Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Plant Sci., 21 January 2026

Sec. Plant Abiotic Stress

Volume 16 - 2025 | https://doi.org/10.3389/fpls.2025.1740476

This article is part of the Research TopicInnovative Practices for Sustaining Mediterranean Agriculture Under Abiotic StressView all 5 articles

Controlled drainage stabilized cotton yield by enhancing photosynthesis, the antioxidant defenses and osmoregulation at reduced nitrogen fertilization

Yonggang Duan,Yonggang Duan1,2Jiajia FengJiajia Feng1Weihan WangWeihan Wang1Shuaikang Liu*Shuaikang Liu3*Dongliang Qi,,*Dongliang Qi1,2,4*
  • 1School of hydraulic Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou, China
  • 2Zhejiang Key Laboratory of River-Lake Water Network Health Restoration, Hangzhou, China
  • 3College of Life Science, Zaozhuang University, Zaozhuang, Shandong, China
  • 4Engineering Research Center of Ecology and Agriculture Use of Wetland, Ministry of Education, Yangtze University, Jingzhou, Hubei, China

Controlled drainage (CD) can improve crop yield by optimizing the soil water and nutrient environment. Nevertheless, the combined effects of reduced nitrogen fertilization and CD on crop leaf senescence characteristics is unclear. Thus, a two-year field experiment was conducted to address the effects of nitrogen fertilizer rates (280, 252, 224, and 196 kg N ha-1, denoted as N1, N2, N3, and N4, respectively) on the leaf area index (LAI), SPAD value, net photosynthetic rate (Pn), activities of superoxide dismutase (SOD), peroxidases (POD), catalase (CAT), and the contents of soluble protein (SP) and malondialdehyde (MDA) in plant leaves, and the seed yield of cotton under CD and free drainage (FD). CD resulted in greater LAI, SPAD value, Pn, SOD, POD, and CAT activities, and SP content, and smaller MDA content at the three reduced nitrogen rates, and thus obtained a relatively high seed cotton yield. The delayed leaf senescence characteristics were due to greater soil moisture and NO3--N content in the plough (0–40 cm) layer under CD. Notably, all reduced nitrogen rates significantly decreased the cottonseed yield under FD, but N2 and N3 had comparable cottonseed yields under CD. Therefore, we concluded that controlled drainage could stabilize seed cotton yield by improving photosynthesis, the antioxidant defenses and osmoregulation at 80%-90% of normal nitrogen fertilizer rate. The results also reveal the physiological mechanisms through which the drainage regime mediates crop yield under varying nitrogen rates.

1 Introduction

The global population is projected to reach 9.6 billion by 2050 (Jouni et al., 2018). To tackle this challenge and eliminate global hunger and poverty, food and fiber production must be doubled by the end of 2050 (FAO STAT, 2020). Nevertheless, the available agricultural land is limited. Therefore, enhancing the per-unit land area productivity is a feasible way to meet the demand of growing population. Controlled drainage (CD), a drainage water management approach, has been developed to improve crop productivity for sustainable agricultural production (Youssef et al., 2023; Zhang et al., 2025). Through the artificial elevation of the outlet, CD reduces the overall drainage volume (Ballantine and Tanner, 2013) and the loss of nitrogen and phosphorus from croplands (King et al., 2022; Youssef et al., 2023). This resulted in an enhancement of soil fertility and an improvement of soil moisture content (Dou et al., 2021; Qi and Zhu, 2023). Moreover, CD enhanced the harvesting or utilization of precipitation, leading to high crop water productivity (Tolomio and Borin, 2018; Yan et al., 2022). The increased accessibility of water and nutrients contributes to the improvement of plant physiological performance. For instance, under an optimized water and nitrogen management strategy, maize plants exhibited relatively high leaf relative water content, chlorophyll and soluble protein content, as well as a high photosynthetic rate (Qi et al., 2021). Notably, CD is characterized by high resource utilization efficiency and low environmental costs (Shedekar et al., 2021; Wesström et al., 2014; Jouni et al., 2018; Wang et al., 2020), and thus it can be considered an eco-friendly tool to save agricultural resources (Ritzema, 2016). However, previous studies have shown that the impact of CD on crop yield is inconsistent. CD has been found to increase crop yield (Wesström et al., 2014; Jouni et al., 2018; Dou et al., 2021; Qi and Zhu, 2023). Nevertheless, there were adverse effects, no effects, or uncertainties concerning the influence of CD on crop yield (Poole et al., 2013; Awale et al., 2015; Karegoudar et al., 2019; Youssef et al., 2023). Consequently, the physiological mechanisms underpinning the impacts of CD on crop yield necessitate further exploration.

Besides freshwater, nitrogen is another essential resource for crop growth and development. The nitrogen fertilization greatly affects soil water and nitrogen levels, leading to variations of shoot and root growth, and consequently the final yield (Qiu et al., 2022; Qi and Hu, 2022). Improved nitrogen fertilizer management strategies have also been developed to improve crop yield and resource use efficiency. For example, compared with conventional nitrogen fertilization, the optimized nitrogen regime (reduced and top-dressing nitrogen) enhanced soil nitrogen availability and root growth, thus obtain relatively higher yield, crop water productivity and nitrogen use efficiency in rice (Yan et al., 2022). Foliar spraying can replace soil nitrogen topdressing to realize efficient yield formation in late sown cotton production system in the Yangtze River Valley, China (Zhang et al., 2024). However, the effects of nitrogen fertilization on crop yield under CD remains largely unknown (Awale et al., 2015; Qi and Zhu, 2023).

Plants regulate their cellular metabolism and defense mechanisms in the face of drought, waterlogging, salinity, and other abiotic stresses (Ahmed et al., 2002). Superoxide dismutase (SOD), peroxidases (POD), and catalase (CAT) are three crucial protective enzymes involved in active oxygen metabolism for scavenging oxygen free radicals during plant physiological processes (Foyer and Noctor, 2000). Malondialdehyde (MDA), a stable product of membrane lipid peroxidation, reflects the degree of oxidative damage through its levels (Ren et al., 2023). Soluble proteins, the main components of various cells and organelles, its content is closely related to photosynthetic capacity (Qi et al., 2021). Chlorophyll is the most crucial and efficient pigment essential for normal photosynthesis in plants. Its content, indicated by the leaf SPAD value, is closely correlated with the extent of leaf senescence (Yu et al., 2023). Drought, nitrogen deficiency, and their combination reduced antioxidant enzyme activities, raised MDA contents, and accelerated chlorophyll degradation, thus speeding up leaf senescence (Li et al., 2020; Qi et al., 2021). Efficient water management (water-saving irrigation or CD) and nitrogen fertilization strategies jointly mediate plant physiological processes to boost crop yield and resource use efficiency by adjusting soil moisture and nutrient contents (Deichmann et al., 2019; Lu et al., 2021). For example, compared with traditional furrow irrigation, alternate partial root-zone irrigation enhanced soil nitrogen availability (Qi et al., 2021), which contributed to increased SOD, POD, and CAT activities, net photosynthetic rate (Pn), and SPAD value, thereby maintaining leaf greenness (Fu et al., 2024; Li et al., 2020). Moreover, improved water management strategies (CD or alternate wetting and drying irrigation) alleviated the negative impacts of nitrogen deficiency on rice plant growth and yield (Xu et al., 2018; Wu et al., 2023). However, limited information exists on the combined effects of CD and nitrogen fertilization strategies on crop growth and development. Thus, exploring the impacts of CD and nitrogen rates on plant physiological characteristics is crucial for promoting CD regimes and nitrogen management strategies.

Cotton is the most significant fiber crop worldwide and is vital for poverty reduction. Water and nitrogen are two essential factor to determine cotton yield. For instance, compared with conventional irrigation, a mulch drip irrigation system could enhance root growth in the upper soil profile, resulting in a 30% increase in cotton yield (Zhang et al., 2017). Optimizing nitrogen application promoted the synergistic enhancement of efficient radiation utilization and leaf water utilization, thereby increasing cotton yield (Zhang et al., 2024). Moreover, the interaction between nitrogen fertilizer management and water management mediates the soil environment, thereby exerting an influence on crop growth and yield (Xu et al., 2018; Qi et al., 2020a, b; Qi and Zhu, 2023; Hu et al., 2023). Therefore, scientific management of water and nitrogen is vital for sustainable cotton production and thus has attracted wide attention (Hanrahan et al., 2021; Wang et al., 2021; Yuan et al., 2022; Liu et al., 2022). A considerable body of data exists concerning the impact of either drainage regimes or nitrogen application rates on soil mineral nitrogen content, nitrogen loss, and crop yield (Thapa et al., 2015; Karegoudar et al., 2019; Wang et al., 2020; Liu et al., 2022; Youssef et al., 2023). However, the combined effect of these factors remains ambiguous (Awale et al., 2015; Qi and Zhu, 2023); particularly the effects on leaf senescence characteristics. In addition, the Jianghan Plain in China is a crucial region for cotton production, with the planted area reaching 100,000-150,000 hectares by the end of 2020 (Liu et al., 2022). Also, in the local area, excess water is predominantly drained freely through open trenches, leading to a reduction in crop yield and waste of chemical fertilizer (King et al., 2022; Tanga et al., 2025). Therefore, exploring an improved drainage regime that delays leaf senescence under nitrogen reduction is of significant importance for the sustainable development of cotton production in this region.

The primary objectives of this study were to elucidate the impacts of CD on leaf senescence and cotton yield by examining the LAI, activities of SOD, POD, and CAT, Pn, soil and SPAD value, soluble protein content, and MDA content under conditions of reduced nitrogen fertilizer application rates, and to expound the potential reasons. It was hypothesized that CD results in higher soil nitrogen and water contents in the plough layer by reducing nitrogen loss and water discharge via runoff, sustains normal plant growth, and thereby contributes to delay leaf senescence and consequently the stabilization of cotton yield at reduced nitrogen fertilization. The findings can offer a scientific foundation for guiding drainage and nitrogen fertilization practices in cotton cultivation within the Jianghan Plain and other regions featuring comparable environmental conditions.

2 Materials and methods

2.1 Experimental site

A two-year field experiment (2018-2019) was conducted at the agricultural test station in Jingzhou City, central China (29° 26′N, 111° 15′E, 28 m above sea level). This area features a typical subtropical monsoon climate, with an average yearly rainfall of about 1,050 mm. The region enjoys a mean annual sunshine duration surpassing 1,725 hours and an average yearly temperature of 16.6°C. Figure 1 displays monthly precipitation, mean air temperature, and sunshine duration during both cotton cultivation seasons, together with the related 30-year averages (1988-2017). According to FAO standards, the soil at the experimental site is categorized as calcareous alluvial, with a field capacity (Fc) averaging 23.8% and a pH of 6.9. Analysis of the topsoil (0–40 cm) showed that organic matter content, total N, total phosphorus, and total potassium were 17.58, 1.25, 0.48, and 22.23 g kg-1, respectively. Moreover, available phosphorus, available potassium, nitrate N (NO3--N), and ammonium N (NH4+ -N) were 12.21, 85.10, 4.87, and 9.28 mg kg-1, respectively.

Figure 1
Bar charts depicting monthly weather data from May to November for the years 2018 and 2019, compared to a 30-year average. The top chart shows precipitation in millimeters, the middle chart shows sunshine duration in hours, and the bottom chart shows average temperature in degrees Celsius. Each chart illustrates data with bars in green for 2018, brown for 2019, and blue for the 30-year average.

Figure 1. Monthly weather condition (precipitation, sunshine duration, and average temperature) during the cotton growing season in 2018 and 2019 at the experimental site.

2.2 Experimental design

A split-plot design was utilized, where drainage regime served as the main plot and nitrogen (N) fertilizer rate acted as the sub-plot factor. Each plot covered an area of 24 m2 (6 m × 4 m) and was repeated three times. Two parallel drainage ditches were built in every plot, each being 6 m long, 10 cm deep, and 15 cm wide. Polyethylene film was placed within backfilled trenches to a depth of 1 m along the boundary of each plot to form a hydraulic barrier. The drainage regimes consisted of free drainage (FD) and controlled drainage (CD). In the FD regime, field ditches were handled according to natural drainage patterns, in line with locally suggested farming practices. In the CD regime, an iron sluice gate was installed at one end of the drainage ditches, and the other end was blocked with a polyvinyl chloride board to retain surface runoff within the experimental plot. The sluice gate stayed shut until the water level in the ditch reached 5 cm—a level recognized as possibly inducing waterlogging stress in cotton plants (Qi and Zhu, 2023). The sluice gate was manually operated based on visually observed water depths during rainfall occurrences. A graduated steel ruler, 20 cm long, was set up in the middle of each ditch to check the depth of collected water. Four N application rates were assessed: a reference rate of 280 kg N ha-1, together with three reduced levels equivalent to 90%, 80%, and 70% of the suggested nitrogen rate, namely 252, 224, and 196 kg N ha-1, designated as N1, N2, N3, and N4, respectively. The rate of 280 kg N ha-1 was taken as the recommended N level for local cotton growing according to soil test outcomes (Qi and Zhu, 2023).

2.3 Field management

Before sowing, calcium superphosphate (with 17% P2O5) and muriate of potash (with 60% K2O) were applied at rates of 529 kg ha kg-1 and 300 kg ha kg-1 respectively. Urea (46% N) was used as the nitrogen source and applied in split doses: 30% as basal fertilizer, then 30% at the bud stage and 40% at the flowering stage as topdressing. The basal fertilizers of N, P2O5, and K2O were applied by banding, while N topdressing was put into the planting holes. A commercial cotton variety (Gossypium hirsutum L.), Zhongmiansuo No.63, was used as the test material. Sowing occurred on May 10 and 12, and harvesting was carried out on November 19 and 20 in the 2018 and 2019 growing seasons respectively. Seeding furrows, each 3.5 cm deep and 5.0 cm wide, were made by an machine-drawn plough with a row spacing of 80 cm. By using a manual hill-drop sowing method, four to six seeds were placed per hill at intervals of 23.7 cm within the rows. Cotton seedlings were thinned to a density of 5.24 plants per square meter at the two-leaf stage. Each experimental plot had five rows, each 6.0 meters long and spaced 80 cm apart. Throughout the growing season, the crop depended only on natural rainfall without any additional irrigation. During both years of the study, diseases, weeds, and insect pests were well managed in all treatments.

2.4 Data collection

2.4.1 Leaf area index and SPAD values

At six crucial growth stages-seeding, squaring, budding, flowering, boll setting, and maturity, measurements of leaf area and SPAD values were conducted. In 2018, these stages took place at 34, 55, 83, 99, 126, and 156 days after planting (DAP), respectively. For the 2019 season, the corresponding DAP values were 35, 56, 84, 100, 127, and 158 DAP. A portable area meter (LI-3050C; Li-Cor, NE, USA) was utilized to determine leaf area with green leaves gathered from eight hills. Following the method outlined by Li et al. (2020), the LAI was calculated as the overall leaf area per unit land area. SPAD values were measured using a handheld SPAD - 502 chlorophyll meter (Minolta Camera Co., Japan).

2.4.2 Physiological measurements

Functional leaves, which are defined as the last fully-developed leaves, were sampled from three randomly-selected plants during the flowering, boll-setting, and maturity stages for measurement purposes. These measurements were performed on the same days as leaf area evaluations. Between 11:00 and 14:00 hours under clear sky conditions, Pn was measured using a portable photosynthesis system (LI-6400; Li-Cor Inc. NE, USA), with the photosynthetically active radiation kept at 1500 μmol m-2 s-1 above the canopy. Following the procedures of Ren et al. (2018), POD, SOD, and CAT were assayed using guaiacol colorimetry, nitro blue tetrazolium, and potassium nitration methods, respectively. The MDA content was quantified by the TBA method as per Du and Bramlage (1992). Soluble protein content was analyzed in accordance with the protocol devised by Mohammadkhani and Heidari (2007).

2.4.3 Seed yield of cotton

In each growing season, the two central rows of cotton plants were manually harvested on four different dates: from September 20 to November 15 in 2018; and from September 20 to November 14 in 2019. After being sun dried for 15 days under natural conditions, the cottonseed was ginned when its moisture content reached ≤11%.

2.5 Statistical analysis

All the measured data were individually processed using a randomized complete block design (RCBD) method with the PROC GLM procedure in SAS for variance analysis. The means were compared by Duncan’s multiple range test at a significance level of P < 0.05. Although most of the measured N, water, and physiological parameters exhibited variation between years, there was neither year × drainage regime nor year × N interactions (Table 1). Therefore, we merged the data from the two different years.

Table 1
www.frontiersin.org

Table 1. Analysis of variance of SPAD value, superoxide dismutase (SOD), peroxidases (POD), catalase (CAT), net photosynthetic rate (Pn), leaf area index (LAI), SPAD value, malondialdehyde (MDA) and soluble protein contents under condition of drainage regimes and nitrogen management strategies interaction.

3 Results

3.1 Leaf area index and SPAD values

The LAI at the seeding and squaring stages were comparable for the different treatments (Figure 2). However, the LAI at the other measured stages varied among the treatments. Compared to N1, the reduced N treatments significantly reduced LAI at the bud, flowering, boll setting and maturity stages (10.6%-35.5% smaller) under the two drainage regimes. Moreover, CD significantly increased LAI at the flowering, boll setting and maturity stages (9.5%-30.0% greater) at the reduced N rates when compared to FD. The CDN1 resulted in the greatest LAI at the flowering and boll setting stages, and the FDN4 resulted in the smallest LAI (Figure 2). SPAD values in the measured growth stages under different treatments showed similar variations compared with the LAI in the corresponding stages (Figure 3).

Figure 2
Bar chart comparing leaf area index across different growth stages: seeding, squaring, bud, flowering, boll setting, and maturity. Each stage displaysvalues for groups FDN1, FND2, FDN3, FDN4, CDN1, CDN2, CDN3, and CDN4, indicatedby different colors. Values range approximately between 0.5 to 5.5 square meters per square meter. Different letters denote statistical significance among groups within each stage.

Figure 2. Leaf area index at the varied growth stages of cotton as affected by different nitrogen rates and drainage regimes. CD and FD represents controlled drainage and free drainage, respectively. N1, N2, N3 and N4 represent 280, 252, 224 and 196 kg N ha-1, respectively. Values (mean ± standard error, n = 6) are mean of 2 years and three replicates. Means within a same stage by different letters are significantly different at p < 0.05.

Figure 3
Bar chart showing SPAD values across different growth stages: seeding, squaring, bud, flowering, boll setting, and maturity. Each stage displays values foreight categories: FDN1, FND2, FDN3, FDN4, CDN1, CDN2, CDN3, CDN4, with variousletter annotations indicating statistical differences. SPAD values range from 0 to 80.

Figure 3. SPAD values of cotton leaves at the varied growth stages as affected by different nitrogen rates and drainage regimes. Note: CD and FD represents controlled drainage and free drainage, respectively. N1, N2, N3 and N4 represent 280, 252, 224 and 196 kg N ha-1, respectively. Values (mean ± standard error, n = 6) are mean of 2 years and three replicates. Means within a same stage by different letters are significantly different at p < 0.05.

3.2 Activities of superoxide dismutase, peroxidases, and catalase

In all treatments, the maximum SOD, POD and CAT activities were found at the boll setting stage. Reduced N treatments significantly reduced activities of the SOD, POD and CAT at the flowering, boll setting and maturity stages (decreased by 7.8%-47.6%) under FD, while their activities at the boll setting and maturity stages were only significantly smaller in N4 (decreased by 11.1%-32.7%) under CD (Table 2). CD rather than FD resulted in 3.6%-31.4% higher SOD, POD and CAT activities at the three growth stages at each N rate, although the difference did not reach a significant level at N1. N4 resulted in the smallest SOD, POD and CAT activities under the two drainage regimes. The CDN1 resulted in the greatest SOD, POD and CAT activities at the three growth stages, and the FDN4 resulted in the smallest SOD, POD and CAT activities (Table 2).

Table 2
www.frontiersin.org

Table 2. Superoxide dismutase (SOD), peroxidases (POD), and catalase (CAT) of cotton leaves at the flowering, boll setting and maturity stages as affected by different nitrogen rates and drainage regimes.

3.3 Net photosynthetic rate

Compared to normal nitrogen (N1) application, all the reduced N treatments (N2, N3, and N4) significantly reduced Pn (decreased by 10.2%-33.1%) at the flowering, boll setting and maturity stages under the two drainage regimes (Figure 4). Moreover, CD significantly increased Pn by 9.6%-23.7% at the flowering, boll setting and maturity stages at each N rate when compared to FD. The CDN1 resulted in the greatest Pn at the three growth stages, and the FDN4 resulted in the smallest Pn (Figure 4).

Figure 4
Bar chart showing net photosynthetic rate (mmol CO₂/m²·s) across three growth stages: flowering, boll setting, and maturity. Each stage has eight coloredbars representing different conditions (FDN1, FND2, etc.). Values range from about 16 to 36, with letters indicating statistical significance.

Figure 4. Net photosynthetic rate of cotton at the flowering, boll setting and maturity stages as affected by different nitrogen rates and drainage regimes.

3.4 Soluble protein content

N2, N3, and N4 significantly reduced soluble protein content (decreased by 8.7%-24.5%) at the flowering, boll setting and maturity stages under FD when compared to N1 (Figure 5). However, N2 and N3 had a comparable soluble protein content at the flowering and maturity stage when compared to normal N rate (N1). Moreover, CD significantly increased soluble protein content by 10.1%-29.4% at the boll setting stage at each N rate when compared to FD. The CDN1 resulted in the greatest soluble protein content at the three growth stages, and the FDN4 resulted in the smallest soluble protein content (Figure 5).

Figure 5
Bar chart showing soluble protein content in milligrams per milligram across three growth stages: flowering, boll setting, and maturity. Each stage includes bars for FDN1, FND2, FDN3, FDN4, CDN1, CDN2, CDN3, and CDN4, with content ranging from 0 to 50 mg. Data points are labeled with letters a, b, c, indicating statistical differences. The legend shows different colors for each category.

Figure 5. Soluble protein content of cotton leaves at the flowering, boll setting and maturity stages as affected by different nitrogen rates and drainage regimes. CD and FD represents controlled drainage and free drainage, respectively. N1, N2, N3 and N4 represent 280, 252, 224 and 196 kg N ha-1, respectively. Values (mean ± standard error, n = 6) are mean of 2 years and three replicates. Means within a same stage by different letters are significantly different at p < 0.05.

3.5 Malondialdehyde content

All the reduced N treatments significantly increased MDA content by 9.2%-38.7% at the flowering, boll setting and maturity stages under the two drainage regimes (Figure 6). Moreover, CD significantly decreased MDA content by 12.1%-36.8% at the three growth stages at each N rate when compared to FD. The CDN1 resulted in the smallest MDA content at the three growth stages, and the FDN4 resulted in the greatest MDA content (Figure 6).

Figure 6
Bar chart showing malondialdehyde content in different groups (FDN1, FND2, FDN3, FDN4, CDN1, CDN2, CDN3, CDN4) across growth stages: flowering, boll setting, and maturity. The Y-axis measures content in micromoles per gram, ranging from 0 to 0.7. Each group is represented by distinct colors. Error bars and labeled lettersdenote statistical differences among groups.

Figure 6. Malondialdehyde (MDA) content of cotton leaves at the flowering, boll setting and maturity stages as affected by different nitrogen rates and drainage regimes. CD and FD represents controlled drainage and free drainage, respectively. N1, N2, N3 and N4 represent 280, 252, 224 and 196 kg N ha-1, respectively. Values (mean ± standard error, n = 6) are mean of 2 years and three replicates. Means within a same stage by different letters are significantly different at p < 0.05.

3.6 Seed cotton yield

Reductions of N application rates significantly reduced seed cotton yield by 9.2%-18.6% under FD; while only N4 significantly reduced seed cotton yield (decreased by 13.0%) under CD. FDN4 resulted in the smallest seed cotton yield (Figure 7).

Figure 7
Bar chart showing seed cotton yield in kilograms per hectare for different treatments labeled FDN1, FND2, FDN3, FDN4, CDN1, CDN2, CDN3, and CDN4.Error bars indicate variability. Treatments FDN1, CDN1, and CDN3 show the highest yield around 3200.0 kg ha-1, labeled with “a”. FND2, FDN3, and CDN2 have slightly lower yields labeled with “b”. FDN4 has the lowest yield labeled “c”.

Figure 7. Seed cotton yield as affected by different nitrogen rates and drainage regimes. Note: CD and FD represents controlled drainage and free drainage, respectively. N1, N2, N3 and N4 represent 280, 252, 224 and 196 kg N ha-1, respectively. Values (mean ± standard error, n = 6) are mean of 2 years and three replicates. Means within a same stage by different letters are significantly different at p < 0.05.

4 Discussion

The influences of drainage pattern, nitrogen levels, and their interaction effects on crop yield have been assessed previously (Wu et al., 2023; Youssef et al., 2023). Moreover, our prior study has shown that a 10%-20% reduction in nitrogen fertilizer rate can keep cotton seed yield under CD (Qi and Zhu, 2023). Nevertheless, the physiological mechanism by which CD helps to stabilize cotton yield at decreased nitrogen levels is still unclear. This current research clarified that the drainage patterns and nitrogen fertilizer levels together affected the Pn, LAI, SPAD value, activities of SOD, POD, CAT, and contents of MDA and soluble protein in cotton leaves, thus impacting cotton seed yield. Obviously, CD interacted with N2 or N3 to produce a positive interaction for delaying leaf senescence by maintaining photosynthesis, the antioxidant defense and osmoregulation, finally leading to a relatively high seed cotton yield.

4.1 Effects of drain regimes and reduced nitrogen rates on leaf senescence

A decrease in the LAI and SPAD value can mirror the leaf senescence status. The SPAD value offers an indirect assessment of the relative chlorophyll content, can be employed to indicate the plant’s potential ability to absorb light energy (Ren et al., 2023). The LAI can serve as an indicator of the photosynthetic potential of the canopy., thereby influencing biomass accumulation and the final crop yield (Gitelson et al., 2014). In the current study, CD generally led to greater LAI and SPAD values (Figures 2, 3) during the bud, flowering, boll setting, and maturity stages. This implies that controlled drainage can improve functioning of cotton leaves in the middle and late growth stages. Three potential mechanisms are responsible for this phenomenon. Firstly, CD augmented the soil moisture content (Supplementary Figure S1) by prolonging the retention of shallow water in croplands after irrigation or precipitation (Tolomio and Borin, 2018). It also diminished the total nitrogen loss via runoff, resulting in a higher soil nitrogen availability in the plough layer during the cotton growth season (Qi and Zhu, 2023), as evidenced by the increased soil NO3--N content (Supplementary Table S1). The reduced total nitrogen loss through runoff was related to the significantly smaller drainage volume under CD (King et al., 2022; Tanga et al., 2025). Alternately, in low humidity (high suction) soil, the existing form of NO3--N is wholly or partially solid nitrate. In contrast, in high humidity (low suction) soil, the existing form of NO3--N is nitrate ions dissolved in the soil solution. Solid nitrate is fixed in the soil, whereas the soil solution containing nitrate ions can migrate to soil with lower moisture and high suction, driven by the matrix suction in unsaturated soil (Wang et al., 2021). During this process, the solid nitrate in the low moisture soil dissolves, leading to an increase in soil NO3--N contents in high moisture soil (Wang et al., 2021; Qi and Zhu, 2023). The improved soil moisture and nitrogen contents in the plough layer are conducive to expanding leaf size (Qi and Hu, 2022). Secondly, CD could improve the morphological characteristics of roots in oilseed sunflower (Dou et al., 2021) due to the improved soil water and nitrogen availability (Wang et al., 2021; Qi et al., 2023). The enhanced root growth resulted in various positive physiological effects mediated by abscisic acid (ABA) signaling (Liu et al., 2005). As a result, the capacity of roots to absorb soil water and nutrients was obviously enhanced (Wang et al., 2016; Zhang et al., 2021).This brought a greater leaf water content, which help to maintain large size and function of leaf (Yang et al., 2022). Thirdly, CD up-regulated the activities of SOD, POD, and CAT (Table 2) and down-regulated the MDA content at the post growth stages (Figure 5), suggesting a better reactive oxygen species scavenging ability for plants treated with CD. Moreover, CD lowering the reduction of LAI and SPAD values caused by decreased nitrogen rates as the enhanced soil moisture (Supplementary Figure S1) and NO3--N contents (Supplementary Table S1). Therefore, it was not surprised that the CDN1 treatment resulted in the greatest LAI and SPAD values (Figures 2, 3). This outcome suggests that when fertility is not a limiting factor, the improved soil moisture regulation inherent in CD can be fully harnessed by the crop, leading to enhanced leaf growth. In contrast, the FDN4 treatment had the lowest NO3--N content (Supplementary Table S1) and smaller soil moisture content (Supplementary Figure S1) during the cotton growth season, corresponding to the lowest LAI and SPAD values in the middle and late growth stages.

The capacity to scavenge reactive oxygen species is closely associated with plant senescence (Choudhury et al., 2017). MDA interacts with proteins in the cell membrane structure and inactivates them; its content indicates the level of lipid peroxidation (Qiu et al., 2025). CD led to higher activities of SOD, POD, and CAT (Table 2), along with a lower MDA content (Figure 6), suggesting an enhanced reactive oxygen species scavenging ability under controlled drainage. This was consistent with the previously published findings of that improved water management was useful to the antioxidant defenses and osmoregulation (Hu et al., 2010). Such kind findings could also serve as the new physiological evidence to support the beneficial effects of CD on crop production, as reported in previous studies (Jouni et al., 2018; Dou et al., 2021). This was associated with a more oxygen-enriched rhizosphere, improved soil moisture, and enhanced nutrient availability under controlled drainage condition (Kaur et al., 2020). Moreover, the CDN2 and CDN3 exhibited relatively higher activities of SOD, POD, and CAT (Table 2), indicating better reactive oxygen species scavenging ability in plants treated with CD when N fertilizer was reduced by 10%-20%. This is parallel with the findings of Meng et al. (2023) that the sufficient water supply treatment mediated cotton growth at reduced nitrogen fertilization by enhancing photosynthesis and the activities of nitrogen metabolism enzymes. Additionally, optimal water and nitrogen management strategies up-regulate activities of antioxidant enzyme by enhancing the expression of related genes (Ozcubukcu et al., 2014). These highlight a coupling effect between water and nitrogen fertilizer, achieving both ‘regulating water with fertilizer’ and ‘promoting fertilizer with water’.

Through accumulation to augment the water-holding capacity of cells and safeguard the structure of biological membranes, the content of soluble protein is frequently employed as an indicator for detecting the abiotic stress-resistance capabilities of plants. The photosynthetic capacity can be denoted by the levels of Pn (Li et al., 2020). In the measured growth stages, CD led to an increase in Pn (Figure 4) and soluble protein content (Figure 5). This implies that controlled drainage facilitates the improvement of metabolic activities and the enhancement of photosynthetic capability, laying a solid foundation for shoot biomass accumulation (Qi et al., 2024). A high Pn was closely related with the enhanced soluble protein content, LAI, and SPAD values due to improved soil moisture content (Wang et al., 2016). Besides, an enhanced LAI was consistently accompanied by a higher leaf water content (Li et al., 2010). The elevated water status can suppress the production of ABA, resulting in a high stomatal conductance in leaves (Bahrun et al., 2002), and consequently, high Pn levels (Kang and Zhang, 2004). Alternatively, an obvious positive correlation existed between the activity of nitrogen-related metabolism enzymes and the root physiological characteristics in plants (Fu et al., 2024). CD optimized the rhizosphere soil environment (Youssef et al., 2023), which enhanced the root vitality (Qi et al., 2023). This phenomenon is corroborated by the relatively higher nitrogen accumulation in plants treated with CD (Qi and Zhu, 2023). Moreover, the CDN2 and CDN3 treatments had relatively high Pn and soluble protein content (Figures 4, 5), suggesting that CD can stabilize the plant’s photosynthetic capability with a 10%-20% reduction in normal nitrogen fertilizer input.

4.2 Effects of controlled drainage regimes and reduced nitrogen rates on seed cotton yield

In this research, all the decreased N treatments led to a significant reduction in seed cotton yield under FD, whereas only the N4 significantly decreased seed cotton yield under CD (Figure 7). This suggests a positive interaction between CD and 10%-20% reduced nitrogen fertilization (N2 and N3) regarding cotton yield. One possible reason is that CD enhanced the soil moisture status in the plough layer (Supplementary Figure S1). Under conditions of ample water supply, reduced nitrogen fertilizer application was beneficial for increasing the nitrification rate and decreasing the denitrification level (Bateman and Baggs, 2005). As a result, nitrogen losses through emission, leaching, or runoff from crop fields were reduced (Ju et al., 2009; Qi and Zhu, 2023). Alternatively, at the N2 and N3 levels, CD exhibited elevated LAI, SPAD value, Pn, SOD, POD, and CAT activities, as well as high soluble protein content (Figures 2-5; Table 2), while demonstrating low MDA content (Figure 6). These contributed to the relatively high cotton yield. Besides, CD had a comparable number of bolls, boll weight, and lint percentage at N2 and N3 (Qi and Zhu, 2023). Consistently, enhanced water management practices (such as water-saving irrigation) can partly offset the adverse effects of reduced nitrogen fertilizer rates on plant growth, thus stabilizing crop yields (Xu et al., 2018; Hu et al., 2023). This is in line with previous findings and indicates that controlled drainage adjusts the soil water environment and/or nutrient availability to improve crop yield (Jouni et al., 2018; Dou et al., 2021; Tanga et al., 2025). Nevertheless, it has been shown that drainage patterns have no impacts on the growth and yields of maize and sugar beet (Awale et al., 2015) and may even cause a reduction in maize yield (Youssef et al., 2023). These contradictions might be associated with differences in drainage patterns, weather conditions, soil fertility, crop types, etc (Kaur et al., 2020). Indeed, the reasons are still unknown and require further exploration.

In the future, the underlying mechanisms by which CD contributes to a relatively high cotton yield with a 80%-90% of normal nitrogen fertilization should be investigated from the perspective of physio-ecological characteristics (including dry weight, volume, length, surface area, oxidation activity, and the content of indole-3-acetic acid) in root and soil microbial community structure. Moreover, effects of title drainage (a more popular drainage method and it is implemented by artificially raising the outlet elevation of a subsurface drainage system) and nitrogen application rates on crop growth and development merits a further study. Furthermore, as climate patterns undergo changes, specifically with the rise in growing-season temperatures and the unpredictable distribution of precipitation, the efficacy of CD in managing soil water and nutrient storage to ensure optimal crop utilization becomes increasingly significant.

5 Conclusions

Controlled drainage retarded leaf senescence under a 10%-30% reduction in nitrogen fertilizer application rate by enhancing photosynthesis, the antioxidant defense system, and osmoregulation. The augmented soil moisture and NO3--N accounted for the relatively long-lasting greenness under such kind combination. Most notably, controlled drainage can be implemented without sacrificing cottonseed yield even with a 10%-20% reduction in nitrogen fertilization. This study provided the physiological mechanisms underlying controlled drainage mediates cotton yield at reduced nitrogen fertilization in humid regions.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, upon request.

Author contributions

YD: Methodology, Writing – original draft. JF: Data curation, Methodology, Software, Writing – original draft. WW: Conceptualization, Validation, Writing – original draft. SL: Project administration, Writing – review & editing. DQ: Funding acquisition, Resources, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. We are grateful to Scientific Research Foundation of Zhejiang University of Water Resources and Electric Power (Grant No. JBGS2025005) and Key laboratory of Nonpoint Source Pollution Control, Ministry of Agriculture and Rural Affairs of P. R. China (1610132016005) and the National Natural Science Fund of China (U21A2039).

Acknowledgments

The authors are thankful to Ms. Yin Xu and Mr. Cheng Zhen, for providing the assistance in field investigation and nitrogen contents measurements.

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2025.1740476/full#supplementary-material

Supplementary Figure 1 | Changes in soil moisture content in the 0–80 cm soil depths during the cotton growing season under free drainage and controlled drainage. Values (mean ± standard error, n = 24) are mean of 2 years, three replicates and four nitrogen rates.

Supplementary Table 1 | Nitrate nitrogen content (mg kg-1) in the 0–80 cm soil depths during the cotton growing season as affected by different nitrogen rates and drainage regimes. CD and FD represents controlled drainage and free drainage, respectively. N1, N2, N3 and N4 represent 280, 252, 224 and 196 kg N ha-1, respectively. Values (mean ± standard error, n = 6) are mean of 2 years and three replicates. Means within a same stage by different letters are significantly different at p  < 0.05.

References

Ahmed, S., Nawata, E., Hosokawa, M., Domae, Y., and Sakuratani, T. (2002). Alterations in photosynthesis and some antioxidant enzymatic activities of mungbean subjected to waterlogging. Plant Sci. 163, 117–123. doi: 10.1016/S0168-9452(02)00080-8

Crossref Full Text | Google Scholar

Awale, R., Chatterjee, A., Kandel, H., and Ransom, J. K. (2015). Tile drainage and nitrogen fertilizer management influences on nitrogen availability, losses, and crop yields. Open J. Soil Sci. 5, 211–226. doi: 10.4236/ojss.2015.510021

Crossref Full Text | Google Scholar

Bahrun, A., Jensen, C. R., Asch, F., and Mogensen, V. O. (2002). Drought-induced changes in xylem pH, ionic composition, and ABA concentration act as early signals in field-grown maize (Zea mays L.). J. Exp. Bot. 53, 251–263. doi: 10.1093/jexbot/53.367.251

PubMed Abstract | Crossref Full Text | Google Scholar

Ballantine, D. J. and Tanner, C. C. (2013). Controlled drainage systems to reduce contaminant losses and optimize productivity from New Zealand pastoral systems. New Zeal J. Agric. Res. 56, 171–185. doi: 10.1080/00288233.2013.781509

Crossref Full Text | Google Scholar

Bateman, E. J. and Baggs, E. M. (2005). Contributions of nitrification and denitrification to N2O emissions from soils at different water-filled pore space. Biolo Ferti Soil 41, 379–388. doi: 10.1007/s00374-005-0858-3

Crossref Full Text | Google Scholar

Choudhury, F. K., Rivero, R. M., Blumwald, E., and Mittler, R. (2017). Reactive oxygen species, abiotic stress and stress combination. Plant J. 90, 856–867. doi: 10.1111/tpj.13299

PubMed Abstract | Crossref Full Text | Google Scholar

Deichmann, M. M., Andersen, N. M., Thomsen, K. I., and Borgesen, D. C. (2019). Impacts of controlled drainage during winter on the physiology and yield of winter wheat in Denmark. Agric. Water Manage. 216, 118–126. doi: 10.1016/j.agwat.2019.01.013

Crossref Full Text | Google Scholar

Dou, X., Shi, H. B., Li, R. P., Miao, Q. F., Tian, F., Yu, D. D., et al. (2021). Effects of controlled drainage on the content change and migration of moisture, nutrients, and salts in soil and the yield of oilseed sunflower in the Hetao Irrigation District. Sustainability 13, 9835. doi: 10.3390/su13179835

Crossref Full Text | Google Scholar

Du, Z. Y. and Bramlage, W. J. (1992). Modified thiobarbituric acid assay for measuring lipid oxidation in sugar-rich plant tissue extracts. J. Agric. Food Chem. 40, 1566–1570. doi: 10.1021/jf00021a018

Crossref Full Text | Google Scholar

FAO STAT (2020). Prod Stat (New York: Core production data base). Available online at: http://faostat.fao.org/.

Google Scholar

Foyer, C. H. and Noctor, G. (2000). Oxygen processing in photosynthesis: regulation and signalling. New Phytol. 146, 359–388. doi: 10.1046/j.1469-8137.2000.00667.x

Crossref Full Text | Google Scholar

Fu, J., Ma, M. J., Zhang, Q. F., Duan, J. Q., Wang, Y. T., Wang, F. H., et al. (2024). Effects of alternate wetting and drying irrigation and different nitrogen application levels on photosynthetic characteristics and nitrogen absorption and utilization of japonica rice. Acta Agron.Sin 50, 1787–1804. doi: 10.3724/SP.J.1006.2024.32056

Crossref Full Text | Google Scholar

Gitelson, A., Peng, Y., Arkebauer, T., and Schepers, J. (2014). Relationships between gross primary production, green LAI, and canopy chlorophyll content in maize: implications for remote sensing of primary production. Remote Sens Environ. 144, 65–72. doi: 10.1016/j.rse.2014.01.004

Crossref Full Text | Google Scholar

Hanrahan, B. R., King, K. W., and Williams, M. R. (2021). Controls on subsurface nutrient losses from agricultural fields during precipitation-driven events. Sci. Total Environ. 754, 142047. doi: 10.1016/j.scitotenv.220.142047

Crossref Full Text | Google Scholar

Hu, T. T., Yuan, L. N., Wang, J. F., Kang, S. Z., and Li, F. S. (2010). Antioxidation responses of maize roots and leaves to partial root-zone irrigation. Agric. Water Manage. 98, 164–171. doi: 10.1016/j.agwat.2010.06.019

Crossref Full Text | Google Scholar

Hu, Y. X., Zeeshan, M., Wang, G. Y., Pan, Y. Q., Liu, Y. X., and Zhou, X. B. (2023). Supplementary irrigation and varying nitrogen fertilizer rate mediate grain yield, soil-maize nitrogen accumulation and metabolism. Agric. Water Manage. 276, 108066. doi: 10.1016/j.agwat.2022.108066

Crossref Full Text | Google Scholar

Jouni, H. J., Liaghat, A., Hassanoghli, A., and Henk, R. (2018). Managing controlled drainage in irrigated farmers’ fields: a case study in the Moghan plain, Iran. Agric. Water Manage. 208, 393–405. doi: 10.1016/j.agwat.2018.06.037

Crossref Full Text | Google Scholar

Ju, X. T., Xing, G. X., Chen, X. P., Zhang, S., Zhang, L., Liu, X., et al. (2009). Reducing environmental risk by improving N management in intensive Chinese agricultural systems. PANS 106, 3041–3046. doi: 10.1073/pnas.0813417106

PubMed Abstract | Crossref Full Text | Google Scholar

Kang, S. Z. and Zhang, J. H. (2004). Controlled alternate partial root zone irrigation: its: physiological consequences and impact on water use efficiency. J. Exp. Bot. 55, 2437–2446. doi: 10.1093/jxb/erh249

PubMed Abstract | Crossref Full Text | Google Scholar

Karegoudar, A. V., Vishwanath, J., Anand, S. R., Rajkumar, R. H., Ambast, S. K., and Kaledhonkar, M. J. (2019). Feasibility of controlled drainage in saline vertisols of TBP command area of Karnataka, India. Irrig Drain 68, 969–978. doi: 10.1002/ird.2374

Crossref Full Text | Google Scholar

Kaur, G., Singh, G., Motavalli, P. P., Nelson, K. A., Orlowski, J. M., and Golden, B. (2020). Impacts and management strategies for crop production in waterlogged or flooded soils: a review. Agron. J. 112, 1475–1501. doi: 10.1002/agj2.20093

Crossref Full Text | Google Scholar

King, K. W., Hanrahan, B. R., Stinner, J., and Shedekar, V. S. (2022). Field scale discharge and water quality response, to drainage water management. Agric. Water Manage. 264, 107421. doi: 10.1016/j.agwat.2021.107421

Crossref Full Text | Google Scholar

Li, F. S., Wei, C. H., Zhang, F. C., Zhang, J. H., Nong, M. L., and Kang, S. Z. (2010). Wateruse efficiency and physiological responses of maize under partial root-zone irrigation. Agric. Water Manage. 97, 1156–1164. doi: 10.1016/j.agwat.2010.01.024

Crossref Full Text | Google Scholar

Li, G. H., Zhao, B., Dong, S. T., Zhang, J. W., Liu, P., and Lu, W. P. (2020). Controlled-release urea combining with optimal irrigation improved grain yield, nitrogen uptake, and growth of maize. Agric. Water Manage. 227, 105834. doi: 10.1016/j.agwat.2019.105834

Crossref Full Text | Google Scholar

Liu, A. D., Ma, X. L., Zhang, Z., Liu, H., Luo, D., Yang, L. R., et al. (2022). Single dose fertilization at reduced nitrogen rate improves nitrogen utilization without yield reduction in late-planted cotton under a wheat-cotton cropping system. Indus Crop Pro 176, 114346. doi: 10.1016/j.indcrop.2021.114346

Crossref Full Text | Google Scholar

Liu, F. L., Jensen, C. R., Shahnazari, A., Andersen, M. N., and Jacobsen, S. E. (2005). ABA regulated stomatal control and photosynthetic water use efficiency of potato (Solanum tuberosum L.) during progressive soil drying. Plant Sci. 168, 831–836. doi: 10.1016/j.plantsci.2004.10.016

Crossref Full Text | Google Scholar

Lu, J. S., Hu, T. T., Zhang, B. C., Wang, L., Yang, S. H., Fan, J. L., et al. (2021). Nitrogen fertilizer management effects on soil nitrate leaching, grain yield and economic benefit of summer maize in Northwest China. Agric. Water Manage. 247, 106739. doi: 10.1016/j.agwat.2021.106739

Crossref Full Text | Google Scholar

Meng, Y. J., Ma, X. Y., Song, C., Sun, H. C., Liu, L. T., Zhang, K., et al. (2023). Effects of water and nitrogen regulation on physiological characteristics and yield of cotton. Chin. J. Eco-Agricult 31, 1379–1391. doi: 10.12357/cjea.20230002

Crossref Full Text | Google Scholar

Mohammadkhani, N. and Heidari, R. (2007). Effects of drought stress on protective enzyme activities and lipid peroxidation in two maize cultivars. Pak. J. Biol. Sci. 10, 3835–3840. doi: 10.3923/pjbs.2007.3835.3840

PubMed Abstract | Crossref Full Text | Google Scholar

Ozcubukcu, S., Ergun, N., and Ilhan, E. (2014). Waterlogging and nitric oxide induce gene expression and increase antioxidant enzyme activity in wheat (Triticum aestivum L.). Acta Biol. Hung 65, 47–60. doi: 10.1556/ABIOL.65.2014.1.5

PubMed Abstract | Crossref Full Text | Google Scholar

Poole, C. A., Skaggs, R. W., Cheschier, G. M., Youssef, M. A., and Crozier, C. R. (2013). Effects of drainage water management on crop yields in North Carolina. J. Soil Water Conserv. 68, 429–437. doi: 10.2489/jswc.68.6.429

Crossref Full Text | Google Scholar

Qi, D. L., Chen, S., Yue, W. J., and Duan, Y. G. (2024). Leaf senescence characteristics and economic benefits of rice under alternate wetting and drying irrigation and blended use of polymer coated and common urea. Front. Plant Sci. 15. doi: 10.3389/fpls.2024.1444819

PubMed Abstract | Crossref Full Text | Google Scholar

Qi, D. L. and Hu, T. T. (2022). Effects of nitrogen application rates and irrigation regimes on root growth and nitrogen−use efficiency of maize under alternate partial root−zone irrigation. J. Soil Sci. Plant Nutri 22, 2793–2804. doi: 10.1007/s42729-022-00846-4

Crossref Full Text | Google Scholar

Qi, D. L., Hu, T. T., and Song, X. (2020). Effects of nitrogen application rates and irrigation regimes on grain yield and water use efficiency of maize under alternate partial root-zone irrigation. J. Inter Agric. 19, 2792–2806. doi: 10.1016/S2095-3119(20)63205-1

Crossref Full Text | Google Scholar

Qi, D. L., Li, X., Pan, C., Li, J. F., Xu, Y., and Zhu, J. Q. (2021). Effect of nitrogen supply methods on the gas exchange, antioxidant enzymatic activities, and osmoregulation of maize (Zea mays L.) under alternate partial root-zone irrigation. J. Soil Sci. Plant Nutri 21, 2083–2095. doi: 10.1007/S42729-021-00504-1

Crossref Full Text | Google Scholar

Qi, D. L. and Zhu, J. Q. (2023). Controlled drainage mediates cotton yield at reduced nitrogen rates by improving soil nitrogen and water contents. J. Soil Sci. Plant Nutr. 23, 3655–3665. doi: 10.1007/S42729-023-01285-5

Crossref Full Text | Google Scholar

Qi, D. L., Zhu, J. Q., and Wang, X. G. (2023). Root growth in rice (Liangyou 152) under alternate wetting and drying irrigation and mixed application of polymer-coated and common urea. J. Soil Sci. Plant Nutri 23, 6838–6850. doi: 10.1007/S42729-023-01546-3

Crossref Full Text | Google Scholar

Qiu, H. N., Yang, S. H., Jiang, Z. W., Xu, Y., and Jiao, X. Y. (2022). Effect of irrigation and fertilization management on rice yield and nitrogen loss: a meta-analysis. Plants 11, 1190. doi: 10.3390/plants11131690

PubMed Abstract | Crossref Full Text | Google Scholar

Qiu, S., Zhang, Y. J., Dai, J. L., and Dong, H. Z. (2025). Physiological mechanisms and agronomic strategies underlying flood tolerance variability in dryland crops: A global meta-analysis. Field Crop Res. 334, 110146. doi: 10.1016/j.fcr.2025.110146

Crossref Full Text | Google Scholar

Ren, B. Z., Yu, W. Z., Liu, P., Zhao, B., and Zhang, J. W. (2023). Responses of photosynthetic characteristics and leaf senescence in summer maize to simultaneous stresses of waterlogging and shading. Crop J. 11, 269–277. doi: 10.1016/j.cj.2022.06.003

Crossref Full Text | Google Scholar

Ren, B. Z., Zhang, J. W., Dong, S. T., Liu, P., and Zhao, B. (2018). Responses of carbon metabolism and antioxidant system of summer maize to waterlogging at different stages. J. Agron. Crop Sci. 204, 505–514. doi: 10.1111/jac.12275

Crossref Full Text | Google Scholar

Ritzema, H. P. (2016). Drain for gain: managing salinity in irrigated lands-review. Agric. Water Manage. 176, 18–28. doi: 10.1016/j.agwat.2016.05.014

Crossref Full Text | Google Scholar

Shedekar, V., King, K. W., Fausey, N. R., Islam, K. R., Soboyejo, A. B., Kalcic, M. M., et al. (2021). Exploring the effectiveness of drainage water management on water budgets and nitrate loss using three evaluation approaches. Agric. Water Manage. 243, 106501. doi: 10.1016/j.agwat.220.106501

Crossref Full Text | Google Scholar

Tanga, S., Crolla, A., Tsiouras, A., Ibarra, I. R., and Kinsley, C. (2025). Controlled drainage – Effects on nutrient attenuation and water quality – A field study in Eastern Ontario, Canada. Agric. Water Manage. 319, 109764. doi: 10.1016/j.agwat.2025.109764

Crossref Full Text | Google Scholar

Thapa, R., Chatterjee, A., Johnson, J. M. F., and Awale, R. (2015). Stabilized nitrogen fertilizers and application rate influence nitrogen losses under rainfed spring wheat. Agron. J. 107, 1–10. doi: 10.2134/agronj15.0081

Crossref Full Text | Google Scholar

Tolomio, M. and Borin, M. (2018). Water table management to save water and reduce nutrient losses from agricultural fields – 6 years of experience in North-Eastern Italy. Agric. Water Manage. 201, 1–10. doi: 10.1016/j.agwat.2018.01.009

Crossref Full Text | Google Scholar

Wang, G. Y., Hu, Y. X., Liu, Y. X., Ahmad, S., and Zhou, X. B. (2021). Effects of supplement irrigation and nitrogen application levels on soil carbon–nitrogen content and yield of one-year double cropping maize in subtropical region. Water 13, 1180. doi: 10.3390/W13091180

Crossref Full Text | Google Scholar

Wang, Z. Y., Shao, G. C., Lu, J., Zhang, K., Gao, Y., and Ding, J. H. (2020). Effects of controlled drainage on crop yield, drainage water quantity and quality: A meta-analysis. Agric. Water Manage. 239, 106253. doi: 10.1016/j.agwat.2020.106253

Crossref Full Text | Google Scholar

Wang, Z. Q., Zhang, W. Y., Beebout, S. S., Zhang, H., Liu, L. J., Yang, J. C., et al. (2016). Grain yield, water and nitrogen use effciencies of rice as influenced by irrigation regimes and their interaction with nitrogen rates. Field Crop Res. 193, 54–69. doi: 10.1016/j.fcr.2016.03.006

Crossref Full Text | Google Scholar

Wesström, I., Joel, A., and Messing, I. (2014). Controlled drainage and subirrigation – a water management option to reduce non-point source pollution from agricultural land. Agric. Ecosys Environ. 198, 74–82. doi: 10.1016/j.agee.2014.03.017

Crossref Full Text | Google Scholar

Wu, Q., Wu, Q. X., Deng, C., Liu, K. W., Qi, D. L., and Zhu, J. Q. (2023). The effect of controlled drainage and nitrogen fertilization on growth, nitrogen uptake and yield of cotton. J. Irrigation Drainage 42, 32–38.

Google Scholar

Xu, G. W., Lu, D. K., Wang, H. Z., and Li, Y. J. (2018). Morphological and physiological traits of rice roots and their relationships to yield and nitrogen utilization as influenced by irrigation regime and nitrogen rate. Agric. Water Manage. 203, 385–394. doi: 10.1016/j.agwat.2018.02.033

Crossref Full Text | Google Scholar

Yan, J., Wu, Q. X., Qi, D. L., and Zhu, J. Q. (2022). Rice yield, water productivity, and nitrogen use efficiency responses to nitrogen management strategies under supplementary irrigation for rain-fed rice cultivation. Agric. Water Manage. 263, 107486. doi: 10.1016/j.agwat.2022.107486

Crossref Full Text | Google Scholar

Yang, Z. Y., Li, N., Ma, P., Li, Y., Zhang, R. P., Song, Q., et al. (2022). Improving nitrogen and water use efficiencies of hybrid rice through methodical nitrogen–water distribution management. Field Crop Res. 246, 107698. doi: 10.1016/j.fcr.2019.107698

Crossref Full Text | Google Scholar

Youssef, M. A., Stroch, J., Bagheri, E., Reinhart, B. D., Abendroth, L. J., Chighlazde, G., et al. (2023). Impact of controlled drainage on corn yield under varying precipitation patterns: A synthesis of studies across the U.S. Midwest Southeast Agric. Water Manage. 275, 10793. doi: 10.1016/j.agwat.2022.107993

Crossref Full Text | Google Scholar

Yu, H. D., Chu, Z. Y., Wang, S. Y., Guo, Y. Q., Ren, B. Z., and Zhang, J. W. (2023). Effects of different controlled nitrogen ratios on leaf senescence and grain filling characteristics of summer maize. Sci. Agric. Sin. 56, 3511–3529. doi: 10.3864/j.issn.0578-1752.2023.18.003

Crossref Full Text | Google Scholar

Yuan, Y., Lin, F., Maucieri, C., and Zhang, Y. J. (2022). Efficient irrigation methods and optimal nitrogen dose to enhance wheat yield, inputs efficiency and economic benefits in the North China Plain. Agronomy 12, 273. doi: 10.3390/agronomy12020273

Crossref Full Text | Google Scholar

Zhang, H., Khan, A., Tan, D. K. Y., and Luo, H. (2017). Rational water and nitrogen management improves root growth, increases yield and maintains water use efficiency of cotton under mulch drip irrigation.Front. Plant Sci. 8. doi: 10.3389/fpls.2017.00912

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, W. X., Wang, S. L., Jiao, P. J., Xu, D., and Zheng, S. Y. (2025). Short-trem and long-term of drainage control after waterlogging on soil water improvement and soybean growth. Shuili Xuebao 56, 455–464. doi: 10.13243/j.cnki.slxb.20240294

Crossref Full Text | Google Scholar

Zhang, W. Y., Xu, Y. J., Wang, Z. Q., Liu, L. J., Zhang, H., Gu, J. F., et al. (2021). Alternate wetting and drying irrigation combined with the proportion of polymer-coated urea and conventional urea rates increases grain yield, water and nitrogen use efficiencies in rice. Field Crop Res. 268, 108165. doi: 10.1016/j.fcr.2021.108165

Crossref Full Text | Google Scholar

Zhang, Z., Qiu, S., Rebecca, J. T., Yao, X. F., Daniel, K. Y. T., Wang, D. S., et al. (2024). Optimizing nitrogen application methods and frequency to increase cotton yield in summer direct sown condition. Ind. Crops Products 213, 118468. doi: 10.1016/J.INDCROP.2024.118468

Crossref Full Text | Google Scholar

Keywords: drainage regime, Gossypium hirsutum L., leaf senescence characteristics, nitrogen rates, soil environment

Citation: Duan Y, Feng J, Wang W, Liu S and Qi D (2026) Controlled drainage stabilized cotton yield by enhancing photosynthesis, the antioxidant defenses and osmoregulation at reduced nitrogen fertilization. Front. Plant Sci. 16:1740476. doi: 10.3389/fpls.2025.1740476

Received: 06 November 2025; Accepted: 29 December 2025; Revised: 21 December 2025;
Published: 21 January 2026.

Edited by:

Lia Dinis, University of Trás-os-Montes and Alto Douro, Portugal

Reviewed by:

Ana Isabel Marques Monteiro, University of Trás-os-Montes and Alto Douro, Portugal
Zhao Zhang, Huazhong Agricultural University, China

Copyright © 2026 Duan, Feng, Wang, Liu and Qi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Shuaikang Liu, U2tsaXV1QDE2My5jb20=; Dongliang Qi, cWRsMTk4Nzk5QDEyNi5jb20=

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.