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Water and Nitrogen Management in Soil–Crop Systems—4th Edition

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A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Crop Physiology and Crop Production".

Deadline for manuscript submissions: 20 November 2026 | Viewed by 3494

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Editors

Dr. Puyu Feng

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Guest Editor

College of Land Science and Technology, China Agricultural University, Beijing 100193, China
Interests: precision crop modelling; AI-driven yield forecasting; precision water & nitrogen management; data-driven agronomy; climate- risk adaptation in agriculture; uncertainty quantification; decision support systems; physics-informed machine learning; agricultural model ensembles; site-specific management practices
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Kelin Hu

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Guest Editor

College of Land Science and Technology, China Agricultural University, Key Laboratory of Arable Land Conservation (North China), Ministry of Agriculture and Rural Affairs, Beijing 100193, China
Interests: land degradation and restoration; land quality assessment; spatiotemporal variability of land quality; ecological model; climate change; machine learning
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Special Issue Information

Dear Colleagues,

Water and nitrogen (N) fertilizer play an important role in improving crop yield and quality in agricultural production. With the increase in agricultural water consumption and N fertilization, water shortages and environmental pollution caused by N losses have become common issues around the world. Therefore, it is essential that we promote crop productivity while minimizing negative environmental impacts. For this Special Issue, we welcome original research articles, technology reports, methods, opinions, perspectives, and solicited reviews and mini-reviews on water and N management in soil–crop systems. Topics of interest include, but are not limited to, the following: (1) the effects of different water and N management practices on crop yield, N fate, and water and N use efficiencies; (2) optimized irrigation practices, cropping systems, and agronomic strategies for improving water use efficiency and crop productivity; (3) innovative and novel N fertilizer application technologies, such as 4R technology (right source, right rate, right time, right place) and fertigation techniques for field or facility crops; (4）modeling water and N processes in soil–crop systems and related decision-making processes; (5）water and N management in addressing climate change impacts.

Dr. Puyu Feng
Prof. Dr. Kelin Hu
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

crop yield
cropping system
irrigation scheduling
irrigation method
water use efficiency
nitrogen management
nitrogen losses
nitrogen use efficiency
modeling
decision-making
climate change

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Related Special Issues

Water and Nitrogen Management in Soil-Crop System in Plants (19 articles)
Water and Nitrogen Management in Soil-Crop System II in Plants (17 articles)
Water and Nitrogen Management in the Soil–Crop System (3rd Edition) in Plants (21 articles)

Published Papers (6 papers)

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Research

20 pages, 3241 KB

Open AccessArticle

Interactive Effects of Irrigation Amount, Irrigation Salinity, and Nitrogen Rate on Soil Enzyme Activities and Maize (Zea mays L.) Yield Under Mulched Drip Irrigation

by Dongmei Han, Qijin Zhou, Zhanli Ma, Zhenhua Wang, Jinzhu Zhang and Yunkai Li

Plants 2026, 15(14), 2165; https://doi.org/10.3390/plants15142165 - 14 Jul 2026

Viewed by 390

Abstract

Brackish water and fertilizer must be used more efficiently to sustain maize production in arid regions affected by freshwater scarcity and soil salinization. Yet, the coupled effects of irrigation amount, irrigation salinity, and nitrogen application on soil biochemical processes and maize productivity under mulched drip irrigation remain unclear. We conducted a two-year field experiment (2023–2024) in a sandy loam field in arid northwestern China to evaluate irrigation amount (450 mm, W1; 675 mm, W2), irrigation salinity (1.3 dS m⁻¹, S1; 3.5 dS m⁻¹, S2; 5.7 dS m⁻¹, S3), and nitrogen rate (225 kg ha⁻¹, N1; 330 kg ha⁻¹, N2; 435 kg ha⁻¹, N3). The experiment measured four soil enzyme activities, soil physicochemical properties, and maize yield. Higher irrigation increased soil water storage by about 27%, but it also increased salt accumulation by about 9% across the two seasons. Increasing irrigation salinity from S1 to S3 reduced urease, alkaline phosphatase, protease, and sucrase activities by 8.52%, 6.72%, 13.75%, and 3.65%, respectively, suggesting weaker nutrient turnover and uptake under salinity stress. By contrast, the higher irrigation amount (W2) increased these activities by 10.27%, 9.73%, 11.08%, and 9.47%, respectively. Structural equation modeling indicated that soil salt accumulation constrained yield mainly by reducing grain number rather than 1000-grain weight. Although higher irrigation increased mean yield, the integrated evaluation identified W1S2N2 as the best combination. This regime produced the highest grain yield (18,355.76 kg ha⁻¹) and irrigation water productivity (40.79 kg mm⁻¹), which were 82.17% and 155.26% higher than the corresponding lowest values, while maintaining relatively high partial factor productivity of nitrogen (55.62 kg kg⁻¹) in 2024. These findings suggest that controlled deficit irrigation (450 mm) and moderate nitrogen input (330 kg ha⁻¹) are recommended for long-term sustainability in arid regions, but longer-term salinity monitoring is required before a broad recommendation can be made when using brackish water irrigation. Full article

(This article belongs to the Special Issue Water and Nitrogen Management in Soil–Crop Systems—4th Edition)

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19 pages, 5867 KB

Open AccessArticle

Comparison of Isotope Mass Balance and AquaCrop Model in Evapotranspiration Partitioning in a Maize Field of North China

by Jingjing Wang, Zixuan Wang, Zixun Chen, Bingsun Wu, Guitong Li and Baoguo Li

Plants 2026, 15(13), 2059; https://doi.org/10.3390/plants15132059 - 2 Jul 2026

Viewed by 397

Abstract

Understanding evapotranspiration (ET) partitioning into soil evaporation (E) and plant transpiration (T) is crucial for improving agricultural water use efficiency in water-scarce regions. The isotope mass balance (IMB) method and AquaCrop model are two widely used approaches for ET partitioning, yet their comparative performance across different crop growth stages remains poorly characterized. This study systematically compared these two methods using two consecutive years (2012–2013) of field isotopic observations in a summer maize field on the North China Plain, a core maize production area facing severe agricultural water scarcity. Stable isotope analysis showed that the local meteoric water line (LMWL) had a slope lower than the global meteoric water line. The 0–5 cm surface soil water evaporation lines had slopes of 5.84 (2012) and 8.06 (2013), confirming significant evaporative enrichment in the topsoil. Plant water isotopic composition closely resembled that of 40–100 cm deep soil water, indicating limited root uptake from the surface layer. IMB-estimated transpiration ratio (T/ET) exhibited distinct phenological patterns, increasing from 37 to 44% at jointing to a peak of 94–96% at filling, then declining to 84–85% at maturity. The two methods agreed well during filling to maturity (differences of 2–10%), but compared with the IMB method, AquaCrop substantially underestimated T/ET at jointing (0.9% vs. 43.8% in 2013) due to its canopy-cover-based transpiration algorithm. These findings identify the filling stage as the critical water demand period, providing a quantitative reference for precision irrigation management under similar climate and soil conditions. Full article

(This article belongs to the Special Issue Water and Nitrogen Management in Soil–Crop Systems—4th Edition)

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41 pages, 37345 KB

Open AccessArticle

Nine Coupled Irrigation–Agronomic Treatments for Water-Saving Rice Production on Albic Soil: An Interpretable Machine-Learning Diagnosis

by Jing Wang, Haomin Wang, Hui Guo, Zhenjiang Si and Tao Liu

Plants 2026, 15(13), 2037; https://doi.org/10.3390/plants15132037 - 1 Jul 2026

Viewed by 369

Abstract

Sustaining rice productivity under the dual constraints of freshwater scarcity and low-temperature stress represents a pressing challenge for high-latitude japonica rice systems worldwide. There is an urgent need to develop coupled irrigation–agronomic management strategies that jointly safeguard yield stability and water use efficiency (WUE) in cold-region rice production. In this study, a two-year field experiment was conducted in 2024–2025 on albic soil (Albic Luvisols, WRB; θfc 38.2% v/v, pH 5.80, clayey texture with poor permeability and a propensity for subsurface waterlogging) in the Sanjiang Plain, Heilongjiang Province, China (47°15′ N, 133°28′ E), with nine coupled “irrigation regime × auxiliary practice” treatments, comprising conventional continuous flooding, four-level controlled irrigation (CI) at lower thresholds of 60%, 70%, 75%, and 80% θfc, and their combinations with film mulching (FM) or a humic-acid-based soil amendment (SA). An interpretable machine-learning diagnostic framework was developed, with elastic net (EN) as the primary analytical model and random forest (RF) as a nonlinear control, to simultaneously identify core yield predictors and outlier treatments. The principal findings were: (i) The soil-amendment-coupled 75% θfc CI treatment (SACI) increased grain yield by 12.3% and reduced water input by 17.0% relative to conventional continuous flooding, with WUE reaching 1.801 kg m⁻³, a 35.3% gain over the control (p < 0.05); these improvements were consistent across both individual years (year × treatment interaction: p = 0.601; inter-year rank correlation ρ = 0.967). Lowering the CI threshold below 75% θfc significantly reduced grain yield through diminished effective-panicle retention. (ii) Multi-method consensus analysis (Kendall’s W = 0.871, p < 0.01) identified root volume at the milk stage as the most strongly and consistently associated statistical predictor of yield formation, with convergent mechanistic support from independent rhizosphere evidence (Eh, TTC reductive activity). Definitive causal validation awaits isotope-tracing experiments. (iii) The film-mulching × continuous-flooding treatment (FMCG) was diagnosed as a yield-response outlier (permutation test p = 0.003), three in situ rhizosphere measurements (redox potential, root TTC-reducing activity, and rhizosphere temperature) supported the proposed mechanism of hot–anoxic rhizospheric inhibition. Methodologically, this study develops a four-level evidence convergence framework that integrates intra-model self-consistency, cross-model (EN vs. RF) consensus, independent rhizosphere evidence, and distribution-free permutation testing, with Jackknife+ conformal prediction and companion Monte Carlo simulations (1000 replicates) used to quantify the reliability boundaries under small-sample conditions (n = 27). These findings provide an evidence-based irrigation–soil co-management strategy for cold-region rice production in Northeast China, and the proposed diagnostic paradigm offers a generalizable, reliability-quantified methodological template for interpretable small-sample modeling in multifactorial coupled field experiments. Full article

(This article belongs to the Special Issue Water and Nitrogen Management in Soil–Crop Systems—4th Edition)

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26 pages, 3834 KB

Open AccessArticle

Optimizing Sowing Date and Nitrogen Management to Trade Off Yield and Nitrate Leaching in Maize-Soybean Intercropping Under CMIP6 Climate Scenarios in the North China Plain

by Xiaoli Niu, Zhen Yang, Jie Zhang, Xiaoqing Sun, Zhandong Liu, Shihao Jin, Jiaxing Cai, Bingwu Zhang and Yunyan Sun

Plants 2026, 15(11), 1753; https://doi.org/10.3390/plants15111753 - 4 Jun 2026

Viewed by 510

Abstract

Climate change threatens nitrogen cycling in agricultural ecosystems. Optimizing sowing dates and nitrogen management for maize–soybean intercropping is critical for sustainable production in the North China Plain (NCP). Using a calibrated Agricultural Production Systems Simulator (APSIM) model driven by three representative global climate models (GCMs) selected from 20 Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs, we evaluated management strategies under two Shared Socioeconomic Pathway scenarios (SSP2-4.5 and SSP5-8.5) across three climatic zones for near-term (2030–2059) and long-term (2070–2099) periods. Under SSP5-8.5, warming was 1.8–2.2 times greater than under SSP2-4.5, nitrate nitrogen (NO₃⁻-N) leaching increased by 12.1%, and nitrate storage in the 100–150 cm soil layer rose by 53.4% in Zone III. Biological nitrogen fixation contributed 20.1–29.1% of soybean nitrogen uptake under low nitrogen and 14.9–23.4% under medium nitrogen. Optimal strategies were identified: sowing on 7 June (S3) with medium nitrogen (220.8 kg N ha⁻¹) under SSP2-4.5, and advancing sowing to 28 May (S2) with medium nitrogen under SSP5-8.5 to alleviate heat stress. This study reveals a climate-driven “earlier supply–shortened demand–concentrated leaching” mismatch, providing adaptive management guidance for maize–soybean intercropping systems in the NCP. Full article

(This article belongs to the Special Issue Water and Nitrogen Management in Soil–Crop Systems—4th Edition)

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22 pages, 8621 KB

Open AccessArticle

Comparative Study on Nitrogen and Phosphorus Removal Efficiency and Rhizosphere Microbial Mechanisms of Six Wetland Plants in Eutrophic Water

by Haoliang Cheng, Jingjing He, Xuan Zhang, Yongwen Huang and Wen Jiang

Plants 2026, 15(9), 1346; https://doi.org/10.3390/plants15091346 - 28 Apr 2026

Cited by 2 | Viewed by 459

Abstract

To address the limited understanding of interspecific differences in eutrophic-water remediation, six representative wetland plants—Myriophyllum spicatum, Oenanthe javanica, Zizania latifolia, Ipomoea aquatica, Iris pseudacorus, and Typha orientalis—were evaluated in a unified hydroponic system. The removal efficiencies of total nitrogen (TN), total phosphorus (TP), and ammonium nitrogen (NH₄⁺-N) were compared together with plant biomass accumulation and root-associated and fepiphytic microbial community characteristics. The results showed marked interspecific differences in growth and pollutant removal, with the M. spicatum treatment exhibiting the highest overall purification performance, achieving removal rates of 83.3% for NH₄⁺-N, 87.3% for TN, and 78.6% for TP after 42 days. Community-composition analysis suggested that the superior purification performance of M. spicatum was associated with a greater relative abundance of Proteobacteria and putative nitrogen- and phosphorus-cycling bacterial groups. By integrating a plant-free control with a side-by-side comparison of six wetland plants under identical hydroponic conditions, this study establishes a comparative framework linking nutrient removal to plant growth and microbial community assembly. Overall, M. spicatum was identified as the most promising species, providing new insight for wetland-plant selection and eutrophic-water remediation. Full article

(This article belongs to the Special Issue Water and Nitrogen Management in Soil–Crop Systems—4th Edition)

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21 pages, 3011 KB

Open AccessArticle

Optimal Nitrogen Application Strategies for Alfalfa Under Different Precipitation Patterns: Balancing Yield, Nitrogen Fertilizer Use Efficiency, and Soil Nitrogen Residue

by Yanbiao Wang, Yuanbo Jiang, Haiyan Li, Boda Li, Jinxi Chen, Minhua Yin, Yanxia Kang, Guangping Qi, Yanlin Ma, Bojie Xie, Haoxiang Jin, Tongjin Wu and Shan Li

Plants 2026, 15(2), 333; https://doi.org/10.3390/plants15020333 - 22 Jan 2026

Viewed by 706

Abstract

Rational nitrogen applications can not only improve nutrient use efficiency, but also reduce environmental pollution caused by nitrogen leaching. To explore reasonable nitrogen application strategies for synergistically enhancing alfalfa production and ecological benefits, this study calibrated and validated the APSIM–Lucerne model based on field experiments conducted from 2021 to 2023. The effects of nitrogen application levels of 0, 80, 120, 140, 160, 180, 200, and 240 kg/ha on alfalfa yield, soil NO₃⁻–N and NH₄⁺–N residues, and nitrogen use efficiency under dry, normal, and wet years were simulated. The results indicate: (1) The calibrated APSIM–Lucerne model effectively simulates alfalfa yield and soil nitrogen residuals (R² ranging from 0.67 to 0.91, NRMSE between 6.55% and 24.03%). (2) Increased nitrogen application significantly elevates soil nitrogen residue, yet alfalfa yield follows a pattern of initial increase followed by decline, with nitrogen fertilizer use efficiency continuously decreasing. Under identical nitrogen application rates, the wet year type proves more advantageous for achieving high yields, low nitrogen residue, and high nitrogen fertilizer use efficiency. (3) The nitrogen application thresholds for achieving increased alfalfa yields and high efficiency during dry years, normal years, and wet years are 107–140 kg/ha, 135–160 kg/ha, and 150–183 kg/ha, respectively. Full article

(This article belongs to the Special Issue Water and Nitrogen Management in Soil–Crop Systems—4th Edition)

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