Agricultural Water Management最新文献

{"title":"Optimized parameters for SCS-CN model in runoff prediction in ridge-furrow rainwater harvesting in semiarid regions of China","authors":"Qi Wang ,&nbsp;Xiaole Zhao ,&nbsp;Fuchun Li ,&nbsp;Wucheng Zhao ,&nbsp;Ibrahim Awuku ,&nbsp;Wen Ma ,&nbsp;Qinglin Liu ,&nbsp;Bing Liu ,&nbsp;Tao Cai ,&nbsp;Yanping Liu ,&nbsp;Xuchun Li","doi":"10.1016/j.agwat.2025.109363","DOIUrl":"10.1016/j.agwat.2025.109363","url":null,"abstract":"<div><div>Soil erosion and water loss are the major drivers of land degradation, ecosystem malfunction, and low crop production in water-scarce regions. The Loess Plateau in China, one of the most erosion-prone areas globally, has implemented ridge-furrow rainwater harvesting technology to address water loss and soil erosion. Numerous hydrological models have been applied for runoff and sediment prediction in small watersheds. However, the application of the SCS-CN model to runoff and sediment prediction in small-scale fields has remained uncertain. Predictive models for runoff and sediment yield in ridge-furrow rainwater harvesting remained limited. This study utilized regression analysis of precipitation and runoff data from 2015 to 2018 to determine initial abstraction. The statistical parameters, including root mean square deviation (RMSE) and Nash-Sutcliffe efficiency (NSE), were employed to optimize initial abstraction ratios and potential maximum retention values of the SCS-CN model based on rainfall-runoff data from 2015 to 2018. Validation of the SCS-CN model with optimized parameters was performed using rainfall-runoff data from 2019 to 2023, leveraging NSE and coefficients of determination (R²) as evaluation criteria. The optimized initial abstraction ratios for flat planting, open-ridging, and tied-ridging were 0.09–0.14, 0.06–0.07, and 0.04–0.05, respectively. Corresponding potential maximum retention values were 58.3–93.9, 129.5–154.2, and 188.9–237.7 mm, respectively, while the curve numbers (CN) were 73.0–81.3, 62.2–66.2, and 51.7–57.3, respectively. For slope gradients of 5° and 10°, the optimized initial abstraction ratios were 0.05 and 0.07, respectively, with potential maximum retention values of 181.4 and 127.0 mm, respectively. The CN values for these slopes were 58.3 and 66.7, respectively. Significantly, increased slope gradients resulted in higher optimized initial abstraction ratios and CN values, along with reduced potential maximum retention values. The study concluded that ridge-furrow rainwater harvesting technology, particularly tied-ridging, demonstrated lower optimized initial abstraction ratios and CN values, coupled with higher potential maximum retention values, compared to flat planting. The SCS-CN model, incorporating optimized parameters, is a robust tool for accurately predicting runoff in ridge-furrow rainwater harvesting systems in the Loess Plateau of China.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109363"},"PeriodicalIF":5.9,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An agent-based model of farmer decision making: Application to shared water resources in Arid and semi-arid regions","authors":"Imane El Fartassi ,&nbsp;Alice E. Milne ,&nbsp;Helen Metcalfe ,&nbsp;Rafiq El Alami ,&nbsp;Alhousseine Diarra ,&nbsp;Vasthi Alonso-Chavez ,&nbsp;Joanna Zawadzka ,&nbsp;Toby W. Waine ,&nbsp;Ron Corstanje","doi":"10.1016/j.agwat.2025.109357","DOIUrl":"10.1016/j.agwat.2025.109357","url":null,"abstract":"<div><div>The study presents an agent-based modelling framework that integrates behavioural and biophysical models to investigate shared irrigation water management in an arid region. The behavioural model simulates farmers' decisions about their water irrigation sources (dam or groundwater) and whether to continue cultivating in the face of drought. This model was parameterised using survey data. The biophysical model component quantifies the impact of water availability and irrigation sources on soil salinity accumulation and its effects on crop productivity. Applied to the Al Haouz Basin, in Morocco, the integrated model reveals several key findings: (1) Increased groundwater access through water abstraction authorization can initially boost productivity but leads to widespread salinisation and farm abandonment, particularly under climate change scenarios. (2) Scenarios with reduced dam water availability demonstrate that mixed irrigation strategies mitigate short-term productivity losses but fail to prevent long-term soil salinity issues. (3) Land abandonment is significantly influenced by the level of water abstraction authorizations, with higher abstraction leading to more severe environmental degradation and social impacts. (4) Policy scenarios reveal that there is a theoretical optimal level of groundwater abstraction that maximises productivity while minimising land abandonment and salinity build-up. These results highlight the complex trade-offs between short-term gains and long-term sustainability, emphasising the need for holistic water governance policies that balance individual and collective interests.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109357"},"PeriodicalIF":5.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal water, nitrogen, and density management increased wheat yield by improving population uniformity","authors":"Yanmei Gao ,&nbsp;Qi Wang ,&nbsp;Yang Liu ,&nbsp;Jie He ,&nbsp;Weiwei Chen ,&nbsp;Jun Xing ,&nbsp;Min Sun ,&nbsp;Zhiqiang Gao ,&nbsp;Zhimin Wang ,&nbsp;Meng Zhang ,&nbsp;Yinghua Zhang","doi":"10.1016/j.agwat.2025.109362","DOIUrl":"10.1016/j.agwat.2025.109362","url":null,"abstract":"<div><div>The ideal population type is the basis of high-yield and high-efficiency cultivation of wheat. Population uniformity is an important index to evaluate the population ideotype. Therefore, it is necessary to analyze the yield difference of winter wheat at different spike layers between different populations because spike layer affects the production function of population. Here, two 2-year field experiments were conducted to investigate the effects of irrigation times, nitrogen application rate, and planting density on wheat yield, population traits, sugar and dry matter accumulation, and photosynthetic parameters at different spike layers. The results indicated that optimal planting density (SD3), nitrogen (N2) and irrigation (W1 or W2) deceased the ineffective tillers number at flowering stage and improved the spike number at upper and middle spike layers, which leading to lower coefficient of variation (CV) and higher population uniformity. Increasing planting density, nitrogen, and irrigation promoted high grain yield and population-scale biomass accumulation mainly due to the increment of spike number and yield at upper and middle spike layers. But, the single-stem biomass and grain dry weight reduced with increased planting density whereas improved with an increase of nitrogen and irrigation. Increasing planting density, nitrogen, and irrigation improved the leaf area index (LAI) and light interception at the upper and middle canopy, but decreased it at the lower canopy. Furthermore, the chlorophyll content at flag leaf and penultimate leaf was higher than that of top third leaf. Thus, the single-stem and each organ biomass accumulation, and sugar content gradually decreased from the upper to the lower layers, leading to decreased grains number per spike and average grain weight. Increasing planting density decreased spike length, total soluble sugar content and dry matter accumulation of spike at different spike layers but improved these indicators in stem, which leading to decreases in grain number per spike; whereas these indicators improved with increased irrigation. Overall, these findings provided theoretical and practical basis for building ideal crop population, and breeding and cultivation of winter wheat with high yield.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109362"},"PeriodicalIF":5.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-frequency insights: Uncovering the drivers of reference evapotranspiration across China","authors":"Shuting Zhao ,&nbsp;Jinglong Wu ,&nbsp;Rangjian Qiu ,&nbsp;Tao Zhang ,&nbsp;Yufeng Luo ,&nbsp;Wei Hu","doi":"10.1016/j.agwat.2025.109367","DOIUrl":"10.1016/j.agwat.2025.109367","url":null,"abstract":"<div><div>Reference evapotranspiration (ET_o) is an important variable required in many disciplines and is influenced by many factors. However, the bivariate and multivariate relationships between ET_o and affecting factors across multiple time-frequency domains remain unknown. Here, we identified the primary factors affecting ET_o across time-frequency domain in 653 meteorological stations of mainland China based on the combination of wavelet transform coherence (WTC) and multiwavelet coherence (MWC) methods. The results indicated that ET_o and all affecting factors (solar radiation, R_s; vapor pressure deficit, VPD; air temperature, T_a; wind speed, <em>u</em>₂) during 1967–2016 exhibited a frequency ranging from 2 days to 211 months, and had a continuous annual (374 d) periodicity (except <em>u</em>₂) for almost all sites. Results of percentage area of significant coherence (PASC) of WTC indicated that VPD or R_s is the dominant single factor driving variations of ET_o across time-frequency space in majority sites (66.3 % and 32.0 %, respectively), while <em>u</em>₂ is only dominant in limited (11) sites. This quite differs from the daily scale, where daily ET_o was primarily influenced by daily R_s at 361 sites, daily VPD at 286 sites, and daily T_a at 6 sites. Results of MWC showed that the explanation for the time-frequency variations of ET_o can be further improved using two-factors in 40.7 % of all sites as indicated by absolute increased PASC of MWC by 5 %. Overall, we found that the variation of ET_o across time-frequency domain can be well explained by using only one variable (VPD or R_s) in 59.3 % of all sites, while by combinations of VPD-R_s and VPD-<em>u</em>₂ in remaining sites. This study provides novel insights into understanding the variations of ET_o across multiple time-frequency spaces.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109367"},"PeriodicalIF":5.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved MobileVit deep learning algorithm based on thermal images to identify the water state in cotton","authors":"Kaijun Jin ,&nbsp;Jihong Zhang ,&nbsp;Ningning Liu ,&nbsp;Miao Li ,&nbsp;Zhanli Ma ,&nbsp;Zhenhua Wang ,&nbsp;Jinzhu Zhang ,&nbsp;Feihu Yin","doi":"10.1016/j.agwat.2025.109365","DOIUrl":"10.1016/j.agwat.2025.109365","url":null,"abstract":"<div><div>Thermal imaging combined with deep learning algorithms offers an efficient and non-invasive method for monitoring crop water status, facilitating precise irrigation management over large agricultural areas. This study introduces a method for identifying the moisture state of cotton using an enhanced MobileVit deep learning algorithm. This approach incorporates the Efficient Channel Attention (ECA) mechanism into the Fusion component of the MobileVit model, optimizes the first convolution in the Fusion component by replacing it with Depthwise Separable Convolution (DsConv), and substitutes the Local representation with the MobileOne block. These enhancements aim to improve model performance while maintaining its compact size. A dataset of thermal images of cotton canopies representing three different water states was developed for this study. Ablation studies were performed to evaluate the effect of each modification. Grad-CAM was utilized to illustrate the final layer features of the proposed algorithm. Various deep learning models were also trained, tested, and validated, allowing for a comparative analysis of the proposed model against traditional deep learning models in identifying cotton moisture states. The results show that the F1-score of the proposed model reaches 0.9677, achieving a recognition speed of 50.370 ms while maintaining a size of 4.94 M, outperforming other classical deep learning models. The findings of this study provide technical support for the development of future precision irrigation systems. The relevant code and datasets will be made available on GitHub (<span><span>https://github.com/kingcuzamu/identifying-cotton-water-state</span><svg><path></path></svg></span>) upon publication.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109365"},"PeriodicalIF":5.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calibration and validation of the AquaCrop model for simulating cotton growth under a semi-arid climate in Uzbekistan","authors":"Julien Boulange ,&nbsp;Sherzod Nizamov ,&nbsp;Aziz Nurbekov ,&nbsp;Musulmon Ziyatov ,&nbsp;Bakhtiyor Kamilov ,&nbsp;Sirojiddin Nizamov ,&nbsp;Abduaziz Abduvasikov ,&nbsp;Gulnoza Khamdamova ,&nbsp;Hirozumi Watanabe","doi":"10.1016/j.agwat.2025.109360","DOIUrl":"10.1016/j.agwat.2025.109360","url":null,"abstract":"<div><div>Cotton is a crucial fiber crop, but its conventional production methods are heavily water intensive. In regions where water availability already limits cotton yields, there is a growing need to explore alternative field management practices that stabilize yields while reducing irrigation demands. Crop models, such as the AquaCrop model, are instrumental in these efforts, enabling simulations of the complex interactions between field management, water dynamics, crop growth, and yield. However, the variability in calibrated parameter values reported across AquaCrop studies for cotton raises concerns about the transferability and reliability of previously calibrated models.</div><div>In this study, we calibrated and validated the AquaCrop crop model, developed by the Food and Agriculture Organization (FAO), to predict canopy growth, biomass accumulation and yield of cotton. The calibration protocol developed here is rather conservative, adhering strictly to the guidelines provided in the AquaCrop documentation. The calibration involved approximately 1500,000 simulations per treatment, employing a Monte Carlo (MC) protocol to systematically assess the effects of varying input parameters across multiple evaluation criteria, including their impact on water stress.</div><div>The calibrated AquaCrop model delivered good to acceptable performance levels in simulating canopy growth, biomass accumulation, and yield under various irrigation treatments, comparable to previous AquaCrop cotton applications. Additionally, the MC protocol uncovered a previously undiscover bug in the model, which shifted the crop’s planting date by approximately two weeks without user awareness, when the minimum rooting depth is set below 0.18 m. Furthermore, the rigorous calibration protocol clearly depicted compensatory interactions between parameters, where changes to one parameter can be offset by adjustments to another, highlighting the subjectivity and limitations encompassed in trial-and-error calibration approaches.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109360"},"PeriodicalIF":5.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stable soil moisture promotes shoot performance and shapes the root-rhizosphere microbiome","authors":"Dichuan Liu ,&nbsp;Zhuan Wang ,&nbsp;Guolong Zhu ,&nbsp;Aiguo Xu ,&nbsp;Renlian Zhang ,&nbsp;Ray Bryant ,&nbsp;Patrick J. Drohan ,&nbsp;Huaiyu Long ,&nbsp;Viola Willemsen","doi":"10.1016/j.agwat.2025.109354","DOIUrl":"10.1016/j.agwat.2025.109354","url":null,"abstract":"<div><div>Soil moisture is a key factor limiting crop productivity and has been widely studied to optimize agriculture production. However, the majority of previous studies focus only on the soil moisture content and ignore its temporal variation. This study investigates the impact of different soil moisture conditions, specifically fluctuating soil moisture (FSM) and stable soil moisture (SSM), on the rhizosphere microbiome and the plant performance of romaine lettuce. Plants were grown in natural and sterilized soils, which were subjected to SSM through negative pressure irrigation to achieve high, mid, and low moisture levels and FSM through manual irrigation. Shoot performance parameters, such as plant height, leaf count, -size, and biomass, were significantly enhanced under SSM compared to FSM. The findings reveal SSM enhances shoot performance and crop water productivity (WPc) independent of root size, as indicated by a lower root/shoot ratio. Analyses of the soil microbiome showed that the root-associated rhizosphere microbial community composition differs for SSM and FSM conditions, while the bulk soil microbial community was unaffected. This suggests that the response of the romaine lettuce rhizosphere microbial community to soil moisture temporal variation is driven by root microbiome interactions. This study indicates that stable soil moisture, together with the recruited root microbiome, induces shoot performance without enhancing root growth. Overall, the findings highlight the importance of optimizing soil moisture dynamics to improve plant growth and resource efficiency, offering valuable implications for sustainable agricultural practices.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109354"},"PeriodicalIF":5.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptation of VegSyst-DSS for N, P and K recommendations for grafted tomato grown in perlite in Mediterranean greenhouses","authors":"M. Gallardo ,&nbsp;J.M. Cedeño ,&nbsp;J.J. Magán ,&nbsp;M.D. Fernández ,&nbsp;R.B. Thompson","doi":"10.1016/j.agwat.2025.109351","DOIUrl":"10.1016/j.agwat.2025.109351","url":null,"abstract":"<div><div>Substrate is commonly used for greenhouse vegetable production in the Mediterranean regions of the EU and Türkiye. These are mostly free-draining systems in which drainage enters underlying soil. These systems are generally very contaminating. Unlike substrate-growing systems with recirculation of drainage, very few tools and strategies have been developed to optimize nutrient management for free-draining substrate. The VegSyst-DSS V2 and its component VegSyst V3 simulation model were both adapted to provide recommended N, P and K concentrations for nutrient solution (NS) applied to tomato in free-draining perlite substrate. Firstly, the VegSyst model calibration for tomato, developed for non-grafted plants, was adapted to grafted plants. The recalibrated model was then used to simulate N, P and K uptake in crop dry matter. The apparent nutrient retention in or loss from perlite was calculated. Using these data, the VegSyst model V3 simulated nutrient uptake by the cropping system (i.e., in dry matter plus the apparent retention in/loss from substrate). These values were then used to simulate nutrient uptake concentrations for the growing system. These latter values were used with the mass balance equation of Sonneveld (2000), in the adapted VegSyst-DSS V2, to calculate the recommended concentrations of N, P and K in the applied NS. This work was conducted in the context of a Long Cycle (early autumn to late spring) and a Spring Cycle of grafted tomato crop grown in free-draining perlite, each with a conventional (CT) and optimized nutrient management treatment (OT) (which was based on ratios of nutrient concentrations in drainage and NS). The Long Cycle CT was used for calibration, the other three crops for validation. A suite of statistical indices indicated generally good performance of simulation of nutrient uptake in crop dry matter and by the cropping system, and of crop uptake concentration for N, P and K. The recommended NS concentrations calculated by the adapted VegSyst-DSS V2 were very similar to those of the OT treatments in Long Cycle and Spring crops. Scenario analyses demonstrated how perlite age affected recommended NS concentrations through differential nutrient retention in/loss from perlite substrate.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109351"},"PeriodicalIF":5.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Composite microbial agent improves cotton yield and resource use efficiency under mild salt stress by optimizing plant resource allocation","authors":"Xiao Zhao ,&nbsp;Panpan Guo ,&nbsp;Xiong Wu ,&nbsp;Meng Zhu ,&nbsp;Shaozhong Kang ,&nbsp;Taisheng Du ,&nbsp;Jian Kang ,&nbsp;Jinliang Chen ,&nbsp;Ling Tong ,&nbsp;Risheng Ding ,&nbsp;Wanli Xu ,&nbsp;Guangmu Tang","doi":"10.1016/j.agwat.2025.109358","DOIUrl":"10.1016/j.agwat.2025.109358","url":null,"abstract":"<div><div>Soil salinization and low resource utilization efficiency present significant challenges to cotton production. The application of salt-tolerant composite plant growth-promoting rhizobacteria (STC-PGPR) is considered an effective strategy to address these issues. However, its broad adaptability and regulatory mechanisms require further exploration. We hypothesize that under non-saline or moderately saline conditions, STC-PGPR directs resources to shoots, especially reproductive organs, by altering the rhizosphere bacterial community, thereby enhancing seed cotton yield (SY) and resource use efficiency. To validate our hypothesis, we conducted an experiment using two cotton varieties: Xinluzao 72 (G1) and Zhongmiansuo 49 (G2); two microbial treatments: without STC-PGPR (B1) and with STC-PGPR (B2); and three salinity levels: 0, 4, and 8 g NaCl kg⁻¹ soil (S1, S2, S3). The results demonstrated that STC-PGPR enhanced SY and resource use efficiency under both S1 and S2 salinity levels, with significant improvements observed in G2S1 and G1S2 . Under G2S1, STC-PGPR increased nitrogen uptake efficiency, optimized shoot resource allocation to stems and squares, enhanced stem support, and improved resource storage and transport. Consequently, SY and nitrogen partial factor productivity (NPFP) increased by 9.1 % and 9.0 %, respectively. Under G1S2, STC-PGPR reduced the root-shoot ratio, directing more resources to shoots, which led to increases in SY, irrigation water productivity, and NPFP by 46.2 %, 44.8 %, and 45.9 %, respectively. These changes were primarily due to altered indigenous biomarkers after STC-PGPR application, rather than the bacteria in STC-PGPR. This study highlights the potential of STC-PGPR, emphasizing the importance of optimizing resource allocation rather than merely promoting growth. Additionally, it underscores the significant role of indigenous biomarkers in mediating these effects.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"310 ","pages":"Article 109358"},"PeriodicalIF":5.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the allometry between ear saturated water accumulation and dry mass for diagnosing winter wheat water status during the reproductive growth","authors":"Tingxuan Zhuang ,&nbsp;Ben Zhao ,&nbsp;Syed Tahir Ata-Ul-Karim ,&nbsp;Gilles Lemaire ,&nbsp;Xiaojun Liu ,&nbsp;Yongchao Tian ,&nbsp;Yan Zhu ,&nbsp;Weixing Cao ,&nbsp;Qiang Cao","doi":"10.1016/j.agwat.2025.109364","DOIUrl":"10.1016/j.agwat.2025.109364","url":null,"abstract":"<div><div>The ear, which begins to form and develop during the reproductive growth phase, relies on maintaining a normal water status for its formation, grain filling, and overall yield. Accurate diagnosis of water status during the reproductive growth phase is imperative for achieving precision water management in winter wheat cultivation. Previous studies used the allometric relationship between plant dry mass (PDM) and plant saturated water accumulation (SWA_P) to develop critical SWA_P curves, which were employed to assess the water status of winter wheat and maize during their vegetative growth phase. However, it remains uncertain whether this method is applicable to the ear of winter wheat during its reproductive growth phase. The study focused on developing and validating a model to quantify the water status of winter wheat during reproductive growth phase by using critical ear saturated water accumulation (SWA_E) curves and water diagnostic index (WDI) based on ear, and to analyze the effect of water-nitrogen interaction on it. Field experiments involving four water and two nitrogen treatments were conducted from 2019 to 2023 to determine the relationship between ear dry mass (EDM) and SWA_E during the reproductive growth phase of winter wheat. The impact of water-nitrogen interaction on EDM-SWA_E allometry was also analyzed. In addition, the ear WDI was defined as the ratio of the actual SWA_E value to the critical SWA_E value under the same EDM. The critical SWA_E curves under nitrogen limited (N1) and non-nitrogen limited (N2) conditions were constructed (N1: SWA_E = 3.53EDM^0.48; N2: SWA_E = 4.53EDM^0.47). Nitrogen deficiency lowered the SWA_E value at the same EDM, but it did not impact its accumulation rate. The indirect soil nitrogen deficiency, reduction of grain number per ear and early grain filling caused by drought were the three main factors leading to the decrease of ear WDI. The ear WDI effectively distinguishes varying degrees of water stress; however, it is essential to minimize errors resulting from its uncertainty before application. These findings will provide valuable insights into the water status of winter wheat under varying water and nitrogen conditions during the reproductive growth phase. Additionally, they will serve as a foundation for advancing future research on precise irrigation strategies.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"309 ","pages":"Article 109364"},"PeriodicalIF":5.9,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}