Agricultural Water Management最新文献_第9页

Water productivity of soybean production systems: A study integrating machine learning and global meta-analysis 大豆生产系统的水分生产力：一项整合机器学习和全球元分析的研究

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-02-05 DOI: 10.1016/j.agwat.2026.110203

Huifang Zheng , Luchang An , Wending Wang , Yanyu Wang , Xinhua Li , Xiying Zhang

Soybean (Glycine max) is one of the most significant crops globally. With its relatively low water productivity (WP), huge amount of water was consumed annually in soybean production. Understanding soybean WP on a global scale is useful for identifying limitations in WP improvement to reduce water use. A meta-analysis was conducted on global soybean WP, based on 2247 observations from 274 studies published from April 2000 to January 2025, with aims to quantify the current WP and its influencing factors, and estimate the boundary function for WP in the different soybean agroecological zones in the world. The global average WP was 6.4 kg ha⁻¹ mm⁻¹. The mean WP followed the order of Americas (mean: 8.1 kg ha⁻¹ mm⁻¹) > Asia (mean: 5.8 kg ha⁻¹ mm⁻¹) > Europe (mean: 5.6 kg ha⁻¹ mm⁻¹) > Africa (mean: 4.5 kg ha⁻¹ mm⁻¹). The boundary function model indicated that the theoretical potential WP values could reach 15.2 kg ha⁻¹ mm⁻¹, 9.6 kg ha⁻¹ mm⁻¹, 14.6 kg ha⁻¹ mm⁻¹ and 6.2 kg ha⁻¹ mm⁻¹ in Asia, Europe, the Americas and Africa, respectively. Combining machine learning and mixed effects model analysis revealed that key limiting factors of WP included mean annual precipitation (MAP), mean annual temperature (MAT)and soil organic matter (SOM). For different management measures, the meta-analysis showed that plastic film mulching played an important role in improving global soybean WP (30.6 % increase, p < 0.05), followed by nitrogen fertilizer application (24.4 % increase, p < 0.05), using irrigation (21.0 % increase, p < 0.05), and optimized irrigation management (7.4 % increase, p < 0.05). These findings provide a scientific basis for optimizing field management strategies to improve soybean WP.

大豆（Glycine max）是全球最重要的作物之一。大豆的水分生产力（WP）相对较低，每年的耗水量巨大。在全球范围内了解大豆的可湿性对确定改善可湿性以减少用水的限制是有用的。基于2000年4月至2025年1月间发表的274项研究的2247项观测数据，对全球大豆可湿性进行了荟萃分析，旨在量化全球大豆可湿性现状及其影响因素，并估算世界不同大豆农业生态区可湿性的边界函数。全球平均WP为6.4 kg ha−1 mm−1。平均WP遵循美洲的顺序(意思是:8.1 公斤 公顷−1毫米−1)祝辞 亚洲(意思是:5.8 公斤 公顷−1毫米−1)祝辞 欧洲(意思是:5.6 公斤 公顷−1毫米−1)在非洲(意思是:4.5 公斤 公顷−1毫米−1)。边界函数模型表明，亚洲、欧洲、美洲和非洲的理论潜在WP值分别达到15.2 kg ha−1 mm−1、9.6 kg ha−1 mm−1、14.6 kg ha−1 mm−1和6.2 kg ha−1 mm−1。结合机器学习和混合效应模型分析，发现年平均降水量（MAP）、年平均气温（MAT）和土壤有机质（SOM）是影响土壤水分含量的关键因素。不同管理措施,荟萃分析表明,塑料薄膜覆盖发挥了重要作用改善全球大豆WP(30.6 %增加,p & lt; 0.05),其次是氮施肥(24.4 %增加,p & lt; 0.05),使用灌溉(21.0 %增加,p & lt; 0.05),和优化灌溉管理(7.4 %增加,p & lt; 0.05)。这些研究结果为优化田间管理策略以提高大豆WP提供了科学依据。

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引用次数: 0

Coupled effects of meteorological and irrigation factors differentiate spatiotemporal variability and seasonal fluctuations of groundwater levels 气象和灌溉因子的耦合作用区分了地下水位的时空变化和季节波动

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-28 DOI: 10.1016/j.agwat.2026.110196

Qize Gao , Jingsi Zhu , Long Sun , Wentan Chen , Yong Zhang , Bo Liu , Chengpeng Lu

Given the scarcity of groundwater resources in the North China Plain (NCP) – a region important to both ecological integrity and socioeconomic development – understanding the spatiotemporal evolution and seasonal fluctuations of groundwater levels (GWLs) helps support effective groundwater management. This study integrates the Self-Organizing Map (SOM), an improved Innovative Trend Analysis (ITA), the Geographically Weighted Regression (GWR) model, and the Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors (SARIMAX) model to analyze GWL variations in the NCP affected by meteorological and irrigation factors from 2018 to 2023. Winter wheat irrigation was estimated based on daily water stress factors, and spring irrigation demand across the region was effectively quantified. The results reveal significant spatial variability in GWLs, with levels generally higher in the northeast and lower in the southwest. The improved ITA method shows that the shallow GWLs rose by 26% and 39% in the low and high value parts and the deep GWLs rose by 11% and 20% in the low and high value parts, respectively. This indicates an overall upward trend in GWLs across the NCP. Shallow aquifers exhibit greater sensitivity to environmental changes and increasing spatial heterogeneity, while deep aquifers are relatively stable, with decreasing spatial variability. Quantitative analysis using the GWR model confirms that precipitation is the main source of groundwater recharge, while potential evaporation and irrigation are the main causes of discharge. Spring irrigation, in particular, exerts a strong influence on shallow aquifer GWLs. The SARIMAX model further demonstrates clear seasonal patterns in GWLs, highlighting the lagged effects of different influencing factors. Precipitation and irrigation are identified as the dominant drivers of seasonal groundwater fluctuations in the NCP. These findings provide useful insights for improving the prediction and adaptive management of groundwater resources in the region.

华北平原是一个对生态完整性和社会经济发展具有重要意义的地区，由于地下水资源的稀缺性，了解地下水位的时空演变和季节波动有助于有效的地下水管理。利用自组织图（SOM）、改进的创新趋势分析（ITA）、地理加权回归（GWR）模型和季节自回归综合移动平均与外生回归（SARIMAX）模型，分析了2018 - 2023年受气象和灌溉因子影响的中国西北大区GWL变化。基于日水分胁迫因子对冬小麦灌溉进行估算，有效量化了区域春灌需求。结果表明，全球暖化指数存在显著的空间变异性，总体表现为东北高、西南低。改进后的ITA方法显示，低、高值区浅层gwl分别上升26%和39%，低、高值区深层gwl分别上升11%和20%。这表明在全国范围内，gwl总体呈上升趋势。浅层含水层对环境变化的敏感性更强，空间异质性增加，而深层含水层相对稳定，空间变异性减小。利用GWR模型进行定量分析，证实降水是地下水补给的主要来源，潜在蒸发和灌溉是径流的主要原因。特别是春灌对浅层含水层的gwl影响较大。SARIMAX模型进一步揭示了gwl的明显季节特征，突出了不同影响因子的滞后效应。降水和灌溉被确定为NCP地下水季节性波动的主要驱动因素。这些发现为改善该地区地下水资源的预测和适应性管理提供了有益的见解。

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引用次数: 0

Impact of irrigation and nitrogen application strategies on cotton yield, agronomic nitrogen use efficiency, and environmental nitrogen fate 灌溉和施氮策略对棉花产量、农艺氮利用效率和环境氮命运的影响

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-28 DOI: 10.1016/j.agwat.2026.110194

Zhen Luo , Wei Tang , Xiyuan Duan , Hequan Lu , Cundong Li , Liantao Liu , Xiangqiang Kong

This study evaluated the impacts of different irrigation-nitrogen (N) application strategies and N application rates on cotton growth and yield, agronomic N use efficiency (ANUE), and fertilizer-N fate in arid region. A split-plot design was employed to compare traditional irrigation and N application (TIN) with alternate partial root-zone irrigation combined with root-zone fertilization (ADI-RZF), under three N rates (0, 220, and 275 kg ha⁻¹). The results revealed that the seed cotton yield, harvest index (HI), ANUE, irrigation water productivity (WP_I) and fertilizer N recovery efficiency (FNRE) significantly increased under the ADI-RZF treatment relative to TIN. The expression of nitrate transporter genes (GhNRT1.1 and GhNRT1.5) was upregulated by 2.3- and 2.7-fold in hydrated root zones under ADI-RZF, explaining the 34.7–52.9 % enhancement in FNRE. At N_220, the optimized ADI-RZF system achieved 95 % of the maximum yield potential (equivalent to the N₂₇₅ yield under ADI-RZF), while it reduced N input by 20 % and lowered the fertilizer N loss rate (FNLR) by 38.5–42.7 % compared to TIN at equivalent N rates. This reduction is attributed to the spatially targeted N placement in ADI-RZF, which minimized the soil residual N by 11.9–30.3 % through enhanced root foraging precision. In conclusion, ADI-RZF at the N₂₂₀ rate represents a sustainable strategy for cotton production in arid regions such as Xinjiang, China, effectively balancing high yield with a reduced environmental N footprint.

研究了不同灌溉施氮策略和施氮量对干旱区棉花生长和产量、氮素农艺利用效率（ANUE）和肥氮命运的影响。在3种施氮量（0、220和275 kg ha⁻¹）下，采用分块设计比较传统灌溉施氮（TIN）与部分根区灌溉加根区施肥（ADI-RZF）。结果表明，与TIN相比，ADI-RZF处理显著提高了籽棉产量、收获指数（HI）、ANUE、灌溉水生产力（WPI）和氮肥恢复效率（FNRE）。硝酸盐转运基因（GhNRT1.1和GhNRT1.5）在水合根区表达上调了2.3倍和2.7倍，这解释了在ADI-RZF作用下，FNRE中硝酸盐转运基因（GhNRT1.1和GhNRT1.5）表达增加34.7-52.9 %。在氮素水平为220时，优化后的ADI-RZF系统达到了最高产量潜力的95 %（相当于ADI-RZF下的N275产量），与同等氮素水平下的TIN相比，氮素投入减少了20 %，氮肥损失率（FNLR）降低了38.5-42.7 %。这主要归因于ADI-RZF的空间定向施氮，通过提高根系觅食精度，使土壤残氮减少11.9-30.3 %。综上所述，N220速率下的ADI-RZF是中国新疆等干旱地区棉花生产的可持续策略，可以有效地平衡高产和减少环境氮足迹。

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引用次数: 0

Integrated organic-inorganic fertilization enhances soil microbial diversity and mitigates the yield-quality trade-off in pakchoi (Brassica chinensis L.) 有机无机配施提高了小白菜土壤微生物多样性，缓解了小白菜产量与质量的权衡

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-24 DOI: 10.1016/j.agwat.2026.110189

Shudong Lin , Xiaole Zhao , Qiuping Fu , Zhenghu Ma , Yingjie Ma , Tingrui Yang

The sustainability of agricultural production systems is increasingly constrained by the trade-off between yield and quality, largely driven by declines in soil microbial diversity under conventional intensive management characterized by excessive synthetic fertilizer inputs. This study elucidates the synergistic mechanisms through which integrated low-rate inorganic-organic fertilization (IO1) alleviates this trade-off in pakchoi (Brassica chinensis L.) by regulating rhizosphere microbial communities. A hierarchical pathway model was developed to quantify the linkages among soil microbial diversity, crop growth dynamics, yield formation, and quality attributes. Compared with inorganic-only fertilization (I1), the IO1 treatment significantly enhanced bacterial Shannon diversity and Chao1 richness, which accelerated the average growth rates of plant height (0.736 cm/d) and leaf area index (0.121 cm²/(cm²·d)). As a result, pakchoi yield increased to 5.58 kg/m², representing a 24.77 % improvement over I1. At the mechanistic level, improved microbial functional balance optimized nitrogen metabolic pathways, leading to substantial increases in soluble sugars (64.37 %), soluble proteins (39.21 %), and vitamin C content (82.04 %), while simultaneously reducing nitrate accumulation by 14.78 %. Mantel test results further revealed that bacterial communities primarily governed biomass accumulation through fresh weight dynamics (4.239 g/(plant·d)), whereas fungal communities played a key role in regulating photosynthate redistribution via organic matter catabolism, thereby establishing a "growth prioritization-quality compensation" dynamic equilibrium. Model predictions indicated that each unit increase in bacterial Shannon diversity corresponded to a 0.534 kg/m² increase in yield, while each unit rise in the Pielou evenness index resulted in a 2.218 mg/g reduction in nitrate content. Overall, these findings provide a robust theoretical basis for microbial driven precision fertilization strategies aimed at enhancing yield, quality, and sustainability in vegetable production systems.

农业生产系统的可持续性越来越受到产量和质量之间权衡的限制，这主要是由于传统集约化管理下土壤微生物多样性的下降，其特征是过量的合成肥料投入。本研究阐明了低比例无机-有机综合施肥（IO1）通过调节小白菜根际微生物群落来缓解这种权衡的协同机制。建立了土壤微生物多样性、作物生长动态、产量形成和品质属性之间的层次路径模型。与纯无机施肥（I1）相比，IO1处理显著提高了细菌Shannon多样性和Chao1丰富度，提高了株高（0.736 cm/d）和叶面积指数（0.121 cm2/(cm2·d)）的平均生长率。结果，小白菜产量增加到5.58 kg/m2，比11提高24.77 %。在机制水平上，改善的微生物功能平衡优化了氮代谢途径，导致可溶性糖（64.37 %）、可溶性蛋白（39.21 %）和维生素C含量（82.04 %）大幅增加，同时硝酸盐积累减少14.78 %。Mantel试验结果进一步表明，细菌群落主要通过鲜重动态控制生物量积累（4.239 g/（株·d）），而真菌群落则通过有机质分解代谢调节光合产物再分配，从而建立了“生长优先-质量补偿”的动态平衡。模型预测表明，细菌Shannon多样性每增加一个单位对应的产量增加0.534 kg/m2，而Pielou均匀度指数每增加一个单位对应的硝酸盐含量减少2.218 mg/g。总的来说，这些发现为微生物驱动的精确施肥策略提供了坚实的理论基础，旨在提高蔬菜生产系统的产量、质量和可持续性。

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引用次数: 0

Estimation of wetting patterns for surface drip irrigation using moment analysis and interpretable PSO-SVM-AdaBoost model 利用矩分析和可解释PSO-SVM-AdaBoost模型估计地表滴灌的湿润模式

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-23 DOI: 10.1016/j.agwat.2026.110177

Ge Li, Weibo Nie, Yuchen Li

A thorough understanding of soil wetting patterns during infiltration is essential for designing surface drip irrigation systems and placing soil moisture sensors. This study systematically evaluated variations in centroid depth (z_c), horizontal (σ_x) and vertical (σ_z) standard deviations across nine soil textures, three discharge rates (1, 2, and 3 L·h⁻¹), and three initial soil water contents (30 %, 50 %, 70 % of maximum available water) using Hydrus-2D/3D numerical simulations combined with spatial moment analysis. Based on these results, a machine learning model combining particle swarm optimization (PSO), support vector machine (SVM), and adaptive boosting (AdaBoost) was developed and compared with multiple linear regression (MLR), SVM, and PSO-SVM models. Soil texture and initial water content had greater influence on z_c, σ_x, and σ_z than discharge rates. The PSO-SVM-AdaBoost model achieved the highest accuracy, with Bias, Root Mean Square Error (RMSE), and the Coefficient of Determination (R²) for the test set of −0.129 cm, 1.139 cm, and 0.989 for z_c; −0.034 cm, 0.366 cm, and 0.996 for σ_x; and −0.169 cm, 1.426 cm, and 0.984 for σ_z. Furthermore, to address concerns regarding the “black-box” nature of the model, the explainable artificial intelligence (XAI) framework SHapley Additive exPlanations (SHAP) was applied, revealing that cumulative infiltration flux (Q_3D) contributed most significantly to z_c, σ_x, and σ_z, while discharge rates contributed the least. The PSO-SVM-AdaBoost model and its interpretability framework proposed in this study provide technical support for the design of surface drip irrigation systems and the optimal placement of soil moisture sensors.

深入了解渗透过程中的土壤湿润模式对于设计地表滴灌系统和放置土壤湿度传感器至关重要。本研究利用Hydrus-2D/3D数值模拟结合空间矩分析，系统评价了9种土壤质地的质心深度（zc）、水平（σx）和垂直（σz）标准差、3种排放速率（1、2和3 L·h−1）和3种初始土壤含水量（最大有效水量的30 %、50 %和70 %）的变化。基于这些结果，建立了粒子群优化（PSO）、支持向量机（SVM）和自适应增强（AdaBoost）相结合的机器学习模型，并与多元线性回归（MLR）、支持向量机（SVM）和PSO-SVM模型进行了比较。土壤质地和初始含水量对zc、σx和σz的影响大于排放速率。PSO-SVM-AdaBoost模型获得了最高的精度，测试集的偏差、均方根误差（RMSE）和决定系数（R2）分别为- 0.129 cm、1.139 cm和0.989；−0.034 cm, 0.366 cm, 0.996 σx；σz为- 0.169 cm, 1.426 cm, 0.984。此外，为了解决模型“黑箱”性质的问题，应用可解释人工智能（XAI）框架SHapley加性解释（SHAP），揭示了累积入渗通量（Q3D）对zc、σx和σz的贡献最大，而流量的贡献最小。本文提出的PSO-SVM-AdaBoost模型及其可解释性框架为地表滴灌系统的设计和土壤湿度传感器的优化配置提供了技术支持。

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引用次数: 0

Stomatal conductance modeling for drip-irrigated kiwifruit in seasonal drought regions of South China: Evaluation of improved empirical models and interpretable machine learning approaches 华南季节性旱区滴灌猕猴桃气孔导度建模：改进的经验模型和可解释性机器学习方法的评价

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-16 DOI: 10.1016/j.agwat.2026.110153

Shunsheng Zheng , Ningbo Cui , Quanshan Liu , Shouzheng Jiang , Daozhi Gong , Xiaoxian Zhang

Accurate modeling of stomatal conductance (g_s) enhances understanding of plant water relations and supports advancements in eco-physiological modeling and adaptive irrigation practices. This study provides a comprehensive evaluation of g_s modeling for drip-irrigated kiwifruit through parallel development of three Jarvis-type empirical models (JV, JV1, JV2) and five machine learning algorithms (XGBoost, LightGBM, CatBoost, SVR, LR) based on three years of field measurements comprising synchronized records of g_s and key environmental drivers. Models were assessed via year-wise grouped cross-validation, with performance measured by R², RMSE, and MAE, and interpretability analyzed using SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs). Results showed that deficit irrigation significantly reduced g_s, with sensitivity being most pronounced during stage II. The incorporation of soil water content (SWC) substantially improved the accuracy of both empirical and machine learning models. Among empirical models, JV2, featuring a stage-specific nonlinear SWC response function, demonstrated the highest accuracy (R² ranging from 0.736 to 0.814) and minimized bias under extreme SWC conditions. Using vapor pressure deficit (VPD), air temperature (Ta), photosynthetically active radiation (PAR), and SWC as input variables, CatBoost outperformed both empirical models and other machine learning algorithms across all growth stages (R² = 0.815–0.839; RMSE = 0.065–0.076 mol m⁻² s⁻¹; MAE = 0.054–0.064 mol m⁻² s⁻¹). SHAP analysis and PDPs identified VPD as the dominant driver of g_s variation, followed by SWC. Overall, the improved JV2 model offers a structurally transparent framework for g_s estimation with acceptable accuracy, while CatBoost combined with SHAP analysis and PDPs provides superior predictive performance and robust interpretability under complex environmental conditions. These findings support the reliable modeling and regulation of kiwifruit g_s under varying SWC scenarios in drip-irrigated orchards.

气孔导度（gs）的精确建模增强了对植物水分关系的理解，并支持生态生理建模和适应性灌溉实践的进步。本研究基于三年的田间测量数据，包括同步记录的gs和关键环境驱动因素，通过并行开发三种jarvis型经验模型（JV、JV1、JV2）和五种机器学习算法（XGBoost、LightGBM、CatBoost、SVR、LR），对滴灌猕猴桃gs模型进行了全面评估。通过年度分组交叉验证对模型进行评估，使用R2、RMSE和MAE测量模型的性能，并使用SHapley加性解释（SHAP）和部分依赖图（pdp）分析模型的可解释性。结果表明，亏缺灌溉显著降低了gs，在II期敏感性最为明显。土壤含水量（SWC）的结合大大提高了经验模型和机器学习模型的准确性。在经验模型中，JV2具有特定阶段的非线性SWC响应函数，在极端SWC条件下具有最高的精度（R2范围为0.736 ~ 0.814）和最小的偏差。使用蒸汽压差（VPD）、空气温度（Ta）、光合有效辐射（PAR）和SWC作为输入变量，CatBoost在所有生长阶段都优于经验模型和其他机器学习算法（R2 = 0.815-0.839; RMSE = 0.065-0.076 mol m−2 s−1;MAE = 0.054-0.064 mol m−2 s−1）。SHAP和pdp分析表明VPD是gs变化的主要驱动因素，其次是SWC。总体而言，改进的JV2模型为gs估计提供了一个结构透明的框架，具有可接受的精度，而CatBoost结合SHAP分析和pdp提供了优越的预测性能和复杂环境条件下的鲁棒可解释性。这些发现支持了滴灌果园中猕猴桃在不同SWC情景下的可靠建模和调控。

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引用次数: 0

Effects of irrigation and fertilization on the yield of traditional and modern foxtail millet varieties 灌溉和施肥对传统和现代谷子品种产量的影响

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-19 DOI: 10.1016/j.agwat.2026.110168

Ke Ma , Zheng Jia , Xinya Wen , Fu Chen

To elucidate the mechanisms underlying yield formation in response to water and fertilizer management in traditional and modern foxtail millet varieties, a field experiment was conducted using the traditional cultivar Jingu 6 and the modern cultivar Changsheng 13. Three irrigation regimes (rainfed, pre‑sowing supplemental irrigation, and full growth‑stage irrigation) and two fertilizer levels (high and low) were implemented. Phenotypic traits, photosynthetic parameters, dry matter accumulation and translocation, photosynthate content, and yield were measured. Multivariate statistical analysis was performed to reveal the intrinsic factors responsible for yield differences between the varieties under varying water and fertilizer conditions. The results indicated that the traditional cultivar exhibited low yield potential but high stability, with minimal inter‑annual variation and low sensitivity to water and fertilizer inputs. Under rainfed conditions, its yield decreased by 16.98–39.18 %, which was maintained primarily through optimized photoprotective mechanisms and pre‑flowering dry matter allocation. In contrast, the modern cultivar showed high yield potential but poor stability, with yield increases ranging from 39.09 % to 272.42 % under conditions of high water and high fertilizer inputs. Its high yield depended on full growth‑stage irrigation, achieved mainly through improved plant architecture, enhanced photosynthetic efficiency, and strengthened source‑sink coordination. Therefore, traditional cultivars are suitable for rainfed dryland agriculture, whereas modern cultivars require reliable irrigation. Future breeding strategies should integrate the water‑saving and stress‑tolerance traits of traditional cultivars with the high‑yield potential of modern cultivars to develop water‑efficient and high‑yielding hybrids, which is crucial for building a climate‑resilient foxtail millet production system.

为了阐明水肥管理对传统和现代谷子品种产量形成的影响机制，以传统品种金谷6号和现代品种长胜13号为试验材料进行了田间试验。采用了三种灌溉方式（雨灌、播前补灌和全生育期灌溉）和两种施肥水平（高施肥和低施肥）。测定了表型性状、光合参数、干物质积累和转运、光合产物含量和产量。通过多元统计分析，揭示了不同水肥条件下各品种产量差异的内在因素。结果表明，传统品种产量潜力低，稳定性好，年际变化小，对水肥投入敏感性低。在旱作条件下，其产量下降16.98 ~ 39.18 %，主要是通过优化光保护机制和花前干物质分配来维持。相比之下，现代品种表现出高产潜力，但稳定性较差，在高水肥投入条件下，产量增幅为39.09 % ~ 272.42 %。其高产依赖于全生育期灌溉，主要通过改善植株结构、提高光合效率和加强源库协调来实现。因此，传统品种适合旱地雨养农业，而现代品种需要可靠的灌溉。未来的选育策略应将传统品种的节水、耐胁迫特性与现代品种的高产潜力相结合，培育出节水、高产的杂交种，这对建立气候适应型谷子生产体系至关重要。

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引用次数: 0

Responses of tree water uptake to soil water content variability under combined threshold effects 复合阈值效应下树木水分吸收对土壤含水量变异的响应

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-31 DOI: 10.1016/j.agwat.2026.110197

Xiao Zhang , Ziqiang Liu , Xinxiao Yu , Longqi Zhang , Guodong Jia

In the context of global climate change, seasonal droughts significantly impact tree water use and soil water source contribution (WSC) in forest ecosystems. However, studies on the threshold effects of the soil water content (SWC) and previous precipitation on tree water uptake are scarce. In the study, the focus was placed on the two tree species Platycladus orientalis and Quercus variabilis, which grow in the mountainous areas of northern China. Using eco-hydrological monitoring data from 3 years, we investigated the nonlinear threshold relationship between the SWC and the WSC in different precipitation treatments (zero, half, natural, and double precipitation). A combination of structural equation modeling, random forest modeling, and S-shaped curve threshold analysis was applied to evaluate the indirect effects of previous precipitation on the SWC and WSC. S-shaped threshold analysis identified SWC thresholds spanning approximately 3–26 %; Quercus variabilis showed a consistent deep-layer transition at low SWC (φ1 = 6.3–8.4 % across zero, half and natural treatments), whereas Platycladus orientalis exhibited clear cross-layer thresholds mainly under half precipitation (φ1 = 7.0–9.8 %). Thresholds generally shifted upward under wetter conditions. Based on the results, SWC, as the dominant factor influencing the WSC, exhibited complex and significant threshold effects at different soil depths. The two species displayed contrasting water use strategies at similar threshold levels, effectively reducing competition for water. The indirect influence of previous precipitation on the SWC and WSC also varied significantly with soil depth and precipitation amount. The results of this study highlight the complex threshold effects of the SWC on WSC in different precipitation scenarios, providing a scientific basis for understanding forest water dynamics under climate change and developing adaptive management strategies.

在全球气候变化背景下，季节性干旱显著影响森林生态系统树木水分利用和土壤水源贡献。然而，关于土壤含水量（SWC）和既往降水对树木水分吸收阈值效应的研究很少。在研究中，重点研究了生长在中国北方山区的两种树种——侧柏（Platycladus orientalis）和栎（Quercus variabilis）。利用3年生态水文监测数据，研究了不同降水处理（零降水、半降水、自然降水和双降水）下SWC与WSC之间的非线性阈值关系。采用结构方程模型、随机森林模型和s形曲线阈值分析相结合的方法评价了以往降水对SWC和WSC的间接影响。s形阈值分析确定SWC阈值范围约为3-26 %；变异栎在低SWC条件下表现出一致的深层过渡（φ1 = 6.3 ~ 8.4 %，跨越零、半和自然处理），而侧柏在半降水条件下表现出明确的跨层阈值（φ1 = 7.0 ~ 9.8 %）。在较潮湿的条件下，阈值通常向上移动。结果表明，在不同土层深度，土壤水分承载力作为影响土壤水分承载力的主导因子，表现出复杂而显著的阈值效应。这两个物种在相似的阈值水平上表现出截然不同的水利用策略，有效地减少了对水的竞争。以往降水对SWC和WSC的间接影响也随土壤深度和降水量的变化而显著变化。研究结果揭示了不同降水情景下森林水碳对水碳的复杂阈值效应，为理解气候变化下森林水动态和制定适应性管理策略提供了科学依据。

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引用次数: 0

Drip irrigation-mediated application of multi-walled carbon nanotubes and Bacillus subtilis improves maize salt tolerance in saline agricultural ecosystems 滴灌介导的多壁碳纳米管和枯草芽孢杆菌的应用提高了盐碱化农业生态系统中玉米的耐盐性

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-30 DOI: 10.1016/j.agwat.2026.110192

Yi Liu , Wenzhi Zeng , Chang Ao , Yutian Zuo , Ying Luo , Zhen Li

Soil salinization impairs fertility and reduces crop productivity across more than 6 % of the world’s arable land. Traditional remediation approaches, like chemical amendments, are often costly and involve ecological compromises. This study investigates an innovative nano-bio strategy that integrates multi-walled carbon nanotubes (MWCNTs) with Bacillus subtilis (B. subtilis) under drip irrigation to boost maize tolerance in saline environments. Germination tests and field studies were conducted in soils treated with 50 mM NaCl. The results from four comparative treatments revealed that MWCNTs markedly improved seed germination (achieving 52 % by day two versus 24 % in controls) and enhanced root elongation by 52.36 %. These effects were linked to the upregulation of key ion transporters (ZmSKOR). Furthermore, MWCNTs application enhanced the expression of aquaporin genes ZmPIP1;1 and ZmPIP2;1. Although B. subtilis alone had a minimal impact on germination, its combination with MWCNTs fostered stronger soil-microbe-nanomaterial interactions under drip irrigation. This synergy increased maize yield by 20.6 %, raised the 1000-grain weight by 3.08 %, lowered the leaf Na⁺/K⁺ ratio by 19.93 %, and improved antioxidant defense mechanisms, such as a 10.44 % rise in SOD activity. Importantly, while MWCNTs alone decreased soil nitrogen in non-saline conditions, adding B. subtilis helped rebalance nutrients, an effect that was reinforced by the uniform distribution provided by drip irrigation. The mechanism involves improved nutrient assimilation, better stomatal control, and reduced reactive oxygen species under salt stress. These findings indicate that the MWCNTs and B. subtilis act synergistically with drip irrigation via molecular soil-root interactions to mitigate salt toxicity. This integrated approach, which combines nanotechnology, microbiome engineering, and water-efficient irrigation, offers a sustainable and effective solution for reclaiming saline soils and advancing stress-resistant agriculture.

土壤盐碱化损害了全球60%以上可耕地的肥力，降低了作物生产力。传统的补救方法，如化学修正，往往是昂贵的，并涉及生态妥协。本研究研究了一种创新的纳米生物策略，该策略将多壁碳纳米管（MWCNTs）与枯草芽孢杆菌（B. subtilis）在滴灌下结合，以提高玉米在盐水环境中的耐受性。在50 mM NaCl处理的土壤中进行了发芽试验和田间研究。四个比较处理的结果显示，MWCNTs显著提高了种子萌发率（第2天达到52% %，而对照组为24% %），并使根伸长率提高了52.36% %。这些效应与关键离子转运体（ZmSKOR）的上调有关。此外，MWCNTs的应用增强了水通道蛋白基因ZmPIP1的表达；1、ZmPIP2；虽然枯草芽孢杆菌单独对种子萌发的影响很小，但在滴灌条件下，与MWCNTs结合可促进土壤-微生物-纳米材料的更强相互作用。这种协同作用使玉米产量提高20.6 %，千粒重提高3.08 %，使叶片Na + /K +比降低19.93 %，并改善抗氧化防御机制，如SOD活性提高10.44 %。重要的是，虽然MWCNTs单独降低了非盐碱化条件下的土壤氮，但添加枯草芽孢杆菌有助于重新平衡养分，滴灌提供的均匀分布强化了这一效果。其机制包括在盐胁迫下改善养分同化、改善气孔控制和减少活性氧。这些发现表明，MWCNTs和枯草芽孢杆菌通过分子土壤-根相互作用与滴灌协同作用，以减轻盐毒性。这种综合方法结合了纳米技术、微生物组工程和节水灌溉，为开垦盐碱地和推进抗逆性农业提供了一种可持续和有效的解决方案。

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引用次数: 0

Quantification of water in ginseng roots (Panax ginseng C. A. Meyer) in soil using 3D neutron imaging 利用三维中子成像定量土壤中人参根（Panax ginseng C. A. Meyer）中的水分

IF 6.5 1区农林科学 Q1 AGRONOMY

Agricultural Water Management

Pub Date : 2026-03-31 Epub Date: 2026-01-23 DOI: 10.1016/j.agwat.2026.110183

Cheul Muu Sim , TaeJoo Kim , Hwasuk Oh , Robert Bellarmin Nshimirimana , Michael Frei , Bernd Honermeier

The ginseng plant is threatened with extinction owing to the prevalence of soil-borne pathogens and water shortage in field cultivation due to climate change. To optimize water management in controlled cultivation that can sustain ginseng production, a 3D neutron imaging method was developed to quantitatively measure water content of roots growing in soil. It was determined that, according to a Monte Carlo simulation, the neutron penetration rate is 32 %, which allows quantitative measurement of water thicknesses up to 30 mm in aluminum phantom using 3D neutron imaging. In the simulation, the aluminum phantom was buried in soil with 12 % moisture content contained in a 50 mm diameter aluminum pot. In practical experiments, the neutron penetration rate of an aluminum phantom buried in soil with a moisture content of 7.7 % was 18 % at a water thickness of 30 mm. A calibration curve was created to quantitatively measure the water content of aluminum phantom buried in aluminum pot soil with 1.3∼7.7 % moisture. The water content of 3-year-old ginseng roots growing in aluminum pot soil with a moisture content of 7.7 % was quantitatively determined to be 70.0 % (±5 %), 55.0 % (±5 %) and 70.0 % (± 5 %) on the basis of the calibration curve. It is concluded that, the in vivo 3D neutron imaging is a unique way to analyze the hydrology throughout the seedling and culturing stages of plant roots in soil for controlled cultivation.

由于土壤病原菌的流行和气候变化导致的田间栽培缺水，人参植物面临灭绝的威胁。为了优化控制栽培中的水分管理，以维持人参的生产，开发了一种三维中子成像方法来定量测量土壤中根系的水分含量。根据蒙特卡罗模拟，确定了中子穿透率为32 %，这使得使用3D中子成像可以定量测量铝模中高达30 mm的水厚度。在模拟中，铝模埋在直径为50 mm的铝锅中，土壤含水量为12 %。在实际实验中，铝模埋在含水量为7.7 %的土壤中，水厚为30 mm时，中子穿透率为18 %。建立了定量测定水分为1.3 ~ 7.7 %的铝锅土中铝模含水量的校准曲线。在7.7 %铝盆土中生长的3年生人参根系，根据标定曲线定量测定其含水量分别为70.0 %（±5 %）、55.0 %（±5 %）和70.0 %（±5 %）。综上所述，体内三维中子成像是一种独特的方法，可以分析植物根系在土壤中整个苗期和育成阶段的水文情况，以进行控制栽培。

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引用次数: 0