European Journal of Agronomy最新文献

{"title":"Re-evaluating onion varieties in organic farming: Evidence from a decade of multi-environment trials","authors":"M.L. Romo-Pérez,&nbsp;A. Rekowski,&nbsp;C. Zörb","doi":"10.1016/j.eja.2025.127969","DOIUrl":"10.1016/j.eja.2025.127969","url":null,"abstract":"<div><div>Onion landraces and traditional open-pollinated varieties are gaining renewed interest in organic farming due to their potential for regional adaptation, on-farm seed use, and distinct flavor profiles. However, comprehensive long-term field-based evaluations of their agronomic and quality traits remain scarce. This study assessed the agronomic performance, compositional quality, and environmental responsiveness of traditional open-pollinated onion varieties grown under certified organic conditions across diverse environments in Germany. Between 2014 and 2024, 19 field trials were conducted at seven research and on-farm locations. Three open-pollinated varieties, including one landrace, were evaluated alongside commercial references. Yield, quality traits, and environmental interactions were analyzed using meta-analyses, linear mixed-effects models (including site-year as a random effect), and principal component analysis. The landrace Birnenförmige (Bif) and the traditional open-pollinated variety Stunova (Stu) generally matched or approached the performance of commercial varieties. Birnenförmige showed the most consistent and statistically robust advantages in compositional traits, combining early maturity with high dry matter, sugar, and pyruvate levels. In contrast, Stunova—tested only at research stations—showed positive but more variable responses, with high fructan concentrations and favorable yield trends in early trial years. By comparison, the traditional open-pollinated variety Rijnsburger 4 (Rij) showed increased sensitivity to humid conditions, with reduced marketable yield and quality. Relative humidity negatively affected dry matter and sugar accumulation but tended to increase pyruvate levels, particularly in Stu. These findings underscore the importance of variety selection tailored to environmental conditions and organic production goals. Traditional open-pollinated onion varieties can contribute to the diversification and resilience of organic farming systems. Their distinct compositional profiles and climatic responses offer valuable options for producers seeking alternatives to hybrids in the context of organic seed system development and climate adaptation.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127969"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823035","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":"Long-term fertilization reshapes stoichiometric networks driving shifts in microbial life history strategies across China’s croplands","authors":"Xiaodong Sun ,&nbsp;Andong Cai ,&nbsp;Chengjie Ren ,&nbsp;Shuohong Zhang ,&nbsp;Qiang Li ,&nbsp;Shutang Liu ,&nbsp;Shuiqing Zhang ,&nbsp;Huimin Zhang ,&nbsp;Yu Li ,&nbsp;Kailou Liu ,&nbsp;Minggang Xu","doi":"10.1016/j.eja.2025.127928","DOIUrl":"10.1016/j.eja.2025.127928","url":null,"abstract":"<div><div>The balance of carbon (C), nitrogen (N), and phosphorus (P) stoichiometry fundamentally regulates nutrient cycling and microbial metabolism in terrestrial ecosystems. However, the mechanisms through which long-term fertilization and climate jointly shape multidimensional stoichiometric networks and microbial life history strategies remain unclear. In this study, six long-term (27–44 years) fertilization experiments across a 17° latitudinal gradient in China were examined under three treatments: no fertilizer (CK), mineral fertilizer (CF), and mineral plus manure fertilizer (CFM). By integrating ecological stoichiometry with metagenomic approaches, this study assessed how fertilization and climate affect soil, resource, microbial, and enzyme stoichiometry, and how these stoichiometric shifts influence microbial life history strategies. Results showed that long-term fertilization altered stoichiometric patterns, strengthening network connectivity among soil, resource, microbial, and enzymatic stoichiometry. CFM reduced soil and microbial C:P and N:P ratios by 35–70 % and decreased DOC:Olsen-P and DON:Olsen-P by up to 95 %. These shifts restructured microbial life history strategies, promoting a transition from resource acquisition (A) to growth yield (Y) strategies, with Y strategists increasing to 45–56 % under fertilization. Moreover, available resource and microbial stoichiometry, particularly DOC:Olsen-P and DON:Olsen-P ratios, were the primary predictors of microbial strategies, linking stoichiometric balance to microbial energetic allocation. Fertilization and climate jointly regulated microbial life history strategies by alleviating C:P and N:P imbalances and promoting stoichiometric homeostasis. Overall, these findings establish a mechanistic framework connecting nutrient supply, stoichiometric regulation, and microbial adaptation, thereby providing theoretical guidance for optimizing fertilization practices and maintaining soil nutrient sustainability across climatic regions.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127928"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583818","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":"Process-based assessment of wheat yield gap in Mediterranean rainfed conditions: Cultivar, nutrient, and sowing optimization","authors":"Lahcen Ousayd ,&nbsp;El Houssaine Bouras ,&nbsp;Achraf Mamassi ,&nbsp;Abdelghani Chehbouni ,&nbsp;Victor Ongoma","doi":"10.1016/j.eja.2025.127967","DOIUrl":"10.1016/j.eja.2025.127967","url":null,"abstract":"<div><div>Wheat production in Morocco remains constrained by persistent yield gaps arising from climatic variability, soil fertility decline, and suboptimal farm management. This study aimed to quantify attainable and actual yields of bread wheat (<em>Triticum aestivum L.</em>) and to identify management pathways for reducing these gaps under rainfed conditions in Morocco. The Environmental Policy Integrated Climate (EPIC) model was calibrated and validated for five representative cultivars across major rainfed agroecological zones using multi-season field observations. Model evaluation showed high predictive accuracy for grain yield (R² = 0.87, RMSE = 0.25 t/ha, NRMSE = 12.5 %), above-ground biomass (R² = 0.93, RMSE = 1.2 t/ha, NRMSE = 8.7 %), and leaf area index (R² = 0.81, RMSE = 0.73, NRMSE = 15.2 %). Simulated potential yield (<span><math><msub><mrow><mi>Y</mi></mrow><mrow><mi>p</mi></mrow></msub></math></span>) averaged 5.4 t/ha, of which 66 % was attainable under water-limited rainfed conditions (<span><math><msub><mrow><mi>Y</mi></mrow><mrow><mi>w</mi></mrow></msub></math></span> = 3.6 t/ha) and 48 % was realized as observed farmer yield (<span><math><msub><mrow><mi>Y</mi></mrow><mrow><mi>a</mi></mrow></msub></math></span> = 2.6 t/ha), resulting in an exploitable yield gap of approximately 52 % (2.8 t/ha). Scenario analysis indicated yield gains of 25–35 % from improved nitrogen use and 30–40 % from supplemental irrigation, while integrated management closed 40–65 % of the exploitable gap and raised mean yields to 3.8–4.2 t/ha. Across management strategies, intermediate-input scenarios delivered strong economic performance, achieving marginal rate of return values of 257–433 % with modest additional costs (266–1389 MAD/ha). These findings demonstrate that targeted integration of water and nutrient management can substantially enhance wheat productivity and resilience, offering a practical framework for advancing sustainable intensification and national food self-sufficiency.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"174 ","pages":"Article 127967"},"PeriodicalIF":5.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883405","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":"Precision detection and geolocation of missed pre-tassels in hybrid maize seed production using UAV-based deep learning","authors":"Chenchen Ding ,&nbsp;Ruirui Zhang ,&nbsp;Jiangtao Qi ,&nbsp;Yuxin Xie ,&nbsp;Tongchuan Yi ,&nbsp;Longlong Li ,&nbsp;Mingqi Wu ,&nbsp;Weirong Zhang ,&nbsp;Zhiyuan Bao","doi":"10.1016/j.eja.2025.127923","DOIUrl":"10.1016/j.eja.2025.127923","url":null,"abstract":"<div><div>Hybrid maize seed production relies on detasseling, a critical process to ensure genetic purity by removing male pre-tassels from female plants. However, missed pre-tassels, which are immature tassels partially enclosed by leaves and similar in color to maize foliage, remain difficult to detect and typically require labor-intensive manual inspection. This study proposes an improved UAV-based detection framework, YOLO for Missed Pre-Tassel (YOLO-MPT), built upon YOLOv7 for precise identification and geolocation of missed pre-tassels in hybrid maize fields. YOLO-MPT integrates deformable convolutions (DCNv2) for adaptive feature extraction, the S²-MLPv2 attention mechanism for enhanced spatial representation, and an additional small-object detection head to increase sensitivity to tiny or occluded targets. A comprehensive UAV-derived pre-tassel dataset was constructed under diverse agronomic and lighting conditions to support model training and validation. The impact of input image size on detection performance was systematically analyzed to identify the optimal training resolution. Experimental results show that YOLO-MPT achieved an average precision (AP) of 93.8 %, precision (P) of 93.3 %, recall (R) of 90.2 %, and an F1-score of 91.7 %, outperforming baseline models. Furthermore, a geographic coordinate extraction method was developed and integrated into a standalone “Missed Pre-Tassel Detection and Localization Software,” enabling automatic conversion of pixel detections into precise geospatial locations. Field experiments verified the workflow’s robustness and positioning accuracy, demonstrating the system’s potential to improve post-detasseling efficiency and quality assurance in hybrid maize seed production.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127923"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553996","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":"Influence of fertilization, tillage, and residue management on soil organic carbon, total nitrogen, and soil pH in black soils of Northeast China","authors":"N’Dri Yves Bohoussou ,&nbsp;Guoxiang Zheng ,&nbsp;Shanbo Zhang ,&nbsp;Wenbo Wu ,&nbsp;Fengtao Ju ,&nbsp;Olouwatogni Michael Ayenikafo ,&nbsp;Stopira Yannick Benz Boboua ,&nbsp;Yash Pal Dang","doi":"10.1016/j.eja.2025.127911","DOIUrl":"10.1016/j.eja.2025.127911","url":null,"abstract":"<div><div>Black soils in Northeast China are among the most fertile soils and play a vital role in national food security. However, despite numerous field studies, there remains a lack of comprehensive synthesis on how agronomic practices, such as tillage, fertilization, and residue management, affect black soil. Thus, we conducted a meta-analysis of 802 comparisons from 80 peer-reviewed articles to determine how agronomic practices influence SOC, TN, and soil pH dynamics at 0–30 cm soil depth and their impact on crop yields. The analysis revealed that organic fertilizers significantly improved SOC and TN stock by 32.89 % and 29.74 %, respectively, while mixed fertilizers enhanced SOC (17.98 %) and TN (22.93 %) compared to unfertilized soils. Residue retention increased SOC and TN by 10.91 % and 11.13 %, respectively, compared to residue removal, while no-tillage increased TN by 10.88 % relative to conventional tillage. Soil pH declined significantly under chemical, mixed fertilizers, residue retention, and tillage. In contrast, organic fertilizer increased soil pH by 3.04 %, indicating its potential to buffer against soil acidification. Mixed fertilizers achieved the highest grain yield increase (77.17 %). Grain yield exhibited a negative relationship with soil pH, indicating the need to manage long-term acidification. Our findings highlight the importance of balanced agronomic practices, particularly organic fertilizer application, in improving TN, SOC stock, and crop yield while mitigating soil acidification risks. Implementing these practices is crucial for maintaining soil fertility and crop productivity of black soils in Northeast China.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127911"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145473186","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":"Amaranth: From Aztec tradition to climate-smart agriculture – Examining genetic resources, nutritional benefits, and resilience","authors":"S.S. Sonu ,&nbsp;Latha Rangan","doi":"10.1016/j.eja.2025.127892","DOIUrl":"10.1016/j.eja.2025.127892","url":null,"abstract":"<div><div>Pressing challenges of rising food demand, malnutrition, competition for essential resources (land, water and energy), changing climate, and unforeseen events such as pandemics, have heightened the urgency for resilient, nutritious and diversified crops. Amaranth, an ancient grain with roots in Aztec culture, comprising of approximately 60–70 species can be categorized as vegetable, grain, or wild types. Known for its remarkable nutritional profile – rich in protein, squalene, essential amino acids and unique phytochemicals – amaranth has re-emerged as a superfood. Its resilience to environmental stress, low care and availability of diverse genetic resources for breeding, makes it a promising candidate for addressing modern agricultural challenges. In this review, we explore into the diverse aspects of amaranth that positions it as a key player in tackling food security and agricultural issues. It explores the historical context and geographical distribution of grain amaranth, tracing its journey from a staple food in ancient diets to its reintroduction as a superfood. The major points include: 1) C4 efficiency and stress tolerance detailing mechanism along with anatomical and biochemical adaptations; 2) advances in genomics, including high-quality genome assemblies and plastome characterization crucial for understanding its evolutionary relationships and genetic diversity; 3) specific databases that facilitate access to genomic information and support population genetic analyses for crop improvement; and 4) potential as a functional food and its therapeutic benefits. Collectively, this review advocates for amaranth as a super crop with significant promise for enhancing global food security and promoting sustainable agricultural practices, while suggesting future avenues for research.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127892"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145384479","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":"Deciphering low nitrogen tolerance of wheat in mega-environments using integrated multivariate approaches","authors":"Gopalareddy Krishnappa ,&nbsp;Hanif Khan ,&nbsp;Amaresh ,&nbsp;Vinayaka ,&nbsp;T. Lakshmi Pathy ,&nbsp;Arun Gupta ,&nbsp;Anju Mahendru-Singh ,&nbsp;Arvind Kumar Ahlawat ,&nbsp;Jasavantlal Manilal Patel ,&nbsp;Suma S. Biradar ,&nbsp;Harohalli Masthigowda Mamrutha ,&nbsp;Rinki Khobra ,&nbsp;Vanita Pandey ,&nbsp;Gyanendra Pratap Singh ,&nbsp;Ratan Tiwari","doi":"10.1016/j.eja.2025.127919","DOIUrl":"10.1016/j.eja.2025.127919","url":null,"abstract":"<div><div>Enhancing low nitrogen (LN) tolerance is crucial for maintaining wheat productivity, particularly in the era of climate change and increasing input costs. This study aimed to identify high-yielding, LN-tolerant, and stable wheat genotypes using integrated multivariate approaches. Fifty diverse genotypes, including globally sourced germplasm and landmark Indian cultivars, were evaluated across three agro-climatic zones under two nitrogen regimes for two consecutive years. Pooled ANOVA revealed significant effects of genotype, nitrogen level, and genotype × environment interaction. Hierarchical clustering identified four clusters, with cluster I comprising high-yielding, nitrogen-efficient genotypes. For grain yield under nitrogen stress, NARBADA 4 was the only genotype with a BLUP based Z-score above + 2, indicating exceptional stability and yield potential. Based on the GGE’s Mean vs. Stability plot for grain yield, KRL 1–4 exhibited the highest mean performance coupled with stability. A novel metric, Gain<em>_d</em> (decadal gain index) was introduced to assess genetic gains for LN tolerance across decades. Decadal trend analysis showed non-linear gains in low-N tolerance, peaking in the 1970s and 2000s but declining in the 2010s. Comprehensive multivariate index analysis based on pooling the index ranks highlighted MACS 6222, NARBADA 4, MACS 2496, K 307, and HI 1544 as the most promising genotypes. These genotypes are promising for LN-specific breeding and genetic improvement programs, offering potential for both commercial cultivation and the mapping of nitrogen use efficiency traits. The findings pave the way for developing widely adapted LN-tolerant wheat cultivars.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127919"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579798","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":"Two decades of organic farming in rice-wheat agroecosystems: An impact assessment of environmental footprints reduction and carbon credit potential for climate resilience","authors":"Nilutpal Saikia ,&nbsp;Vijay Pooniya ,&nbsp;Anamika Barman ,&nbsp;Y.S. Shivay ,&nbsp;R.R. Zhiipao ,&nbsp;Dinesh Kumar ,&nbsp;S.K. Prajapati ,&nbsp;Niraj Biswakarma ,&nbsp;Arti Bhatia ,&nbsp;Santanu Kundu ,&nbsp;Kritanjal Goswami","doi":"10.1016/j.eja.2025.127915","DOIUrl":"10.1016/j.eja.2025.127915","url":null,"abstract":"<div><div>Organic farming is a sustainable agricultural approach that enhances soil health and reduces environmental pollution by avoiding synthetic inputs. We assessed the 23-year effects of co-applying organic amendments in the rice–wheat system (RWS) using a randomized block design. Treatments combined <em>Sesbania</em> green manure (SGM), <em>Leucaena</em> green leaf manure (GLM), blue-green algae (BGA), farmyard manure (FYM), and <em>Azotobacter chroococcum</em> culture (seed treatment), and were compared with the sole application of each amendment. The SBF-R (SGM + BGA + FYM to rice) followed by LAF-W (GLM + <em>Azotobacter</em> + FYM to wheat) treatment produced the highest rice-equivalent yield (REY) and net energy + 80 % and + 77 % over the control (no organic amendment nor chemical fertilizers), and + 9–15 (REY) and + 2–17 % (net energy) over sole-organic treatments. Water footprints were 8–14 % lower than sole-organic treatments under SBF-R fb LAF-W. Co-application treatments (including SBF-R fb LAF-W and SF-R fb LF-W) increased CH₄ and N₂O relative to other treatments; nevertheless, SBF-R fb LAF-W achieved the highest C-sequestration (at 0–45 cm depth) (3944 kg ha⁻¹) and thereby reducing net GHG emissions, C-footprint and improving carbon sustainability index (CSI), and carbon efficiency. Economically, SBF-R fb LAF-W delivered the highest returns + 8–15 % (gross) and + 10–12 % (net) versus sole-organic along with higher C-credits (1765 kg CO₂-eq ha⁻¹) and social value of CO₂-equivalent (US$ 39 ha⁻¹). Overall, co-application of complementary organic amendments outperformed sole applications, sustaining RWS by improving productivity, optimizing energy and water use, lowering the C-footprint, and increasing profitability.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127915"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520621","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":"Integration of artificial intelligence and remote sensing for crop yield prediction and crop growth parameter estimation in Mediterranean agroecosystems: Methodologies, emerging technologies, research gaps, and future directions","authors":"Wondimagegn Abebe Demissie,&nbsp;Luca Sebastiani,&nbsp;Rudy Rossetto","doi":"10.1016/j.eja.2025.127894","DOIUrl":"10.1016/j.eja.2025.127894","url":null,"abstract":"<div><h3>Context</h3><div>Crop yield prediction (CYP) along with crop growth parameter estimation (CGPE) recently gained prominence as essential means for optimizing agricultural resource use and addressing global food security challenges, particularly in regions with vulnerable climates and diverse agricultural systems, such as the Mediterranean one. Artificial intelligence (AI) and remote sensing (RS) play an important role in achieving such objectives.</div></div><div><h3>Objective</h3><div>To identify present methodologies and frameworks, emerging trends, research gaps and future directions in the integrated use of AI and RS in the Mediterranean area for CYP and CGPE.</div></div><div><h3>Methods</h3><div>We systematically reviewed the published scientific literature on the topic (106 studies) by means of the PRISMA methodology.</div></div><div><h3>Result and conclusions</h3><div>We found that integration of AI, particularly machine learning methods such as Random Forest, Support Vector Machine, and Artificial Neural Networks, along with satellite-based RS platforms such as Sentinel-2, Sentinel-1, MODIS, and Landsat-8, demonstrated strong potential to enhance monitoring and support adaptive agricultural decision-making. Deep learning models, such as Convolutional Neural Networks and Long Short Term Memories, are emerging tools for spatio-temporal modelling, although their use is limited, likely due to data and computational constraints. Wheat is the most frequently analyzed crop, alongside high-value perennial crops like olives and vineyards. Data acquisition relies predominantly on satellite imagery, though hybrid approaches incorporating unmanned aerial vehicle and ground-based data are promising in improving prediction accuracy. Despite these advancements, significant challenges persist, including uneven geographical research coverage, limited model transferability, and insufficient consideration of crop phenology. A critical lack of standardized validation datasets and the underrepresentation of North African and Middle Eastern countries further constrain progress.</div></div><div><h3>Significance</h3><div>To fully harness AI-RS integration for sustainable agriculture and food security in the Mediterranean area, and similar agroecosystems, future efforts should aim at i) prioritizing cross-regional collaboration, ii) focusing on hybrid AI-RS methods, iii) developing phenology-aware models, and iv) widening access to data.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127894"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404602","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":"The impact of HvAACT1 gene conferring aluminium toxicity tolerance on barley yield in acid soils","authors":"Ce Guo ,&nbsp;Sergey Shabala ,&nbsp;Ke Liu ,&nbsp;Meixue Zhou ,&nbsp;Chenchen Zhao","doi":"10.1016/j.eja.2025.127907","DOIUrl":"10.1016/j.eja.2025.127907","url":null,"abstract":"<div><div>Aluminium toxicity in acid soils is a major constraint to global crop production, particularly for cereal crops like barley, which are vital to food security. Although the <em>HvAACT1</em> gene within the <em>Alp</em> QTL has been recognized as a key factor in aluminium tolerance through citrate secretion, its direct impact on barley yield under dynamic, real-world acidic conditions remains poorly understood. Most existing studies have focused on fixed pH levels, limiting insights into crop performance across the broader pH spectrum typical of acidic field conditions. In this study, we evaluated barley yield and agronomic traits across eight soil pH levels (4.0–4.8), using two near-isogenic lines (NILs): RGT Planet (acid soil susceptible) and P33–1 (acid soil tolerant, introgressed with <em>Alp</em>). Our results demonstrate that P33–1 consistently outperformed RGT Planet, maintaining higher yield and better agronomic traits. Notably, yield reductions under acidic conditions were primarily driven by decreases in fertile tiller number and kernels per spike (P &lt; 0.01), rather than changes in grain size or 1000-kernel weight, providing new insights into the physiological basis underpinning yield loss. By quantifying the complex relationship between soil pH and agronomic trait losses, our study delivers essential data that will inform crop modeling and advance breeding efforts for acid soil-tolerant varieties, contributing to more resilient and sustainable crop production in marginal soils worldwide.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":"173 ","pages":"Article 127907"},"PeriodicalIF":5.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145441745","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}