Effect of Regulated and Controlled Deficit Irrigation on Yield and Yield Response Factor of Processing Tomato

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A. Badr, Eman Ali, S. R. Salman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7162684/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 Deficit irrigation (DI) can contribute to water conservation and help alleviate water scarcity. For this purpose, two field experiments were conducted in 2023 and 2024 to adopt a strategy that involves lower water use without compromising yield. In 2023, regulated deficit irrigation (RDI) was applied at 100% (V100), 80% (V80), 60% (V60), 40% (V40), and 0% (V0), while in 2024, controlled deficit irrigation (CDI) was applied at 100% (V100) or 50% (V50) during the whole growing season, 50% reduction up to the first fruit set, then 100% restoration (V50-100), and 100% until the beginning of ripening, then 50% reduction (V100-50), and 0% (V0) of evapotranspiration (ET). In 2023, RDI decreased yield by 9.1, 26.2, and 51.1% for V80, V60, and V40, respectively, with a remarkable increase in water productivity (WP) for all treatments compared to V100. In 2024, CDI included a reduction of water early in the season (V50-100) did not lead to significant losses in yield but resulted in a water saving of 25% compared to (V100), while the yield was negatively affected by the reduction of water late in the season (V100-50). WP was positively affected by both treatments, but (V50-100) appreciably increased WP. The sensitivity of tomato to DI was higher when water was applied at different intensities with RDI ( K y = 0.96) than at individual growth stages with CDI ( K y = 0.87). These results indicated that DI during the vegetative growth stage was a better strategy to optimize yield, coupled with water saving and improving WP. water stress tomato yield water productivity yield response factor Figures Figure 1 Figure 2 Highlights Water scarcity poses a significant challenge to tomato production, which necessitates efficient irrigation strategies. RDI reduced fruit yield under all levels but improved water use efficiency. CDI early in the season produced a comparable yield to full irrigation coupled with a significant amount of water saving. Strategy that considered timing of water deficits can mitigate adverse effect on yield with appreciable amount of water saving. A yield response factor ( K y) lower than one indicates that tomato is relatively tolerant of water stress. 1. Introduction The continuous escalation in the demand for freshwater on a global scale to meet the needs of natural ecosystems will force irrigation to operate under water scarcity. In many areas of the world, irrigation processes are still practiced until now with disregard to basic principles of resource preservation. The increasing competition for water resources between agriculture and other sectors compels the adoption of irrigation strategies in arid regions, which may allow saving irrigation water and still maintaining satisfactory levels of production (Nangare et al., 2016 ). Under such conditions, there is an urgent need for a water-saving strategy that must be seen as the major threat to food security in the future. Soil and water management is most likely the best option in most agricultural systems for increasing the efficiency of water use (Khapte et al., 2019 ). The process of crop water use has two main components of water losses: evaporation from the soil and the plant, as well as all the losses resulting from the distribution of water to the land (Fereres and Soriano, 2007 ). However, reducing crop ET without a penalty in crop production is much more difficult because evaporation from crop canopies is tightly coupled with the assimilation of carbon (Steduto et al., 2007 ). Thus, some of the water losses are unavoidable and are needed to be minimized with efficient irrigation methods and by appropriate management. The main approach to achieve this goal involves adopting more efficient irrigation techniques, such as drip irrigation, which reduce evaporation losses (Khapte et al., 2019 ), as well as using deficit irrigation (DI) strategy (Douh et al., 2021 ; Kiyan et al., 2022 ). In this way, the entire root zone is irrigated with lower amounts of water while the minor stress that develops has minimal effects on the yield. Controlled deficit irrigation (CDI) is an alternative for areas where DI evidenced a negative effect on yield, as it seeks to optimize the use of water stress only in noncritical periods of the development of the plant. The timing and stage at which stress is imposed, as well as the intensity of stress also influence water productivity. This mode of irrigation requires close control of the timing and level of water deficit so that water deficits can be imposed at times when it has a minimum effect on yield (Valcárcel et al., 2020 ). Tomato is one of the most widely cultivated vegetables globally, valued for its nutritional content and economic importance. However, water scarcity poses a significant challenge to tomato production, necessitating efficient irrigation strategies. Tomato is relatively resistant to water stress; hence, deficit irrigation could be managed because it can tolerate drought to some degree (Hanson and May, 2004 ; Patane et al., 2011). Regulated deficit irrigation (RDI) and controlled deficit irrigation (CDI) can be considered as two strategies that aim to improve water use without compromising crop yield. Many studies showed that the response of tomato yield to deficit irrigation at various growth stages was different, depending on the period and the degree of water deficit (Zegbe et al., 2006 ; Chen et al., 2013 ; Kuscu et al., 2014 ). However, the tomato plant is particularly sensitive to water deficit during reproductive development, as it causes physiological disturbances leading to the loss of flower buds and open flowers, as well as a reduction in fruit set, which has a negative impact on commercial yield (Lamin-Samu et al., 2021 ). It was reported that there were no adverse effects on tomato yield and fruit quality by imposing a certain degree of water stress during the vegetative stage (Marouelli and Silva, 2007 ; Kuscu et al., 2014 ). Moreover, the study of Ngouajio et al. ( 2007 ) showed that withholding irrigation between transplanting and flowering may save the amount of irrigation water by 20% while increasing tomato yield by 8–15%. Chen et al., ( 2013 ) stated that tomato yield was sensitive to water deficit during fruit development and ripening, while fruit quality was mainly affected by water deficit during fruit ripening. Patanè et al., ( 2011 ) reported that CDI of 100–50% ET crop offered a similar performance compared to DI covering 50% ET crop, with no significant impact on marketable yield and TDM. Similarly, Jiang et al., ( 2019 ) confirmed an acceptable balance between high water productivity and yield, supplying 2/3 of FI at flowering and fruit development. Although DI has been assessed for tomato, giving different results, many of the obtained results have shown that DI saves substantial amounts of irrigation water and increases water productivity (Kirda et al., 2004 ; Topcu et al., 2007 ; Patane and Cosentino, 2010). However, few studies were reported about the application of DI in water yield relations of tomato, and so far as the literature reported, no modeling equations have been evaluated for the effects of different degrees of water deficit at various growth stages. The aim of the present study was to (i) determine the effect of deficit irrigation throughout the growing season and at different growth stages on yield and yield-water relationships of processing tomato (ii) develop an irrigation strategy that ensures water savings to irrigate more land, especially under desert agro-systems. This aspect is of utmost importance given the difficulty of providing more water needed for the agricultural sector especially in arid and semi-arid regions. 2. Materials and Methods 2.1. Site and soil description. Field experiments were conducted on a vegetable farm located in the Serapium area, Ismailia province, east of the Nile Delta, Egypt, during the late summer growing season (August-December) 2023 and 2024 using a drip irrigation system. This area is a desert region included in the agricultural expansion program and has recently become productive land for many crops. The site is located in the arid climate at latitude 30°58 N and longitude 32°23 E with an elevation of 13 m above mean sea level. The area experiences a hot and dry climate with very little rainfall throughout the year. Temperatures can be very high in summer (June to August), often exceeding 35°C during the day, with little relief at night. Winter months (November to February) are mild, with daytime temperatures ranging from 15°C to 25°C and cooler nights, sometimes dropping to around 10°C or lower. The mean monthly evapotranspiration ranged from 6.9 to 2.5 mm in the respective cropping season. The climate parameters recorded from August to December during both growing seasons are summarized in Table 1 . The average soil water content at field capacity from the surface soil layer down to 80 cm depth at 20 cm intervals was 0.18 (v/v), and the permanent wilting point for the corresponding depths was 0.08 (v/v), respectively. Average available N, P, and K from the surface soil layer down to 60 cm depth at 20 cm intervals were 12, 7, and 43 mg kg⁻¹ soil, respectively, before the initiation of the experiment. Table 1 Average monthly maximum ( T max ) and minimum ( T min ) temperature, relative humidity, rainfall, evapotranspiration (ET 0 ), and wind speed during the growing season. Month T max ( o C) T min ( o C) Relative humidity (%) Rain fall (mm) ET 0 (mm) Wind speed (km h − 1 ) 2023 August 36.1 22.0 53 0.0 6.7 15.6 September 33.5 20.2 50 0.1 5.9 16.1 October 30.5 17.4 56 2.0 4.6 15.2 November 26.4 13.5 59 5.5 3.2 15.6 December 21.6 9.7 60 7.4 2.5 15.9 2024 August 35.3 21.9 54 0.0 6.9 15.6 September 33.2 19.6 53 0.0 6.4 15.8 October 32.7 17.7 57 2.3 4.6 15.7 November 26.4 14.4 59 7.7 3.4 15.9 December 21.9 9.7 60 2.9 2.6 15.8 2.2. Experimental design and treatments. Processing tomato plants were subjected to different irrigation treatments based on crop evapotranspiration (ETc) in a complete randomized block design with three replicates. Five irrigation treatments were imposed over 2 years, including regulated deficit irrigation (RDI) in 2023 and controlled deficit irrigation (CDI) in 2024 under field conditions (Table 2 ). RDI involved a consistent reduction in water supply throughout the growing season, while CDI maintained a consistent reduction in water supply throughout definite growing stages. Table 2 Description of irrigation treatments applied to tomato in two growing seasons. Year Treatments Description Water applied (mm) 2023 V100 100% ETc (full irrigation) 374 V80 80% ETc of full irrigation 314 V60 60% ETc of full irrigation 240 V40 40% ETc of full irrigation 165 V0 No irrigation after plant establishment 47 2024 V100-100 100% ETc (full irrigation) 386 V50-50 50% ETc during the whole season 206 V50-100 50% ETc reduction up to 1st fruit set, 100% ETc restoration 303 V100-50 100% ETc reduction up to start of maturity stage, 50% ETc restoration 318 V0 No irrigation after plant establishment 55 Before tomato transplanting, drip tubing (twin-wall, 15 mm inner diameter, in-line drippers at 40 cm distance delivering 2.5 liter h –1 at operating pressure 100 kPa) was laid out along each row at 100 cm apart in the center of the soil beds. Tomato seedling ( Solanum Lycopersicum L.) cultivar ‘Castle Rock’ was directly transplanted to the main field at 25 cm intervals along drip lines (40000 plants ha –1 ) in all the treatments in the middle of August. Plants were arranged in north-south-oriented soil beds pre-furrowed to receive 40 t ha –1 of organic manure in plots (4.5 m wide × 15.0 m long). All treatments received the same amount of phosphorus, 150 kg P ha –1 as single super phosphate and 250 kg K ha –1 as potassium sulphate before transplanting, which was incorporated into the soil beds. Nitrogen fertilizer was applied as ammonium nitrate in water-soluble form at 7-day intervals in the drip irrigation system using a venturi-type injector. Fertigation events of N were started two weeks after planting in 12 equal doses and stopped 30 days prior to the end of the growing season. 2.3. Estimation of crop water requirement. Meteorological data were calculated from the weather station of the Central Laboratory of Agricultural Climate for Ismailia province located near the experimental field. The irrigation water was applied on a daily basis according to Penman-Monteith’s semi-empirical formula (ETc = ET 0 × K c) as proposed by Allen et al. ( 1998 ). The actual crop evapotranspiration rate (ETc) was based on the product of ET 0 and crop coefficient ( K c) for different months based on crop growth stages using values for tomato ( K c initial = 0.45, K c developmental = 0.75, K c middle = 1.15, K c maturity = 0.85) for growth stages 30/40/40/25 days (Allen et al., 1998 ). The values of ETc were reduced frequently to account for the percentage of wetted area resulting from the drip line spacing in the field. The percentages of wetted area were determined as the average horizontal area wetted of the crop root zone as a percentage of the total crop area. Cumulative ETc for the different irrigation treatments and the relative quantity of water saving during the whole growing period were presented in (Table 2 ). During the initial stage of growth, tomato plants were irrigated daily to encourage establishment, but thereafter irrigation frequency was running at 2–3 day intervals. The irrigation process was ceased at 120 DAP (15 days before the last picking) to prevent secondary growth. 2.4. Yield response factor. The functional relationship between crop yield and water use is called the water-production function (ratio of actual to maximum ET) that limits the crop yield, assuming that all the other factors are at the optimum level. Seasonal values of the yield response factor ( K y) were calculated for each experimental year as follows: $$\:1-\left(\frac{\text{Y}\text{a}}{\text{Y}\text{m}}\right)=Ky\:\left(1-\frac{\text{E}\text{T}\text{a}}{\text{E}\text{T}\text{m}}\right)$$ 1 where Ym (kg ha − 1 ) and Ya (kg ha − 1 ) are maximum (that obtained from fully irrigated treatment) and actual yield, respectively, ETm (mm ha − 1 ) and ETa (mm ha − 1 ) are maximum (that obtained from fully irrigated treatment) and actual ET, respectively, K y is the yield response factor, that is defined as the decrease in yield per unit decrease in ET (Stewart et al., 1977 ). According to the Ky calculation, K ss was calculated by the Eq. ( 1 ), replacing Ym with maximum total dry biomass (SSm) and Ya with actual total dry biomass (SSa) as follows: $$\:1-\left(\frac{\text{S}\text{S}\text{a}}{\text{S}\text{S}\text{m}}\right)=Kss\:\left(1-\frac{\text{E}\text{T}\text{a}}{\text{E}\text{T}\text{m}}\right)$$ 2 where K ss indicates the biomass response factor, which is the correlation factor between relative total dry biomass loss and relative ET reduction. 2.5. Measurements of crop parameters. Maximum biomass production was determined by harvesting three representative plant per treatment replicate at 90 DAT. Plant growth components were determined from 10 randomly selected plants in each plot, including total fresh fruit yield per plant, fruit number per plant, and average fruit weight per plant. At harvest, three representative selected plants were sampled from each experimental plot and plant parts (stems + leaves + fruits) were dried in a thermo-ventilated oven at 70 ◦C until constant weight, for dry biomass measurement. Harvesting of the tomatoes was made on the last week of November until the end of December for both seasons. Total fresh fruit yield was recorded on at least 50 plants in a row in each treatment in all the replications, and data were presented as tons per hectare. 2.6. Water productivity. Water productivity is an indicator related to the water consumed by crops as to produce a certain yield and calculated for each irrigation treatment as the ratio between total epigeous dry matter at harvest and total water used, as measured by water balance equation: $$\:\text{W}\text{P}=\left(\frac{\text{y}\text{i}\text{e}\text{l}\text{d}\:{\text{k}\text{g}\:\text{h}\text{a}}^{-1}}{\text{E}\text{T}\:\left(\text{m}\text{m}\right)}\right)$$ where WP is water productivity (kg ha − 1 mm − 1 ) ET is the seasonal plant evapotranspiration (mm). 2.3. Statistical analysis. All data were subjected to the analysis of variance (ANOVA) appropriate to the experimental design to evaluate the effects of treatments on tomato yield, total dry biomass, shoot dry weight, N and P uptake. CoStat (Version 6.311, CoHort, USA, 1998–2005) was used to conduct the analysis of variance. Comparison of treatment means was carried out using the least significant difference (LSD) at a 5% probability level. Regression analysis was performed between total seasonal water use and total fruit yield of the crop for both seasons. 3. Results 3.1. Climate trend and irrigation variables Although most tomato plants grow and produce best in sunny summer weather, it is possible to grow tomatoes in late summer, particularly in most hot climates. During the growth season, the values of climate parameters differed from (Aug to Dec), where the greatest differences were recorded in Des, both for temperature and relative humidity. During the cropping cycle, one can point out sparse precipitation that occurred without effective amounts for both seasons. The air temperature was higher during the first part of the cycle, in Aug, when the max temperatures were almost over 35 o C. Afterwards, in Seb, the daily min and max temperatures decreased and followed the same trend till the end of Des. The described climate parameter, though typical for that area, reduced crop water use due to the low values of daily ET 0 from the planting till harvest and made a clear differentiation of the compared irrigated theses. 3.2. Tomato yield and TDM. The yield components, including biomass production, fruit weight, harvest index, and WP were significantly affected (P < 0.05) by deficit irrigation treatments applied in 2023 (Table 3 ). Yield was severely depressed by soil water deficit when irrigation was stopped early in the season (V0) in both years, as the plants failed to develop under drier conditions. RDI resulted in a slight reduction in fruit yield by 9.1% in V80, while in V60 and V40 the yield was strongly reduced by 26.2% and 51.1% compared to V100 respectively. The accumulation of TDM also decreased with increasing deficit irrigation, but the differences compared to the V100 were much smaller and amounted to 7.4, 22.8, and 41.8% with V80, V60, and V40, respectively. Average fruit weight was also affected by deficit irrigation, leading to a noticeable decrease in the overall fruit size. This reduction not only impacts yield but also has potential repercussions on market value and consumer preference, especially at V60 and V40, which were significantly reduced compared to the other treatments. The relationship between fruit yield and TDM was very strong (R² = 0.98), indicating that the crop regulates its fruit yield proportional to total dry matter production. Table 3 Total yield, biomass production, fruit weight, harvest index and WP of tomato as affected by deficit irrigation treatments in 2023 for RDI and 2024 for CDI. Irrigation treatments Biomass (t ha − 1 ) Fruit weigh (g fruit − 1 ) Harvest index WP kg ha − 1 mm − 1 Fruit Shoot DW Total DW 2023 (RDI) V100 58.80a 1.82a 4.76a 98a 0.62 157 V80 53.45b 1.74a 4.41b 92b 0.61 170 V60 43.38c 1.52b 3.69c 85c 0.59 181 V40 28.74d 1.19c 2.77d 67d 0.57 174 V0 5.59e 0.48d 0.78e 45e 0.39 -- 2024 (CDI) V100 62.25a 1.93a 5.04a 97a 0.62 161 V50 45.76c 1.65b 3.94c 82c 0.58 222 V50-100 59.87a 1.90a 4.89a 95a 0.61 197 V100-50 51.64b 1.76b 4.34b 87b 0.58 165 V0 7.89d 0.67c 1.11d 43d 0.39 -- Values within the column followed by different letters are significantly different based on least significant difference (LSD) at P ≤ 0.05. In 2024, deficit irrigation at a reduced rate (50% ETc) during the whole growing season (V50) significantly reduced yield by 26.5% compared to V100, as many small green fruits were aborted, besides the decline in the average fruit weight. On the other hand, different degrees of yield reduction were observed in the treatments with deficit irrigation at one growth stage (early or late stage-CDI) compared to full irrigation. Early-stage CDI (V50–100) does not induce significant losses in fruit yield, while reduction of water during the late stage (V100–50) resulted in a significant 17.1% lower yield compared to V100. Similarly, TDM showed significant differences between irrigation treatments, especially in prolonged deficit irrigation (V50) and in late reduction of water, which were 22.0% and 14.0%, respectively lower than in V100, while early reduction of water (V50-100) resulted in lower losses in final dry biomass (3.1%). Biomass allocation and total biomass index decreased significantly in response to (V50) and late-stage water reduction (V100-50), which was associated with reduced biomass distribution on fruits and hence lower yield. Mean fruit weight was not significantly affected by deficit irrigation except for V50 and V05-100, which decreased significantly compared to V100. The harvest index with V100-50 was almost close to V100, which may be associated with favorable growing conditions, while it decreased significantly with other treatments. Similar to the first season, the relationship between fruit yield and TDM was very strong (R² = 0.98), confirming the high correlation between both parameters. 3.3. Water productivity and production function. The effects of different irrigation treatments on tomato yield in terms of WP varied widely in both years (Table 3 ). In 2023, RDI induced increases of WP values as much as 8.3, 15.0, and 10.8% for V80, V60, and V40, respectively, compared to V100 which resulted in lowest the lowest value. Despite the yield reductions under all deficit irrigation levels, maximum value of WP corresponded to irrigation treatment (V60) indicating that deficit irrigation can still be a viable strategy to enhance water use efficiency. In 2024, maximum WP was found in the treatment with the minimum water supply (V50), but only late stage CDI (V100-50) did so without significant yield reduction compared to V100. Although the savings in water was almost equal in both V50-100 and V100-50, but WP was markedly higher by 22.3% versus 2.3% for both treatments, respectively, compared to V100. The relationship from regression analysis between seasonal ETc and fruit yield in both years was shown by a linear function (Fig. 3). As expected, the relationships between fruit yield and ETc were linear (a single line represented all five irrigation treatments applied in both years). The production function (total amount of irrigation water vs. fresh fruit yield) through linear regression analysis, showed a significant correlation coefficient ( R 2 = 0.97 and 0.90) for RDI and CDI, respectively. Over the range of water inputs, 47–55 mm for V0 to 374–386 mm for V100 between planting and harvest, tomato yield increased by about 167 and 177 kg ha − 1 for each mm of water applied for RDI and CDI, respectively. 3.4. Yield response factor The relationship between crop yield and water use was determined through an empirical model that links the relative yield decrease with the corresponding relative ET reduction, and the product of this model is a yield response factor ( K y). This factor was calculated in this experiment for both total yield ( K y) and total dry matter ( K ss) produced by the crop for both RDI and CDI (Table 4 ). In 2023, the treatments with RDI showed persistent higher K y and K ss values with increasing levels of deficit irrigation, indicating that they were less tolerant under higher water stress. However, the treatment with V80 showed a minimum value compared to the maximum value with V40 or even greater with V0 when water supply was cut off very early in the season. In 2024, the treatments with CDI showed lower K y and K ss factors in V50–100 versus higher values for the same parameters in V100–50 which indicates to the sensitivity of tomato to deficit irrigation in the last part of the crop cycle. Table 4 Yield response factor for yield K y and total dry biomass K ss of tomato for each individual treatment applied in 2023 for RDI and 2024 for CDI. Year Treatments K y K ss Year Treatments K y K ss 2023 V100 -- -- 2024 FI -- -- V80 0.56 0.44 V50 0.55 0.47 V60 0.72 0.64 V50-100 0.18 0.14 V40 0.91 0.75 V100-50 0.94 0.78 V0 -- -- V0 -- -- The relationships between seasonal ET and yield of tomato for all irrigation treatments applied during both years were well fitted using a linear regression forced to the origin with the regression coefficients (Fig. 3). The slopes of the fitted regressions, which represent the K y and the Kss , were 0.96 and 0.86 for RDI, while they were 0.87 and 0.77 for the same parameters for CDI, respectively, indicating that in both cases the reduction in crop yield is proportionally less than the relative ET reduction. In this regard, tomato seems to be less sensitive to water deficit in terms of total dry biomass, as the last was less affected by water deficit than fruit yield production. However, the calculation of K y for each specific stage of crop growth may help in defending the most critical period of the crop to water. 4. Discussion 4.1. Response of fruit yield and TDM. Tomato is one of the most important vegetable crops that is widely grown around the world, but they are also one of the most water-intensive crops. However, deficit irrigation provides a water-saving strategy that has become very popular in arid and semi-arid regions as an important means of reducing water consumption. In 2023, full irrigation resulted in the highest fruit yield and TDM, but there were significant reductions in both parameters when applying less amounts of water. However, the reductions were less evident between the full irrigation and V80 than between the other deficit irrigation treatments. Many authors have widely reported that deficit irrigation depresses tomato yield depending on period and degree of water deficit (Zegbe et al., 2006 ; Favati et al., 2009 ; Patanè and Cosentino, 2010 ). In 2024, fruit yield and TDM were significantly depressed with extended reduction of irrigation water during the whole growing season in V50 with respect to full irrigation, since many small green fruits aborted or did not enlarge enough under drier conditions. However, it is important to avoid prolonged stress, which may stunt plant growth and reduce overall biomass. Deficit irrigation, which included deficit of water supply early in the season (V50-100), resulted in better yield and TDM than deficit at the later stage of the growth (V100-50). However, CDI early in the season typically targets the vegetative growth phase, where tomato plants are less sensitive to water stress and could preserve water without severely impacting fruit yield. This result was probably due to the reduction of irrigation water at the early stage, which did not cause enough water stress to affect the formation of tomato yield since the early soil water deficit at the vegetative stage is too early to affect physiological status (Ngouajio et al., 2007 ; Wang and Zhang, 2013 ; Nangare et al., 2016 ). Moreover, moderate water stress during the vegetative stage has been shown to help roots growth, which makes it easier for plants to get to deeper soil moisture reserves ((Nangare et al., 2016 ; Cui et al., 2019 ; Liu et al., 2019 ). Similarly, a lower fruit weight per plant as soil water tension during fruit development and maturation increased, which resulted in lower fruit size as also reported by Hanson et al., ( 2006 ), Marouelli and Silva, ( 2007 ), and Favati et al., ( 2009 ). Total dry matter distribution and the values of total HI in 2023 showed a continuous decline with increasing levels of water deficit compared to the control, indicating a low ability of the stressed plants to recover after rewarding. In 2024, HI measurements decreased significantly in response to V50 and late water deficit, which was associated with a reduced TDM distribution among fruits and thus a yield reduction. However, in the (V50-100) treatment, HI remained very close to the control, which was related to the favorable growth conditions promoted by initial canopy development, higher water use, and dry fruit biomass. These results indicate that the indeterminacy of the tomato plant and irrigation during the second part of tomato growth coincided with the phonological stages that are most sensitive to water stress (Wang, and Zhang, 2013 ; Valcárcel et al., 2020 ). 4.2. Water-yield relationships. Efficient water distribution through a deficit irrigation regimes has been identified as a potential approach to improve the sustainability of horticultural production in water-scarce regions. Water productivity increased with a water shortage, and its maximum value corresponded to irrigation treatment receiving a minimum water supply in V40 and V50 in the years 2023 and 2024, respectively. This result suggests that the crop can still benefit from the water when this last is supplied to fulfill half of its water requirements. However, it is possible to save water and improve water use efficiency in tomato, but water should be applied to the crop throughout the whole growing season, even at a low rate, to minimize fruit losses in arid and semi-regions. Although identical irrigation management during the whole growth period, as this study, did not achieve maximum water saving, it was easy to operate because water supply during various growth periods could be directly determined according to the changes of crop coefficient ( K c) and meteorological conditions. The relationship between total fruit yield and crop ET showed significant differences when the latter decreased across the different irrigation regimes (Table 3 ). Although the savings in water were close in both treatments, V50-100 increased WP markedly compared to V100-50 and attained superior effect on yield production. This is in agreement with previous findings in tomato cultivated under a wide range of deficit irrigation treatments (Favati et al., 2009 ; Ozbahce and Tari, 2010 ; Patanè et al., 2011 ). The acceptable level of deficit irrigation in most of the studies has consistently increased WP of tomato crop with negligible to marginal yield reduction (Kirda et al., 2004 ; Patanè et al., 2011 ; Kuscu et al., 2014 ; Nangare et al., 2016 ). The production function (total volume of applied water versus fresh fruit yield) through linear regression analysis and a mathematical function showed a significant determination factor (R 2 = 0.979 and 0.903) in 2023 and 2024, respectively (Fig. 2 ). As expected, the relationships between fruit yield and crop ET were linear (a single line represented all four irrigation treatments), found in many other crops such as sunflower (Karam et al., 2007 ), sweet corn (Oktem, 2008 ), green bean (Sezen et al., 2008 ), and maize and sorghum (Farré and Faci, 2006 ). Many studies have also shown that tomato yield responded linearly to the amount of applied water (Lovelli et al., 2007 ; Patanè et al., 2011 ; Kuscu et al., 2014 ). 4.3. Yield and TDM response factors Crop productivity is strictly linked to the water supply to achieve acceptable yield quantity and quality. However, tomato plants were more tolerant to deficit irrigation than other vegetable crops such as eggplant (Lovelli et al., 2007 ; Karam et al., 2011 ) and potato (Hill et al., 2021 ; Badr et al., 2022 ). The equation model of K y proposed by Doorenbos and Kassam ( 1986 ) allowed for the prediction of crop productivity as a response to their water use by means of the equation reported by Stewart et al., ( 1977 ). This factor is crop-specific and indicates the ability of the crop to withstand water stress when its value is less than one, with a little reduction in yield and stability in water productivity. Given that the observed yield reductions were less than the ET reductions applied under the different irrigation regimes, this may indicate the validity of the yield response factor to water (Ky) as a synthesized criterion for measuring a crop's ability to tolerate water stress. At a value of Ky less than 1, tomatoes show good tolerance to water-deficit regimes with only a slight reduction in yield and significant stability in water productivity. However, tomato seemed to be more sensitive to the severity of the deficit irrigation (throughout the whole growing season) as shown in 2023 under RDI, although the difference between K y factors going from the V100 treatment to V40 was sensible, but all values were still lower than one even with V0 when the water supply was cut off very early in the season. On the other hand, reduce of irrigation water early in the season in 2024 under CDI typically results in lower K y values compared to late-stage, indicating a more resilient response to early-season water stress. This resilience is attributed to the plant's ability to compensate for early deficits through enhanced root growth and improved physiological adaptations. Conversely, reduced of water in late stage might show higher K y values due to increased sensitivity of fruit development processes to water shortage (Fig. 4). Calculating this coefficient as referring to plant TDM rather than yield, the values of K ss in both years were markedly lower than K y, which indicates a different behavior for the TDM towards exposure to water deficit. The water regime effect on assimilating distribution and on yield components may explain the difference in this behavior, where the HI change markedly under water deficit treatments indicates that biomass accumulation of tomato is less affected by soil water deficit than fruit yield, and this is because fruit losses increase with increasing soil water deficit. The slope of the fitted regressions represents the yield response factor for yield, and TDM for all treatments confirms the previous results with the same trend (Fig. 3). Patane et al., (2011) reported that the yield response factor was 0.76 for marketable yield ( K y) and 0.49 for total dry biomass ( K ss), indicating that in both cases, the reduction in crop productivity is proportionally less than the relative ET reduction. These findings suggest that while both RDI and CDI can enhance water productivity, they also lead to a reduction in total fruit yield. CDI appears to be more advantageous than RDI due to its lower impact on yield reduction and lower K y value. This implies that strategic timing of water deficits can mitigate adverse effects on crop performance. Considering the specific character of tomato growth, the yield of each harvest was summed up at the end of the cropping season as the total yield, which was used to calibrate the water-yield models. Nuruddin et al., ( 2003 ) reported that the period of fruit growth was most responsible for the improvement of tomato yield, which was also confirmed by Yang et al., ( 2019 ). When the early-ripening fruits were harvested, the water deficit would not affect them, but the rest of the fruits were still developing and ripening, which explains the lower fruit weight of the crop. However, due to the indeterminate nature of the tomato growth, the overlaps between fruit development and fruit ripening lead to many times of harvest during the fruit ripening stage, which may affect the productivity of the total yield. Given that all the crop growth stages were not equally sensitive to water stress, the response of tomato to drought stress is complex and depends on the intensity and duration of the stress as well as the developmental stage at which the stress occurs. Nuruddin et al., ( 2003 ) reported that the period of fruit growth was most responsible for the improvement of tomato yield, which was also confirmed by Chen et al. ( 2014 ) and Valcarcel et al., (2020). Finally, the water yield model has a potential use in optimizing irrigation water allocation during the growth season, thus achieving efficient production in consideration of the compromise between tomato yield and water productivity. 5. Conclusions Processing tomato, a vital crop for the food industry, requires substantial amounts of water throughout the growing season. Applying an irrigation strategy that focuses on a partial restoration of the water consumption during the whole growing season is not advisable for tomato. Conversely, controlled deficit irrigation presents a promising strategy for managing water resources in tomato cultivation. The timing of irrigation deficits plays a crucial role in determining their impact on yield, where not all growth stages are equally sensitive to water stress. However, the early stage of growth appears to offer a balanced approach by promoting efficient water use while maintaining acceptable yields. However, careful management is essential when applying controlled deficit irrigation during the later stage to avoid adverse effects on fruit yield. For that reason, a proper application of deficit irrigation may contribute to obtaining a good compromise between yields and the saving of irrigation water. This aspect is particularly important in arid regions, where water scarcity is an increasing concern and water costs are continuously rising. Declarations This research paper was funded by the National Research Centre (NRC) according to the agreement with STDF. Conflict of Interest All the authors of the manuscript under the title "Effect of regulated and controlled deficit irrigation on yield and yield response factor of processing tomato" do not have a conflict of interest with any other person or entity, and this is our acknowledgment regarding this matter. Author Contribution All authors participated in defining the experimental plan and parameters, implementing the crop cultivation process, estimating plant characteristics, conducting the necessary laboratory analyses, and writing and reviewing the research. 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(2007). Water tension thresholds for processing tomatoes under drip irrigation in central Brazil. Irrigation Science 25, 41–418. https://doi.org/10.1007/s00271-006-0056-6 Nangare, D.D.; Singh, Y.; Kumar, P.S.; Minhas, P.S. (2016). Growth, fruit yield, and quality of tomato ( Lycopersicon esculentum Mill.) as affected by deficit irrigation regulated on a phenological basis. Agric. Water Manage. 171: 73-79. https://doi.org/10.1016/j.agwat.2016.03.016 Ngouajio, M., Wang, G., Goldy, R. (2007). Withholding of drip irrigation between transplanting and flowering increases the yield of field-grown tomato under plastic mulch. Agric. Water Manag. 87, 285–291. https://doi.org/10.1016/j.agwat.2006.07.007 Nuruddin, M.M., Madramootoo, C.A., Dodds, G.T. (2003). Effects of water stress at different growth stages on greenhouse tomato yield and quality. HortScience38, 1389–1393. https://doi.10.21273/HORTSCI.38.7.1389 Oktem, A. (2008). Effects of water shortage on yield and protein and mineral composition of drip-irrigated sweet corn in sustainable agricultural systems. Agric. Water Manag. 95, 1003–1010. https://doi.org/10.1016/j.agwat.2008.03.006 Ozbahce, A., Tari, A.F. (2010). Effects of different emitter space and water stress on yield and quality of processing tomato under semi-arid climate conditions. Agric. Water Manag. 97, 1405–1410. https://doi.org/10.1016/j.agwat.2010.04.008 Patanè, C., Cosentino, S.L. (2010). Effects of soil water deficit on yield and quality of processing tomato under a Mediterranean climate. Agric. Water Manag. 97, 131–138. https://doi.org/10.1016/j.agwat.2009.08.021 Patanè, C., Tringali, S., Sortinob, O. (2011). Effects of deficit irrigation on biomass, yield, water productivity, and fruit quality of processing tomato under semi-arid Mediterranean climate conditions. Sci. 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Agron. 26, 64–70. https://doi.org/10.1016/j.eja.2006.08.004 Valcárcel, M., Lahoz, I., Campillo C., Martí R., Leiva-Brondo M., Roselló S., Cebolla-Cornejo J. (2020). Controlled deficit irrigation as a water-saving strategy for processing tomato. Sci. Hortic., 261 (5), Article 108972, 10.1016/j.scienta.2019.108972 Wang, Y.M., Zhang, H.J. (2013). Effect of regulated deficit irrigation on yield and water use efficiency of processing tomato ( Solanum lycopersicum ). AMR, 864–867, 2009–2012. https://doi.org/10.4028/www.scientific.net/amr.864-867.2009. Yang H., Shukla M.K., Mao X., Kang S., Du T. (2019). Interactive regimes of reduced irrigation and salt stress depressed Tomato water use efficiency at leaf and plant scales by affecting leaf physiology and stem sap flow. Front. Plant Sci. 10:160. doi: 10.3389/fpls.2019.00160 Zegbe, J.A., Behboudian, M.H., Clothier, B.E. (2006). Responses of ‘Petoride’ processing tomato to partial root zone drying at different phonological stages. Irrig. Sci. 24,203–210 https://doi.10.1007/s00271-005-0018-4 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7162684","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491180813,"identity":"6995f3fc-e3ca-4b7c-aa28-8ba9adb66892","order_by":0,"name":"M. A. Badr","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACAzBiOCBnAOFaEK/F2ICBGcSVIF5L4gawFgYitJizH9726UbNnfTt7P1HN/wokGDgb+9OwKvFsieteHbOsWe5O3sOs93sATpM4szZDfgddiDHmDmH7XDuhhvJbDd4gFoMJHIJaDn/Bqjl3+F0A6CWm3+I0nIDaEtu2+EEkJbbRNliOeNZMXNu3zPDDWcOm92WMZDgIegXc/7kzcw53+7IGxxvfHbzzR8bOf72XvxaMAAPacpHwSgYBaNgFGAFAAwySmWYDOfFAAAAAElFTkSuQmCC","orcid":"","institution":"National Research Centre","correspondingAuthor":true,"prefix":"","firstName":"M.","middleName":"A.","lastName":"Badr","suffix":""},{"id":491180815,"identity":"24f493c9-e44e-490c-97f2-e5bcc4abc003","order_by":1,"name":"Eman Ali","email":"","orcid":"","institution":"National Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Eman","middleName":"","lastName":"Ali","suffix":""},{"id":491180816,"identity":"6db014c9-6ebe-4ff2-89e5-c42bb0b6f356","order_by":2,"name":"S. R. Salman","email":"","orcid":"","institution":"National Research Centre","correspondingAuthor":false,"prefix":"","firstName":"S.","middleName":"R.","lastName":"Salman","suffix":""}],"badges":[],"createdAt":"2025-07-19 07:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7162684/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7162684/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87695218,"identity":"62440200-e748-4e01-9c80-35e14d920d11","added_by":"auto","created_at":"2025-07-28 05:52:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":18540,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between total tomato yield and seasonal water applied in 2023 for RDI (a) and 2024 for CDI (b) through regression analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7162684/v1/3d12e354fbc9c68dc84e5374.png"},{"id":87695221,"identity":"2e456b8a-ddbe-44ac-87a8-45de2b7ca22c","added_by":"auto","created_at":"2025-07-28 05:52:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":21131,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between relative yield decrease (solid curve) and total dry biomass decrease (dotted curve) vs. relative ET decrease in 2023 for (RDI) and 2024 for (CDI).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7162684/v1/e2af680f0d93b61887240b91.png"},{"id":88502846,"identity":"37bcbc34-0f84-49b1-9ea4-92a791729df6","added_by":"auto","created_at":"2025-08-07 07:02:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":943890,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7162684/v1/9cd16b18-0333-4733-8358-17d78aba7ff2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEffect of Regulated and Controlled Deficit Irrigation on Yield and Yield Response Factor of Processing Tomato\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003eWater scarcity poses a significant challenge to tomato production, which necessitates efficient irrigation strategies.\u003c/li\u003e\n \u003cli\u003eRDI reduced fruit yield under all levels but improved water use efficiency.\u003c/li\u003e\n \u003cli\u003eCDI early in the season produced a comparable yield to full irrigation coupled with a significant amount of water saving.\u003c/li\u003e\n \u003cli\u003eStrategy that considered timing of water deficits can mitigate adverse effect on yield with appreciable amount of water saving.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eA yield response factor (\u003cem\u003eK\u003c/em\u003ey) lower than one indicates that tomato is relatively tolerant of water stress.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eThe continuous escalation in the demand for freshwater on a global scale to meet the needs of natural ecosystems will force irrigation to operate under water scarcity. In many areas of the world, irrigation processes are still practiced until now with disregard to basic principles of resource preservation. The increasing competition for water resources between agriculture and other sectors compels the adoption of irrigation strategies in arid regions, which may allow saving irrigation water and still maintaining satisfactory levels of production (Nangare et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Under such conditions, there is an urgent need for a water-saving strategy that must be seen as the major threat to food security in the future. Soil and water management is most likely the best option in most agricultural systems for increasing the efficiency of water use (Khapte et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe process of crop water use has two main components of water losses: evaporation from the soil and the plant, as well as all the losses resulting from the distribution of water to the land (Fereres and Soriano, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, reducing crop ET without a penalty in crop production is much more difficult because evaporation from crop canopies is tightly coupled with the assimilation of carbon (Steduto et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Thus, some of the water losses are unavoidable and are needed to be minimized with efficient irrigation methods and by appropriate management.\u003c/p\u003e\u003cp\u003eThe main approach to achieve this goal involves adopting more efficient irrigation techniques, such as drip irrigation, which reduce evaporation losses (Khapte et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as well as using deficit irrigation (DI) strategy (Douh et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kiyan et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this way, the entire root zone is irrigated with lower amounts of water while the minor stress that develops has minimal effects on the yield. Controlled deficit irrigation (CDI) is an alternative for areas where DI evidenced a negative effect on yield, as it seeks to optimize the use of water stress only in noncritical periods of the development of the plant. The timing and stage at which stress is imposed, as well as the intensity of stress also influence water productivity. This mode of irrigation requires close control of the timing and level of water deficit so that water deficits can be imposed at times when it has a minimum effect on yield (Valc\u0026aacute;rcel et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTomato is one of the most widely cultivated vegetables globally, valued for its nutritional content and economic importance. However, water scarcity poses a significant challenge to tomato production, necessitating efficient irrigation strategies. Tomato is relatively resistant to water stress; hence, deficit irrigation could be managed because it can tolerate drought to some degree (Hanson and May, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Patane et al., 2011). Regulated deficit irrigation (RDI) and controlled deficit irrigation (CDI) can be considered as two strategies that aim to improve water use without compromising crop yield. Many studies showed that the response of tomato yield to deficit irrigation at various growth stages was different, depending on the period and the degree of water deficit (Zegbe et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kuscu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, the tomato plant is particularly sensitive to water deficit during reproductive development, as it causes physiological disturbances leading to the loss of flower buds and open flowers, as well as a reduction in fruit set, which has a negative impact on commercial yield (Lamin-Samu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It was reported that there were no adverse effects on tomato yield and fruit quality by imposing a certain degree of water stress during the vegetative stage (Marouelli and Silva, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Kuscu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, the study of Ngouajio et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) showed that withholding irrigation between transplanting and flowering may save the amount of irrigation water by 20% while increasing tomato yield by 8\u0026ndash;15%. Chen et al., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) stated that tomato yield was sensitive to water deficit during fruit development and ripening, while fruit quality was mainly affected by water deficit during fruit ripening. Patan\u0026egrave; et al., (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) reported that CDI of 100\u0026ndash;50% ET crop offered a similar performance compared to DI covering 50% ET crop, with no significant impact on marketable yield and TDM. Similarly, Jiang et al., (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) confirmed an acceptable balance between high water productivity and yield, supplying 2/3 of FI at flowering and fruit development.\u003c/p\u003e\u003cp\u003eAlthough DI has been assessed for tomato, giving different results, many of the obtained results have shown that DI saves substantial amounts of irrigation water and increases water productivity (Kirda et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Topcu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Patane and Cosentino, 2010). However, few studies were reported about the application of DI in water yield relations of tomato, and so far as the literature reported, no modeling equations have been evaluated for the effects of different degrees of water deficit at various growth stages. The aim of the present study was to (i) determine the effect of deficit irrigation throughout the growing season and at different growth stages on yield and yield-water relationships of processing tomato (ii) develop an irrigation strategy that ensures water savings to irrigate more land, especially under desert agro-systems. This aspect is of utmost importance given the difficulty of providing more water needed for the agricultural sector especially in arid and semi-arid regions.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Site and soil description.\u003c/h2\u003e\u003cp\u003eField experiments were conducted on a vegetable farm located in the Serapium area, Ismailia province, east of the Nile Delta, Egypt, during the late summer growing season (August-December) 2023 and 2024 using a drip irrigation system. This area is a desert region included in the agricultural expansion program and has recently become productive land for many crops. The site is located in the arid climate at latitude 30\u0026deg;58 N and longitude 32\u0026deg;23 E with an elevation of 13 m above mean sea level. The area experiences a hot and dry climate with very little rainfall throughout the year. Temperatures can be very high in summer (June to August), often exceeding 35\u0026deg;C during the day, with little relief at night. Winter months (November to February) are mild, with daytime temperatures ranging from 15\u0026deg;C to 25\u0026deg;C and cooler nights, sometimes dropping to around 10\u0026deg;C or lower. The mean monthly evapotranspiration ranged from 6.9 to 2.5 mm in the respective cropping season. The climate parameters recorded from August to December during both growing seasons are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The average soil water content at field capacity from the surface soil layer down to 80 cm depth at 20 cm intervals was 0.18 (v/v), and the permanent wilting point for the corresponding depths was 0.08 (v/v), respectively. Average available N, P, and K from the surface soil layer down to 60 cm depth at 20 cm intervals were 12, 7, and 43 mg kg⁻\u0026sup1; soil, respectively, before the initiation of the experiment.\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\u003eAverage monthly maximum (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e) and minimum (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003emin\u003c/em\u003e\u003c/sub\u003e) temperature, relative humidity, rainfall, evapotranspiration (ET\u003csub\u003e0\u003c/sub\u003e), and wind speed during the growing season.\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=\"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=\"left\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonth\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\u003cp\u003e(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003csub\u003emin\u003c/sub\u003e\u003c/p\u003e\u003cp\u003e(\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelative\u003c/p\u003e\u003cp\u003ehumidity (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRain fall\u003c/p\u003e\u003cp\u003e(mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eET\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e\u003cp\u003e(mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eWind speed (km h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAugust\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeptember\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e16.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOctober\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNovember\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecember\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAugust\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeptember\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOctober\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNovember\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecember\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.8\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=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Experimental design and treatments.\u003c/h2\u003e\u003cp\u003eProcessing tomato plants were subjected to different irrigation treatments based on crop evapotranspiration (ETc) in a complete randomized block design with three replicates. Five irrigation treatments were imposed over 2 years, including regulated deficit irrigation (RDI) in 2023 and controlled deficit irrigation (CDI) in 2024 under field conditions (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). RDI involved a consistent reduction in water supply throughout the growing season, while CDI maintained a consistent reduction in water supply throughout definite growing stages.\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\u003eDescription of irrigation treatments applied to tomato in two growing seasons.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreatments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWater applied (mm)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100% ETc (full irrigation)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e374\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80% ETc of full irrigation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e314\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60% ETc of full irrigation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e240\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40% ETc of full irrigation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo irrigation after plant establishment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV100-100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100% ETc (full irrigation)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e386\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV50-50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50% ETc during the whole season\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e206\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV50-100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50% ETc reduction up to 1st fruit set, 100% ETc restoration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e303\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV100-50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100% ETc reduction up to start of\u003c/p\u003e\u003cp\u003ematurity stage, 50% ETc restoration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e318\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo irrigation after plant establishment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e55\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\u003eBefore tomato transplanting, drip tubing (twin-wall, 15 mm inner diameter, in-line drippers at 40 cm distance delivering 2.5 liter h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e at operating pressure 100 kPa) was laid out along each row at 100 cm apart in the center of the soil beds. Tomato seedling (\u003cem\u003eSolanum Lycopersicum\u003c/em\u003e L.) cultivar \u0026lsquo;Castle Rock\u0026rsquo; was directly transplanted to the main field at 25 cm intervals along drip lines (40000 plants ha\u003csup\u003e\u0026ndash;1\u003c/sup\u003e) in all the treatments in the middle of August. Plants were arranged in north-south-oriented soil beds pre-furrowed to receive 40 t ha\u003csup\u003e\u0026ndash;1\u003c/sup\u003e of organic manure in plots (4.5 m wide \u0026times; 15.0 m long). All treatments received the same amount of phosphorus, 150 kg P ha\u003csup\u003e\u0026ndash;1\u003c/sup\u003e as single super phosphate and 250 kg K ha\u003csup\u003e\u0026ndash;1\u003c/sup\u003e as potassium sulphate before transplanting, which was incorporated into the soil beds. Nitrogen fertilizer was applied as ammonium nitrate in water-soluble form at 7-day intervals in the drip irrigation system using a venturi-type injector. Fertigation events of N were started two weeks after planting in 12 equal doses and stopped 30 days prior to the end of the growing season.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Estimation of crop water requirement.\u003c/h2\u003e\u003cp\u003eMeteorological data were calculated from the weather station of the Central Laboratory of Agricultural Climate for Ismailia province located near the experimental field. The irrigation water was applied on a daily basis according to Penman-Monteith\u0026rsquo;s semi-empirical formula (ETc\u0026thinsp;=\u0026thinsp;ET\u003csub\u003e0\u003c/sub\u003e \u0026times; \u003cem\u003eK\u003c/em\u003ec) as proposed by Allen et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The actual crop evapotranspiration rate (ETc) was based on the product of ET\u003csub\u003e0\u003c/sub\u003e and crop coefficient (\u003cem\u003eK\u003c/em\u003ec) for different months based on crop growth stages using values for tomato (\u003cem\u003eK\u003c/em\u003ec initial\u0026thinsp;=\u0026thinsp;0.45, \u003cem\u003eK\u003c/em\u003ec developmental\u0026thinsp;=\u0026thinsp;0.75, \u003cem\u003eK\u003c/em\u003ec middle\u0026thinsp;=\u0026thinsp;1.15, \u003cem\u003eK\u003c/em\u003ec maturity\u0026thinsp;=\u0026thinsp;0.85) for growth stages 30/40/40/25 days (Allen et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The values of ETc were reduced frequently to account for the percentage of wetted area resulting from the drip line spacing in the field. The percentages of wetted area were determined as the average horizontal area wetted of the crop root zone as a percentage of the total crop area. Cumulative ETc for the different irrigation treatments and the relative quantity of water saving during the whole growing period were presented in (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). During the initial stage of growth, tomato plants were irrigated daily to encourage establishment, but thereafter irrigation frequency was running at 2\u0026ndash;3 day intervals. The irrigation process was ceased at 120 DAP (15 days before the last picking) to prevent secondary growth.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Yield response factor.\u003c/h2\u003e\u003cp\u003eThe functional relationship between crop yield and water use is called the water-production function (ratio of actual to maximum ET) that limits the crop yield, assuming that all the other factors are at the optimum level. Seasonal values of the yield response factor (\u003cem\u003eK\u003c/em\u003ey) were calculated for each experimental year as follows:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:1-\\left(\\frac{\\text{Y}\\text{a}}{\\text{Y}\\text{m}}\\right)=Ky\\:\\left(1-\\frac{\\text{E}\\text{T}\\text{a}}{\\text{E}\\text{T}\\text{m}}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere Ym (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and Ya (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) are maximum (that obtained from fully irrigated treatment) and actual yield, respectively, ETm (mm ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and ETa (mm ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) are maximum (that obtained from fully irrigated treatment) and actual ET, respectively, \u003cem\u003eK\u003c/em\u003ey is the yield response factor, that is defined as the decrease in yield per unit decrease in ET (Stewart et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). According to the \u003cem\u003eKy\u003c/em\u003e calculation, \u003cem\u003eK\u003c/em\u003ess was calculated by the Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), replacing Ym with maximum total dry biomass (SSm) and Ya with actual total dry biomass (SSa) as follows:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:1-\\left(\\frac{\\text{S}\\text{S}\\text{a}}{\\text{S}\\text{S}\\text{m}}\\right)=Kss\\:\\left(1-\\frac{\\text{E}\\text{T}\\text{a}}{\\text{E}\\text{T}\\text{m}}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eK\u003c/em\u003ess indicates the biomass response factor, which is the correlation factor between relative total dry biomass loss and relative ET reduction.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Measurements of crop parameters.\u003c/h2\u003e\u003cp\u003eMaximum biomass production was determined by harvesting three representative plant per treatment replicate at 90 DAT. Plant growth components were determined from 10 randomly selected plants in each plot, including total fresh fruit yield per plant, fruit number per plant, and average fruit weight per plant. At harvest, three representative selected plants were sampled from each experimental plot and plant parts (stems\u0026thinsp;+\u0026thinsp;leaves\u0026thinsp;+\u0026thinsp;fruits) were dried in a thermo-ventilated oven at 70 ◦C until constant weight, for dry biomass measurement. Harvesting of the tomatoes was made on the last week of November until the end of December for both seasons. Total fresh fruit yield was recorded on at least 50 plants in a row in each treatment in all the replications, and data were presented as tons per hectare.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Water productivity.\u003c/h2\u003e\u003cp\u003eWater productivity is an indicator related to the water consumed by crops as to produce a certain yield and calculated for each irrigation treatment as the ratio between total epigeous dry matter at harvest and total water used, as measured by water balance equation:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{W}\\text{P}=\\left(\\frac{\\text{y}\\text{i}\\text{e}\\text{l}\\text{d}\\:{\\text{k}\\text{g}\\:\\text{h}\\text{a}}^{-1}}{\\text{E}\\text{T}\\:\\left(\\text{m}\\text{m}\\right)}\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere WP is water productivity (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) ET is the seasonal plant evapotranspiration (mm).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Statistical analysis.\u003c/h2\u003e\u003cp\u003eAll data were subjected to the analysis of variance (ANOVA) appropriate to the experimental design to evaluate the effects of treatments on tomato yield, total dry biomass, shoot dry weight, N and P uptake. CoStat (Version 6.311, CoHort, USA, 1998\u0026ndash;2005) was used to conduct the analysis of variance. Comparison of treatment means was carried out using the least significant difference (LSD) at a 5% probability level. Regression analysis was performed between total seasonal water use and total fruit yield of the crop for both seasons.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Climate trend and irrigation variables\u003c/h2\u003e\u003cp\u003eAlthough most tomato plants grow and produce best in sunny summer weather, it is possible to grow tomatoes in late summer, particularly in most hot climates. During the growth season, the values of climate parameters differed from (Aug to Dec), where the greatest differences were recorded in Des, both for temperature and relative humidity. During the cropping cycle, one can point out sparse precipitation that occurred without effective amounts for both seasons. The air temperature was higher during the first part of the cycle, in Aug, when the max temperatures were almost over 35 \u003csup\u003eo\u003c/sup\u003eC. Afterwards, in Seb, the daily min and max temperatures decreased and followed the same trend till the end of Des. The described climate parameter, though typical for that area, reduced crop water use due to the low values of daily ET\u003csub\u003e0\u003c/sub\u003e from the planting till harvest and made a clear differentiation of the compared irrigated theses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Tomato yield and TDM.\u003c/h2\u003e\u003cp\u003eThe yield components, including biomass production, fruit weight, harvest index, and WP were significantly affected (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) by deficit irrigation treatments applied in 2023 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Yield was severely depressed by soil water deficit when irrigation was stopped early in the season (V0) in both years, as the plants failed to develop under drier conditions. RDI resulted in a slight reduction in fruit yield by 9.1% in V80, while in V60 and V40 the yield was strongly reduced by 26.2% and 51.1% compared to V100 respectively. The accumulation of TDM also decreased with increasing deficit irrigation, but the differences compared to the V100 were much smaller and amounted to 7.4, 22.8, and 41.8% with V80, V60, and V40, respectively. Average fruit weight was also affected by deficit irrigation, leading to a noticeable decrease in the overall fruit size. This reduction not only impacts yield but also has potential repercussions on market value and consumer preference, especially at V60 and V40, which were significantly reduced compared to the other treatments. The relationship between fruit yield and TDM was very strong (R\u0026sup2; = 0.98), indicating that the crop regulates its fruit yield proportional to total dry matter production.\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\u003eTotal yield, biomass production, fruit weight, harvest index and WP of tomato as affected by deficit irrigation treatments in 2023 for RDI and 2024 for CDI.\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\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eIrrigation treatments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eBiomass (t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFruit weigh\u003c/p\u003e\u003cp\u003e(g fruit\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHarvest index\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eWP\u003c/p\u003e\u003cp\u003ekg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFruit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eShoot DW\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal DW\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e2023 (RDI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.80a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.82a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.76a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e157\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53.45b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.74a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.41b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e170\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.38c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.52b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.69c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e85c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.74d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.19c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.77d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e174\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.59e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.48d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.78e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e2024 (CDI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.25a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.93a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.04a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e97a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e161\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.76c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.65b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.94c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e82c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e222\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV50-100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.87a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.90a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.89a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV100-50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51.64b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.76b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.34b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.89d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.67c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.11d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eValues within the column followed by different letters are significantly different based on least significant difference (LSD) at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn 2024, deficit irrigation at a reduced rate (50% ETc) during the whole growing season (V50) significantly reduced yield by 26.5% compared to V100, as many small green fruits were aborted, besides the decline in the average fruit weight. On the other hand, different degrees of yield reduction were observed in the treatments with deficit irrigation at one growth stage (early or late stage-CDI) compared to full irrigation. Early-stage CDI (V50\u0026ndash;100) does not induce significant losses in fruit yield, while reduction of water during the late stage (V100\u0026ndash;50) resulted in a significant 17.1% lower yield compared to V100.\u003c/p\u003e\u003cp\u003eSimilarly, TDM showed significant differences between irrigation treatments, especially in prolonged deficit irrigation (V50) and in late reduction of water, which were 22.0% and 14.0%, respectively lower than in V100, while early reduction of water (V50-100) resulted in lower losses in final dry biomass (3.1%). Biomass allocation and total biomass index decreased significantly in response to (V50) and late-stage water reduction (V100-50), which was associated with reduced biomass distribution on fruits and hence lower yield. Mean fruit weight was not significantly affected by deficit irrigation except for V50 and V05-100, which decreased significantly compared to V100. The harvest index with V100-50 was almost close to V100, which may be associated with favorable growing conditions, while it decreased significantly with other treatments. Similar to the first season, the relationship between fruit yield and TDM was very strong (R\u0026sup2; = 0.98), confirming the high correlation between both parameters.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Water productivity and production function.\u003c/h2\u003e\u003cp\u003eThe effects of different irrigation treatments on tomato yield in terms of WP varied widely in both years (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In 2023, RDI induced increases of WP values as much as 8.3, 15.0, and 10.8% for V80, V60, and V40, respectively, compared to V100 which resulted in lowest the lowest value. Despite the yield reductions under all deficit irrigation levels, maximum value of WP corresponded to irrigation treatment (V60) indicating that deficit irrigation can still be a viable strategy to enhance water use efficiency. In 2024, maximum WP was found in the treatment with the minimum water supply (V50), but only late stage CDI (V100-50) did so without significant yield reduction compared to V100. Although the savings in water was almost equal in both V50-100 and V100-50, but WP was markedly higher by 22.3% versus 2.3% for both treatments, respectively, compared to V100.\u003c/p\u003e\u003cp\u003eThe relationship from regression analysis between seasonal ETc and fruit yield in both years was shown by a linear function (Fig.\u0026nbsp;3). As expected, the relationships between fruit yield and ETc were linear (a single line represented all five irrigation treatments applied in both years). The production function (total amount of irrigation water vs. fresh fruit yield) through linear regression analysis, showed a significant correlation coefficient (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.97 and 0.90) for RDI and CDI, respectively. Over the range of water inputs, 47\u0026ndash;55 mm for V0 to 374\u0026ndash;386 mm for V100 between planting and harvest, tomato yield increased by about 167 and 177 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for each mm of water applied for RDI and CDI, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Yield response factor\u003c/h2\u003e\u003cp\u003eThe relationship between crop yield and water use was determined through an empirical model that links the relative yield decrease with the corresponding relative ET reduction, and the product of this model is a yield response factor (\u003cem\u003eK\u003c/em\u003ey). This factor was calculated in this experiment for both total yield (\u003cem\u003eK\u003c/em\u003ey) and total dry matter (\u003cem\u003eK\u003c/em\u003ess) produced by the crop for both RDI and CDI (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In 2023, the treatments with RDI showed persistent higher \u003cem\u003eK\u003c/em\u003ey and \u003cem\u003eK\u003c/em\u003ess values with increasing levels of deficit irrigation, indicating that they were less tolerant under higher water stress. However, the treatment with V80 showed a minimum value compared to the maximum value with V40 or even greater with V0 when water supply was cut off very early in the season. In 2024, the treatments with CDI showed lower \u003cem\u003eK\u003c/em\u003ey and \u003cem\u003eK\u003c/em\u003ess factors in V50\u0026ndash;100 versus higher values for the same parameters in V100\u0026ndash;50 which indicates to the sensitivity of tomato to deficit irrigation in the last part of the crop cycle.\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\u003eYield response factor for yield \u003cem\u003eK\u003c/em\u003ey and total dry biomass \u003cem\u003eK\u003c/em\u003ess of tomato for each individual treatment applied in 2023 for RDI and 2024 for CDI.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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=\"char\" char=\".\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreatments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eK\u003c/em\u003ey\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eK\u003c/em\u003ess\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTreatments\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eK\u003c/em\u003ey\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eK\u003c/em\u003ess\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFI\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\u003e--\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eV50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eV50-100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eV100-50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eV0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e--\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eV0\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\u003e--\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 relationships between seasonal ET and yield of tomato for all irrigation treatments applied during both years were well fitted using a linear regression forced to the origin with the regression coefficients (Fig.\u0026nbsp;3). The slopes of the fitted regressions, which represent the \u003cem\u003eK\u003c/em\u003ey and the \u003cem\u003eKss\u003c/em\u003e, were 0.96 and 0.86 for RDI, while they were 0.87 and 0.77 for the same parameters for CDI, respectively, indicating that in both cases the reduction in crop yield is proportionally less than the relative ET reduction. In this regard, tomato seems to be less sensitive to water deficit in terms of total dry biomass, as the last was less affected by water deficit than fruit yield production. However, the calculation of \u003cem\u003eK\u003c/em\u003ey for each specific stage of crop growth may help in defending the most critical period of the crop to water.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Response of fruit yield and TDM.\u003c/h2\u003e\u003cp\u003eTomato is one of the most important vegetable crops that is widely grown around the world, but they are also one of the most water-intensive crops. However, deficit irrigation provides a water-saving strategy that has become very popular in arid and semi-arid regions as an important means of reducing water consumption. In 2023, full irrigation resulted in the highest fruit yield and TDM, but there were significant reductions in both parameters when applying less amounts of water. However, the reductions were less evident between the full irrigation and V80 than between the other deficit irrigation treatments. Many authors have widely reported that deficit irrigation depresses tomato yield depending on period and degree of water deficit (Zegbe et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Favati et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Patan\u0026egrave; and Cosentino, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn 2024, fruit yield and TDM were significantly depressed with extended reduction of irrigation water during the whole growing season in V50 with respect to full irrigation, since many small green fruits aborted or did not enlarge enough under drier conditions. However, it is important to avoid prolonged stress, which may stunt plant growth and reduce overall biomass. Deficit irrigation, which included deficit of water supply early in the season (V50-100), resulted in better yield and TDM than deficit at the later stage of the growth (V100-50). However, CDI early in the season typically targets the vegetative growth phase, where tomato plants are less sensitive to water stress and could preserve water without severely impacting fruit yield. This result was probably due to the reduction of irrigation water at the early stage, which did not cause enough water stress to affect the formation of tomato yield since the early soil water deficit at the vegetative stage is too early to affect physiological status (Ngouajio et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Wang and Zhang, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Nangare et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, moderate water stress during the vegetative stage has been shown to help roots growth, which makes it easier for plants to get to deeper soil moisture reserves ((Nangare et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cui et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similarly, a lower fruit weight per plant as soil water tension during fruit development and maturation increased, which resulted in lower fruit size as also reported by Hanson et al., (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), Marouelli and Silva, (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and Favati et al., (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTotal dry matter distribution and the values of total HI in 2023 showed a continuous decline with increasing levels of water deficit compared to the control, indicating a low ability of the stressed plants to recover after rewarding. In 2024, HI measurements decreased significantly in response to V50 and late water deficit, which was associated with a reduced TDM distribution among fruits and thus a yield reduction. However, in the (V50-100) treatment, HI remained very close to the control, which was related to the favorable growth conditions promoted by initial canopy development, higher water use, and dry fruit biomass. These results indicate that the indeterminacy of the tomato plant and irrigation during the second part of tomato growth coincided with the phonological stages that are most sensitive to water stress (Wang, and Zhang, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Valc\u0026aacute;rcel et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Water-yield relationships.\u003c/h2\u003e\u003cp\u003eEfficient water distribution through a deficit irrigation regimes has been identified as a potential approach to improve the sustainability of horticultural production in water-scarce regions. Water productivity increased with a water shortage, and its maximum value corresponded to irrigation treatment receiving a minimum water supply in V40 and V50 in the years 2023 and 2024, respectively. This result suggests that the crop can still benefit from the water when this last is supplied to fulfill half of its water requirements. However, it is possible to save water and improve water use efficiency in tomato, but water should be applied to the crop throughout the whole growing season, even at a low rate, to minimize fruit losses in arid and semi-regions. Although identical irrigation management during the whole growth period, as this study, did not achieve maximum water saving, it was easy to operate because water supply during various growth periods could be directly determined according to the changes of crop coefficient (\u003cem\u003eK\u003c/em\u003ec) and meteorological conditions.\u003c/p\u003e\u003cp\u003eThe relationship between total fruit yield and crop ET showed significant differences when the latter decreased across the different irrigation regimes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Although the savings in water were close in both treatments, V50-100 increased WP markedly compared to V100-50 and attained superior effect on yield production. This is in agreement with previous findings in tomato cultivated under a wide range of deficit irrigation treatments (Favati et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Ozbahce and Tari, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Patan\u0026egrave; et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The acceptable level of deficit irrigation in most of the studies has consistently increased WP of tomato crop with negligible to marginal yield reduction (Kirda et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Patan\u0026egrave; et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kuscu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nangare et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe production function (total volume of applied water versus fresh fruit yield) through linear regression analysis and a mathematical function showed a significant determination factor (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.979 and 0.903) in 2023 and 2024, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As expected, the relationships between fruit yield and crop ET were linear (a single line represented all four irrigation treatments), found in many other crops such as sunflower (Karam et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), sweet corn (Oktem, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), green bean (Sezen et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and maize and sorghum (Farr\u0026eacute; and Faci, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Many studies have also shown that tomato yield responded linearly to the amount of applied water (Lovelli et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Patan\u0026egrave; et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kuscu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Yield and TDM response factors\u003c/h2\u003e\u003cp\u003eCrop productivity is strictly linked to the water supply to achieve acceptable yield quantity and quality. However, tomato plants were more tolerant to deficit irrigation than other vegetable crops such as eggplant (Lovelli et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Karam et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and potato (Hill et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Badr et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The equation model of \u003cem\u003eK\u003c/em\u003ey proposed by Doorenbos and Kassam (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1986\u003c/span\u003e) allowed for the prediction of crop productivity as a response to their water use by means of the equation reported by Stewart et al., (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). This factor is crop-specific and indicates the ability of the crop to withstand water stress when its value is less than one, with a little reduction in yield and stability in water productivity. Given that the observed yield reductions were less than the ET reductions applied under the different irrigation regimes, this may indicate the validity of the yield response factor to water (Ky) as a synthesized criterion for measuring a crop's ability to tolerate water stress. At a value of Ky less than 1, tomatoes show good tolerance to water-deficit regimes with only a slight reduction in yield and significant stability in water productivity. However, tomato seemed to be more sensitive to the severity of the deficit irrigation (throughout the whole growing season) as shown in 2023 under RDI, although the difference between \u003cem\u003eK\u003c/em\u003ey factors going from the V100 treatment to V40 was sensible, but all values were still lower than one even with V0 when the water supply was cut off very early in the season. On the other hand, reduce of irrigation water early in the season in 2024 under CDI typically results in lower \u003cem\u003eK\u003c/em\u003ey values compared to late-stage, indicating a more resilient response to early-season water stress. This resilience is attributed to the plant's ability to compensate for early deficits through enhanced root growth and improved physiological adaptations. Conversely, reduced of water in late stage might show higher \u003cem\u003eK\u003c/em\u003ey values due to increased sensitivity of fruit development processes to water shortage (Fig.\u0026nbsp;4).\u003c/p\u003e\u003cp\u003eCalculating this coefficient as referring to plant TDM rather than yield, the values of \u003cem\u003eK\u003c/em\u003ess in both years were markedly lower than \u003cem\u003eK\u003c/em\u003ey, which indicates a different behavior for the TDM towards exposure to water deficit. The water regime effect on assimilating distribution and on yield components may explain the difference in this behavior, where the HI change markedly under water deficit treatments indicates that biomass accumulation of tomato is less affected by soil water deficit than fruit yield, and this is because fruit losses increase with increasing soil water deficit. The slope of the fitted regressions represents the yield response factor for yield, and TDM for all treatments confirms the previous results with the same trend (Fig.\u0026nbsp;3). Patane et al., (2011) reported that the yield response factor was 0.76 for marketable yield (\u003cem\u003eK\u003c/em\u003ey) and 0.49 for total dry biomass (\u003cem\u003eK\u003c/em\u003ess), indicating that in both cases, the reduction in crop productivity is proportionally less than the relative ET reduction. These findings suggest that while both RDI and CDI can enhance water productivity, they also lead to a reduction in total fruit yield. CDI appears to be more advantageous than RDI due to its lower impact on yield reduction and lower \u003cem\u003eK\u003c/em\u003ey value. This implies that strategic timing of water deficits can mitigate adverse effects on crop performance.\u003c/p\u003e\u003cp\u003eConsidering the specific character of tomato growth, the yield of each harvest was summed up at the end of the cropping season as the total yield, which was used to calibrate the water-yield models. Nuruddin et al., (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) reported that the period of fruit growth was most responsible for the improvement of tomato yield, which was also confirmed by Yang et al., (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). When the early-ripening fruits were harvested, the water deficit would not affect them, but the rest of the fruits were still developing and ripening, which explains the lower fruit weight of the crop. However, due to the indeterminate nature of the tomato growth, the overlaps between fruit development and fruit ripening lead to many times of harvest during the fruit ripening stage, which may affect the productivity of the total yield. Given that all the crop growth stages were not equally sensitive to water stress, the response of tomato to drought stress is complex and depends on the intensity and duration of the stress as well as the developmental stage at which the stress occurs. Nuruddin et al., (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) reported that the period of fruit growth was most responsible for the improvement of tomato yield, which was also confirmed by Chen et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Valcarcel et al., (2020). Finally, the water yield model has a potential use in optimizing irrigation water allocation during the growth season, thus achieving efficient production in consideration of the compromise between tomato yield and water productivity.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eProcessing tomato, a vital crop for the food industry, requires substantial amounts of water throughout the growing season. Applying an irrigation strategy that focuses on a partial restoration of the water consumption during the whole growing season is not advisable for tomato. Conversely, controlled deficit irrigation presents a promising strategy for managing water resources in tomato cultivation. The timing of irrigation deficits plays a crucial role in determining their impact on yield, where not all growth stages are equally sensitive to water stress. However, the early stage of growth appears to offer a balanced approach by promoting efficient water use while maintaining acceptable yields. However, careful management is essential when applying controlled deficit irrigation during the later stage to avoid adverse effects on fruit yield. For that reason, a proper application of deficit irrigation may contribute to obtaining a good compromise between yields and the saving of irrigation water. This aspect is particularly important in arid regions, where water scarcity is an increasing concern and water costs are continuously rising.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThis research paper was funded by the National Research Centre (NRC) according to the agreement with STDF.\u003c/p\u003e\n\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eAll the authors of the manuscript under the title \u0026quot;Effect of regulated and controlled deficit irrigation on yield and yield response factor of processing tomato\u0026quot; do not have a conflict of interest with any other person or entity, and this is our acknowledgment regarding this matter.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors participated in defining the experimental plan and parameters, implementing the crop cultivation process, estimating plant characteristics, conducting the necessary laboratory analyses, and writing and reviewing the research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllen, R.G., Pereira, L.S., Raes, D., Smith, M. (1998). Crop evapotranspiration. Guidelines for computing crop water requirements. FAO Irrigation and Drainage. Paper No. 56, FAO, Rome, Italy, p. 300.\u003c/li\u003e\n\u003cli\u003eBadr, M.A., El-Tohamy W.A., Salman S.R., Gruda N. (2022). Yield and water use relationships of potato under different timing and severity of water stress. Agric. Water Manag. 271, Article 107793. https://doi.org/10.1016/j.agwat.2022.107793\u003c/li\u003e\n\u003cli\u003eChen, J., Kang, S., Du, T., Qiu, R., Guo, P., Chen, R. (2013). Quantitative response of greenhouse tomato yield and quality to water deficit at different growth stages. Agric. Water Manag. 129, 152\u0026ndash;162. https://doi.org/10.1016/j.agwat.2013.07.011\u003c/li\u003e\n\u003cli\u003eChen, J.L., Kang, S.Z., Du, T.S., Guo, P., Qiu, R.J., Chen, R.Q., Gu, F. (2014). Modeling relations of tomato yield and fruit quality with water deficit at different growth stages under greenhouse condition. Agric. Water Manag., 146, 131\u0026ndash;148. https://doi.10.1016/j.agwat.2014.07.026\u003c/li\u003e\n\u003cli\u003eCoStat Version 6.303 Copyright (1998-2004) CoHort Software798 Lighthouse Ave. PMB 320, Monterey, CA, 93940, USA.\u003c/li\u003e\n\u003cli\u003eCui, J., Shao, G., Lu, J., Keabetswe, L., Hoogenboom, G. (2019). Yield, quality, and drought sensitivity of tomato to water deficit during different growth stages. Scientia Agricola, 77(2), e20180390. https://doi.org/10.1590/1678-992X-2018-0390\u003c/li\u003e\n\u003cli\u003eDoorenbos, J., Kassam, A.H. (1986). Yield response to water. FAO Irrigation and Drainage, Paper No. 33. Food and Agriculture Organization of the United Nations, Rome, Italy, p. 193.\u003c/li\u003e\n\u003cli\u003eDouh, B., Mguidiche, A., Al-Marri, M.J.A., Moussa, M., Rjeb, H. (2021). 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(2013). Effect of regulated deficit irrigation on yield and water use efficiency of processing tomato (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e). AMR, 864\u0026ndash;867, 2009\u0026ndash;2012. https://doi.org/10.4028/www.scientific.net/amr.864-867.2009.\u003c/li\u003e\n\u003cli\u003eYang H., Shukla M.K., Mao X., Kang S., Du T. (2019). Interactive regimes of reduced irrigation and salt stress depressed Tomato water use efficiency at leaf and plant scales by affecting leaf physiology and stem sap flow. Front. Plant Sci. 10:160. doi: 10.3389/fpls.2019.00160\u003c/li\u003e\n\u003cli\u003eZegbe, J.A., Behboudian, M.H., Clothier, B.E. (2006). Responses of \u0026lsquo;Petoride\u0026rsquo; processing tomato to partial root zone drying at different phonological stages. Irrig. Sci. 24,203\u0026ndash;210 https://doi.10.1007/s00271-005-0018-4\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"water stress, tomato yield, water productivity, yield response factor","lastPublishedDoi":"10.21203/rs.3.rs-7162684/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7162684/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDeficit irrigation (DI) can contribute to water conservation and help alleviate water scarcity. For this purpose, two field experiments were conducted in 2023 and 2024 to adopt a strategy that involves lower water use without compromising yield. In 2023, regulated deficit irrigation (RDI) was applied at 100% (V100), 80% (V80), 60% (V60), 40% (V40), and 0% (V0), while in 2024, controlled deficit irrigation (CDI) was applied at 100% (V100) or 50% (V50) during the whole growing season, 50% reduction up to the first fruit set, then 100% restoration (V50-100), and 100% until the beginning of ripening, then 50% reduction (V100-50), and 0% (V0) of evapotranspiration (ET). In 2023, RDI decreased yield by 9.1, 26.2, and 51.1% for V80, V60, and V40, respectively, with a remarkable increase in water productivity (WP) for all treatments compared to V100. In 2024, CDI included a reduction of water early in the season (V50-100) did not lead to significant losses in yield but resulted in a water saving of 25% compared to (V100), while the yield was negatively affected by the reduction of water late in the season (V100-50). WP was positively affected by both treatments, but (V50-100) appreciably increased WP. The sensitivity of tomato to DI was higher when water was applied at different intensities with RDI (\u003cem\u003eK\u003c/em\u003ey = 0.96) than at individual growth stages with CDI (\u003cem\u003eK\u003c/em\u003ey = 0.87). These results indicated that DI during the vegetative growth stage was a better strategy to optimize yield, coupled with water saving and improving WP.\u003c/p\u003e","manuscriptTitle":"Effect of Regulated and Controlled Deficit Irrigation on Yield and Yield Response Factor of Processing Tomato","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 05:52:18","doi":"10.21203/rs.3.rs-7162684/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":"6617a77b-76d2-4f63-9ea4-ee10da0baaa7","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-07T06:54:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-28 05:52:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7162684","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7162684","identity":"rs-7162684","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}