European Journal of Agronomy最新文献

From UAV imagery to mapping: Detecting sunflower heads in fields using a novel lightweight deep learning network 从无人机图像到测绘：使用新型轻量级深度学习网络检测田间向日葵头

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-05-01 Epub Date: 2026-02-13 DOI: 10.1016/j.eja.2026.128018

Rui Jing , Qinglin Niu , Qingqing Zhao , Jingcui Shao , Zongpeng Li , Bowei Qi , Guize Chao , Yuanzhi Ma , Dongwei Li , Xinguo Zhou

Efficient and non-invasive field-scale detection and localization of sunflower heads (SHs), together with spatial distribution mapping, can support pre-harvest yield prediction, optimization of mechanical harvesting, field management, and high-throughput phenotyping. Unmanned aerial vehicle (UAV) imagery, with its low cost and high spatiotemporal resolution, makes such field-scale monitoring practically feasible. However, accurately detecting and mapping individual SHs from high-resolution UAV images remains challenging, especially under resource-constrained computing environments. To address this, we used UAV RGB imagery to construct a sunflower head detection dataset covering both flowering and maturity stages. Furthermore, a lightweight deep learning network, built upon YOLOv8n improvements, was proposed to enable efficient head detection and mapping. First, the DWCSP module is introduced, utilizing depthwise convolution and multi-branch feature fusion for feature extraction, thereby significantly reducing the network complexity. Additionally, a lightweight detection head integrating partial convolution was designed to further accelerate inference speed, and the WIoU loss function was adopted to enhance detection performance. Experimental results revealed that, when compared to the baseline, the computational complexity and parameters of the proposed model were reduced by 60.5 % and 49.5 %, respectively, with values reaching 3.2 GFLOPs and 1.52 M and a model size of only 3.1 MB. This model achieved an impressive 96.2 % [email protected]. When deployed on a CPU and the Jetson Orin Nano platform, inference speeds of 16 FPS and 67 FPS were attained, representing improvements of 33.3 % and 24.1 % over the baseline. Additionally, the model was employed to perform overlapping slice detection on UAV orthomosaic images from two sample fields, mapping individual SHs locations to geographic coordinates and generating spatial and density distribution maps of the heads. This produces an end-to-end workflow from UAV imagery to geospatial data, which provides an effective approach for pre-harvest yield estimation and analysis of agronomic variability in sunflowers, with the potential to reduce resource waste and labor demands, while providing cost-effective tools for breeding evaluation and decision-making.

向日葵籽粒的高效、无创田间检测和定位，以及向日葵籽粒的空间分布图谱，可为收获前产量预测、机械收获优化、田间管理和高通量表型分析提供支持。无人机（UAV）图像以其低成本和高时空分辨率，使这种野外规模的监测在现实中可行。然而，从高分辨率无人机图像中准确检测和绘制单个SHs仍然具有挑战性，特别是在资源受限的计算环境下。为了解决这个问题，我们使用无人机RGB图像构建了一个涵盖开花和成熟阶段的向日葵头部检测数据集。此外，提出了基于YOLOv8n改进的轻量级深度学习网络，以实现高效的头部检测和映射。首先，引入DWCSP模块，利用深度卷积和多分支特征融合进行特征提取，显著降低了网络复杂度；设计了轻量化的部分卷积检测头，进一步加快了推理速度，采用WIoU损失函数提高了检测性能。实验结果表明，与基线相比，该模型的计算复杂度和参数分别降低了60.5 %和49.5 %，分别达到3.2 GFLOPs和1.52 M，模型大小仅为3.1 MB。该模型达到了令人印象深刻的96.2 % [email protected]。当部署在CPU和Jetson Orin Nano平台上时，推理速度达到了16 FPS和67 FPS，比基线提高了33.3% %和24.1% %。此外，利用该模型对来自两个采样场的无人机正射影像进行重叠切片检测，将单个SHs位置映射到地理坐标，生成头部的空间和密度分布图。这产生了从无人机图像到地理空间数据的端到端工作流程，为向日葵收获前产量估算和农艺变异分析提供了有效方法，有可能减少资源浪费和劳动力需求，同时为育种评估和决策提供具有成本效益的工具。

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引用次数: 0

Artificial intelligence for pest identification and decision support in sustainable crop protection: A critical review 人工智能在可持续作物保护中的害虫识别和决策支持：综述

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-05-01 Epub Date: 2026-02-13 DOI: 10.1016/j.eja.2026.128040

Azam Amiri , Ali R. Bandani

Plant pest and disease management is a critical pillar of global food security because insect pests and pathogens significantly reduce crop yield and quality. Integrating artificial intelligence (AI) into pest management is an emerging frontier that can transform how crop protection decisions are made and implemented in the field. Here, we consider AI as an umbrella covering machine learning and deep learning, which learn patterns from data to support prediction and classification. This review synthesizes recent AI-based approaches for field-relevant identification and decision support in sustainable crop protection, with an emphasis on image-based diagnostics and their integration into operational Integrated Pest Management (IPM). AI can complement manual scouting and broad-spectrum pesticide use, which are increasingly constrained by resistance evolution, non-target impacts, regulatory pressure, and labor demands. Beyond describing tools, we critically map how AI-enabled sensing and inference (e.g., automated identification, counting, forecasting, and uncertainty/explainability) become decision-relevant outputs that can be linked to action/economic thresholds and embedded in decision-support systems (DSS) under real field variability. Key limitations include biased and geographically concentrated datasets, difficulty separating pests from beneficials or morphologically similar taxa, weak transferability under real field conditions, and barriers related to interpretability, infrastructure, and adoption in low-resource settings. By organizing the evidence around an end-to-end operational IPM workflow (moving from monitoring to pest pressure indicators, thresholds to DSS recommendations, and interventions to feedback and field validation), this review clarifies where AI adds actionable value and what must be validated to deliver robust, context-appropriate tools for sustainable crop protection.

植物病虫害管理是全球粮食安全的重要支柱，因为病虫害和病原体会严重降低作物产量和质量。将人工智能（AI）整合到害虫管理中是一个新兴的前沿领域，可以改变作物保护决策在田间的制定和实施方式。在这里，我们将人工智能视为涵盖机器学习和深度学习的保护伞，后者从数据中学习模式以支持预测和分类。本综述综合了最近基于人工智能的方法，用于可持续作物保护领域相关的识别和决策支持，重点是基于图像的诊断及其与可操作的病虫害综合治理（IPM）的整合。人工智能可以补充人工侦察和广谱农药使用，这两种方法越来越受到耐药性进化、非靶标影响、监管压力和劳动力需求的限制。除了描述工具之外，我们还批判性地描绘了人工智能感知和推理（例如，自动识别、计数、预测和不确定性/可解释性）如何成为与决策相关的输出，这些输出可以与行动/经济阈值相关联，并在实际现场可变性下嵌入决策支持系统（DSS）。主要的限制包括有偏见和地理上集中的数据集，难以将有害生物与有益生物或形态相似的分类群区分开来，在实际野外条件下的弱可转移性，以及与可解释性、基础设施和在低资源环境中采用相关的障碍。通过围绕端到端可操作的IPM工作流程组织证据（从监测到害虫压力指标，从阈值到DSS建议，从干预到反馈和现场验证），本综述阐明了人工智能在哪些方面增加了可操作价值，以及必须验证哪些内容才能为可持续作物保护提供强大的、适合具体情况的工具。

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引用次数: 0

Deep fertilization effects on potato production and GHG emissions depend on soil C:N:P-enzyme interactions: Evidence from a 4-year study 深度施肥对马铃薯生产和温室气体排放的影响取决于土壤C:N: p酶的相互作用：来自一项为期4年的研究的证据

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-01-13 DOI: 10.1016/j.eja.2026.128001

Zhaoyang Li , Nan Shi , Yixuan Yuan , Haiyang Chang , Yuling Meng , Weixing Shan , Moskvicheva Elena , Ansabayeva Assiya , Zhikuan Jia , Xiaolong Ren , Kadambot H.M. Siddique , Ruixia Ding , Peng Wu , Huaze Li , Jiangang Liu , Peng Zhang

Context and problem

As potato is one of the four major food crops, enhancing yield is crucial, particularly when considering the mitigation of environmental impacts. Deep fertilization represents a potential strategy for efficient nutrient utilization; however, its specific on potato yield, quality and greenhouse gas emissions require further elucidation.

Methods

We conducted a four-year field experiment (2020–2023) using potatoes as the test crop. We investigated the impacts of four fertilization depths (D5, 5 cm, control with locally conventional fertilization depth; D15, 15 cm; D25, 25 cm; D35, 35 cm) on soil C, N, and P content and ratios, enzyme activity, greenhouse gas emissions, potato growth, yield, and quality.

Results

Deep fertilization significantly increased the soil SOC:TN, SOC:TP, MBC:MBN, and SIC:SIN ratios, while decreasing the MBC:MBP, MBN:MBP, and POC:PON ratios. In addition to soil catalase, the activities of invertase, urease and phosphatase were closely related to the soil C:N:P ratio. Specifically, deep fertilization increased soil invertase and phosphatase activities but decreased catalase and urease activities. Correlation analysis showed that N₂O and CO₂ emissions were positively correlated with soil urease activity, whereas CH₄ uptake and CO₂ emissions were negatively correlated with soil phosphatase and sucrase activities, respectively. Furthermore, increase of soil phosphatase activity enhanced the leaf area index, net photosynthetic rate, and dry matter accumulation of potato while reducing stem lodging, ultimately improving yield and quality. Among these treatments, D25 achieved the highest improvements in large potato rate (16.4 %) and yield (11.5 %), while simultaneously resulting in high tuber quality in starch (42.5 %), reducing sugar (52.7 %), protein (33.4 %), and vitamin C (31.9 %) content. In addition, its greenhouse gas emission intensity was also at the lowest level (decreased by 32.7 %).

Conclusions

Deep fertilization affects enzyme activity by altering soil C:N:P ratios, thereby promoting potato production and reducing greenhouse gas emissions. In this region, fertilization depths of 15–25 cm exhibited distinct advantage in terms of yield enhancement, whereas depths exceeding 35 cm were more effective in reducing emissions.

背景和问题马铃薯是四大粮食作物之一，提高产量至关重要，特别是在考虑减轻对环境的影响时。深层施肥是一种有效利用养分的潜在策略；然而，其对马铃薯产量、质量和温室气体排放的具体影响有待进一步阐明。方法以马铃薯为试验作物，进行为期4年（2020-2023年）的田间试验。研究了4种施肥深度（D5、5 cm，与当地常规施肥深度对照；D15、15 cm; D25、25 cm; D35、35 cm）对土壤C、N、P含量及比值、酶活性、温室气体排放、马铃薯生长、产量和品质的影响。结果深度施肥显著提高了土壤SOC:TN、SOC:TP、MBC:MBN和SIC:SIN比值，降低了MBC:MBP、MBN:MBP和POC:PON比值。除土壤过氧化氢酶外，转化酶、脲酶和磷酸酶活性与土壤C:N:P比密切相关。深层施肥提高了土壤转化酶和磷酸酶活性，降低了过氧化氢酶和脲酶活性。相关分析表明，N2O和CO2排放量与土壤脲酶活性呈正相关，CH4吸收和CO2排放量分别与土壤磷酸酶和蔗糖酶活性负相关。土壤磷酸酶活性的提高提高了马铃薯的叶面积指数、净光合速率和干物质积累，减少了茎秆倒伏，最终提高了产量和品质。在这些处理中，D25处理在大薯率（16.4 %）和产量（11.5 %）方面取得了最大的改善，同时在淀粉（42.5 %）、还原糖（52.7 %）、蛋白质（33.4 %）和维生素C（31.9 %）含量方面取得了较高的块茎品质。此外，其温室气体排放强度也处于最低水平（下降了32.7% %）。结论深度施肥通过改变土壤C:N:P比值影响酶活性，从而促进马铃薯生产，减少温室气体排放。在该区域，施肥深度为15 ~ 25 cm的增产效果明显，而施肥深度超过35 cm的减排效果更好。

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引用次数: 0

Reducing pesticide use through the adaptation of crop management strategies has little impact on farm economic performance 通过调整作物管理策略减少农药使用对农业经济绩效影响不大

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-02-12 DOI: 10.1016/j.eja.2026.128030

Nandillon Romain , Guinet Maé , Munier-Jolain Nicolas

Although necessary for environmental and human health reasons, pesticide use reduction has been limited, partly due to the perceived risk of lower farm economic performance in case of reduced pest control. Previous research, based on comparisons of farms with contrasted pesticide use, showed that low pesticide use is compatible with maintaining economic performances. However, these results may be suspected of being biased because the production context of the compared farms could differ slightly. Moreover, the economic feasibility to transition to farming systems with low pesticide input remains to be demonstrated on a large scale. We used a diachronic approach, monitoring over time 867 arable French farms classified into eight farm types according to their crop productions. Many farmers re-designed their cropping system during the monitoring period, and adopted measures reducing pest pressure, and therefore succeeded in reducing pesticide inputs. We studied the link between changes in pesticide use, driven by changes in pest management strategies, and two metrics of farm economic performance: gross product and gross margin, both expressed in euros per hectare. In all farm types, some farms were able to reduce pesticide use while maintaining economic performances. For most farms, no antagonism was found between pesticide use reduction and either gross margin or gross product. We bring additional evidence that farmers can reduce pesticide use without impacting these metrics of farm economic performances.

虽然出于环境和人类健康的原因，减少农药使用是必要的，但其效果有限，部分原因是人们认为，如果减少虫害防治，农业经济绩效可能会下降。先前的研究基于对不同农药使用的农场的比较，表明低农药使用与保持经济效益是相容的。然而，这些结果可能被怀疑是有偏差的，因为比较农场的生产环境可能略有不同。此外，向低农药投入农业系统过渡的经济可行性仍有待大规模论证。我们采用历时方法，长期监测867个法国耕地农场，根据其作物产量将其分为八种农场类型。在监测期间，许多农民重新设计了他们的种植制度，并采取了减少有害生物压力的措施，因此成功地减少了农药投入。我们研究了由病虫害管理策略变化驱动的农药使用变化与农业经济绩效的两个指标之间的联系：总产值和毛利率，两者都以每公顷欧元表示。在所有类型的农场中，一些农场能够在保持经济效益的同时减少农药的使用。对于大多数农场来说，减少农药使用与毛利或总产值之间没有拮抗作用。我们带来了额外的证据，证明农民可以在不影响这些农业经济绩效指标的情况下减少农药的使用。

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引用次数: 0

Layered nitrogen application drives changes in nitrogen nutrition status of wheat by affecting key soil microbial clusters 分层施氮通过影响土壤关键微生物群驱动小麦氮素营养状况的变化

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-01-20 DOI: 10.1016/j.eja.2026.128011

Yang Zhou, Pengjia Wu, Yanjie Qu, Shengyan Pang, Haimeng Mu, Min Yang, Xiang Lin, Dong Wang

Optimizing nitrogen (N) fertilizer management is essential for improving wheat yield and nitrogen use efficiency, yet the mechanisms by which layered N application regulates crop N nutrition through soil microbial processes across growth stages remain unclear. Here, we conducted a four-year field experiment to examine how layered N fertilization modulates soil microbial communities and nutrient dynamics to better match wheat N demand and enhance productivity. Treatments included conventional N application at 8 cm soil depth (N8), layered N application at 8, 16, and 24 cm in a 1:2:1 ratio (N1–2–1), and a no-N control (NCK). Layered N fertilization increased grain yield by 18.7 % and total N accumulation by 19.0 % compared with conventional N application, while maintaining an optimal nitrogen nutrition index throughout wheat development. These yield gains were associated with a marked increase in soil available phosphorus (AP), which enhanced bacterial diversity (Shannon index) and richness (Chao1 index). Co-occurrence network analysis identified two key microbial modules (Module 1 and Module 5) that strongly predicted wheat N accumulation and yield (p < 0.01). The functional roles of these modules shifted from saprotrophic and nitrifying processes at the regreening stage to aromatic compound degradation and root symbiosis at anthesis. Dominant taxa within these modules, particularly Stanjemonium and Coniochaeta, were the strongest contributors to wheat N concentration at the regreening and anthesis stages, respectively. Random forest analysis further indicated that AP exerted a direct regulatory effect on microbial module abundance, while soil N availability influenced wheat N nutrition indirectly through its interactions with AP and microbial network structure. Structural equation modeling confirmed that these pathways ultimately determined wheat nitrogen nutritional status and yield. Overall, layered N fertilization enhances wheat N uptake and productivity by reshaping soil microbial network organization through AP-mediated mechanisms, highlighting the importance of microbial ecological clusters in synchronizing crop N demand with nutrient supply across growth stages.

优化氮肥管理对提高小麦产量和氮素利用效率至关重要，但分层施氮通过不同生长阶段土壤微生物过程调节作物氮素营养的机制尚不清楚。在此，我们进行了为期四年的田间试验，以研究分层施氮如何调节土壤微生物群落和养分动态，从而更好地匹配小麦对氮的需求并提高产量。处理包括土壤深度为8 cm （N8）的常规施氮，8、16和24 cm按1:2:1的比例分层施氮（N1-2-1）和不施氮对照（NCK）。与常规施氮相比，分层施氮可使籽粒产量提高18.7 %，总氮积累提高19.0 %，同时在小麦发育过程中保持最佳氮素营养指数。土壤有效磷（AP）显著增加，细菌多样性（Shannon指数）和丰富度（Chao1指数）增加。共现网络分析发现，两个关键微生物模块（模块1和模块5）对小麦氮素积累和产量具有较强的预测作用（p <； 0.01）。这些模块的功能作用从绿植阶段的腐养和硝化过程转向开花阶段的芳香族化合物降解和根系共生过程。在复绿期和开花期，各模块内的优势类群对小麦氮素的贡献最大，其中以石竹属和针毛纲的贡献最大。随机森林分析进一步表明，氮素对微生物模块丰度具有直接调节作用，而土壤氮有效性通过与氮素和微生物网络结构的相互作用间接影响小麦氮素营养。结构方程模型证实了这些途径最终决定了小麦氮素营养状况和产量。总体而言，分层施氮通过ap介导的机制重塑土壤微生物网络组织，从而提高小麦对氮的吸收和生产力，突出了微生物生态集群在作物生长各阶段氮需求和养分供应同步中的重要性。

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引用次数: 0

Synergistic effects of subsoil vertical drilling and fodder maize on soil physical properties and fodder beet yield 地下垂直钻孔与饲料玉米对土壤物理性质和饲料甜菜产量的协同效应

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-01-15 DOI: 10.1016/j.eja.2026.128005

Muhammad Ali, Muhammad Qaswar, Ajit Borundia, Abdul Mounem Mouazen

Subsoil compaction remains a critical constraint to agricultural productivity, necessitating effective mitigation strategies to enhance soil health and crop performance. This study investigates the synergistic effects of subsoil vertical drilling and fodder maize cropping on fodder beet (Beta vulgaris L.) yield and soil physical properties compared to direct beet cultivation in a Cambisol sandy-textured soil. A field experiment was carried out on a commercial farm in Beervelde, Belgium, employing a semi-autonomous soil vertical drilling machine to apply six treatments with varying drilling depths (50 cm and 90 cm) and hole-to-hole spacings (50 cm, 75 cm, and 100 cm) in a completely randomized design with three replicates across two fields representing two cropping scenarios: 1) fodder maize followed by fodder beet rotation and 2) direct fodder beet cultivation. Treatments included T1 (50 cm depth × 50 cm spacing), T2 (50 cm × 75 cm), T3 (50 cm × 100 cm), T4 (90 cm × 50 cm), T5 (90 cm × 75 cm), T6 (90 cm × 100 cm), and a no-drilling control (T0). Soil bulk density (BD), penetration resistance (PR), and moisture content (MC) were measured at 40 cm and 70 cm depths, alongside fodder beet yield. Results showed that in the maize-beet rotation system, T4 significantly reduced BD by 4.27 % and PR by 20.02 % at 70 cm, increased MC by 15.28 % at 40 cm, and boosted yield by 26.28 % compared to T0. Conversely, direct beet cultivation showed negligible BD reductions, variable PR changes, and yield reductions in most treatments (up to 31 % in T5), with only T6 yielding a 19.8 % increase. In both cropping systems, yield was negatively correlated with BD and PR. These correlations were stronger in the maize-beet rotation system (r = –0.94 for BD, r = –0.86 for PR at 70 cm) than in direct beet cultivation (r = –0.76 for BD, r = –0.61 for PR at 70 cm), highlighting the role of improved soil structure in enhancing productivity. These results demonstrate that maize–beet rotation combined with vertical soil drilling outperforms direct beet cultivation in mitigating subsoil compaction and increasing fodder beet yield. In particular, subsoil drilling at 90 cm depth with 50 cm spacing (T4) showed the most pronounced effects. These findings underscore the value of integrating crop diversification with targeted drilling applications for sustainable soil management in compacted sandy soils.

底土压实仍然是农业生产力的一个严重制约因素，需要采取有效的缓解战略，以提高土壤健康和作物性能。研究了在Cambisol砂质土壤中，与直接种植甜菜相比，地下垂直钻孔和饲料玉米种植对饲料甜菜产量和土壤物理性质的协同效应。在比利时Beervelde的一个商业农场进行了一项田间试验，采用半自主土壤垂直钻孔机，采用完全随机设计，采用不同钻孔深度（50 cm和90 cm）和孔间距（50 cm， 75 cm和100 cm）的六种处理，在两个大田中进行三个重复，代表两种种植方案：1)饲料玉米轮作饲料甜菜和2)直接种植饲料甜菜。治疗包括T1(50 ×50厘米深度 厘米间距),T2(50 cm×75 厘米),T3(50 cm×100 厘米),T4(90 厘米×50 厘米),T5(90 厘米×75 厘米),T6(90 厘米×100 厘米),和一个no-drilling控制(T0)。在40 cm和70 cm深度测定土壤容重（BD）、抗渗透能力（PR）和含水量（MC），同时测定饲用甜菜产量。结果表明，在玉米-甜菜轮作系统中，与T0相比，T4在70 cm处显著降低BD 4.27 %,PR 20.02 %，在40 cm处显著提高MC 15.28 %，增产26.28 %。相反，在大多数处理中，直接甜菜栽培显示出微不足道的BD降低，可变的PR变化和产量降低（T5高达31% %），只有T6产量增加19.8% %。在种植制度、产量与市场及公关负相关。这些相关性强maize-beet旋转系统( = -0.94 BD, r = -0.86 公关在70 厘米)比直接甜菜种植( = -0.76 BD, r = -0.61 公关在70 厘米),强调对于提高产量改善土壤结构的作用。这些结果表明，玉米-甜菜轮作结合垂直土壤钻孔在减轻底土压实和提高饲料用甜菜产量方面优于直接种植甜菜。其中，深度为90 cm、间距为50 cm （T4）的底土钻孔效果最为显著。这些发现强调了将作物多样化与有针对性的钻井应用相结合，对压实沙质土壤进行可持续土壤管理的价值。

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引用次数: 0

Beyond pesticide reduction: Exploring synergies between contrasted territorial scenarios 除农药减少之外：探索不同地域方案之间的协同作用

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-01-28 DOI: 10.1016/j.eja.2026.128009

Myrto Parmantier , Marc Moraine , Rémy Ballot , Lorène Prost

Pesticide use creates significant environmental, health and socioeconomic challenges and its reduction is hindered by sociotechnical lock-ins. The territorial level, combined with systemic approaches, is promising to overcome these systemic challenges. This research proposes an original methodological approach which, instead of aiming at creating consensus, explores contrasted pesticide reduction scenarios with local stakeholders based on existing initiatives in order to identify pathways for collective action. The study was conducted in the Western Plain of Montpellier, in Southern France, and involved a diversity of stakeholders from the territory and outside of the territory in 5 steps, using the Co-Click’Eau tool and workshops. The scenarios explored the potential of diversification for food production, biodiversity conservation and crop-livestock integration to meet pesticide reduction challenges. In addition to an important pesticide use reduction, each scenario proposed significant land-use and farming practices transformations. The analysis revealed that the approach was able to create spaces for dialogue through the formulation of synergies between these strategies by participants, especially on land-use management, technical levers, linking production to consumers and highlighted complementary contributions of biodiversity and livestock to the territory. Beyond its agronomic dimensions, the process opens the pathway to better coordination with the identification of synergies and tensions between different visions, helping to identify coherent strategies including agricultural production, biodiversity, and food objectives. By doing so, our approach contributes to embedding pesticide reduction into a broader, systemic reconfiguration of agroecosystems and territorial governance.

农药的使用造成了重大的环境、健康和社会经济挑战，而且由于社会技术的束缚，阻碍了农药的减少。地域层面，结合系统方法，有望克服这些系统性挑战。本研究提出了一种新颖的方法方法，其目的不是建立共识，而是在现有倡议的基础上，与当地利益相关者探讨农药减少方案的对比，以确定集体行动的途径。这项研究是在法国南部蒙彼利埃西部平原进行的，使用Co-Click 'Eau工具和研讨会，分5个步骤，涉及来自境内和境外的各种利益相关者。这些情景探讨了粮食生产多样化、生物多样性保护和作物-牲畜一体化的潜力，以应对减少农药的挑战。除了农药使用量大幅减少外，每种情景还提出了土地利用和耕作方式的重大转变。分析表明，该方法能够通过参与者制定这些战略之间的协同作用创造对话空间，特别是在土地使用管理、技术杠杆、将生产与消费者联系起来以及强调生物多样性和牲畜对领土的互补贡献方面。除了农艺方面，这一进程还为更好地协调不同愿景之间的协同作用和紧张关系开辟了道路，有助于确定包括农业生产、生物多样性和粮食目标在内的连贯战略。通过这样做，我们的方法有助于将农药减少纳入农业生态系统和领土治理的更广泛、系统性重构中。

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引用次数: 0

Innovative integrated management achieves high productivity and profitability of sugarcane in China with low environmental costs 创新的综合管理以低环境成本实现了中国甘蔗的高生产率和高盈利能力

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-01-07 DOI: 10.1016/j.eja.2026.127985

Huayang Wang , Yinghe Yao , Hui Wang , Jiaxing Chen , Xiao Tang , Prakash Lakshmanan , Xinping Chen , Yan Deng , Fusuo Zhang

Sugarcane (Saccharum officinarum L.) production in China faces challenges of high input costs, substantial emissions, and low efficiency. While individual sustainable practices such as fertilizer reduction, enhanced-efficiency nitrogen fertilizers, organic amendments, and straw return offer partial benefits, they lack integrated effectiveness. We hypothesize that systematically combining these practices could enhance productivity, reduce emissions, and improve soil health through synergistic nutrient cycling and carbon sequestration. However, empirical evidence and systematic evaluations of such integrated practices in Chinese sugarcane systems remain limited. To address this, a two-year field study was conducted at two representative sugarcane plantations in Guangxi under straw return conditions to evaluate the effects of five regimes on yield, nutrient use efficiency, soil organic carbon (SOC) sequestration, greenhouse gas (GHG) emissions, and net ecosystem economic benefit (NEEB). The treatments included CK (no fertilizer), FP (farmer practice), OPT (optimized NPK), IKPS1 (based on OPT, integrating further optimized nutrient inputs with controlled-release urea), and IKPS2 (based on IKPS1, substituting 30 % of N with organic fertilizer). Compared with FP, both IKPS1 and IKPS2 reduced total NPK inputs by 47 %, while increasing cane yield by 4.6–5.8 % (up to 109.3 t ha⁻¹) and sugar yield by 6.2–9.0 %. Additionally, compared to FP, nutrient use efficiency for N, P, and K under IKPS1 and IKPS2 improved significantly by 81.2–82.0 %, 148.1–255.8 %, and 76.4–101.6 %, respectively. Environmentally, IKPS1 and IKPS2 markedly reduced Nr losses by 57.7–68.7 % and GHG emissions by 40.7–43.8 % relative to FP. Notably, IKPS2 achieved carbon neutrality (-151.9 kg CO₂-eq ha⁻¹), primarily attributed to enhanced SOC sequestration. Economically, both systems increased NEEB over FP, with gains of 114.5 % under IKPS1 and 61.2 % under IKPS2. Comprehensive evaluation indices further confirmed their superiority (0.59 for IKPS1, 0.81 for IKPS2). A stepwise strategy is proposed to prioritize cost-effective practices of IKPS1, while advancing toward carbon neutrality by IKPS2. Overall, this study provides an evidence-based framework to advance sustainable sugarcane production and support the green transformation of tropical agriculture.

中国甘蔗生产面临高投入成本、高排放和低效率的挑战。虽然减肥、增效氮肥、有机改良剂和秸秆还田等个别可持续做法提供了部分效益，但它们缺乏综合效益。我们假设系统地结合这些做法可以通过协同养分循环和碳固存来提高生产力，减少排放，改善土壤健康。然而，这种综合实践在中国甘蔗系统中的经验证据和系统评价仍然有限。为解决这一问题，在广西2个具有代表性的甘蔗种植园进行了秸秆还田条件下为期2年的田间研究，评估了5种制度对产量、养分利用效率、土壤有机碳（SOC）固存、温室气体（GHG）排放和净生态系统经济效益（NEEB）的影响。处理包括CK（不施肥）、FP（农民实践）、OPT（优化氮磷钾）、IKPS1（基于OPT，将进一步优化的养分投入与控释尿素相结合）和IKPS2（基于IKPS1，用有机肥替代30% %的氮）。与FP相比，IKPS1和IKPS2减少了氮磷钾总投入47% %，而甘蔗产量提高4.6-5.8 %（最高109.3 t ha - 1），糖产量提高6.2-9.0 %。此外，与FP相比，IKPS1和IKPS2处理的N、P、K养分利用效率分别显著提高81.2 ~ 82.0 %、148.1 ~ 255.8 %和76.4 ~ 101.6 %。在环境方面，相对于FP， IKPS1和IKPS2显著减少了57.7 - 68.7% %的Nr损失和40.7 - 43.8% %的温室气体排放。值得注意的是，IKPS2实现了碳中和（-151.9 kg CO2-eq ha -1），这主要归功于增强的有机碳固存。在经济上，两个系统都增加了NEEB而不是计划生育，在IKPS1下收益为114.5 %，在IKPS2下收益为61.2 %。综合评价指标进一步证实了其优势（IKPS1为0.59，IKPS2为0.81）。提出了一种循序渐进的策略，优先考虑IKPS1的成本效益实践，同时通过IKPS2推进碳中和。总体而言，本研究为促进甘蔗可持续生产和支持热带农业绿色转型提供了一个循证框架。

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引用次数: 0

Forecasting crop yield through a data-driven framework of remote sensing and biophysical knowledge: A case study for wheat and maize in the Guanzhong Plain, China 利用数据驱动的遥感和生物物理知识框架预测作物产量：以中国关中平原小麦和玉米为例

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-02-12 DOI: 10.1016/j.eja.2026.128038

Zhikai Cheng, Xiaobo Gu, Yuanling Zhang, Tongtong Zhao, Shikun Sun, Yadan Du, Huanjie Cai

Accurate early yield forecasts are essential for maximizing benefits and ensuring food security in the Guanzhong Plain, China. Process-based crop models are often constrained by uncertain input data, which limits their ability to forecast yield at the regional grid level (e.g., 1 km × 1 km). Statistical models, ignore the biophysical mechanisms underlying crop growth and development, and their performance is limited by the quantity and quality of available training data. Therefore, there is an urgent need for a more comprehensive and robust grid-level wheat and maize yield forecasting approach for the Guanzhong Plain. In this study, an interpretable data-driven framework was developed to forecast wheat and maize yields by combining remote sensing (solar-induced chlorophyll fluorescence, SIF; spectral indices, SIs) and biophysical knowledge (APSIM outputs and extreme climatic events) data. A Bayesian integration model (BIM) was trained on high-quality synthetic datasets (obtained by the synthetic minority oversampling technique for regression, SMOTER) to achieve accurate harvest-time yield forecasts at specific time windows. The results showed that the integration of multi-source data reduced the yield prediction error, with the overall normalized root mean square error (NRMSE) decreasing by 0.6 %–39.0 % compared to the single-source models. The data-driven model trained on the SMOTER -based synthetic dataset achieved the highest yield forecasting accuracy (wheat: NRMSE = 16.2 %; maize: NRMSE = 20.7 %). The SIF made the largest contribution to yield forecasts and showed strong interactions and synergies with other feature variables (e.g., aboveground biomass, drought, and low temperature stress), further enhancing model performance. Overall, the proposed data-driven framework demonstrates a promising way for improving grid-level yield forecasting and provides useful insights for the sustainable development of agricultural systems.

准确的早期产量预测对于实现效益最大化和确保关中平原的粮食安全至关重要。基于过程的作物模型经常受到不确定输入数据的约束，这限制了它们在区域网格级预测产量的能力（例如，1 km × 1 km）。统计模型忽略了作物生长发育的生物物理机制，其性能受到可用训练数据的数量和质量的限制。因此，迫切需要一种更全面、更可靠的关中平原小麦和玉米网格级产量预测方法。在这项研究中，开发了一个可解释的数据驱动框架，通过结合遥感（太阳诱导叶绿素荧光，SIF；光谱指数，si）和生物物理知识（APSIM输出和极端气候事件）数据来预测小麦和玉米产量。贝叶斯集成模型（BIM）在高质量的合成数据集（通过合成少数派过采样技术进行回归，SMOTER）上进行训练，以在特定的时间窗口实现准确的收获时间产量预测。结果表明，与单源模型相比，多源数据集成降低了产量预测误差，总体归一化均方根误差（NRMSE）降低0.6 % ~ 39.0 %。在SMOTER合成数据集上训练的数据驱动模型的产量预测精度最高（小麦：NRMSE = 16.2 %；玉米：NRMSE = 20.7 %）。SIF对产量预测的贡献最大，并与其他特征变量（如地上生物量、干旱和低温胁迫）表现出强烈的相互作用和协同作用，进一步提高了模型的性能。总体而言，所提出的数据驱动框架展示了一种改善电网级产量预测的有希望的方法，并为农业系统的可持续发展提供了有用的见解。

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引用次数: 0

Advancements in weed mapping: A systematic review 杂草制图的进展：系统综述

IF 5.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2026-04-01 Epub Date: 2026-01-16 DOI: 10.1016/j.eja.2026.127992

Mohammad Jahanbakht , Alex Olsen , Ross Marchant , Emilie Fillols , Mostafa Rahimi Azghadi

Weed mapping plays a critical role in precision management by providing accurate and timely data on weed distribution, enabling targeted control and reduced herbicide use. This minimizes environmental impacts, supports sustainable land management, and improves outcomes across agricultural and natural environments. Recent advances in weed mapping leverage ground-vehicle Red Green Blue (RGB) cameras, satellite and drone-based remote sensing combined with sensors such as spectral, Near Infra-Red (NIR), and thermal cameras. The resulting data are processed using advanced techniques including big data analytics and machine learning, significantly improving the spatial and temporal resolution of weed maps and enabling site-specific management decisions. Despite a growing body of research in this domain, there is a lack of comprehensive literature reviews specifically focused on weed mapping. In particular, the absence of a structured analysis spanning the entire mapping pipeline, from data acquisition to processing techniques and mapping tools, limits progress in the field. This review addresses these gaps by systematically examining state-of-the-art methods in data acquisition (sensor and platform technologies), data processing (including annotation and modelling), and mapping techniques (such as spatiotemporal analysis and decision support tools). In the data processing stage, weed detection was identified as a critical enabling component of the mapping pipeline; accordingly, dedicated sections were included to systematically review state-of-the-art methods. Following PRISMA guidelines, we critically evaluate and synthesize key findings from the literature to provide a holistic understanding of the weed mapping landscape. This review serves as a foundational reference to guide future research and support the development of efficient, scalable, and sustainable weed management systems.

杂草测绘通过提供准确和及时的杂草分布数据，实现有针对性的控制和减少除草剂的使用，在精确管理中起着至关重要的作用。这将最大限度地减少对环境的影响，支持可持续土地管理，并改善农业和自然环境的成果。杂草测绘的最新进展利用了地面车辆红绿蓝（RGB）相机、卫星和无人机遥感以及光谱、近红外（NIR）和热像仪等传感器。结果数据使用包括大数据分析和机器学习在内的先进技术进行处理，显着提高了杂草地图的时空分辨率，并使特定地点的管理决策成为可能。尽管这一领域的研究越来越多，但缺乏专门针对杂草测绘的全面文献综述。特别是，从数据采集到处理技术和绘图工具，缺乏跨越整个绘图管道的结构化分析，限制了该领域的进展。本综述通过系统地研究数据采集（传感器和平台技术）、数据处理（包括注释和建模）和制图技术（如时空分析和决策支持工具）方面的最新方法来解决这些差距。在数据处理阶段，杂草检测被确定为映射管道的关键启用组件；因此，设立了专门的部门系统地审查最新的方法。遵循PRISMA的指导方针，我们批判性地评估和综合文献中的关键发现，以提供对杂草测绘景观的整体理解。本综述可作为指导未来研究和支持高效、可扩展和可持续杂草管理系统开发的基础参考。

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引用次数: 0