5 11.5 0.98 0.99 1.00 0.3 11.1 0.99 1.00 0.82 5.70 2.00 -0.84 0.79 T4 0.99 6.3 17.9 0.95 0.99 1.00 0.4 14.3 0.98 1.00 0.74 12.20 4.40 -2.63 0.68 T5 1.00 3.6 9.5 0.99 1.00 1.00 0.3 9.4 0.99 1.00 0.80 7.40 2.60 -1.54 0.74 T6 1.00 2.9 7.5 0.99 1.00 1.00 0.3 8.3 0.99 1.00 0.80 4.40 1.60 -0.30 0.77 T7 0.99 6.2 18.4 0.94 0.99 1.00 0.5 17.6 0.97 0.99 0.63 11.10 4.00 -0.30 0.75 T8 0.97 6.8 20.3 0.93 0.98 0.99 0.5 19.4 0.96 0.99 0.59 19.90 7.20 -4.18 0.55 T9 0.99 4.6 12.5 0.97 0.99 1.00 0.3 11.7 0.99 1.00 0.73 9.10 3.20 -0.12 0.80 T10 0.99 5.6 15.2 0.97 0.99 0.99 0.4 13.9 0.98 1.00 0.74 3.60 1.30 0.00 0.81 T11 0.96 7.2 20.6 0.92 0.98 0.99 0.6 19.6 0.95 0.99 0.57 17.30 6.30 -0.51 0.71 T12 0.99 8.0 21.1 0.91 0.98 0.99 0.8 25.2 0.92 0.98 0.54 24.40 9.00 -1.14 0.66 T13 0.99 6.2 18.1 0.94 0.99 0.99 0.5 16.5 0.97 0.99 0.72 10.70 3.80 -0.35 0.78 3.3. Validation of Aquacrop The Aquacrop validation was made at each treatment based on the observed and simulated data’s is shown in Fig. 5 – 7 . During validation, the observed biomass ranged from 7.599 to 8.650 t ha-1, while the simulated biomass ranged from 7.524 to 9.129 t ha-1, with small deviations of (-0.99) to (+ 5.54). The observed dry yield ranged from 4.211 to 5.357 t ha-1 between treatments, while the validated dry yield values ranged from 4.138 to 5.751 t ha-1, with a relatively minor deviation variance of (-1.73) - (+ 7.35). Model validation performance was also evident in the SWC, with observed values ranging from 267.2 to 292.0 mm and simulated values ranging from 284.1 to 294.2 mm, with deviations ranging from (+ 0.38) to (+ 6.77). The observed WPET was between 1.79–1.50 (kg m-3) in the calibration season and 1.99–1.63 (kg m-3) in the validation season. The simulated WPET ranged from 1.86–1.45 (kg m-3) in the calibration season with a deviation of -3.33–4.32% and 2.12–1.60 (kg m-3) in the validation season with a deviation of -1.84–7.45%. 3.3.1. Validation performance on canopy covers (CC) Based on the report suggested by Raes et al , (2022), the obtained performance value on CC were in ranges of very good r ≥ 0.96, good (3.1% ≤ RMSE ≤ 7.7%), good and moderate good (8.2% ≤ NRMSE ≤ 20.8%), Very good (EF ≥ 0.91), and very good (d ≥ 0.98) as shown in Table 6 . Table 5 Aquacrop calibration performance values Treatments Canopy cover Biomass Soil water content r RMSE (%) NRMSE (%) EF D r RMSE (t/ha) NRMSE (%) EF d r RMSE (mm) NRMSE (%) EF d T1 1.00 4.7 12.3 0.98 0.99 1.00 0.3 10.7 0.99 1.00 0.57 15.6 5.3 0.30 0.71 T2 0.99 4.2 11.0 0.98 1.00 1.00 0.3 10.7 0.99 1.00 0.62 14.7 5.0 0.38 0.74 T3 0.99 4.4 11.5 0.98 0.99 1.00 0.3 11.2 0.99 1.00 0.65 15.1 5.3 0.35 0.76 T4 0.99 6.0 17.0 0.95 0.99 0.99 0.5 16.0 0.98 0.99 0.51 16.0 5.7 -1.80 0.51 T5 1.00 3.7 9.8 0.98 1.00 1.00 0.3 9.8 0.99 1.00 0.58 15.0 5.2 0.30 0.71 T6 1.00 3.1 8.2 0.99 1.00 1.00 0.3 8.9 0.99 1.00 0.80 10.2 3.5 0.63 0.87 T7 0.99 6.4 18.7 0.94 0.99 1.00 0.5 18 0.97 0.99 0.45 17.8 6.4 -7.75 0.44 T8 0.97 6.9 20.5 0.93 0.98 1.00 0.5 20.3 0.96 0.99 0.39 16.9 6.1 -22.76 0.26 T9 0.99 4.8 12.9 0.97 0.99 1.00 0.3 11.9 0.99 1.00 0.49 15.0 5.2 0.16 0.67 T10 0.98 6.0 16.2 0.96 0.99 1.00 0.5 15.6 0.98 0.99 0.47 18.5 6.7 -1.57 0.58 T11 0.96 7.4 20.8 0.92 0.98 0.98 0.7 20.2 0.95 0.99 0.38 21.3 7.9 -6.24 0.44 T12 0.99 7.7 20.4 0.91 0.98 0.99 0.7 21.8 0.94 0.98 0.20 24.0 9.0 -4.78 0.40 T13 0.99 6.2 18.3 0.94 0.99 0.99 0.5 16.6 0.97 0.99 0.45 16.9 6.1 -8.13 0.44 3.3.2. Validation performance on biomass (BM) The Aquacrop model validation performance on biomass were very good (r ≥ 0.98), good (0.3t/ha ≤ RMSE ≤ 0.7 t/ha), good and moderate good (8.9% ≤ NRMSE ≤ 21.8%), very good (EF ≥ 0.94), and very good (d ≥ 0.98) as shown in Table 5 and Fig. 6 . 3.3.3. Validation performance on soil water content (SWC) Aquacrop model performance on SWC were 0.20 ≤ r ≤ 0.80 at moderate good and moderate poor, 10.2mm ≤ RMSE ≤ 24.0 mm at better, 3.5% ≤ NRMSE ≤ 9.0% under very good and good, -22.76 ≤ EF ≤ 0.63 under poor, and 0.40 ≤ d ≤ 0.87 under good and moderate poor as shown in Table 5 and Fig. 7 . 3.4. Deficit irrigation effects on crop agronomy and yield attributes The agronomic parameters (PH, CC, HI, number of fruit/plant, and Weight of single fruit) had no significant difference at 1% (Fcal > Fprob) (P ≤ 0.05) as shown in Table 6 . At season 1 experiment, the maximum plant height (91.5 cm) was observed at the application of FI applied throughout the crop period. However, the lowest PH (68.2 cm) was found at the application of 100 V 100 F 25 YF 100 R , which was maximum deficit irrigation was applied. Similarly, the obtained PH, CC, and HI from T2 (75 V 100 F 100 YF 100 R ), and T5 (100 V 100 F 100 YF 75 R ), had no significant difference. Corresponding to this, it had no significant difference at T4 (100 V 100 F 75 YF 100 R ), T9 (100 V 100 F 100 YF 50 R ), and T10 (50 V 100 F 100 YF 100 R ). The maximum weight per single fruit was recorded from full irrigation which had no significant difference with T2, and T5. Additionally, T7 and T13 had no significant difference. The recorded number of fruit per plant at T3 with T9, and T4 with T10 had no significant difference. The observed HI ranged between 54.5–62.1% which was in ranges of 55–65% (Raes et al ., 2022). It is also in ranges of 0.5–0.65 which was suggested by Steduto et al ., 1979). Table 6 Effects of Deficit Irrigation on crop agronomy parameters Treatment Season 1 Season 2 PH (cm) CC (%) HI (%) WtSF (g) NFPP PH (cm) CC (%) HI (%) WtSF (g) NFPP T1 91.5 a 77.3 a 62.1 a 51.4 a 25.8 a 90.2 a 76.6 a 61.9 a 50.0 a 24.0 a T2 89.0 b 75.2 b 62.0 b 51.4a 25.6 b 89.4 ab 76.6 a 61.9 a 49.9 ab 24.0 a T3 86.4 c 74.3 c 61.8 c 50.8 c 24.7 e 88.8 b 75.0 c 61.7 b 49.7 cd 23.2 d T4 85.4 d 73.1 d 60.4 d 50.0 f 24.3 f 86.9 c 73.0 d 60.3 c 49.3 f 22.6 e T5 88.7 b 75.2 b 62.0 b 51.1 a 25.4 c 89.3 ab 76.5 b 61.9 a 49.9 ab 23.7 b T6 86.5 c 74.3 c 61.8 c 51.0 b 25.1 d 88.9 b 75.0 c 61.7 b 49.8 bc 23.4 c T7 79.0 f 68.4 f 59.3 f 49.0 g 23.7 h 84.3 d 69.5 e 59.1 e 48.6 g 21.9 g T8 74.6 g 66.2 g 57.9 h 48.3 h 22.0 i 72.5 e 68.0 g 57.7 f 47.6 i 20.5 i T9 85.6 d 73.1 d 60.4 d 50.6 d 24.6 e 86.9 c 73.0 d 60.3 c 49.6 de 22.5 f T10 85.4 d 73.2 d 60.4 d 50.2 e 24.3 f 86.9 c 73.0 d 60.3 c 49.5 e 22.5 f T11 73.7 h 66.2 g 58.0 g 47.8 i 21.5 j 72.4 e 67.6 h 56.3 g 47.3 j 20.2 j T12 68.2 i 61.1 h 54.5 i 44.0 j 19.6 k 68.0 f 64.0 i 55.4 h 44.1 k 18.7 k T13 80.2 e 69.2 e 59.9 e 49.0 g 24.0 g 84.0 d 68.4 f 59.7 d 48.3 h 21.8 h Fcal 0.794 0.735 1.000 1.929 3.062 1.387 1.867 1.565 0.812 1.00 Fprob 0.463 0.49 0.383 0.167 0.065 0.269 0.176 0.23 0.456 0.383 CV 0.308 0.079 0.027 0.089 0.233 0.661 0.043 0.037 0.193 0.072 LSD 0.429 0.094 0.027 0.075 0.094 0.933 0.052 0.037 0.159 0.027 N.B The same letter in columns are significantly similar at P ≤ 0.05, PH = Plant height, CC = Canopy cover, HI = Harvest index, WtSF = Weight of single fruit, NFPP = Number of fruit per plant, CV = Coefficient of variation, and LSD = Least significant difference. From the second season experiment, the maximum observed PH, CC, HI, weight of single fruit, and number of fruit per plant were observed at T1 (FI) which had no significant difference with T2 (75 V 100 F 100 YF 100 R ). The recorded PH at T1, T2, T3, T5, and T6 had no significant difference. Similarly, T4, and T9 had no significant difference with T10 on PH, CC, HI, weight of single fruit, and number of fruit per plant. In general, the maximum crop agronomy was obtained from the application of FI throughout the growth stage but the minimum was from the application of the 100 V 100 F 25 YF 100 R . As water application depth decreased, crop agronomy decreased. The obtained results are consistent with the findings of Ullah et al ., (2021); Cui et al ., (2019), who conclude that as the obtained crop characteristics decreased as deficit level increased. This result was also in line with the finding of Liu et al., ( 2019 ), who proposed that the application depth of irrigation had direct relationship with the agronomic parameters. The decreasing order of the obtained crop agronomy at the application of deficit irrigation level were at initial, development, late, and mid growth stage, respectively. Therefore, the application of deficit irrigation at mid growth stage (fruit setting stage) shows significant difference than other stages at the same deficit irrigation level. This result is also similar to Patanè, and Cosentino, 2010 ); who note that applying deficit irrigation during the yield formation (flower occurred) and late growth stage decreases the number of reproductive organs. Similar effect was observed with Dasgan et al , (2021); concludes that, application of deficit irrigation at flowering and fruit setting stage decreases the crop yield due to flower abortion, sunburn, warm defect, and fruit disease. The minimum crop agronomy found at the application of deficit irrigation at flowering and yield formation stage and the minimum was from initial growth stage. This result revealed that crop agronomy was reduced as the irrigation water amount is decreased during the fruit development period. There was no adverse impact on the number of flowers when deficit irrigation was applied during the vegetative stage (Atilgan et al ., 2022). 3.5. Deficit irrigation effects on biomass and dry yield The analysis of variance indicated that biomass, and dry yield were significantly the same (P < 1%) as shown in Table 7 . Statistically higher biomass of 8.788 t/ha, and dry yield of 5.458 t/ha was recorded from the application of full irrigation throughout the growth stages (no water deficit). While, the minimum biomass of 7.578 ton/ha and dry yield of 4.131 ton/ha were observed at T12 from the application of 100V100F25YF100R. The obtained biomass (BM) at T2 (75 V 100 F 100 YF 100 R ) was significantly the same as T1 and T5. Similarly, T3 (100 V 75 F 100 YF 100 R ) with T6 (50 V 100 F 100 YF 100 R ), and T4 (100 V 100 F 75 YF 100 R ) with T9 (100 V 100 F 100 YF 50 R ) and T10 (50 V 100 F 100 YF 100 R ) had no significant difference at the experimental seasons. Table 7 Effects of deficit irrigation on dry yield, and biomass Treatments BM (ton/ha) (Season 1) BM (ton/ha) (Season 2) DY (ton/ha) (Season 1) DY (ton/ha) (Season 2) Average BM (Ton/ha) Average DY (Ton/ha) T1 8.788 a 8.650 a 5.458 a 5.357 ab 8.719 a 5.408 a T2 8.768 b 8.650 ab 5.439 b 5.357 a 8.709 b 5.398 b T3 8.747 c 8.630 c 5.408 c 5.325 c 8.689 c 5.367 d T4 8.660 d 8.542 d 5.231 d 5.148 d 8.601 d 5.190 e T5 8.767 b 8.649 b 5.438 b 5.356 b 8.708 b 5.397 c T6 8.748 c 8.630 c 5.408 c 5.325 c 8.689 c 5.367 d T7 8.180 f 8.062 f 4.850 f 4.767 f 8.121 f 4.809 g T8 7.915 g 7.797 h 4.585 g 4.502 g 7.856 h 4.544 h T9 8.661 d 8.543 d 5.231 d 5.148 d 8.602 d 5.190 e T10 8.660 d 8.542 d 5.231 d 5.148 d 8.601 d 5.190 e T11 7.898 h 8.001 g 4.583 h 4.501 h 7.950 g 4.542 i T12 7.578 i 7.599 i 4.131 i 4.211 i 7.589 i 4.171 j T13 8.301 e 8.183 e 4.971 e 4.888 e 8.242 e 4.930 f Fcal 2.182 2.182 3.419 3.326 3.864 4.138 Fprob 0.135 0.135 0.049 0.053 0.035 0.029 CV 0.007 0.005 0.021 0.016 0.004 0.016 LSD 0.001 0.001 0.002 0.001 0.001 0.001 Statistically higher dry yield of 5.458 t/ha was recorded from the application of full irrigation throughout the growth stages (no water deficit) which had no significant difference with T1, and T5. While, the minimum biomass of 7.578 ton/ha and dry yield of 4.131 ton/ha were observed at T12 from the application of 100 V 100 F 25 YF 100 R . Generally, the obtained biomass and dry yield decreases as the application irrigation depth of water decreased. This result in coincides with (Banjaw et al ., 2017), who suggests that the biomass and dry were decreased as the deficit irrigation level increases. These results agreed also with Banjaw et al ., (2017), who observed a decrease in vegetative growth and yield in the application of more deficit irrigations was applied. Likewise, Parkash et al ., 2021), reported a negative effect on biomass and dry yield was observed on more water stress applied than the application of full irrigation. 3.6. Identification of Better Deficit Irrigation Level 3.6.1. Water productivity, irrigation water use efficiency and water use efficiency The optimal deficit irrigation levels were shown in Table 8 , and Fig. 8 . The water productivity were found in ranges of 1.49–1.82kg/m 3 at season 1, and 1.69–1.80 kg/m 3 at season 2 with average values were in ranges of 1.59–1.80 kg/m 3 . The irrigation water use efficiency was in ranges of 19.1–21.1 kg/m 3 at season 1, and 20.6–21.9 kg/m 3 at season 2 with an average value of 19.8–21.4 kg/m 3 . The obtained WUE was 14.0-17.2 kg/m 3 (season 1), and 13.5-15.8kg/m 3 (season 2) with average value ranges between 13.8–16.4 kg/m 3 . The range of WUE values obtained in this study is in the ranges of 13.60–28.84 kg/ m 3 (Dasgan et al ., 2021) in India, 15.5–25.3 kg/m 3 (Wang et al ., 2007) in north china plain under drip irrigation system, 10.5–21.4 kg/m 3 (Kuscu et al ., 2014) in sub humid environment. However, the WUE range obtained in this study was lower than in the ranges of 33.00–42.00 kg/m 3 (Hartz, 1993 ) at California, USA; 18.0–42 kg m 3 (Alghamdi et al ., 2023) under furrow and drip irrigated tomato in Ethiopia; 49.1–79.4 kg/m 3 (Malash et al., 2008 ) under drip irrigation plots in Egypt; and 41.83–68.47 kg/m 3 (Chand et al ., 2020) in a solar greenhouse under different amounts of irrigation. The observed differences are most likely related to the environmental features of different regions, to irrigation methods and to the potential crop productivity (Raes, 2017). The water productivity increments were found in ranges of 1.84–12.09% at season 1, 1.15–3.91% at season 2 with average values of 2.37–8.33% were observed at treatments of T2 – T10 including T13. However, water productivity decrement were observed at T11 with values of 7.38% at season 1, 1.18% at season 2 with average value of 3.77%, and T12 with values of 3.23% at season 1, 1.78% at season 2 with average value of 1.85%. The irrigation water use efficiency increments (improving the yield and water productivity) were found in ranges of 0.49–3.32% at all treatments except treatment of T11 (-0.99%), and T12 (-6.81%) at season 1, 0.20–3.9% at all treatments except treatment T12 (− 2.0%) at season 2 with average values of 2.30–3.60% were observed at treatments of T2 – T10 including T13 except treatment T11 (-0.1%), and T12 (-4.5%). The water use efficiency increments were in ranges of 0.00–10.3% at T2 – T10 including T13 at season 1. However, water use efficiency decrement were observed at treatments of T11 (-1.90%), and T12 (-10. 3%). The water use efficiency increments were observed at treatments of T2 (1.90%), T3 (0.9%), T5 (1.40%), and T6 (1.4%) but no increment/decrement were observed at T4, T9, and T10. However, WUE decrement observed at treatments of T7 (1.40%), T8 (1.40%), T11 (4.8%), T12 (9.00%), and T13 (1.40%) at season 2 experiment. The water use efficiency increment were in ranges of 0.20–6.3% at treatments of T2 – T10 including T13 at averaged experimental season. However, water use efficiency decrement were observed at treatments of T11 (-3.7%), and T12 (-10.7%). This shows that, applying 50, and 75% at any growth stages improves the yield and irrigation water. This result was also in line with the finding of Banjaw et al ., (2017); Yohannes, and Tadesse, (1998), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve the WP ET , and WUE. However, the treatments of T11, and T12 didn’t improve the yield, WP ET , IWUE, and WUE. The best WP ET , IWUE and WUE were found at treatment T6 at the application of 50 V 100 F 100 YF 100 R . The best WUE and IWUE were found at T6 at the application of 50 V 100 F 100 YF 100 R . The WUEI, and IWUEI improves the yield and water use efficiency at T2-T10 including T13. This shows that, applying 50, and 75% at any growth stages improves the yield and water use efficiency. This shows that applying stage wise deficit irrigation improves the yield and water productivity than applying full irrigation (Banjaw et al ., 2017). This result was also in line with the finding of Chand et al., (2020), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve CWUE. However, the WUE, and IWUE were negative at T11, and T12 (didn’t improve the yield and water use efficiency). The best WUE and IWUE were found at T6 at the application of 50 V 100 F 100 YF 100 R . The WUEI, and IWUEI were positive at T2-T10 including T13. This shows that, applying 50, and 75% at any growth stages improves the yield and water use efficiency. This shows that applying stage wise deficit irrigation improves the yield and water productivity than applying full irrigation (Banjaw et al ., 2017). This result was also in line with the finding of (Chand et al ., 2020), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve CWUE. However, the WUE, and IWUE were negative at T11, and T12 (didn’t improve the yield and water use efficiency). Overall, applying 50% and 75% irrigation at any growth stage proved to be optimal at any growth stage including at applying 25% at vegetative and ripening growth stage. Table 8 Water productivity, irrigation water use efficiency, and water use efficiency Season 1 Treatment WP ET (kgm − 3 ) IWUE (kgm − 3 ) WUE (kgm − 3 ) WPI ET (%) IWUII/D (%) WUEI/D (%) T 1 1.60 20.40 15.60 0.00 0.00 0.00 T 2 1.63 20.90 15.80 1.84 2.39 1.30 T 3 1.68 20.80 15.60 4.76 1.92 0.00 T 4 1.80 20.80 16.80 11.11 1.92 7.70 T 5 1.78 20.80 17.00 10.11 1.92 9.00 T 6 1.82 21.10 17.20 12.09 3.32 10.30 T 7 1.69 20.90 16.20 5.33 2.39 3.80 T 8 1.71 20.50 15.80 6.43 0.49 1.30 T 9 1.73 21.00 16.50 7.51 2.86 5.80 T 10 1.74 20.80 16.30 8.05 1.92 4.50 T 11 1.49 20.20 15.30 -7.38 -0.99 -1.90 T 12 1.55 19.10 14.00 -3.23 -6.81 -10.30 T 13 1.71 20.80 16.20 6.43 1.92 3.80 Season 2 Treatment WP ET (kgm − 3 ) IWUE (kgm − 3 ) WUE (kgm − 3 ) WPI ET (%) IWUII/D (%) WUEI/D (%) T 1 1.72 21.10 15.40 0.00 0.00 0.00 T 2 1.76 21.80 15.80 2.27 3.40 1.90 T 3 1.80 21.70 15.60 4.44 3.30 0.90 T 4 1.78 21.80 15.40 3.37 3.30 0.00 T 5 1.78 21.80 15.70 3.37 3.50 1.40 T 6 1.79 21.90 15.70 3.91 3.90 1.40 T 7 1.74 21.60 15.10 1.15 2.50 -1.40 T 8 1.74 21.90 15.10 1.15 3.80 -1.40 T 9 1.78 21.80 15.40 3.37 3.30 0.00 T 10 1.78 21.80 15.40 3.37 3.30 0.00 T 11 1.70 21.10 14.40 -1.18 0.20 -4.80 T 12 1.69 20.60 13.50 -1.78 -2.00 -9.00 T 13 1.76 21.70 15.10 2.27 3.10 -1.40 Average Treatment WP ET (kgm − 3 ) IWUE (kgm − 3 ) WUE (kgm − 3 ) WP ET (%) IWUII/D (%) WUEI/D (%) T 1 1.65 20.70 15.40 0.00 0.00 0.00 T 2 1.69 21.30 15.80 2.37 3.00 2.10 T 3 1.74 21.20 15.60 5.17 2.60 1.00 T 4 1.79 21.20 16.10 7.82 2.30 4.10 T 5 1.78 21.30 16.40 7.30 2.90 6.00 T 6 1.80 21.40 16.40 8.33 3.60 6.30 T 7 1.71 21.20 15.70 3.51 2.40 1.50 T 8 1.72 21.20 15.50 4.07 2.30 0.20 T 9 1.75 21.40 15.90 5.71 3.20 3.30 T 10 1.76 21.20 15.80 6.25 2.60 2.50 T 11 1.59 20.70 14.90 -3.77 -0.10 -3.70 T 12 1.62 19.80 13.80 -1.85 -4.50 -10.70 T 13 1.73 21.20 15.60 4.62 2.60 1.30 The exacerbation of water scarcity due to recent climate changes necessitates the optimization of irrigation water in arid and semi-arid regions. Among those methods, staged based deficit drip irrigation system was the best option. The water productivity of tomatoes varies between 1.49 and 1.82 kg/m 3 in season 1, and between 1.69 and 1.80 kg/m 3 in season 2, with average values ranging from 1.59 to 1.80 kg/m 3 and the irrigation water use efficiency (IWUE) ranged between 19.0–21.1 kg/m 3 at season 1, and 20.6–21.9 kg/m 3 at season 2 experiment with average values ranges between 19.8–21.4 kg/m 3 . The water use efficiency varied from 14.0 to 17.2 kg/m 3 in season 1 and from 13.5 to 15.7 kg/m 3 in season 2, with average values ranging from 13.8 to 16.4 kg/m 3 . The highest water productivity (WP ET ), irrigation water use efficiency (IWUE), and water use efficiency (WUE) were observed at treatment T6 (75 V 100 F 100 YF 100 R) at both experimental seasons. The water productivity (WP ET ) at all treatments was greater than full irrigation water application except treatment T11 and T12 at both experimental seasons. The obtained irrigation water use efficiency (IWUE) was greater at all treatments than full irrigation application except treatments T11, and T12 at season 1 as well as T12 at season 2. Similarly, the obtained water use efficiency (WUE) was greater at all treatments except T11, and T12 at season 1, and T7, T8, T11 and T12 at season 2 experiment. Generally, the average water productivity, irrigation water use efficiency, and water use efficiency were above at all treatments than full irrigation application except treatments of T11 and T12. These shows, the application of staged based deficit irrigation were optimum than the full irrigation application. This result was in line with Yohannes, and Tadesse, (1998); and Malash et al., ( 2008 ); who suggests maximum WP ET , and WUE improves the yield by saving irrigation water. Treatments of at T2 – T10 including T13 were optimal with the water productivity (WP ET ), irrigation water use efficiency (IWUE), water use efficiency (WUE), and fresh yield (FY) increments were in ranges of 2.37–8.33%, 2.30–3.60%, 0.2–6.3%, and 2.0–3.4% respectively. However, the water productivity, irrigation water use efficiency, water use efficiency, and fresh yield decrements were found at treatments of T11 with water productivity of 3.77%, irrigation water use efficiency of 0.1%, 3.7%, and 0.3%, and T12 with water productivity of 1.85%, irrigation water use efficiency of 4.5%, 10.7%, and 4.6% which were not optimal. This implies, the application of irrigation 50, and 75%AW at any growth stage improves the yield by saving water. Compared to the previous studies, the optimal deficit irrigation levels for maximum water productivity appeared in the ranges of 50%-100%ET (Chand et al ., 2020; Corbari et al ., 2023). The obtained result was also in line with the result reported by Yersaw and Lohani, (2022), who suggested that, the application of deficit irrigation below 50%ET was optimal for enhancing the crop yield conducted at Arba Minch, Ethiopia on onion crop using furrow irrigation system. Similarly, Colimba-Limaico et al ., (2022), and Patanè et al ., (2020) observed that the highest levels of water productivity in tomatoes occurring with a 50% irrigation replacement, and in relation to irrigation suspension, the longer the number of days without the irrigation before a harvest, the higher the water productivity. In this study, deficit irrigation treatments reduced total fresh yield during flowering and (yield formation (fruit development) stages; drought stress during these two stages has been found to lead to flower abortion. The minimum yield was obtained at the application of deficit irrigation at flowering and yield formation growth stage but the maximum was at vegetative growth stage. This result linked with the finding of Mukherjee et al ., (2023), water restrictions during vegetative stage can promote root growth, which can stimulate water and nutrient transfer to the plant's vegetative parts. Therefore, it hadn’t affected significantly the yield produced as the deficit irrigation applied at vegetative growth stage; and that the tolerance of tomato to water deficit depends on the cultivar, the growth stage at which the deficit occurs, and the severity of the drought stress (Cui et al ., 2019). 3.6.2. Estimated fresh yield increment/decrement The optimal deficit irrigation levels based on yield increment/decrement were shown in Table 9 and Fig. 9 . The obtained tomato yield ranged from 34.5–53.1 ton/ha from season 1 experiment and 33.0–48.0 ton/ha with average value of 33.8–50.5 t/ha. The maximum yield was 53.1 ton/ha (season 1), and 48.0 t/ha (season 2). These values were in ranges of 45–65 t/ha (El Cham et al ., 2023), and 33.56–54.49 t/ha (Raes et al ., 2022). However, the obtained values were less than the value of 69.1–87.0 t/ha suggested by [72, 73]. This may be due to the report suggested by (Mukherjee et al ., 2023), who suggested that growing tomato crops under dry conditions provides the optimum yield than cropping at high rainfall conditions. The yield obtained had direct relationship with the applied water. The highest fresh yield was obtained at application of FI throughout the growth stage but the lowest from the application of 100 V 100 F 25 YF 100 R . In general, the yield production is reduced as the applied crop water decreases. This result agreed with the findings of Mukherjee et al ., (2023); and El Cham et al ., (2023), who reported that as the deficit irrigation level increases, the yield obtained decreases. This result is also consistent with the findings of Alghamdi et al ., (2023), who suggested that the yield was directly related to the amount of water used. The obtained fresh yield increments, and decrement showed the optimum deficit irrigation level without adverse impact on the yield. The average fresh yield increments were in ranges of 0.5–13.2% at treatments of T2 - T10 including T13 of season 1. However, FYD were observed at treatments of T11 with 0.9%, and T12 with 6.7%. The FYI was observed at all treatments except T12 (− 2.0%) at season 2 experiment, and T11 (-0.3%), and T12 (4.6%) in average experiment. This implies, the application of irrigation 50, and 75%FI at any growth stage improves the yield by saving water. The maximum FYI was observed at the application of 50 V 100 F 100 YF 100 R at the experimental seasons. This irrigation level improves the yield, WUE, and IWUE than the other deficit irrigation level. This result was agreed with the finding of (Chand et al ., 2020); who suggested, farmers should distill their efforts to maximize net income per unit of water used rather than per unit of land by selecting water-saving irrigation methods, like the DI, which generally increases IWUE in water limiting areas. However, FYI was negative at the application of 100 V 100 F 25 YF 100 R , and 100 V 100 F 100 YF 25 R except vegetative, and ripening stage. This result was supported by (Yersaw and Lohani, 2022), who reports all over deficit irrigation level applied at yield formation stage didn’t improve the yield and water use efficiency. Table 9 Identification of better deficit irrigation level on yield increment/decrement Season 1 Treatment FY (t/ha) ETa (mm) WS (m 3 /ha) WS (%) YL (%) FYWS (t) TFY(FY + FYWS) (ton) FYI/D (%) T 1 53.1 260 - - - - 53.1 - T 2 52.6 252 80 2.1 0.7 1.7 54.3 2.2 T 3 50.2 241 190 4.9 4.0 4.0 54.2 2.0 T 4 48.6 234 260 6.7 6.2 5.4 54.0 1.7 T 5 51.9 249 110 2.8 1.7 2.3 54.2 2.1 T 6 51.2 243 170 4.4 2.6 3.6 54.8 3.2 T 7 46.5 222 380 9.7 9.1 8 54.5 2.6 T 8 42.5 207 530 13.6 14.6 10.9 53.4 0.5 T 9 49.8 237 230 5.9 4.6 4.8 54.6 2.9 T 10 48.8 235 250 6.4 5.9 5.2 54.0 1.7 T 11 41.1 203 570 14.6 16.6 11.5 52.6 -0.9 T 12 34.5 181 790 20.3 25.7 15.1 49.6 -6.7 T 13 47 226 340 8.7 8.4 7.1 54.1 1.8 Season 2 Treatment FY (t/ha) ETa (mm) WS (m 3 /ha) WS (%) YL (%) FYWS (t) FY + FYWS (ton) FYI/D (%) T 1 48.0 228 - - - - 48.0 - T 2 47.9 220 80 2.3 0.2 1.7 49.6 3.4 T 3 46.1 212 160 4.7 3.3 3.5 49.6 3.3 T 4 44.6 205 230 6.7 5.8 5.0 49.6 3.3 T 5 47.3 217 110 3.2 1.2 2.4 49.7 3.5 T 6 46.6 213 150 4.4 2.4 3.3 49.9 3.9 T 7 42.5 197 310 9.0 9.4 6.7 49.2 2.5 T 8 40.0 183 450 13.1 13.7 9.8 49.8 3.8 T 9 44.6 205 230 6.7 5.8 5.0 49.6 3.3 T 10 44.6 205 230 6.7 5.8 5.0 49.6 3.3 T 11 38.2 181 470 13.7 16.8 9.9 48.1 0.3 T 12 33.0 160 680 19.8 25.6 14.0 47.0 -2.0 T 13 42.1 194 340 9.9 10.1 7.4 49.5 3.1 Average Treatment FY (t/ha) ETa (mm) WS (m 3 /ha) WS (%) YL (%) FYWS (t) FY + FYWS (ton) FYI/D (%) T 1 50.6 244 0 0 0 0 50.6 0 T 2 50.3 236 80 2.2 0.5 1.7 52 2.8 T 3 48.2 227 173 4.7 3.7 3.7 51.9 2.5 T 4 46.6 220 244 6.7 6.1 5.2 51.8 2.3 T 5 49.6 233 112 3.1 1.5 2.4 52 2.7 T 6 48.9 228 160 4.4 2.6 3.4 52.3 3.4 T 7 44.5 209 346 9.5 9.3 7.4 51.9 2.5 T 8 41.3 195 488 13.4 14.1 10.3 51.6 2.0 T 9 47.2 221 225 6.2 5.2 4.8 52 2.8 T 10 46.7 220 241 6.6 5.9 5.1 51.8 2.4 T 11 39.7 192 519 14.2 16.6 10.7 50.4 -0.3 T 12 33.8 171 731 20.0 25.5 14.5 48.3 -4.6 T 13 44.6 210 337 9.2 9.1 7.2 51.8 2.3 N.B: T = Treatment, ETa = Actual evapotranspiration, WS = Water saved, YL = Yield loss, FYWS = Fresh yield from water saved, and FYI/D = Fresh yield increment/decrement. 3.7. Discussions The calibration performances were very good at the application of 75V100F100YF100R (irrigation of 75% at vegetative stage and full irrigation at the remained growth stage), 100V75F100YF100R (irrigation of 75% at flowering stage and full irrigation at the remained growth stage), (50V100F100YF100R) (irrigation of 50% at vegetative stage and full irrigation at the remained growth stage), and I50F×100R (irrigation of 75% at flowering stage and full irrigation at the remained growth stage) rather than applying full irrigation throughout the growth stages. The model performance decreases as the water stress level increases. Researchers agreed that the AquaCrop model predictions were less accurate in the case of the largest deficit irrigation treatments on canola conducted at semi-arid climate conditions (Khorsand et al., 2022 ), on Common Bean (Striˇcevic, 2023 ), on maize (Daniel et al., 2022 ), and on potato (Wale et al., 2022 ). Aquacrop model performed good on CC, BM, and SWC at the application of 100 V 75 F 100 YF 100 R , 50 V 100 F 100 YF 100 R , 100 V 100 F 100 YF 75 R , and 25 V 100 F 100 YF 100 R . However, it poorly performed at the application of 100 V 100 F 25 YF 100 R , and 100 V 25 F 100 YF 100 R . The AquaCrop model accurately simulated the soil water content (SWC) of the tomato, yet it consistently overestimated SWC across all irrigation treatments (EF ≤ 0.00). In a greenhouse experiment on cherry tomato with plastic film mulch (Cheng et al ., 2022) also observed an overestimation of SWC. However, this result contradicts with the result of Zhou et al., ( 2024 ) on maize, Lindel et al ., (2021); Khorsand et al., ( 2022 ) on Canola, who suggests the Aquacrop model performed well on SWC. The Aqua-crop model over estimate at the application of full irrigation (FI) application and the performance value were poor at high deficit irrigation application. The study conforms to the work of Wale et al., ( 2022 ); Cheng et al ., (2022), who suggests the AquaCrop performance decreases as the application of irrigation depth decreases. The performance of the aqua crop varies crop to crop and cultivars. For example, Daniel et al., ( 2022 ) reported ET underestimation when maize in Northeast China is stressed, while Mengistu et al., ( 2021 ) found a better ET agreement for cotton under water stress than not stressed. The water use efficiency increment were in ranges of 0.20–6.3% at treatments of T2 – T10 including T13 at averaged experimental season. However, water use efficiency decrement were observed at treatments of T11 (-3.7%), and T12 (-10.7%). This shows that, applying 50, and 75% at any growth stages improves the yield and irrigation water. This result was also in line with the finding of Chand et al ., (2020); Yersaw and Lohani, (2022), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve the WP ET , and WUE. However, the treatments of T11, and T12 didn’t improve the yield, WP ET , IWUE, and WUE. The best WP ET , IWUE and WUE were found at treatment T6 at the application of 50 V 100 F 100 YF 100 R . The best WUE and IWUE were found at T6 at the application of 50 V 100 F 100 YF 100 R . The WUEI, and IWUEI were positive at T2-T10 including T13. This shows that, applying 50, and 75% at any growth stages improves the yield and water use efficiency. This result was also in line with the finding of Chand et al ., (2020), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve WUE. However, the WUE, and IWUE were negative at T11, and T12 (didn’t improve the yield and water use efficiency). 4. CONCLUSİONS This study examines seasonal adaptation using integrated seasonal and AquaCrop simulations to evaluate the effects of soil moisture dynamics and drip irrigation on tomato production in southern Ethiopia. Three deficit irrigation levels (75%, 50%, and 25%) were applied across growth stages to identify efficient water management strategies. The AquaCrop model accurately simulated canopy cover, biomass, and dry yield, with the highest performance observed at I50V×100R, I75R×100R, I75F×100R, and I75V×100R, outperforming full irrigation. However, model performance for soil water content was comparatively poor. The best water productivity (WPET) of 1.79 kg/m³ occurred under I50V×100R, similar to I75-based treatments. Across seasons, WP ranged from 1.49–1.82 kg/m³ in Season 1 and 1.69–1.80 kg/m³ in Season 2, while irrigation water use efficiency (IWUE) varied between 19.1–21.1 kg/m³ and 20.6–21.9 kg/m³, respectively. Moderate deficit treatments (T2–T10 and T13) enhanced yield, water productivity, and efficiency by up to 12.1%, whereas severe deficits (T11 and T12) reduced performance by up to 10.7%. The optimal treatment (T6) achieved the highest WP, IWUE, and WUE under 50V100F100YF100R irrigation scheduling. Overall, applying 50–75% irrigation during key growth stages improved yield and water conservation, while irrigation below 25% at flowering or yield formation caused significant losses. The findings demonstrate that deficit irrigation (DI) enhances water productivity and yield stability, particularly under moisture-limited conditions, offering a sustainable adaptation pathway for tomato production in semi-arid regions. Declarations Data Availability Statement (DAS) Data available from the corresponding author on reasonable request Ethical approval Not applicable for this study as it did not involve human or animal subjects. Consent to participate Not applicable Consent to publish All authors consent to the publication of this manuscript. Funding Declaration No funding Clinical trial number Not applicable Acknowledgements The authors would like to express their sincere gratitude to Arba Minch University for providing the demonstration farm for conducting this experimental research. Competing Interests The authors declare no conflict of interest. Author Contributions Babur Tesfaye Yersaw conceived and developed the conceptualization, methodology, data collection, and analysis, in model implementation, result interpretation, original draft preparation, and writing, review, and editing. References Alghamdi Abdulaziz G, Anwar A, Aly, Abdulrasoul M, Al-Omran II, Louki, and Arafat Alkhasha. (2023). 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2","display":"","copyAsset":false,"role":"figure","size":91463,"visible":true,"origin":"","legend":"\u003cp\u003eClimate characteristics of the study area\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/63d452fbe7ac33000001f677.jpg"},{"id":99877160,"identity":"4a3f8af2-b012-4b4d-aac5-5b10fe1b7910","added_by":"auto","created_at":"2026-01-09 10:25:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":146484,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental field layout\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/555b71c932a2c1e39cff75be.jpg"},{"id":99877126,"identity":"45079a9a-a766-4483-8383-ff01ba8fbeb4","added_by":"auto","created_at":"2026-01-09 10:25:42","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":253803,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental supportive field layout\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/8f91dedae3d82d0650870d14.jpg"},{"id":99877147,"identity":"02284ff5-7ed3-4d9b-95ed-a1354018d598","added_by":"auto","created_at":"2026-01-09 10:25:48","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":175776,"visible":true,"origin":"","legend":"\u003cp\u003eValidation Comparison of the observed and simulated CC\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/d1e9dad05785d6c41322aa81.jpg"},{"id":99877144,"identity":"f21a477e-efd1-4dcb-8aba-cd7d43ad4f39","added_by":"auto","created_at":"2026-01-09 10:25:47","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":181389,"visible":true,"origin":"","legend":"\u003cp\u003eValidation comparison of the observed and simulated BM\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/79f09ecad44bdaaa5b09a6f2.jpg"},{"id":99877155,"identity":"0d9d245a-60f7-47c5-953e-8ba675b70f3b","added_by":"auto","created_at":"2026-01-09 10:25:50","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":218154,"visible":true,"origin":"","legend":"\u003cp\u003eValidation comparison of the observed and simulated of SWC\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/fc7e83e012e11bcf8bb7ab1a.jpg"},{"id":99877163,"identity":"91b7cd8c-e51e-4b43-a872-b4e2ce8957ac","added_by":"auto","created_at":"2026-01-09 10:25:51","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":104630,"visible":true,"origin":"","legend":"\u003cp\u003eOptimal deficit irrigation level\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/ff81a08e24690182964c235e.jpg"},{"id":99877103,"identity":"c7da5ecd-3984-4608-b7ab-adae9e707a1f","added_by":"auto","created_at":"2026-01-09 10:25:36","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":83127,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification of optimum deficit irrigation based on yield.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/d0341da20299962aca0a1170.jpg"},{"id":100623339,"identity":"f203a32d-5fdd-4337-9a4a-96e253fb9c7b","added_by":"auto","created_at":"2026-01-19 18:48:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4271442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/784f39b7-b5fb-49b0-bb55-01203e431165.pdf"},{"id":99877124,"identity":"1761dba5-efc6-4d43-a7ea-1b2abd8a45ba","added_by":"auto","created_at":"2026-01-09 10:25:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2183238,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7945516/v1/f24fef3570c4e7049860eea2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adaptation under Integrating Seasonal and AQUACROP Simulations to Evaluate Soil Moisture and Drip Irrigation Effects on Tomato Production in Southern Ethiopia","fulltext":[{"header":"1. INTRODUCTİON","content":"\u003cp\u003eClimate change significantly impacts agriculture, affecting crop yields, water availability, and the livelihoods of farming communities. The increasing frequency of extreme weather events, altered precipitation patterns, and rising temperatures disrupt agricultural systems, leading to food insecurity and economic challenges, particularly in developing nations (Majeed \u003cem\u003eet al\u003c/em\u003e., 2023).\u003c/p\u003e \u003cp\u003eWater scarcity is a critical global problem which is caused by climate change, especially in arid and semi-arid regions, where the availability of this vital resource is severely limited. This issue is acutely felt in Ethiopia, where water scarcity not only threatens the livelihoods of millions but also undermines agricultural productivity and food security (Gorjian \u003cem\u003eet al.\u003c/em\u003e, 2021). The situation is further aggravated by the impacts of climate change, which disrupts traditional rainfall patterns and exacerbates water shortages (Pawlak and Małgorzata, 2020). As the global population continues to increase, the demand for food production intensifies; necessitating innovative solutions to optimize water use in agriculture and ensure sustainable development (Christoforidou \u003cem\u003eet al\u003c/em\u003e., 2022).\u003c/p\u003e \u003cp\u003eTo address the pressing issue of water scarcity, innovations in efficient irrigation technologies are transforming water management in agriculture (Choudhary, 2024; Mallareddy \u003cem\u003eet al\u003c/em\u003e., 2023). These advancements focus on maximizing water use efficiency, minimizing wastage, and optimizing crop yields while reducing the environmental impact of irrigation practices. With developments such as precision irrigation systems, sensor-based technologies, and smart water management solutions, these strategies present promising approaches for promoting sustainable agriculture in a world facing water scarcity. Drip irrigation is an efficient irrigation method that delivers water directly to the root zone of plants using a system of pipes, tubing, and emitters. Unlike traditional surface irrigation and sprinkler irrigation, which distributes water uniformly across an entire field, drip irrigation applies water precisely where needed, reducing evaporation, runoff, and soil erosion (Santosh et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This targeted approach enables precise water control, leading to significant water savings and enhanced crop yields. A key advantage of drip irrigation is its adaptability to various terrains and crop layouts. It can be implemented in fields, greenhouses, and on uneven or sloping land where traditional irrigation methods may not be practical. Drip irrigation is particularly effective for row crops, orchards, vineyards, and high-value specialty crops, where precise water delivery is crucial for optimal growth and yields (Santosh et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yersaw \u003cem\u003eet al\u003c/em\u003e., 2024).\u003c/p\u003e \u003cp\u003eUnder climate change projections, modeling tool can be effectively utilized to simulate crop growth and water productivity. From those modeling tools, the Aqua Crop Model under stage-wise deficit irrigation scenarios could be effective in estimation of the yield and water productivity (Wale et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The significance of this research was advancement of scientific knowledge by addressing a gap in understanding the applicability of crop models in water-limited environments under deficit drip irrigation system, particularly in regions where tomato cultivation plays a significant role in agricultural livelihoods. Moreover, the study provides practical recommendations for farmers, policymakers, and agricultural stakeholders in Southern Ethiopia, aiding in the development of sustainable water management practices and enhancing agricultural productivity in the region by conducting field experiments (Raes \u003cem\u003eet al\u003c/em\u003e., 2022).\u003c/p\u003e \u003cp\u003eIn addition to adopting advanced irrigation technologies, implementing effective irrigation scheduling is essential for optimizing water application (Jones, 2004). This method involves accurately measuring soil moisture levels to determine the precise timing and quantity of irrigation needed (Zhe \u003cem\u003eet al\u003c/em\u003e., 2020). Recent advancements in dielectric sensor technology have made it feasible to monitor soil moisture levels more accurately and affordably, thereby facilitating improved irrigation management practices. By employing techniques such as deficit irrigation, which allows for controlled moisture stress during specific growth stages, farmers can enhance crop yields while conserving water resources. Deficit irrigation represents a promising approach to minimizing water usage without significantly compromising crop yields. This method strategically subjects crops to moisture stress during certain growth phases, allowing for the conservation of water resources that can be redirected to irrigate additional land.\u003c/p\u003e \u003cp\u003eStage-wise deficit irrigation (SWDI) has emerged as a crucial strategy in modern agricultural water management, particularly in the context of increasing water scarcity and the need for sustainable farming practices. This technique involves applying irrigation water at levels below the full crop requirements, optimized according to the crop's critical growth stages. Research indicates that plants respond differently to water stress during various phonological phases; for instance, sensitive stages such as flowering and fruit development are particularly crucial for maximizing yields (Cheng \u003cem\u003eet al.\u003c/em\u003e, 2021). By strategically timing water applications, stage wise deficit irrigation (SWDI) can significantly enhance water use efficiency while maintaining acceptable yield levels, thereby reducing both water input and costs under limited resource conditions (Lu \u003cem\u003eet al\u003c/em\u003e., 2021). Furthermore, recent studies have demonstrated that stage wise deficit irrigation (SWDI) not only supports the economic viability of farming in arid regions but also contributes to improved crop resilience against climate variability, promoting sustainable agriculture (Zhang \u003cem\u003eet al\u003c/em\u003e., 2024).\u003c/p\u003e \u003cp\u003eResearch indicates that this practice can be effective across various climates and agronomic conditions, optimizing water use efficiency while maintaining satisfactory yields (Laita et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yufeng \u003cem\u003eet al\u003c/em\u003e., 2021; Fitsum et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Aziz \u003cem\u003eet al\u003c/em\u003e., 2022; Asmamaw \u003cem\u003eet al\u003c/em\u003e., 2021; Eshete \u003cem\u003eet al\u003c/em\u003e., 2022). However, the effectiveness of deficit irrigation can vary based on numerous factors, including soil types, tomato cultivars, capacity of watering and local climatic conditions (Chand \u003cem\u003eet al\u003c/em\u003e., 2020; Kusumiyati \u003cem\u003eet al\u003c/em\u003e., 2023; Rempelos \u003cem\u003eet al\u003c/em\u003e., 2023). This practice has been implemented across various regions, climates, and agronomic management systems, demonstrating notable effects on yield and water use efficiency (Chand \u003cem\u003eet al\u003c/em\u003e., 2020; Kusumiyati \u003cem\u003eet al\u003c/em\u003e., 2023; Rempelos \u003cem\u003eet al\u003c/em\u003e., 2023). While numerous studies have primarily examined the impacts of deficit irrigation at different levels, focusing on specific factors such as tomato cultivars (Vasile \u003cem\u003eet al\u003c/em\u003e., 2020), soil types (Chand \u003cem\u003eet al\u003c/em\u003e., 2020; Kusumiyati \u003cem\u003eet al\u003c/em\u003e., 2023; Rempelos \u003cem\u003eet al\u003c/em\u003e., 2023; Vasile \u003cem\u003eet al\u003c/em\u003e., 2020), irrigation scheduling types (Fran\u0026ccedil;a \u003cem\u003eet al\u003c/em\u003e., 2024; Yersaw and Lohani, 2022), soil texture (Lu \u003cem\u003eet al\u003c/em\u003e., 2021) and local climate conditions (Rempelos \u003cem\u003eet al\u003c/em\u003e., 2023), these factors have been shown to significantly influence yield outcomes. However, the effects of deficit irrigation can vary considerably depending on the specific soil types, tomato varieties, and climatic characteristics present in a given area (Lu \u003cem\u003eet al\u003c/em\u003e., 2021; Yersaw and Lohani, 2022). Furthermore, certain investigations have explored the implications of deficit irrigation without adopting stage-based approaches, which often hinders the identification of optimal deficit irrigation levels (Cheng \u003cem\u003eet al\u003c/em\u003e., 2022; Burato \u003cem\u003eet al\u003c/em\u003e., 2024; Li \u003cem\u003eet al\u003c/em\u003e., 2022). Consequently, this study aims to identify the optimal deficit irrigation levels by combining irrigation scheduling system under stage wise deficit drip irrigation framework to enhance both yield and water use efficiency for tomato cultivation in the climatic conditions of Arba Minch. By addressing these research gaps, future studies can contribute to the development of more effective water management practices that enhance agricultural productivity in water-scarce regions, ultimately supporting sustainable food production in the face of ongoing climate challenges.\u003c/p\u003e"},{"header":"2. MATERİALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Location, and climate characteristics of the experimental site\u003c/h2\u003e \u003cp\u003eThe field experiment was conducted in the south western part of SNNP regional state at Arba Minch Demonstration farm located 500 km south of Addis Ababa during the period of January to April (season 1) from dry season, and June to September (round 2) from wet season. Geographically it is located at 37\u0026deg;20'00'' \u0026minus;\u0026thinsp;37\u0026deg;38'40''E longitude, 5\u0026deg;45'00'' to 6\u0026deg;10'00''N latitude. The catchment topography of elevation is ranging from 1105 to 3486 m above sea level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom the analysis of thirty-two years of data from 1990 to 2020, showed that, the average minimum and maximum temperature were 17.40\u0026deg;C and 30.63\u0026deg;C. Average annual precipitation is 885.2 mm, necessitating supplemental irrigation during the dry months of January to March and June to August. The rainfall pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicates that irrigation was required during dry seasons from January to March and June to August. The source of irrigation water used in the study area was a canal from Kulfo River which is discharged to Lake Chamo.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Soil properties of the study area\u003c/h2\u003e \u003cp\u003eThe soil characteristics of the experimental field are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The soil properties in the study were soil texture, field capacity, permanent wilting point, and bulk density at every 0.25m for total soil layer of 0.75m. Soil texture is determined by using USDA textural triangle method after obtaining soil particle distribution result from the hydrometer (sedimentation test) analysis. Pressure plate and Pressure membrane apparatus were be used for the determination of soil moisture content at field capacity (FC) and permanent wilting point (PWP) at the suction of -1/3 bar and \u0026minus;\u0026thinsp;15 bar, respectively.\u003c/p\u003e \u003cp\u003eThe average percentage of clay, silt, and sand of the field were 45.78, 33.54, and 20.61% respectively. The dominant soil texture based on sedimentation test and the USDA textural triangle was clay soil throughout the soil profile. The average bulk density (\u003cem\u003epd)\u003c/em\u003e, field capacity (FC), and permanent wilting point (PWP) of the experimental field were 1.11 g/cm\u003csup\u003e3\u003c/sup\u003e, 38.85% and 25.25%, respectively.\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 physiochemical properties of the study area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSoil properties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSoil Layer (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;25\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u0026ndash;50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u0026ndash;75\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClay (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilt (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSand (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil Texture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClay\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulk density (g/cm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWP (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAW (mm/m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e138.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECs(dS/m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\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 \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Treatments design and settings\u003c/h2\u003e \u003cp\u003eThe experiment used a random design with three irrigation levels of 75, 50, 25% of full irrigation including full irrigation as a control applied at four stages of vegetative, flowering, yield formation, and ripening) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExperimental treatment design\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment tag\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreatment description\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e (FI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100%ETa (Full irrigation at all stages)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75%FI at vegetative and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e75\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75%FI at flowering and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e75\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75%FI at yield formation and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e75\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75%FI ripening and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50%FI at vegetative and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e50\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50%FI at flowering and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e50\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50%FI at yield formation and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e50\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50%FI at ripening and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25%FI at vegetative and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e25\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25%FI at flowering and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25%FI at yield formation and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e25\u003csub\u003eR\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25%FI at ripening and FI at remaining stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eN.B: T\u0026thinsp;=\u0026thinsp;Treatment, V\u0026thinsp;=\u0026thinsp;Vegetative, F\u0026thinsp;=\u0026thinsp;Flowering, YF\u0026thinsp;=\u0026thinsp;Yield formation, R\u0026thinsp;=\u0026thinsp;Ripening, ETa\u0026thinsp;=\u0026thinsp;Actual Evapotranspiration, and R\u0026thinsp;=\u0026thinsp;Remaining.\u003c/p\u003e \u003cp\u003e \u003cem\u003eRoma Vf\u003c/em\u003e tomato crop variety were transplanted with row and plant spacing of 40 cm (Cheng \u003cem\u003eet al\u003c/em\u003e., 2022). Each plot has four furrows and ten plants measuring 4 m length by 1.6 m width (6.4 m\u003csup\u003e2\u003c/sup\u003e). The distance between treatments and replication was 0.5 m to avoid the influence of irrigation water from one plot to the next. The experimental field has a total area of 397.9 m\u003csup\u003e2\u003c/sup\u003e (width \u0026times;length\u0026thinsp;=\u0026thinsp;23 m x 17. 3m). The experiment is laid out in random complete block design with three replications as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFull irrigation (FI) refers to the practice of providing crops with the entire amount of water they need to reach their full potential for growth, yield, and development throughout the growing season. This approach aims to meet the water requirements of plants by applying the exact amount of water lost through evapotranspiration (ET), which is the combined loss of water through evaporation from the soil and transpiration from plants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Irrigation scheduling\u003c/h2\u003e \u003cp\u003eThe total available water (TAW) of the experimental field was determined by using Eq.\u0026nbsp;1 (Allen \u003cem\u003eet al\u003c/em\u003e., 1998).\u003c/p\u003e \u003cp\u003eT\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{A}\\text{W}=\\left(\\frac{\\left(\\text{F}\\text{C}-\\text{P}\\text{W}\\text{P}\\right)Pd\\text{*}\\text{D}\\text{r}}{100}\\right)\\text{*}\\frac{1}{\\text{P}\\text{w}}\\)\u003c/span\u003e\u003c/span\u003e \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;. (1)\u003c/p\u003e \u003cp\u003eWhere, TAW\u0026thinsp;=\u0026thinsp;Total available water (mm); FC\u0026thinsp;=\u0026thinsp;Field Capacity (%); PWP\u0026thinsp;=\u0026thinsp;Permanent wilting point (%); \u003cem\u003ePd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Bulk density (g/cm\u003csup\u003e3\u003c/sup\u003e); Dr\u0026thinsp;=\u0026thinsp;Root depth (cm); Pw\u0026thinsp;=\u0026thinsp;Density of water (g/cm\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eBulk density was determined by taking undisturbed soil sample using a core-sampler from six representative places in the trial plot at three different depths (0\u0026ndash;25 cm, 25\u0026ndash;50 cm, and 50\u0026ndash;75 cm). The sampled soil was oven-dried at 105\u0026deg;C for 24 h and weighed to determine the dry weight fraction. Then, bulk density was calculated as the ratio of dry weight of the soil to known cylindrical core sampler volume using Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e2\u003c/span\u003e (Hillel, 2004).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:pd=\\frac{\\text{M}\\text{c}}{\\text{V}\\text{t}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u003c/p\u003e \u003cp\u003eWhere, \u003cem\u003ePd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Bulk Density (g/cm\u003csup\u003e3\u003c/sup\u003e); Mc\u0026thinsp;=\u0026thinsp;Dry Weight of Soil (g); and Vt\u0026thinsp;=\u0026thinsp;Volume of core sampler (cm\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe current soil moisture is measured by Time domain reflector meter (TDR) which has some soil moisture uncertainty. Therefore, it requires calibration to change it into gravimetrical soil moisture. The irrigation date was determined by waiting the current soil moisture reaches at management allowed deficit (MAD) of tomato crop (p\u0026thinsp;=\u0026thinsp;40%) expressed in Eq.\u0026nbsp;(3) (Allen \u003cem\u003eet al\u003c/em\u003e., 1998).\u003c/p\u003e \u003cp\u003eRAM\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\left(\\frac{\\left(\\text{F}\\text{C}-\\text{P}\\text{W}\\text{P}\\right)\\text{P}\\text{b}\\text{*}\\text{D}\\text{r}}{100}\\right)\\text{*}\\frac{1}{\\text{P}\\text{w}}\\)\u003c/span\u003e\u003c/span\u003e *p\u0026thinsp;=\u0026thinsp;TAW*p\u0026thinsp;=\u0026thinsp;40%TAW \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;. (3)\u003c/p\u003e \u003cp\u003eWhere, RAM\u0026thinsp;=\u0026thinsp;Readily available moisture (mm), and p\u0026thinsp;=\u0026thinsp;Depletion level (%).\u003c/p\u003e \u003cp\u003eThe irrigation was applied at which the current soil moisture (Ɵi) reaches to readily available moisture (RAM) for full irrigation application and the other treatments gain irrigation based on the deficit irrigation levels of 75%, 50%, and 25% varied with growth stages. The irrigation depth were applied back to the filed capacity by measured the root depth at each irrigation time using Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e4\u003c/span\u003e, and converted to volume using Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e5\u003c/span\u003e (Borena, and Seyoum, 2021; Yerli \u003cem\u003eet al\u003c/em\u003e., 2023).\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{E}\\text{T}\\text{a}\\:=\\:\\frac{\\left(\\text{Ɵ}\\text{F}\\text{C}-\\text{Ɵ}\\text{i}\\right)\\text{*}Pb\\text{*}\\text{D}\\text{r}\\text{*}\\text{D}\\text{w}}{10}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\text{V}=\\text{E}\\text{T}\\text{a}\\text{*}\\text{A}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u003c/p\u003e \u003cp\u003eWhere, ETa\u0026thinsp;=\u0026thinsp;Actual crop evapotranspiration (mm), ƟFC\u0026thinsp;=\u0026thinsp;Moisture retained at field capacity (%), Ɵi\u0026thinsp;=\u0026thinsp;Current moisture before irrigation (%), \u003cem\u003ePd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Bulk density (g/cm\u003csup\u003e3\u003c/sup\u003e), Dr\u0026thinsp;=\u0026thinsp;Root depth (cm), Dw\u0026thinsp;=\u0026thinsp;Wetting fraction, V\u0026thinsp;=\u0026thinsp;Volume (L) and A\u0026thinsp;=\u0026thinsp;Area of plot (6.4m\u003csup\u003e2\u003c/sup\u003e). The wetting fraction used in this study was 0.3 (30%) taken from FAO (Allen \u003cem\u003eet al\u003c/em\u003e., 1998), the surface wetting fraction for drip irrigation ranged between 0.30\u0026ndash;0.40.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Water Application System\u003c/h2\u003e \u003cp\u003eA gravity drip system was used to supply irrigation water to the experimental plots. Drip system consists of Polyvinyl Chloride main lines, and drip laterals. The plots were leveled manually to create uniform plots within the given treatment. There are 39 plots with four laterals per plot. Hence, each plot consisted of four drip lateral lines which had 4m length and consists of 10 emitters (holes). The number of emitters per plant was kept at one and with 1.2 l/hr flow rate fixed for all treatments determined from measuring and calibrated by measuring cylinder. A barrel (drum) of 300 liter capacity is mounted on a stand at a head up to 1.25 m above the ground level. The flow rate was determined by calibration by increasing and decreasing the head of the barrel (drum) at each treatment. The barrel top was covered in order to prevent evaporation loss. One 40 mm diameter size of main line and five lateral line which had diameter of 10 mm used. Operating duration of each treatment varied according to irrigation schedules (irrigation level) and calculated using Eq.\u0026nbsp;\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e6\u003c/span\u003e (Doorenbos, and Pruitt, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1975\u003c/span\u003e).\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:\\text{T}=\\frac{\\text{G}\\text{I}\\text{R}\\text{*}\\text{R}\\text{s}\\text{*}\\text{P}\\text{s}\\text{*}\\text{N}}{\\text{q}\\text{e}}=\\frac{V}{qe}\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003c/p\u003e \u003cp\u003eWhere, Rs\u0026thinsp;=\u0026thinsp;Plant row spacing (cm), Ps\u0026thinsp;=\u0026thinsp;Plant spacing (cm), N\u0026thinsp;=\u0026thinsp;number of dripper present at each treatment (N\u0026thinsp;=\u0026thinsp;40), and qe\u0026thinsp;=\u0026thinsp;Emitter flow rate (l/hr).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Method of Crop data collection\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.6.1. Ethics and consent to participate\u003c/h2\u003e \u003cp\u003eTomato seeds and plant materials used in this study were cultivated in accordance with Ethiopian national agricultural guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.6.2. Plant Materials\u003c/h2\u003e \u003cp\u003eTomato seeds used in this study were obtained from the Arba Minch University Demonstration Farm, Southern Ethiopia. Field trials were conducted at the experimental farm of Arba Minch University, located at 6\u0026deg;03\u0026prime; N, 37\u0026deg;34\u0026prime; E.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.6.3. Crop data collected\u003c/h2\u003e \u003cp\u003eThe leaf length (cm) and leaf width (cm) of plants from each treatment were measured using tape mete every 10 days. The leaf area (A) (Eq.\u0026nbsp;\u003cspan refid=\"Equ5\" class=\"InternalRef\"\u003e7\u003c/span\u003e), leaf area index (LAI) (Eq.\u0026nbsp;\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e8\u003c/span\u003e) and the canopy cover (CC) (Eq.\u0026nbsp;\u003cspan refid=\"Equ7\" class=\"InternalRef\"\u003e9\u003c/span\u003e) were calculated from the leaf length and leaf width. The total leaf area (cm\u003csup\u003e2\u003c/sup\u003e) for tomato leaves was calculated using a relationship based on (Schwarz and Kl\u0026auml;ring, 2006) using Eq.\u0026nbsp;\u003cspan refid=\"Equ5\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The leaf area index was obtained by the ratio of total leaf area of the crop per unit of ground area using Eq.\u0026nbsp;\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Canopy cover (CC, %) was converted by the LAI data using Eq.\u0026nbsp;\u003cspan refid=\"Equ7\" class=\"InternalRef\"\u003e9\u003c/span\u003e (Raes, 2017).\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:\\text{A}=0.2695\\text{*}{\\text{L}}^{0.4759}\\text{*}{\\text{W}}^{1.4184}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:\\text{L}\\text{A}\\text{I}=\\frac{\\text{M}\\text{e}\\text{a}\\text{s}\\text{u}\\text{r}\\text{e}\\text{d}\\:\\text{l}\\text{e}\\text{a}\\text{f}\\:\\text{a}\\text{r}\\text{e}\\text{a}\\:\\text{p}\\text{e}\\text{r}\\:\\text{p}\\text{l}\\text{a}\\text{n}\\text{t}\\:{\\text{c}\\text{m}}^{2}}{100\\text{*}100}\\text{*}\\frac{\\text{n}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{p}\\text{l}\\text{a}\\text{n}\\text{t}\\text{s}}{{\\text{m}}^{2}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;...\u0026hellip;\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\:CC=1.005*{\u0026lceil;1-Exp\\left(-0.6LAI\\right)\u0026rceil;}^{1.2}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003c/p\u003e \u003cp\u003eFresh yield (ton/ha), and weight of single fruit were measured at the harvest time and measured by sensitive balance. Above ground biomass (BM), and dry yield (DY) data samples were taken out at the harvest time for each treatment. The dry biomass of each sample was determined by weighing it after it had been held in an oven for 48 hours at 65\u0026deg;C and the harvest index (HI) was the ratio of dry yield and above ground biomass as shown in Eq.\u0026nbsp;\u003cspan refid=\"Equ8\" class=\"InternalRef\"\u003e10\u003c/span\u003e (Yersaw \u003cem\u003eet al\u003c/em\u003e., 2024; Raes Dirk, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Raes, 2023).\u003cdiv id=\"Equ8\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ8\" name=\"EquationSource\"\u003e\n$$\\:\\text{H}\\text{I}=\\:\\left(\\frac{\\text{D}\\text{Y}}{\\text{B}\\text{M}}\\right)\\text{*}100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e10\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;..\u0026hellip;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Identification of Optimum Deficit Irrigation\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.7.1. Water productivity, irrigation water use efficiency, and Water use efficiency\u003c/h2\u003e \u003cp\u003eWater productivity (WP\u003csub\u003eET\u003c/sub\u003e) is the ratio of dry yield (Yd) per crop transpired [35\u0026ndash;36] as shown in Eq.\u0026nbsp;\u003cspan refid=\"Equ9\" class=\"InternalRef\"\u003e11\u003c/span\u003e, irrigation water-use efficiency (IWUE, kg/m\u003csup\u003e3\u003c/sup\u003e) was calculated as the marketable fruit yield (kg/ha) obtained per unit volume of seasonal irrigation water applied (m\u003csup\u003e3\u003c/sup\u003e/ha) as shown in Eq.\u0026nbsp;12 (Kuscu Hayrettin, Ahmet Turhan, Nese Ozmen, Pinar Aydinol, and Ali Osman Demir, 2014)[40] and Water use efficiency (WUE) was the ratio of fresh yield per unit volume of seasonal evapotranspiration (ET) as shown in Eq.\u0026nbsp;\u003cspan refid=\"Equ10\" class=\"InternalRef\"\u003e13\u003c/span\u003e (Raes, 2017; Raes, 2023).\u003cdiv id=\"Equ9\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ9\" name=\"EquationSource\"\u003e\n$$\\:{\\text{W}\\text{P}}_{\\text{E}\\text{T}}=\\frac{\\text{Y}\\text{d}}{\\text{E}\\text{T}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e11\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u003c/p\u003e \u003cp\u003eIWUE\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\frac{\\text{F}\\text{Y}}{\\text{E}\\text{T}\\text{a}}\\)\u003c/span\u003e\u003c/span\u003e \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip; (12)\u003cdiv id=\"Equ10\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ10\" name=\"EquationSource\"\u003e\n$$\\:\\text{W}\\text{U}\\text{E}=\\frac{\\text{F}\\text{Y}}{\\text{E}\\text{T}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e13\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;\u003c/p\u003e \u003cp\u003eWhere; WP\u003csub\u003eET\u003c/sub\u003e = Water productivity (kg/m\u003csup\u003e3\u003c/sup\u003e), Yd\u0026thinsp;=\u0026thinsp;Dry yield (ton/ha), ET\u0026thinsp;=\u0026thinsp;Evapotranspiration (mm), IWUE\u0026thinsp;=\u0026thinsp;Irrigation water use efficiency (Kg/m\u003csup\u003e3\u003c/sup\u003e), FY\u0026thinsp;=\u0026thinsp;Fresh yield (t/ha), and ETa\u0026thinsp;=\u0026thinsp;Actual Evapotranspiration (mm), and WUE\u0026thinsp;=\u0026thinsp;Water Use Efficiency (Kg/m\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe amount of water saved (WS) per hectare can be obtained by subtracting the amount of water consumption of particular deficit irrigation from the full irrigation requirement using Eq.\u0026nbsp;\u003cspan refid=\"Equ11\" class=\"InternalRef\"\u003e14\u003c/span\u003e (Hassene, and Seid 2017). Additional fresh yield estimated at deficit irrigation levels from water saved can be estimated by the ratio of the multiplication of the fresh yield gain and water saved with the actual evapotranspiration at corresponding treatments using Eq.\u0026nbsp;\u003cspan refid=\"Equ12\" class=\"InternalRef\"\u003e15\u003c/span\u003e (Yersaw and Lohani, 2022). The fresh yield increments can be calculated by subtracting the total fresh yield of each treatment from full irrigation by using Eq.\u0026nbsp;\u003cspan refid=\"Equ13\" class=\"InternalRef\"\u003e16\u003c/span\u003e (Yerli \u003cem\u003eet al\u003c/em\u003e., 2023); (Hassene, and Seid, 2017).\u003cdiv id=\"Equ11\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ11\" name=\"EquationSource\"\u003e\n$$\\:\\text{W}\\text{S}=\\frac{(\\text{E}\\text{T}\\text{a}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}-\\text{E}\\text{T}\\text{a}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{d}\\text{e}\\text{f}\\text{i}\\text{c}\\text{i}\\text{t}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{l}\\text{e}\\text{v}\\text{e}\\text{l})\\text{*}100}{\\text{E}\\text{T}\\text{a}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e14\u003c/div\u003e\u003c/div\u003e\u0026hellip;.\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;\u0026hellip;.\u003cdiv id=\"Equ12\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ12\" name=\"EquationSource\"\u003e\n$$\\:\\:\\text{F}\\text{Y}\\text{W}\\text{S}=\\frac{\\text{F}\\text{Y}\\text{*}\\text{W}\\text{S}}{\\text{E}\\text{T}\\text{a}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{d}\\text{e}\\text{f}\\text{i}\\text{c}\\text{i}\\text{t}\\:\\text{l}\\text{e}\\text{v}\\text{e}\\text{l}\\text{s}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e15\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;\u0026hellip;..\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003cdiv id=\"Equ13\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ13\" name=\"EquationSource\"\u003e\n$$\\:\\text{F}\\text{Y}\\frac{\\text{i}\\text{n}\\text{c}\\text{r}\\text{e}\\text{m}\\text{e}\\text{n}\\text{t}}{\\text{d}\\text{e}\\text{c}\\text{r}\\text{e}\\text{m}\\text{e}\\text{n}\\text{t}}=\\:\\left(\\frac{\\text{T}\\text{F}\\text{Y}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}-\\:\\text{T}\\text{F}\\text{Y}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{d}\\text{e}\\text{f}\\text{i}\\text{c}\\text{i}\\text{t}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:}{\\text{T}\\text{F}\\text{Y}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}\\right)*100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e16\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;.\u003c/p\u003e \u003cp\u003eWhere, WS\u0026thinsp;=\u0026thinsp;Water saved (%), ETa\u0026thinsp;=\u0026thinsp;Actual evapotranspiration (mm), FYWS\u0026thinsp;=\u0026thinsp;Fresh yield from water saved (ton/ha), FY\u0026thinsp;=\u0026thinsp;Fresh Yield (ton/ha), and TFY\u0026thinsp;=\u0026thinsp;Total fresh yield (ton/ha).\u003c/p\u003e \u003cp\u003eThe increment/decrement percentage of evapotranspiration water productivity, water use efficiency, and irrigation water use efficiency can be calculated by using Eq.\u0026nbsp;17\u0026ndash;19 13 (Raes, 2017; Raes, 2023).\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{W}\\text{P}}_{\\text{E}\\text{T}}\\)\u003c/span\u003e \u003c/span\u003e Increment/decrement = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{{\\text{W}\\text{P}}_{\\text{E}\\text{T}\\:\\:}\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}{{\\text{W}\\text{P}}_{\\text{E}\\text{T}}\\:\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{d}\\text{e}\\text{f}\\text{i}\\text{c}\\text{i}\\text{t}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{l}\\text{e}\\text{v}\\text{e}\\text{l}}\\right)*100\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip; (17)\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:\\text{W}\\text{U}\\text{E}\\:\\text{I}\\text{n}\\text{c}\\text{r}\\text{e}\\text{m}\\text{e}\\text{n}\\text{t}/\\text{d}\\text{e}\\text{c}\\text{r}\\text{e}\\text{m}\\text{e}\\text{n}\\text{t}\\)\u003c/span\u003e \u003c/span\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{\\text{W}\\text{U}\\text{E}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}{\\text{W}\\text{U}\\text{E}\\:\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{d}\\text{e}\\text{f}\\text{i}\\text{c}\\text{i}\\text{t}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{l}\\text{e}\\text{v}\\text{e}\\text{l}}\\right)*100\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;,\u0026hellip;\u0026hellip;\u0026hellip; (18)\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:\\text{I}\\text{W}\\text{U}\\text{E}\\:\\text{I}\\text{n}\\text{c}\\text{r}\\text{e}\\text{m}\\text{e}\\text{n}\\text{t}/\\text{d}\\text{e}\\text{c}\\text{r}\\text{e}\\text{m}\\text{e}\\text{n}\\text{t}\\)\u003c/span\u003e \u003c/span\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{\\text{I}\\text{W}\\text{U}\\text{E}\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{f}\\text{u}\\text{l}\\text{l}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}{\\text{I}\\text{W}\\text{U}\\text{E}\\:\\:\\text{f}\\text{r}\\text{o}\\text{m}\\:\\text{d}\\text{e}\\text{f}\\text{i}\\text{c}\\text{i}\\text{t}\\:\\text{i}\\text{r}\\text{r}\\text{i}\\text{g}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{l}\\text{e}\\text{v}\\text{e}\\text{l}}\\right)*100\\)\u003c/span\u003e\u003c/span\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip; (19)\u003c/p\u003e \u003cp\u003eWhere, WP\u003csub\u003eET\u003c/sub\u003e = Evapotranspiration water productivity (%), WUE\u0026thinsp;=\u0026thinsp;Water use efficiency (%), IWUE\u0026thinsp;=\u0026thinsp;Irrigation water use efficiency (%).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe collected data were statistically analyzed using SAS software using a procedure of general linear model for the variance analysis. Mean comparisons were executed using the least significant difference (LSD) of 1% and the graph was illustrated using Origin lab pro 2024.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS AND DİSCUSSİONS","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Actual evapotranspiration, evapotranspiration, and gross depth of irrigation water applied\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the irrigation water amounts applied to the experimental treatments, along with the gross irrigation and seasonal evapotranspiration values for the study period. The actual evapotranspiration (ETa) for the full irrigation application during the vegetative, flowering, yield formation, and ripening stages was 17.8, 62.7, 134.5, and 45 mm for season 1. For season 2, the actual evapotranspiration (ETa) for the vegetative, flowering, yield formation, and ripening stages values were 14.5, 63.9, 104.5, and 45 mm, respectively. The smallest irrigation depths required were observed at vegetative stage, increased up to the yield formation growth stage, and decreased at ripening growth stage at all irrigation levels. Like any other crops, tomato crop require relatively large amount of water during mid-stage (yield formation) followed by ripening growth stage. The obtained result in agreement to the result reported by Lu \u003cem\u003eet al\u003c/em\u003e., (2019), who suggested that, the irrigation requirement of tomato crop was low at the vegetative stage, increased during flowering stage, reached maximum at yield formation stage and slightly declined during harvesting stage. This is also supported by Dirirsa \u003cem\u003eet al\u003c/em\u003e., (2017), who suggested high amount of irrigation depth was applied at mid (yield formation) stage to substitute the evaporation rate due to the presence of high canopy cover which increases the evaporation rate of leaf.\u003c/p\u003e \u003cp\u003eThe average seasonal actual evapotranspiration (ETa), gross irrigation, and evapotranspiration, varied between 171\u0026ndash;244, 180\u0026ndash;257, and 245-327mm, respectively. The highest seasonal ETa was recorded in the full irrigation application, clearly owing to favorable soil moisture during the growing period, whereas the lowest seasonal ETa was recorded in T12, with a prolonged water deficit after the vegetative period recorded in the application of 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e with a prolonged water deficit. The estimated ET values for tomato at full irrigation application was 341 mm at season 1 and 312 mm for the same treatment at season 2 with average value of 327mm. This value is in consistent with in the ranges of 237.5-514.4 mm (Hong \u003cem\u003eet al\u003c/em\u003e., 2022), 215\u0026ndash;841 mm for tomato crop (Mukherjee et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In contradict; this value was less than in ranges of the water requirement of tomato (400-600mm) (Allen \u003cem\u003eet al\u003c/em\u003e., 1998) depending on the climate and the total length of the growing period. The variation may be due to, climate, water supply, soil, and topography, temperature, precipitation, humidity, wind movement and growing-season length, which have the greatest effect on evapotranspiration (Ndiaye \u003cem\u003eet al\u003c/em\u003e., 2020).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStage wise actual gross irrigation and evapotranspiration depth applied (mm).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"13\" nameend=\"c14\" namest=\"c2\"\u003e \u003cp\u003eSeason 1\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eT6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eT7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eT8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eT9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eT10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eT11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eT12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eT13\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eETa (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eET (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e291\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c14\" namest=\"c2\"\u003e \u003cp\u003eSeason 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eETa (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eET (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage ETa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage ET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eN.B\u003c/strong\u003e \u003cp\u003eV\u0026thinsp;=\u0026thinsp;Vegetative, F\u0026thinsp;=\u0026thinsp;Flowering, YF\u0026thinsp;=\u0026thinsp;Yield formation, R\u0026thinsp;=\u0026thinsp;Ripening, ETa\u0026thinsp;=\u0026thinsp;Actual evapotranspiration, GIR\u0026thinsp;=\u0026thinsp;Gross irrigation requirement, and ET\u0026thinsp;=\u0026thinsp;Evapotranspiration.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Calibration of Aqua-Crop\u003c/h2\u003e \u003cp\u003eThe observed and simulated dry yield (DY), biomass (BM), soil water content (SWC) and water productivity (WP\u003csub\u003eET\u003c/sub\u003e) of the Aqua-crop model, focused on the performance of calibration and validation, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Calibration was performed for all deficit irrigation treatments under conditions of water stress only (no nutrient or salinity stress). During calibration, observed biomass ranged from 7.578 to 8.788 t/ha, while simulated biomass ranged from 7.280 to 9.129 t/ha, with deviations between +\u0026thinsp;3.74% and \u0026minus;\u0026thinsp;4.09%. For dry yield during the same period, observed values ranged from 4.131 to 5.458 t/ha, and simulated values ranged from 3.987 to 5.751 t/ha, with errors between +\u0026thinsp;5.37% and \u0026minus;\u0026thinsp;3.49%. The model also showed reasonable calibration for SWC, with observed values between 270.9 and 281.2 mm and simulated values between 268.0 and 285.6 mm, resulting in deviations from \u0026minus;\u0026thinsp;2.05% to +\u0026thinsp;1.58%. The highest BM, DY, and WPET were observed under full irrigation (FI), while the lowest values were associated with the I25YF\u0026times;100R treatment (25% irrigation at yield formation and full irrigation for the remaining stages). Generally, BM, DY, and WPET decreased with decreasing water application depth. This trend aligns with findings from Yersaw \u0026amp; Lohani (2022) and Banjaw \u003cem\u003eet al\u003c/em\u003e. (2017), who reported reductions in biomass and yield with increasing deficit irrigation levels. Similarly, Wang \u003cem\u003eet al\u003c/em\u003e. (2011) observed a negative impact of increased water stress on biomass and dry yield compared to full irrigation.\u003c/p\u003e \u003cp\u003eThe Aquacrop performance on canopy covers was shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Based on the performance classification by Raes et al. (2022), the model demonstrated good calibration for CC, achieving r\u0026thinsp;\u0026ge;\u0026thinsp;0.96, 2.9%\u0026le;RMSE\u0026thinsp;\u0026le;\u0026thinsp;8.0%, 7.5%\u0026le;NRMSE\u0026thinsp;\u0026le;\u0026thinsp;21.1%, 0.91\u0026thinsp;\u0026le;\u0026thinsp;EF\u0026thinsp;\u0026le;\u0026thinsp;0.99, and 0.98\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026le;\u0026thinsp;1.00. Specifically, under full irrigation (FI), the model yielded values of r\u0026thinsp;=\u0026thinsp;1.00, RMSE\u0026thinsp;=\u0026thinsp;4.3%, NRMSE\u0026thinsp;=\u0026thinsp;11.1%, EF\u0026thinsp;=\u0026thinsp;0.98, and d\u0026thinsp;=\u0026thinsp;1.00. In contrast, under high deficit irrigation (DI), the performance metrics were r\u0026thinsp;=\u0026thinsp;0.96, RMSE\u0026thinsp;=\u0026thinsp;8.0%, NRMSE\u0026thinsp;=\u0026thinsp;21.1%, EF\u0026thinsp;=\u0026thinsp;0.91, and d\u0026thinsp;=\u0026thinsp;0.98, indicating a performance range from well to excellent. The model also performed well on BM with r\u0026thinsp;\u0026ge;\u0026thinsp;0.99 (very good), 0.3t/ha\u0026thinsp;\u0026le;\u0026thinsp;RMSE\u0026thinsp;\u0026le;\u0026thinsp;0.8t/ha (very good), 8.3% \u0026le; NRMSE\u0026thinsp;\u0026le;\u0026thinsp;25.2% (very good and moderate good), 0.92\u0026thinsp;\u0026le;\u0026thinsp;EF\u0026thinsp;\u0026le;\u0026thinsp;0.99 (very good), and 0.98\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026le;\u0026thinsp;1.00 (very good). The AquaCrop model's performance in simulating soil water content (SWC), which ranged from moderate to good based on various statistical indicators. Correlation coefficients (0.54\u0026thinsp;\u0026le;\u0026thinsp;r\u0026thinsp;\u0026le;\u0026thinsp;0.82) suggested a moderate to good relationship between simulated and observed values. The Root Mean Square Error (3.60 mm\u0026thinsp;\u0026le;\u0026thinsp;RMSE\u0026thinsp;\u0026le;\u0026thinsp;24.4 mm) and Normalized Root Mean Square Error (1.30%\u0026le;NRMSE\u0026thinsp;\u0026le;\u0026thinsp;9.00%) indicated very good to moderate good model accuracy. However, the Nash-Sutcliffe Efficiency (\u0026minus;\u0026thinsp;4.18\u0026thinsp;\u0026le;\u0026thinsp;EF\u0026thinsp;\u0026le;\u0026thinsp;0.00) indicated poor model efficiency. The index of agreement (0.66\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026le;\u0026thinsp;0.81) suggested good to moderate good agreement between the simulated and observed SWC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAquacrop calibration performance values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eCanopy cover\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003eBiomass (\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c17\" namest=\"c13\"\u003e \u003cp\u003eSoil water content\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSE (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNRMSE (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRMSE (t/ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNRMSE (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eRMSE (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eNRMSE (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003ed\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e11.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e19.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e9.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e17.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e6.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e24.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e10.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.78\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 \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Validation of Aquacrop\u003c/h2\u003e \u003cp\u003eThe Aquacrop validation was made at each treatment based on the observed and simulated data\u0026rsquo;s is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. During validation, the observed biomass ranged from 7.599 to 8.650 t ha-1, while the simulated biomass ranged from 7.524 to 9.129 t ha-1, with small deviations of (-0.99) to (+\u0026thinsp;5.54). The observed dry yield ranged from 4.211 to 5.357 t ha-1 between treatments, while the validated dry yield values ranged from 4.138 to 5.751 t ha-1, with a relatively minor deviation variance of (-1.73) - (+\u0026thinsp;7.35). Model validation performance was also evident in the SWC, with observed values ranging from 267.2 to 292.0 mm and simulated values ranging from 284.1 to 294.2 mm, with deviations ranging from (+\u0026thinsp;0.38) to (+\u0026thinsp;6.77). The observed WPET was between 1.79\u0026ndash;1.50 (kg m-3) in the calibration season and 1.99\u0026ndash;1.63 (kg m-3) in the validation season. The simulated WPET ranged from 1.86\u0026ndash;1.45 (kg m-3) in the calibration season with a deviation of -3.33\u0026ndash;4.32% and 2.12\u0026ndash;1.60 (kg m-3) in the validation season with a deviation of -1.84\u0026ndash;7.45%.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. Validation performance on canopy covers (CC)\u003c/h2\u003e \u003cp\u003eBased on the report suggested by Raes \u003cem\u003eet al\u003c/em\u003e, (2022), the obtained performance value on CC were in ranges of very good r\u0026thinsp;\u0026ge;\u0026thinsp;0.96, good (3.1% \u0026le; RMSE\u0026thinsp;\u0026le;\u0026thinsp;7.7%), good and moderate good (8.2% \u0026le; NRMSE\u0026thinsp;\u0026le;\u0026thinsp;20.8%), Very good (EF\u0026thinsp;\u0026ge;\u0026thinsp;0.91), and very good (d\u0026thinsp;\u0026ge;\u0026thinsp;0.98) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAquacrop calibration performance values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCanopy cover\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eBiomass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eSoil water content\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSE (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNRMSE\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRMSE (t/ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNRMSE (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eRMSE (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNRMSE\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003ed\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-7.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-22.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-6.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e-8.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. Validation performance on biomass (BM)\u003c/h2\u003e \u003cp\u003eThe Aquacrop model validation performance on biomass were very good (r\u0026thinsp;\u0026ge;\u0026thinsp;0.98), good (0.3t/ha\u0026thinsp;\u0026le;\u0026thinsp;RMSE\u0026thinsp;\u0026le;\u0026thinsp;0.7 t/ha), good and moderate good (8.9% \u0026le; NRMSE\u0026thinsp;\u0026le;\u0026thinsp;21.8%), very good (EF\u0026thinsp;\u0026ge;\u0026thinsp;0.94), and very good (d\u0026thinsp;\u0026ge;\u0026thinsp;0.98) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. Validation performance on soil water content (SWC)\u003c/h2\u003e \u003cp\u003eAquacrop model performance on SWC were 0.20\u0026thinsp;\u0026le;\u0026thinsp;r\u0026thinsp;\u0026le;\u0026thinsp;0.80 at moderate good and moderate poor, 10.2mm\u0026thinsp;\u0026le;\u0026thinsp;RMSE\u0026thinsp;\u0026le;\u0026thinsp;24.0 mm at better, 3.5% \u0026le; NRMSE\u0026thinsp;\u0026le;\u0026thinsp;9.0% under very good and good, -22.76\u0026thinsp;\u0026le;\u0026thinsp;EF\u0026thinsp;\u0026le;\u0026thinsp;0.63 under poor, and 0.40\u0026thinsp;\u0026le;\u0026thinsp;d\u0026thinsp;\u0026le;\u0026thinsp;0.87 under good and moderate poor as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Deficit irrigation effects on crop agronomy and yield attributes\u003c/h2\u003e \u003cp\u003eThe agronomic parameters (PH, CC, HI, number of fruit/plant, and Weight of single fruit) had no significant difference at 1% (Fcal\u0026thinsp;\u0026gt;\u0026thinsp;Fprob) (P\u0026thinsp;\u0026le;\u0026thinsp;0.05) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAt season 1 experiment, the maximum plant height (91.5 cm) was observed at the application of FI applied throughout the crop period. However, the lowest PH (68.2 cm) was found at the application of 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e, which was maximum deficit irrigation was applied. Similarly, the obtained PH, CC, and HI from T2 (75\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e), and T5 (100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e75\u003csub\u003eR\u003c/sub\u003e), had no significant difference. Corresponding to this, it had no significant difference at T4 (100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e75\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e), T9 (100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e50\u003csub\u003eR\u003c/sub\u003e), and T10 (50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e). The maximum weight per single fruit was recorded from full irrigation which had no significant difference with T2, and T5. Additionally, T7 and T13 had no significant difference. The recorded number of fruit per plant at T3 with T9, and T4 with T10 had no significant difference. The observed HI ranged between 54.5\u0026ndash;62.1% which was in ranges of 55\u0026ndash;65% (Raes \u003cem\u003eet al\u003c/em\u003e., 2022). It is also in ranges of 0.5\u0026ndash;0.65 which was suggested by Steduto \u003cem\u003eet al\u003c/em\u003e., 1979).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of Deficit Irrigation on crop agronomy parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eSeason 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003eSeason 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePH (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCC (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHI (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWtSF (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNFPP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePH (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCC (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHI (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWtSF (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNFPP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.5\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.4\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.8\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e76.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.4a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.6\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.4\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e76.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.9\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.4\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.3\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.8\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.8\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.7\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.8\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.7\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.2\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.1\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.0\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.3\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.9\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.0\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.3\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.3\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.6\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.4\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.3\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e76.5\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.9\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.5\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.3\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.8\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.1\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.9\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.8\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.4\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.0\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.4\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.3\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.0\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.7\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.3\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69.5\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e59.1\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.6\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.9\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.6\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.2\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.9\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.3\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.0\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.5\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68.0\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.7\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e47.6\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20.5\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.6\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.1\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.6\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.6\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.9\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.0\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.3\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.6\u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.5\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.2\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.2\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.3\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.9\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.0\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.3\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.5\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.5\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.7\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.2\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.0\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.8\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.5\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.4\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e67.6\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e56.3\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e47.3\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20.2\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.2\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.1\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.5\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.0\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.6\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.0\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64.0\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.4\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.1\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e18.7\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.2\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.2\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.9\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.0\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.0\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.0\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68.4\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e59.7\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.3\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.8\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e 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\u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFprob\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eN.B\u003c/strong\u003e \u003cp\u003eThe same letter in columns are significantly similar at P\u0026thinsp;\u0026le;\u0026thinsp;0.05, PH\u0026thinsp;=\u0026thinsp;Plant height, CC\u0026thinsp;=\u0026thinsp;Canopy cover, HI\u0026thinsp;=\u0026thinsp;Harvest index, WtSF\u0026thinsp;=\u0026thinsp;Weight of single fruit, NFPP\u0026thinsp;=\u0026thinsp;Number of fruit per plant, CV\u0026thinsp;=\u0026thinsp;Coefficient of variation, and LSD\u0026thinsp;=\u0026thinsp;Least significant difference.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eFrom the second season experiment, the maximum observed PH, CC, HI, weight of single fruit, and number of fruit per plant were observed at T1 (FI) which had no significant difference with T2 (75\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e). The recorded PH at T1, T2, T3, T5, and T6 had no significant difference. Similarly, T4, and T9 had no significant difference with T10 on PH, CC, HI, weight of single fruit, and number of fruit per plant. In general, the maximum crop agronomy was obtained from the application of FI throughout the growth stage but the minimum was from the application of the 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. As water application depth decreased, crop agronomy decreased. The obtained results are consistent with the findings of Ullah \u003cem\u003eet al\u003c/em\u003e., (2021); Cui \u003cem\u003eet al\u003c/em\u003e., (2019), who conclude that as the obtained crop characteristics decreased as deficit level increased. This result was also in line with the finding of Liu et al., (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who proposed that the application depth of irrigation had direct relationship with the agronomic parameters.\u003c/p\u003e \u003cp\u003eThe decreasing order of the obtained crop agronomy at the application of deficit irrigation level were at initial, development, late, and mid growth stage, respectively. Therefore, the application of deficit irrigation at mid growth stage (fruit setting stage) shows significant difference than other stages at the same deficit irrigation level. This result is also similar to Patan\u0026egrave;, and Cosentino, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); who note that applying deficit irrigation during the yield formation (flower occurred) and late growth stage decreases the number of reproductive organs. Similar effect was observed with Dasgan \u003cem\u003eet al\u003c/em\u003e, (2021); concludes that, application of deficit irrigation at flowering and fruit setting stage decreases the crop yield due to flower abortion, sunburn, warm defect, and fruit disease. The minimum crop agronomy found at the application of deficit irrigation at flowering and yield formation stage and the minimum was from initial growth stage. This result revealed that crop agronomy was reduced as the irrigation water amount is decreased during the fruit development period. There was no adverse impact on the number of flowers when deficit irrigation was applied during the vegetative stage (Atilgan \u003cem\u003eet al\u003c/em\u003e., 2022).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Deficit irrigation effects on biomass and dry yield\u003c/h2\u003e \u003cp\u003eThe analysis of variance indicated that biomass, and dry yield were significantly the same (P\u0026thinsp;\u0026lt;\u0026thinsp;1%) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Statistically higher biomass of 8.788 t/ha, and dry yield of 5.458 t/ha was recorded from the application of full irrigation throughout the growth stages (no water deficit). While, the minimum biomass of 7.578 ton/ha and dry yield of 4.131 ton/ha were observed at T12 from the application of 100V100F25YF100R. The obtained biomass (BM) at T2 (75\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e) was significantly the same as T1 and T5. Similarly, T3 (100\u003csub\u003eV\u003c/sub\u003e75\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e) with T6 (50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e), and T4 (100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e75\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e) with T9 (100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e50\u003csub\u003eR\u003c/sub\u003e) and T10 (50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e) had no significant difference at the experimental seasons.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of deficit irrigation on dry yield, and biomass\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM (ton/ha) (Season 1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBM (ton/ha) (Season 2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDY (ton/ha) (Season 1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDY (ton/ha) (Season 2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAverage BM (Ton/ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAverage DY (Ton/ha)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.788\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.650\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.458\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.357\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.719\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.408\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.768\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.650\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.439\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.357\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.709\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.398\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.747\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.630\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.408\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.325\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.689\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.367\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.660\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.542\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.231\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.148\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.601\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.190\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.767\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.649\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.438\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.356\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.708\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.397\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.748\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.630\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.408\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.325\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.689\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.367\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.180\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.062\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.850\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.767\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.121\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.809\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.915\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.797\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.585\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.502\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.856\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.544\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.661\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.543\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.231\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.148\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.602\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.190\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.660\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.542\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.231\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.148\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.601\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.190\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.898\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.001\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.583\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.501\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.950\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.542\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.578\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.599\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.131\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.211\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.589\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.171\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.301\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.183\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.971\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.888\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.242\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.930\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFcal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFprob\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStatistically higher dry yield of 5.458 t/ha was recorded from the application of full irrigation throughout the growth stages (no water deficit) which had no significant difference with T1, and T5. While, the minimum biomass of 7.578 ton/ha and dry yield of 4.131 ton/ha were observed at T12 from the application of 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. Generally, the obtained biomass and dry yield decreases as the application irrigation depth of water decreased. This result in coincides with (Banjaw \u003cem\u003eet al\u003c/em\u003e., 2017), who suggests that the biomass and dry were decreased as the deficit irrigation level increases. These results agreed also with Banjaw \u003cem\u003eet al\u003c/em\u003e., (2017), who observed a decrease in vegetative growth and yield in the application of more deficit irrigations was applied. Likewise, Parkash \u003cem\u003eet al\u003c/em\u003e., 2021), reported a negative effect on biomass and dry yield was observed on more water stress applied than the application of full irrigation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Identification of Better Deficit Irrigation Level\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e3.6.1. Water productivity, irrigation water use efficiency and water use efficiency\u003c/h2\u003e \u003cp\u003eThe optimal deficit irrigation levels were shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The water productivity were found in ranges of 1.49\u0026ndash;1.82kg/m\u003csup\u003e3\u003c/sup\u003e at season 1, and 1.69\u0026ndash;1.80 kg/m\u003csup\u003e3\u003c/sup\u003e at season 2 with average values were in ranges of 1.59\u0026ndash;1.80 kg/m\u003csup\u003e3\u003c/sup\u003e. The irrigation water use efficiency was in ranges of 19.1\u0026ndash;21.1 kg/m\u003csup\u003e3\u003c/sup\u003e at season 1, and 20.6\u0026ndash;21.9 kg/m\u003csup\u003e3\u003c/sup\u003e at season 2 with an average value of 19.8\u0026ndash;21.4 kg/m\u003csup\u003e3\u003c/sup\u003e. The obtained WUE was 14.0-17.2 kg/m\u003csup\u003e3\u003c/sup\u003e (season 1), and 13.5-15.8kg/m\u003csup\u003e3\u003c/sup\u003e (season 2) with average value ranges between 13.8\u0026ndash;16.4 kg/m\u003csup\u003e3\u003c/sup\u003e. The range of WUE values obtained in this study is in the ranges of 13.60\u0026ndash;28.84 kg/ m\u003csup\u003e3\u003c/sup\u003e (Dasgan \u003cem\u003eet al\u003c/em\u003e., 2021) in India, 15.5\u0026ndash;25.3 kg/m\u003csup\u003e3\u003c/sup\u003e (Wang \u003cem\u003eet al\u003c/em\u003e., 2007) in north china plain under drip irrigation system, 10.5\u0026ndash;21.4 kg/m\u003csup\u003e3\u003c/sup\u003e (Kuscu \u003cem\u003eet al\u003c/em\u003e., 2014) in sub humid environment. However, the WUE range obtained in this study was lower than in the ranges of 33.00\u0026ndash;42.00 kg/m\u003csup\u003e3\u003c/sup\u003e (Hartz, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) at California, USA; 18.0\u0026ndash;42 kg m\u003csup\u003e3\u003c/sup\u003e (Alghamdi \u003cem\u003eet al\u003c/em\u003e., 2023) under furrow and drip irrigated tomato in Ethiopia; 49.1\u0026ndash;79.4 kg/m\u003csup\u003e3\u003c/sup\u003e (Malash et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) under drip irrigation plots in Egypt; and 41.83\u0026ndash;68.47 kg/m\u003csup\u003e3\u003c/sup\u003e (Chand \u003cem\u003eet al\u003c/em\u003e., 2020) in a solar greenhouse under different amounts of irrigation. The observed differences are most likely related to the environmental features of different regions, to irrigation methods and to the potential crop productivity (Raes, 2017).\u003c/p\u003e \u003cp\u003eThe water productivity increments were found in ranges of 1.84\u0026ndash;12.09% at season 1, 1.15\u0026ndash;3.91% at season 2 with average values of 2.37\u0026ndash;8.33% were observed at treatments of T2 \u0026ndash; T10 including T13. However, water productivity decrement were observed at T11 with values of 7.38% at season 1, 1.18% at season 2 with average value of 3.77%, and T12 with values of 3.23% at season 1, 1.78% at season 2 with average value of 1.85%. The irrigation water use efficiency increments (improving the yield and water productivity) were found in ranges of 0.49\u0026ndash;3.32% at all treatments except treatment of T11 (-0.99%), and T12 (-6.81%) at season 1, 0.20\u0026ndash;3.9% at all treatments except treatment T12 (\u0026minus;\u0026thinsp;2.0%) at season 2 with average values of 2.30\u0026ndash;3.60% were observed at treatments of T2 \u0026ndash; T10 including T13 except treatment T11 (-0.1%), and T12 (-4.5%). The water use efficiency increments were in ranges of 0.00\u0026ndash;10.3% at T2 \u0026ndash; T10 including T13 at season 1. However, water use efficiency decrement were observed at treatments of T11 (-1.90%), and T12 (-10. 3%). The water use efficiency increments were observed at treatments of T2 (1.90%), T3 (0.9%), T5 (1.40%), and T6 (1.4%) but no increment/decrement were observed at T4, T9, and T10. However, WUE decrement observed at treatments of T7 (1.40%), T8 (1.40%), T11 (4.8%), T12 (9.00%), and T13 (1.40%) at season 2 experiment. The water use efficiency increment were in ranges of 0.20\u0026ndash;6.3% at treatments of T2 \u0026ndash; T10 including T13 at averaged experimental season. However, water use efficiency decrement were observed at treatments of T11 (-3.7%), and T12 (-10.7%). This shows that, applying 50, and 75% at any growth stages improves the yield and irrigation water. This result was also in line with the finding of Banjaw \u003cem\u003eet al\u003c/em\u003e., (2017); Yohannes, and Tadesse, (1998), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve the WP\u003csub\u003eET\u003c/sub\u003e, and WUE. However, the treatments of T11, and T12 didn\u0026rsquo;t improve the yield, WP\u003csub\u003eET\u003c/sub\u003e, IWUE, and WUE. The best WP\u003csub\u003eET\u003c/sub\u003e, IWUE and WUE were found at treatment T6 at the application of 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. The best WUE and IWUE were found at T6 at the application of 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. The WUEI, and IWUEI improves the yield and water use efficiency at T2-T10 including T13. This shows that, applying 50, and 75% at any growth stages improves the yield and water use efficiency. This shows that applying stage wise deficit irrigation improves the yield and water productivity than applying full irrigation (Banjaw \u003cem\u003eet al\u003c/em\u003e., 2017). This result was also in line with the finding of Chand et al., (2020), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve CWUE. However, the WUE, and IWUE were negative at T11, and T12 (didn\u0026rsquo;t improve the yield and water use efficiency).\u003c/p\u003e \u003cp\u003eThe best WUE and IWUE were found at T6 at the application of 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. The WUEI, and IWUEI were positive at T2-T10 including T13. This shows that, applying 50, and 75% at any growth stages improves the yield and water use efficiency. This shows that applying stage wise deficit irrigation improves the yield and water productivity than applying full irrigation (Banjaw \u003cem\u003eet al\u003c/em\u003e., 2017). This result was also in line with the finding of (Chand \u003cem\u003eet al\u003c/em\u003e., 2020), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve CWUE. However, the WUE, and IWUE were negative at T11, and T12 (didn\u0026rsquo;t improve the yield and water use efficiency). Overall, applying 50% and 75% irrigation at any growth stage proved to be optimal at any growth stage including at applying 25% at vegetative and ripening growth stage.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWater productivity, irrigation water use efficiency, and water use efficiency\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003eSeason 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWP\u003csub\u003eET\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(kgm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIWUE\u003c/p\u003e \u003cp\u003e(kgm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWUE\u003c/p\u003e \u003cp\u003e(kgm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWPI\u003csub\u003eET\u003c/sub\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIWUII/D\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWUEI/D (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.40\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.90\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.80\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.80\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.76\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.80\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e 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align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.00\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.51\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.80\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.80\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.05\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.50\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-7.38\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-0.99\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-1.90\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-3.23\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-6.81\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-10.30\u003c/b\u003e\u003c/p\u003e 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colname=\"c2\"\u003e \u003cp\u003eT 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-1.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e 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align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e 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\u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-3.77\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-0.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-3.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-1.85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-4.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-10.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe exacerbation of water scarcity due to recent climate changes necessitates the optimization of irrigation water in arid and semi-arid regions. Among those methods, staged based deficit drip irrigation system was the best option. The water productivity of tomatoes varies between 1.49 and 1.82 kg/m\u003csup\u003e3\u003c/sup\u003e in season 1, and between 1.69 and 1.80 kg/m\u003csup\u003e3\u003c/sup\u003e in season 2, with average values ranging from 1.59 to 1.80 kg/m\u003csup\u003e3\u003c/sup\u003e and the irrigation water use efficiency (IWUE) ranged between 19.0\u0026ndash;21.1 kg/m\u003csup\u003e3\u003c/sup\u003e at season 1, and 20.6\u0026ndash;21.9 kg/m\u003csup\u003e3\u003c/sup\u003e at season 2 experiment with average values ranges between 19.8\u0026ndash;21.4 kg/m\u003csup\u003e3\u003c/sup\u003e. The water use efficiency varied from 14.0 to 17.2 kg/m\u003csup\u003e3\u003c/sup\u003e in season 1 and from 13.5 to 15.7 kg/m\u003csup\u003e3\u003c/sup\u003e in season 2, with average values ranging from 13.8 to 16.4 kg/m\u003csup\u003e3\u003c/sup\u003e. The highest water productivity (WP\u003csub\u003eET\u003c/sub\u003e), irrigation water use efficiency (IWUE), and water use efficiency (WUE) were observed at treatment T6 (75\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR)\u003c/sub\u003e at both experimental seasons. The water productivity (WP\u003csub\u003eET\u003c/sub\u003e) at all treatments was greater than full irrigation water application except treatment T11 and T12 at both experimental seasons. The obtained irrigation water use efficiency (IWUE) was greater at all treatments than full irrigation application except treatments T11, and T12 at season 1 as well as T12 at season 2. Similarly, the obtained water use efficiency (WUE) was greater at all treatments except T11, and T12 at season 1, and T7, T8, T11 and T12 at season 2 experiment. Generally, the average water productivity, irrigation water use efficiency, and water use efficiency were above at all treatments than full irrigation application except treatments of T11 and T12. These shows, the application of staged based deficit irrigation were optimum than the full irrigation application. This result was in line with Yohannes, and Tadesse, (1998); and Malash et al., (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e); who suggests maximum WP\u003csub\u003eET\u003c/sub\u003e, and WUE improves the yield by saving irrigation water.\u003c/p\u003e \u003cp\u003eTreatments of at T2 \u0026ndash; T10 including T13 were optimal with the water productivity (WP\u003csub\u003eET\u003c/sub\u003e), irrigation water use efficiency (IWUE), water use efficiency (WUE), and fresh yield (FY) increments were in ranges of 2.37\u0026ndash;8.33%, 2.30\u0026ndash;3.60%, 0.2\u0026ndash;6.3%, and 2.0\u0026ndash;3.4% respectively. However, the water productivity, irrigation water use efficiency, water use efficiency, and fresh yield decrements were found at treatments of T11 with water productivity of 3.77%, irrigation water use efficiency of 0.1%, 3.7%, and 0.3%, and T12 with water productivity of 1.85%, irrigation water use efficiency of 4.5%, 10.7%, and 4.6% which were not optimal. This implies, the application of irrigation 50, and 75%AW at any growth stage improves the yield by saving water. Compared to the previous studies, the optimal deficit irrigation levels for maximum water productivity appeared in the ranges of 50%-100%ET (Chand \u003cem\u003eet al\u003c/em\u003e., 2020; Corbari \u003cem\u003eet al\u003c/em\u003e., 2023). The obtained result was also in line with the result reported by Yersaw and Lohani, (2022), who suggested that, the application of deficit irrigation below 50%ET was optimal for enhancing the crop yield conducted at Arba Minch, Ethiopia on onion crop using furrow irrigation system. Similarly, Colimba-Limaico \u003cem\u003eet al\u003c/em\u003e., (2022), and Patan\u0026egrave; \u003cem\u003eet al\u003c/em\u003e., (2020) observed that the highest levels of water productivity in tomatoes occurring with a 50% irrigation replacement, and in relation to irrigation suspension, the longer the number of days without the irrigation before a harvest, the higher the water productivity.\u003c/p\u003e \u003cp\u003eIn this study, deficit irrigation treatments reduced total fresh yield during flowering and (yield formation (fruit development) stages; drought stress during these two stages has been found to lead to flower abortion. The minimum yield was obtained at the application of deficit irrigation at flowering and yield formation growth stage but the maximum was at vegetative growth stage. This result linked with the finding of Mukherjee \u003cem\u003eet al\u003c/em\u003e., (2023), water restrictions during vegetative stage can promote root growth, which can stimulate water and nutrient transfer to the plant's vegetative parts. Therefore, it hadn\u0026rsquo;t affected significantly the yield produced as the deficit irrigation applied at vegetative growth stage; and that the tolerance of tomato to water deficit depends on the cultivar, the growth stage at which the deficit occurs, and the severity of the drought stress (Cui \u003cem\u003eet al\u003c/em\u003e., 2019).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e3.6.2. Estimated fresh yield increment/decrement\u003c/h2\u003e \u003cp\u003eThe optimal deficit irrigation levels based on yield increment/decrement were shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The obtained tomato yield ranged from 34.5\u0026ndash;53.1 ton/ha from season 1 experiment and 33.0\u0026ndash;48.0 ton/ha with average value of 33.8\u0026ndash;50.5 t/ha. The maximum yield was 53.1 ton/ha (season 1), and 48.0 t/ha (season 2). These values were in ranges of 45\u0026ndash;65 t/ha (El Cham \u003cem\u003eet al\u003c/em\u003e., 2023), and 33.56\u0026ndash;54.49 t/ha (Raes \u003cem\u003eet al\u003c/em\u003e., 2022). However, the obtained values were less than the value of 69.1\u0026ndash;87.0 t/ha suggested by [72, 73]. This may be due to the report suggested by (Mukherjee \u003cem\u003eet al\u003c/em\u003e., 2023), who suggested that growing tomato crops under dry conditions provides the optimum yield than cropping at high rainfall conditions.\u003c/p\u003e \u003cp\u003eThe yield obtained had direct relationship with the applied water. The highest fresh yield was obtained at application of FI throughout the growth stage but the lowest from the application of 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. In general, the yield production is reduced as the applied crop water decreases. This result agreed with the findings of Mukherjee \u003cem\u003eet al\u003c/em\u003e., (2023); and El Cham \u003cem\u003eet al\u003c/em\u003e., (2023), who reported that as the deficit irrigation level increases, the yield obtained decreases. This result is also consistent with the findings of Alghamdi \u003cem\u003eet al\u003c/em\u003e., (2023), who suggested that the yield was directly related to the amount of water used.\u003c/p\u003e \u003cp\u003eThe obtained fresh yield increments, and decrement showed the optimum deficit irrigation level without adverse impact on the yield. The average fresh yield increments were in ranges of 0.5\u0026ndash;13.2% at treatments of T2 - T10 including T13 of season 1. However, FYD were observed at treatments of T11 with 0.9%, and T12 with 6.7%. The FYI was observed at all treatments except T12 (\u0026minus;\u0026thinsp;2.0%) at season 2 experiment, and T11 (-0.3%), and T12 (4.6%) in average experiment. This implies, the application of irrigation 50, and 75%FI at any growth stage improves the yield by saving water. The maximum FYI was observed at the application of 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e at the experimental seasons. This irrigation level improves the yield, WUE, and IWUE than the other deficit irrigation level. This result was agreed with the finding of (Chand \u003cem\u003eet al\u003c/em\u003e., 2020); who suggested, farmers should distill their efforts to maximize net income per unit of water used rather than per unit of land by selecting water-saving irrigation methods, like the DI, which generally increases IWUE in water limiting areas. However, FYI was negative at the application of 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e, and 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e25\u003csub\u003eR\u003c/sub\u003e except vegetative, and ripening stage. This result was supported by (Yersaw and Lohani, 2022), who reports all over deficit irrigation level applied at yield formation stage didn\u0026rsquo;t improve the yield and water use efficiency.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIdentification of better deficit irrigation level on yield increment/decrement\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003eSeason 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFY\u003c/p\u003e \u003cp\u003e(t/ha)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eETa\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWS\u003c/p\u003e \u003cp\u003e(m\u003csup\u003e3\u003c/sup\u003e/ha)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWS\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYL\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFYWS\u003c/p\u003e \u003cp\u003e(t)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTFY(FY\u0026thinsp;+\u0026thinsp;FYWS)\u003c/p\u003e \u003cp\u003e(ton)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eFYI/D\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.6\u003c/p\u003e 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colname=\"c5\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e54.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e54.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e 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colname=\"c7\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2\u003c/p\u003e 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colname=\"c9\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e 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6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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colname=\"c8\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e 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\u003cp\u003eFY\u0026thinsp;+\u0026thinsp;FYWS\u003c/p\u003e \u003cp\u003e(ton)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eFYI/D\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50.6\u003c/p\u003e \u003c/td\u003e 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align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eN.B: T\u0026thinsp;=\u0026thinsp;Treatment, ETa\u0026thinsp;=\u0026thinsp;Actual evapotranspiration, WS\u0026thinsp;=\u0026thinsp;Water saved, YL\u0026thinsp;=\u0026thinsp;Yield loss, FYWS\u0026thinsp;=\u0026thinsp;Fresh yield from water saved, and FYI/D\u0026thinsp;=\u0026thinsp;Fresh yield increment/decrement.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Discussions\u003c/h2\u003e \u003cp\u003eThe calibration performances were very good at the application of 75V100F100YF100R (irrigation of 75% at vegetative stage and full irrigation at the remained growth stage), 100V75F100YF100R (irrigation of 75% at flowering stage and full irrigation at the remained growth stage), (50V100F100YF100R) (irrigation of 50% at vegetative stage and full irrigation at the remained growth stage), and I50F\u0026times;100R (irrigation of 75% at flowering stage and full irrigation at the remained growth stage) rather than applying full irrigation throughout the growth stages. The model performance decreases as the water stress level increases. Researchers agreed that the AquaCrop model predictions were less accurate in the case of the largest deficit irrigation treatments on canola conducted at semi-arid climate conditions (Khorsand et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), on Common Bean (Striˇcevic, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), on maize (Daniel et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and on potato (Wale et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAquacrop model performed good on CC, BM, and SWC at the application of 100\u003csub\u003eV\u003c/sub\u003e75\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e, 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e, 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e75\u003csub\u003eR\u003c/sub\u003e, and 25\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. However, it poorly performed at the application of 100\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e25\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e, and 100\u003csub\u003eV\u003c/sub\u003e25\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. The AquaCrop model accurately simulated the soil water content (SWC) of the tomato, yet it consistently overestimated SWC across all irrigation treatments (EF\u0026thinsp;\u0026le;\u0026thinsp;0.00). In a greenhouse experiment on cherry tomato with plastic film mulch (Cheng \u003cem\u003eet al\u003c/em\u003e., 2022) also observed an overestimation of SWC. However, this result contradicts with the result of Zhou et al., (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) on maize, Lindel \u003cem\u003eet al\u003c/em\u003e., (2021); Khorsand et al., (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) on Canola, who suggests the Aquacrop model performed well on SWC.\u003c/p\u003e \u003cp\u003eThe Aqua-crop model over estimate at the application of full irrigation (FI) application and the performance value were poor at high deficit irrigation application. The study conforms to the work of Wale et al., (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); Cheng \u003cem\u003eet al\u003c/em\u003e., (2022), who suggests the AquaCrop performance decreases as the application of irrigation depth decreases. The performance of the aqua crop varies crop to crop and cultivars. For example, Daniel et al., (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported ET underestimation when maize in Northeast China is stressed, while Mengistu et al., (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found a better ET agreement for cotton under water stress than not stressed.\u003c/p\u003e \u003cp\u003eThe water use efficiency increment were in ranges of 0.20\u0026ndash;6.3% at treatments of T2 \u0026ndash; T10 including T13 at averaged experimental season. However, water use efficiency decrement were observed at treatments of T11 (-3.7%), and T12 (-10.7%). This shows that, applying 50, and 75% at any growth stages improves the yield and irrigation water. This result was also in line with the finding of Chand \u003cem\u003eet al\u003c/em\u003e., (2020); Yersaw and Lohani, (2022), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve the WP\u003csub\u003eET\u003c/sub\u003e, and WUE. However, the treatments of T11, and T12 didn\u0026rsquo;t improve the yield, WP\u003csub\u003eET\u003c/sub\u003e, IWUE, and WUE. The best WP\u003csub\u003eET\u003c/sub\u003e, IWUE and WUE were found at treatment T6 at the application of 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. The best WUE and IWUE were found at T6 at the application of 50\u003csub\u003eV\u003c/sub\u003e100\u003csub\u003eF\u003c/sub\u003e100\u003csub\u003eYF\u003c/sub\u003e100\u003csub\u003eR\u003c/sub\u003e. The WUEI, and IWUEI were positive at T2-T10 including T13. This shows that, applying 50, and 75% at any growth stages improves the yield and water use efficiency. This result was also in line with the finding of Chand \u003cem\u003eet al\u003c/em\u003e., (2020), who reports, DI strategies decrease transpiration rate in plant; causing reduction in leaf area and stomata openings which ultimately improve WUE. However, the WUE, and IWUE were negative at T11, and T12 (didn\u0026rsquo;t improve the yield and water use efficiency).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. CONCLUSİONS","content":"\u003cp\u003eThis study examines seasonal adaptation using integrated seasonal and AquaCrop simulations to evaluate the effects of soil moisture dynamics and drip irrigation on tomato production in southern Ethiopia. Three deficit irrigation levels (75%, 50%, and 25%) were applied across growth stages to identify efficient water management strategies. The AquaCrop model accurately simulated canopy cover, biomass, and dry yield, with the highest performance observed at I50V\u0026times;100R, I75R\u0026times;100R, I75F\u0026times;100R, and I75V\u0026times;100R, outperforming full irrigation. However, model performance for soil water content was comparatively poor. The best water productivity (WPET) of 1.79 kg/m\u0026sup3; occurred under I50V\u0026times;100R, similar to I75-based treatments. Across seasons, WP ranged from 1.49\u0026ndash;1.82 kg/m\u0026sup3; in Season 1 and 1.69\u0026ndash;1.80 kg/m\u0026sup3; in Season 2, while irrigation water use efficiency (IWUE) varied between 19.1\u0026ndash;21.1 kg/m\u0026sup3; and 20.6\u0026ndash;21.9 kg/m\u0026sup3;, respectively. Moderate deficit treatments (T2\u0026ndash;T10 and T13) enhanced yield, water productivity, and efficiency by up to 12.1%, whereas severe deficits (T11 and T12) reduced performance by up to 10.7%. The optimal treatment (T6) achieved the highest WP, IWUE, and WUE under 50V100F100YF100R irrigation scheduling. Overall, applying 50\u0026ndash;75% irrigation during key growth stages improved yield and water conservation, while irrigation below 25% at flowering or yield formation caused significant losses. The findings demonstrate that deficit irrigation (DI) enhances water productivity and yield stability, particularly under moisture-limited conditions, offering a sustainable adaptation pathway for tomato production in semi-arid regions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData Availability Statement (DAS)\u003c/p\u003e\n\u003cp\u003eData available from the corresponding author on reasonable request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable for this study as it did not involve human or animal subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to the publication of this manuscript.\u003c/p\u003e\n\u003cp\u003eFunding Declaration\u003c/p\u003e\n\u003cp\u003eNo funding\u003c/p\u003e\n\u003cp\u003eClinical trial number\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Arba Minch University for providing the demonstration farm for conducting this experimental research.\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eBabur Tesfaye Yersaw conceived and developed the conceptualization, methodology, data collection, and analysis, in model implementation, result interpretation, original draft preparation, and writing, review, and editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlghamdi Abdulaziz G, Anwar A, Aly, Abdulrasoul M, Al-Omran II, Louki, and Arafat Alkhasha. 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No.6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou D, Wang H, Wang X, Wang F, Zhang J, Ma D. Evaluation of AquaCrop\u0026rsquo;s Ability to Simulate Water Stress Based on 2-Year Case Study of Maize Crop. Agronomy. 2024;14(2):354. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/agronomy14020354\u003c/span\u003e\u003cspan address=\"10.3390/agronomy14020354\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Aquacrop, Climate change, Seasonal adaptation, Water productivity, Yield","lastPublishedDoi":"10.21203/rs.3.rs-7945516/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7945516/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSeasonal variation analysis revealed slight differences in crop growth and model performance between the calibration (Season 1) and validation (Season 2) periods. The simulated and observed results showed that biomass (BM) and dry yield (DY) exhibited minor seasonal reductions, while soil water content (SWC) and water productivity (WPET) showed modest increases. Specifically, biomass decreased by 1.6%, from 8.788 t ha⁻\u0026sup1; in Season 1 to 8.650 t ha⁻\u0026sup1; in Season 2, whereas dry yield declined by 1.9%, from 5.458 to 5.357 t ha⁻\u0026sup1;. These slight decreases are mainly attributed to higher mean air temperature and reduced mid-season rainfall during the validation period, which increased crop water stress and evapotranspiration demand under deficit irrigation treatments. In contrast, the mean soil water content increased by 1.3%, from 276.1 mm in Season 1 to 279.6 mm in Season 2, likely due to enhanced late-season rainfall and improved soil moisture retention under full irrigation. The most notable seasonal improvement was observed in water productivity, which increased by 10.0%, from 1.65 to 1.81 kg m⁻\u0026sup3;, indicating more efficient water use and higher transpiration efficiency during the slightly drier validation season. Overall, AquaCrop demonstrated stable performance across both seasons, effectively capturing the temporal variability in crop growth and soil moisture dynamics. Although small fluctuations occurred due to climatic variability, the model maintained strong correlations for canopy cover (r\u0026thinsp;\u0026ge;\u0026thinsp;0.96), biomass (r\u0026thinsp;\u0026ge;\u0026thinsp;0.98), and soil water content (r\u0026thinsp;\u0026ge;\u0026thinsp;0.94), confirming its reliability for simulating seasonal crop responses under different irrigation regimes.\u003c/p\u003e","manuscriptTitle":"Adaptation under Integrating Seasonal and AQUACROP Simulations to Evaluate Soil Moisture and Drip Irrigation Effects on Tomato Production in Southern Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 10:24:50","doi":"10.21203/rs.3.rs-7945516/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7c2603f6-8cb6-4155-aa86-45d464c00ee6","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T18:30:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 10:24:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7945516","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7945516","identity":"rs-7945516","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}