European Journal of Agronomy最新文献

{"title":"Evaluating peat pasture performance under elevated groundwater conditions","authors":"Hilde M. van Dijk ,&nbsp;Nyncke J. Hoekstra ,&nbsp;Raimon Ripoll-Bosch ,&nbsp;Idse Hoving ,&nbsp;Jeroen Pijlman ,&nbsp;Nick van Eekeren","doi":"10.1016/j.eja.2025.127961","DOIUrl":"10.1016/j.eja.2025.127961","url":null,"abstract":"<div><div>Historically, Dutch peatlands have been drained for agriculture, particularly as pastures for dairy production. While drainage increases productivity, it degrades the peat layer, leading to high greenhouse gas emissions and soil subsidence. Raising the depth of the groundwater table (WT) to 20 cm below field level, contrasted to commonly drained peat at approximately 50 cm below field level, is considered an effective solution to limit peat degradation. However, it is unclear how raising the WT with an active water infiltration system (AWIS) would affect grass yield and quality, and whether dairy farming can be maintained. We studied the effect of raising WT on grass production, quality, and nitrogen utilization, using experimental plots with different WT and fertilization levels in 2020–2024. Raising WT from 50 to 20 cm below field level resulted in an average decrease of 9 % in herbage dry matter yield (DMY), with significant variation between years due to varying weather conditions. The reduction in DMY could partly be explained by the observed decrease in soil N supply in wetter conditions, due to a lower mineralization rate. Increased N fertilization could mediate the lower DMY but increases nutrient losses. Herbage crude protein concentration was moderately affected by WT, and more strongly by yearly variation. Although results are on plot level, which excludes losses originating from trafficking by machinery and animals, they indicate that raising WT is compatible with relatively high grass production and similar grass quality. Consequences on farm level need to be further explored.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127961"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a crop yield prediction framework accounting for regional heterogeneity: A case study of spring maize in Jilin Province","authors":"Jun Gao ,&nbsp;Daming Dong ,&nbsp;Wenjiang Huang ,&nbsp;Yingying Dong ,&nbsp;Tongren Xu ,&nbsp;Chongya Jiang ,&nbsp;Kun Wang","doi":"10.1016/j.eja.2025.127977","DOIUrl":"10.1016/j.eja.2025.127977","url":null,"abstract":"<div><div>Accurate and timely crop-yield prediction is essential for ensuring food security, managing agricultural risk, and supporting policy formulation. To address the respective limitations of traditional crop growth models and deep learning methods under complex environmental conditions, a hybrid modeling framework is proposed that integrates remote-sensing data assimilation, a process-based crop growth model, and deep learning techniques. Using spring maize in Jilin Province, China (2015–2020) as the case study, leaf area index (LAI) retrieval accuracy is first improved by coupling the PROSAIL model with machine-learning algorithms. A complete meteorological sequence for the target year is then constructed using a dynamic time warping (DTW) algorithm to overcome early-season prediction challenges caused by missing real-time weather data. Retrieved LAI is assimilated into the WOFOST crop growth model through an ensemble Kalman filter (ENKF) to calibrate state variables and enable dynamic yield prediction across growth stages. Finally, a deep learning model (Convolutional Neural Network–Attention Long Short-Term Memory with Multi-Task Learning, CNN-ALSTM-MTL) is developed to fuse assimilation outputs with multi-source heterogeneous data, leveraging multi-task learning to enhance adaptability to regional heterogeneity and improve yield prediction performance at the regional scale. Assimilation is found to substantially improve maize-yield estimation, increasing R² by 0.2 and reducing RMSE by 276 kg ha⁻¹. Compared with the assimilated crop growth model alone, the hybrid framework further increases R² by 35 % and decreases RMSE by 23 % by hierarchically capturing feature information relevant to maize-yield estimation. The best performance is achieved during the key growth stage (jointing to tasseling stage), with an R² of 0.75 and an RMSE of 592 kg ha⁻¹, enabling reliable yield prediction approximately two months before harvest. This framework demonstrates potential for cross-crop and cross-regional applications and provides robust methodological support for regional-scale yield forecasting and food-security early warning.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127977"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From soil stress to sustainable solutions: A bibliometric and systematic review of plant growth promoting rhizobacteria in climate-resilient agriculture","authors":"Deepak Kumar ,&nbsp;Meenakshi Suhag ,&nbsp;Deepak Malik","doi":"10.1016/j.eja.2025.127972","DOIUrl":"10.1016/j.eja.2025.127972","url":null,"abstract":"<div><div>Due to the change of climate conditions and excessive use of xenobiotic compounds, soil fertility is compromised, which ultimately affects the plant-soil interaction, resulting in nutrient imbalances, reduced photosynthesis, decreased plant height and other metabolic disruptions. Plant Growth Promoting Rhizobacteria (PGPR) inoculants are considered one of the solutions for sustainable farming techniques that enhance crop productivity while conserving the ecosystem. This work uses bibliometric and systematic literature review methodologies to examine the recent interest in the scientific communities for mitigating environmental stresses. By evaluating 284 articles in the Web of Science (WoS) database from 2015 to 2024. Keywords co-occurrence analysis revealed that PGPRs enhance plant growth by improving nutrient uptake, increasing stress tolerance, producing phytohormones, activating key stress-tolerance genes, and facilitating phytoremediation and metal detoxification. The study analysis depicts a growing shift towards sustainable farming techniques that enhance crop productivity while conserving the ecosystem by using PGPR-based inoculants, as compared to synthetic fertilizers and pesticides. PGPR enhances plant growth through direct and indirect mechanisms, which are elaborated upon in this work. The positive role of PGPR on plant growth development and yield is also highlighted. Challenges and limitations of PGPR in agriculture are also discussed. There is a growing shift toward multi-strain consortia that offer broader and more stable benefits compared to single isolates. Advances in omics technologies are enabling a deeper understanding of PGPR plant-soil interactions and guiding the selection of highly efficient strains. Researchers are also emphasizing improved inoculant formulations, including encapsulation and biofilm/EPS-based approaches for better root colonization and field performance. Further research work in the area of PGPR-based products will be essential for maximizing their effectiveness in diverse farming environments for sustainable farming in the future.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127972"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling organ dynamics, biomass and N partition of winter wheat under different water supply for trait evaluation","authors":"Yang Lu ,&nbsp;Zhigan Zhao ,&nbsp;Hamish Brown ,&nbsp;Dengpan Xiao ,&nbsp;Xiying Zhang ,&nbsp;Enli Wang","doi":"10.1016/j.eja.2025.127953","DOIUrl":"10.1016/j.eja.2025.127953","url":null,"abstract":"<div><div>Crop models are vital for trait assessment and breeding, yet most lack mechanistic detail in carbon and nutrient partition and its effects on growth and yield. The generic organ arbitrator for biomass partitioning recently was developed, but it has NOT been widely validated apart from the initial testing. The study aimed to assess the organ arbitrator for simulating leaf and tiller numbers, leaf size and leaf area, biomass and nitrogen (N) partition into different organs, and the distributions of root length, root biomass and N in soil profile. We conducted the field experiment with two cultivars of winter wheat under three irrigation treatments in water-limited areas of the North China Plain from 2016 to 2018. The monitoring metrics were employed to assess the performance of APSIM next generation Wheat model (APSIM NG). The findings revealed that original APSIM NG overestimated tiller numbers, leaf area index (LAI), shoot and root biomass and nitrogen (N), but underestimated grain yield, with the Nash Sutcliffe Efficiency (NSE) ranging from <strong>-</strong>12.26–0.92. Modification to leaf, root growth parameters and temperature response curves of thermal time led to improved simulation of the development and growth of winter wheat. The simulation for individual leaf size was optimal (coefficient of determination (R²) = 0.95, NSE = 0.81). Similarly, the simulations for tiller density (except at the recovery stage) and for LAI from recovery to jointing also performed best, with Root Mean Square Error (RMSE) values of 302.91 tillers/m² and 1.83 m²/m², respectively. The biomass in above-ground, stems, grains of winter wheat under different water treatments, providing further confidence for the model to be used for trait evaluations (RMSE ranging from 38.04 to 123.85 g/m², NSE ranging from 0.83 to 0.96). However, the modified model tended to overestimate partitioning to leaves and underestimate that to stems and spikes. In addition, the modifications also overestimated crop N uptake (with RMSE values of 11.09, 10.16, and 1.36 g/m² for the N content in above-ground biomass, leaves, and spikes, respectively). The simulation of root biomass and N and their distributions in the soil profile was good, except for the underestimation of root biomass, length and N in the top soil layer. The study highlights the potential value of improved APSIM NG model to target phenotype, offering potential targets for genotype selecting in water-limited conditions. Further improvement in the model components in N uptake and root growth in the top soil layer is still required for the APSIM NG.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127953"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling mustard water use and its effects on soil water content and subsequent maize performance under projected climate scenarios","authors":"Uzair Ahmad ,&nbsp;Xuejun Dong ,&nbsp;Shah Jahan Leghari ,&nbsp;Gerrit Hoogenboom","doi":"10.1016/j.eja.2025.127971","DOIUrl":"10.1016/j.eja.2025.127971","url":null,"abstract":"<div><div>Mustard (<em>Brassica spp</em>.) grown as a cover crop retains root-zone soil water; however, if terminated late, it may lead to excessive water uptake. We calibrated and evaluated the decision support system for agrotechnology transfer (DSSAT) using field data from 2019 to 20 to simulate soil water content (SWC), leaf area index (LAI), aboveground biomass (AGB), and grain yield for maize (<em>Zea mays</em> L.) in southwest Texas. We applied DSSAT with climate projections from seven global climate models (GCMs) to assess soil water dynamics and crop responses under projected climate scenarios. The model accurately calibrated and evaluated LAI for maize (RMSE = 0.28) and mustard (RMSE = 1.42), and AGB for maize (RMSE = 1092.51 kg ha⁻¹) and mustard (RMSE = 772.54 kg ha⁻¹). Simulated SWC matched observed values in 2019 and closely followed field observations at 10 cm depth in 2020, confirming the model's sensitivity to root-zone moisture dynamics. Future climate impacts were assessed using Seasonal Analysis tool with bias-corrected projections from seven GCMs under RCP 4.5 and RCP 8.5. Results showed that maize yield is projected to peak in 2050 under RCP 4.5 and declined under RCP 8.5. Mustard cover cropping improved SWC (0.29 m³ m⁻³) and subsequently maize yield under moderate to high rainfall scenarios, but had neutral effects under drier conditions (SWC as 0.13 m³ m⁻³). It is critical to maintain SWC above 0.27 m³ m⁻³ for maize yield stability in this region. Maize irrigation demand is projected to increase 20 % by 2100. Sensitivity analysis showed that maize yield is strongly influenced by genetic parameters such as P1, P5, and G2 that regulate phenology and grain filling duration. Our study recommends targeted irrigation at flowering and physiological maturity in maize to optimize WUE, while demonstrating that projected warming and altered rainfall patterns are expected to intensify soil moisture deficits in mustard–maize rotation.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127971"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Legume-cereal mixed culture as green manure enhanced the yield stability of baby Chinese cabbage via disease suppressing","authors":"Zhilong Fan ,&nbsp;Yunyou Nan ,&nbsp;Wen Yin ,&nbsp;Falong Hu ,&nbsp;Cai Zhao ,&nbsp;Hong Fan ,&nbsp;Xiaohua Yan ,&nbsp;Weidong Cao ,&nbsp;Qiang Chai","doi":"10.1016/j.eja.2025.127956","DOIUrl":"10.1016/j.eja.2025.127956","url":null,"abstract":"<div><div>Global agriculture must enhance productivity while mitigating environmental degradation, particularly in intensive vegetable systems vulnerable to soil-borne diseases and nutrient imbalances. A seven-year field study (2018–2024) in Northwest China’s arid irrigation region was conducted to investigate the efficacy of legume-cereal green manure mixed cultures in suppressing the soft rot and the tipburn in baby Chinese cabbage (<em>Brassica rapa</em> subsp. <em>Pekinensis</em> cv. ‘Wawacai’), while improving soil health and yield stability. Six green manure regimes—common vetch (<em>Vicia sativa</em> L.) (CV), hairy vetch (<em>Vicia vilosa</em> Roth.) (HV), barley (<em>Hordeum vulgare</em> L.) (BL), and their mixed cultures (CV×BL, CV×HV, HV×BL)—were evaluated against post-harvest fallow (CF) in a randomized block design. The CV×BL emerged as the most effective intervention, significantly reducing the incidence rate by 20.7–72.4 % for soft rot and by 27.5–80.2 % for tipburn compared to CF, outperforming monocultures and other mixed cultures. Structural equation modeling revealed that yield stability was not only due to direct growth promotion from improved soil properties, but was substantially driven by the effective suppression of soft rot and tipburn. Consequently, CV×BL significantly increased yield by 22.4 % and improved yield stability by 3.6-fold relative to CF. These findings establish legume-cereal mixtures as sustainable alternatives to chemical-intensive practices, effectively addressing soil degradation and disease pressure in arid intensive systems. The common vetch and barley mixed culture as green manure specifically offers a scalable solution for reconciling productivity and sustainability in vegetable production through its dual capacity for disease suppression and yield stabilization.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127956"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Film-mulched drip irrigation in the main potato production areas of Northern China: Assessing future yield, greenhouse gas emissions and drivers under climate change","authors":"Qiaoling Liu ,&nbsp;Jianyu Zhao ,&nbsp;Fengxin Wang ,&nbsp;Kaijing Yang ,&nbsp;Jialu Dai ,&nbsp;Bin Yang","doi":"10.1016/j.eja.2025.127924","DOIUrl":"10.1016/j.eja.2025.127924","url":null,"abstract":"<div><div>Climate change threatens global agriculture through extreme weather and shifting growing conditions. Potatoes, a critical staple crop, face challenges like heat stress and water scarcity. Optimising agronomic practices, such as drip irrigation and film mulching, is critical to achieving climate-smart potato production and ensuring food security. During 2021–2100, the DeNitrification-DeComposition (DNDC) model and the Multiscale Geographically Weighted Regression (MGWR) model were comprehensively used to assess the effects of drip irrigation with and without film mulching on potato yield and global warming potential (GWP) under different future climate scenarios in the main potato producing areas of northern China. The results indicated that the DNDC model could effectively predict potato growth and emissions of nitrous oxide and methane (adjusted R² &gt; 0.81, normalized root mean square error &lt; 0.20). Compared to without film mulching (NM), the aboveground biomass and tuber yield were increased under drip irrigation with film mulch (TM), with the mean annual tuber yield of potatoes being 6.2 %-7.4 % higher under multiple emission scenarios. The GWP of TM increased by 1.1–1.4 times, and the net GWP offset decreased by 9.4 %-16.3 %. The MGWR analysis showed that precipitation had a significant positive effect on tuber yield in Inner Mongolia, Gansu and Ningxia, while temperature was the main negative influence on yield in Shaanxi. The main drivers of GWP were temperature and precipitation, with significant differences between regions. The findings provide a scientific basis for developing management strategies to adapt to and mitigate the effects of climate change on potato production, emphasizing the need to strike a balance between increasing yields and reducing greenhouse gas emissions.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127924"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the regional dynamics of straw mulching and incorporation on crop yields in Northeast China","authors":"Ying Song ,&nbsp;Zhijie Li ,&nbsp;Xiaoling He ,&nbsp;Jiaqiong Zhang ,&nbsp;Jinxia Fu ,&nbsp;Fenli Zheng ,&nbsp;Zhi Li","doi":"10.1016/j.eja.2025.127943","DOIUrl":"10.1016/j.eja.2025.127943","url":null,"abstract":"<div><div>Selecting an appropriate straw return method is crucial for enhancing crop productivity and promoting sustainable agriculture in the black soil region of Northeast China. However, few studies have evaluated the effectiveness of different straw return methods on crop yield, and their regional applicability has not yet been established. This study integrates machine learning approaches and meta-analysis to assess the impact of straw mulch (SM) and straw incorporation (SI) on crop yields under varying climate, soils, and agricultural management conditions in Northeast China’s drylands. Straw return overall increases crop yield by ∼5 %, among which SM and SI have similar mean contributions to yield improvements (5 % vs 4 %). The effects of two straw return methods vary with environmental conditions; specifically, SM outperforms SI under low temperatures (mean annual temperature MAT &lt;6 ℃), drought (mean annual precipitation MAP &lt;600 mm), and moderate erosion (mean annual soil erosion ASE 0.5–2 t/ha), but SI has better effects with high temperatures (MAT &gt;6 ℃), high precipitation (MAP &gt;600 mm), and severe erosion (ASE &gt;2 t/ha). SM achieves the highest yield benefit (8 %) under moderate straw return amounts (6000–10,000 kg/ha), whereas SI performs the best (6 %) at low straw return amounts (&lt; 6000 kg/ha). Furthermore, the yield-enhancing effects of both methods intensifies with increasing experimental duration, with SI's effect gradually and consistently surpassing that of SM. Spatial prediction results reveal that the overall extent of yield increase for SI is 9 %, with higher increasing yield potential observed in the southwest and southeast regions, while the extent of yield increase for SM is lower, at only 3 %. This study elucidates the differentiated yield-enhancing effects of different straw return methods in the black soil region, providing a scientific basis for precision agricultural management and sustainable utilization of black soil in Northeast China and other similar regions.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127943"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On-farm fertilization experiment on small-scale cocoa farms in Côte d′Ivoire: Evaluation of poultry litter compost for sustainable yield and profitability","authors":"Sibylle Lustenberger ,&nbsp;Bassirou Bonfoh ,&nbsp;Bognan Valentin Koné ,&nbsp;Johan Six ,&nbsp;Günther Fink","doi":"10.1016/j.eja.2025.127878","DOIUrl":"10.1016/j.eja.2025.127878","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Context&lt;/h3&gt;&lt;div&gt;In Côte d’Ivoire, cocoa is primarily produced on small-scale monoculture plantations as the main source of income for much of the rural population. Fertilization of cocoa farms remains uncommon, and long-term production without fertilization contributes to soil degradation. The ongoing decrease in productivity on small-scale cocoa farms undermines producers’ livelihoods and aggravates poverty. Poultry litter compost from the emerging poultry industry bares potential as a sustainable alternative to mineral fertilizers, but its effectiveness and profitability for cocoa production remain unknown.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Objective&lt;/h3&gt;&lt;div&gt;Our study aimed to compare productivity and profitability effects of mineral-, compost-, and mixed fertilizers on a representative sample of established small-scale, age-diverse cocoa fields.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;Our randomized controlled on-farm experiment included 120 farmers’ cocoa fields in central Côte d’Ivoire to assess productivity and profitability of three fertilizer options over one production cycle: Organic- (composted poultry litter, 71 kg N ha&lt;sup&gt;−1&lt;/sup&gt;y&lt;sup&gt;−1&lt;/sup&gt;), mineral- (marketed NPK+, 15 kg N ha&lt;sup&gt;−1&lt;/sup&gt;y&lt;sup&gt;−1&lt;/sup&gt;), and 50:50 combined organic and mineral fertilization (43 kg N ha&lt;sup&gt;−1&lt;/sup&gt;y&lt;sup&gt;−1&lt;/sup&gt;). Experimental plots comprised three cocoa trees per treatment and trees were fertilized twice before trees’ main harvest yields were measured. We estimated bean dry weights, annual yields and financial incomes per hectare. Treatment differences in yield and market value per hectare were tested using linear mixed-effects models, and report value-to-cost ratio (VCR = additional cocoa market value divided by total fertilization cost) of treatments’ projected annual harvests. We predicted compost fertilization VCR under both low-end and high-end price scenarios to account for regional variation in commercialization of poultry litter sale and resulting price variance.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results and conclusions&lt;/h3&gt;&lt;div&gt;Organic fertilization led to the highest increase of main harvest productivity (+ 190 kg dryweight per ha (dw), 38 %) followed by mixed fertilization (+ 145 kg ha&lt;sup&gt;−1&lt;/sup&gt; dw, 31 %) and mineral fertilization (+ 118 kg ha&lt;sup&gt;−1&lt;/sup&gt; dw, 22 %). Organic fertilization showed a high positive return on investment (VCR&lt;sub&gt;l&lt;/sub&gt; = 3.08, CI = 1.94, 4.22) in the low cost scenario of USD 104 ha&lt;sup&gt;−1&lt;/sup&gt; y&lt;sup&gt;−1&lt;/sup&gt;, but not when high costs were assumed (VCR&lt;sub&gt;h&lt;/sub&gt; = 0.94, CI = 0.59, 1.29, USD 342 ha&lt;sup&gt;−1&lt;/sup&gt; y&lt;sup&gt;−1&lt;/sup&gt;). The value-to-cost ratio was below one for both the mixed (VCR&lt;sub&gt;l&lt;/sub&gt; = 0.88, CI = 0.47, 1.29, USD 290 and VCR&lt;sub&gt;h&lt;/sub&gt; = 0.62, CI = 0.33, 0.91, USD 409 ha&lt;sup&gt;−1&lt;/sup&gt; y&lt;sup&gt;−1&lt;/sup&gt;) and the mineral fertilizer (VCR = 0.26, CI = 0.01, 0.51, USD 460 ha&lt;sup&gt;−1&lt;/sup&gt; y&lt;sup&gt;−1&lt;/sup&gt;).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Significance&lt;/h3&gt;&lt;div&gt;This study provides first experimental evidence of the effectiveness","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127878"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agronomic and physiological responses of mature ‘Rojo Brillante’ persimmon grafted onto Diospyros lotus and Diospyros virginiana under spring-regulated deficit irrigation in Mediterranean conditions","authors":"Armand Román ,&nbsp;Pablo González-Altozano ,&nbsp;Pau Martí ,&nbsp;Luis Bonet ,&nbsp;María Amparo Martínez-Gimeno ,&nbsp;Eduardo Badal","doi":"10.1016/j.eja.2025.127947","DOIUrl":"10.1016/j.eja.2025.127947","url":null,"abstract":"<div><div>This study assessed the effects of spring-regulated deficit irrigation (RDI) strategies on the physiological and agronomic performance of a ‘Rojo Brillante’ persimmon (<em>Diospyros kaki</em>) orchard grafted onto <em>Diospyros lotus</em> and <em>D. virginiana</em> rootstocks. The trial was conducted from 2016 to 2019 in a commercial orchard located in Llíria (Valencia, Spain), under Mediterranean climate conditions. RDI was applied during late spring at increasing water restriction levels, while control treatments received non-limited irrigation. Results showed that RDI did not reduce yield per tree, even under severe water deficits, and consistently improved irrigation water productivity by up to 21 % in <em>D. lotus</em> and 31 % in <em>D. virginiana</em> compared to fully irrigated controls. The reduction in fruit drop observed in RDI treatments led to a 30 % increase in harvested fruits in <em>D. lotus</em> and 42 % in <em>D. virginiana</em>. On average, fruit drop-to-flowering ratios were lower under RDI (36.5 % in <em>D. lotus</em>, 68.6 % in <em>D. virginiana</em>) than in fully irrigated controls (49.9 % and 81.6 %, respectively). <em>D. lotus</em> trees showed more stable yields and a favourable vegetative-reproductive balance, while <em>D. virginiana</em> exhibited a different water stress response pattern in the seasonal dynamics of stem water potential, which is used to characterise differences in plant water status rather than intrinsic drought tolerance. Still, <em>D. virginiana</em> trees produced lower and more variable yields under both irrigation regimes, likely due to higher fruit drop and a potential biennial bearing pattern. Overall, the findings support spring RDI as a viable strategy to enhance irrigation water productivity in persimmon orchards.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127947"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}