Deep learning technique for rice leaf disease classification and severity level identification via Hybrid ResConvolutional Neural Network
提出混合Res卷积神经网络用于水稻叶部病害分类与严重度识别，结合物联网数据采集。
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Decoding Electro-Priming responses in cotton using an integrated taguchi-machine learning framework for optimizing seed performance
用田口-机器学习框架优化棉花种子电引发处理，提升种子性能。
Multi-attribute spectral imaging with a wavelength-aware band-gated vision transformer for camellia oil adulteration detection
提出波长感知的ViT-BandGate模型，利用多属性光谱成像检测山茶油掺假，实现高精度识别。
Integrating a pesticide risk indicator into a multi-criteria assessment tool for comparing crop protection scenarios
开发了IPM自评估工具ISAT，集成新的农药风险指标PL EU，比较作物保护情景的环境、健康和经济影
International Journal of Artificial Intelligence and Machine Learning 2026, 6(9s)·9月5日 · 周六81 分 论文大豆与油料农业人工智能与决策模型阅读 2
From Orbit to Leaf: A Critical Systematic Review of Artificial Intelligence for Multi-Scale Crop Monitoring and Soybean Leaf Disease Diagnosis（IJAIML 2026, 6(9s), 471-498）
系统综述AI用于多尺度作物监测与大豆叶病诊断，提出FRI评估标准与报告协议。
International Journal for Research Trends in Social Science & Humanities.·9月4日 · 周五69 分 论文单产提升与粮食安全智慧农业 / 农业物联网2 个信源同时报道 阅读 1
AI-Driven Smart Agriculture And Food Security In Developing Countries: A Comparative Perspective
比较六国AI驱动智慧农业对粮食安全的影响，发现数字基础设施和AI准备度是关键。
Design and field validation of a vision-based graded compaction intensity control system for wheat seeding
设计并田间验证了基于视觉的小麦播种分级压实强度控制系统。
EOL-DQN: An intelligent cutting decision of potato seed tubers based on improved deep reinforcement learning
提出EOL-DQN改进深度强化学习模型，用于马铃薯种薯切块智能决策。
VGG21 Deep Learning + Drone Multispectral Imagery Detects Wheat Waterlogging Stress and Silicon Fertilizer Effects
用无人机多光谱和VGG21深度学习检测小麦涝害并评估硅肥效果。
BioIMA: a one-click desktop tool for standardized extraction of phenotypic traits from biological images
开发了BioIMA桌面工具，实现生物图像表型标准化自动提取，无需训练模型。
Artificial intelligence adoption and food security in Saudi Arabia: the critical role of water-use efficiency management
研究沙特AI采用与粮食安全、水资源效率的动态关系，发现AI提升短期粮食安全与工业用水效率。
AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction under Water Stress
提出过程信息神经网络AgriPINN，嵌入作物生长方程，提升水分胁迫下生物量预测精度与可解释性。
A physics-guided hybrid framework for peanut nitrogen monitoring (Computers and Electronics in Agriculture)
提出物理-数据融合框架POSNH，用于花生冠层氮素含量遥感监测，降低样本依赖并提高泛化能力。
Research on interaction mechanisms and operating parameter optimization of soybean threshing based on the discrete element method
用离散元法研究大豆脱粒的相互作用机制并优化操作参数。
From frame-wise detection to instance-level tracking: robust crop row perception for autonomous paddy field navigation
提出从逐帧检测到实例级跟踪的作物行感知方法，用于水稻田自主导航。
Deploying and Evaluating a Smart-Agriculture Agentic Engine for Full-Season Soybean Farm Operations
部署并评估了全季大豆农场的智慧农业智能体系统FAIRY，实现全流程农艺操作。
An Improved Transformer-KAN Model for Soybean Mapping Based on Multi-Temporal Remote Sensing Data
提出改进的Transformer-KAN模型，基于多时相遥感数据实现高精度、可迁移的大豆种植区制图。
Hyperspectral Imaging for Disease Detection in Wheat Crops: A Comprehensive Survey
综述高光谱成像在小麦病害检测中的应用，涵盖方法、挑战与未来方向。
Explainable Deep Learning-Based Potato Leaf Disease Detection and Severity Assessment for Smart Agriculture in Bangladesh
Explainable Deep Learning-Based Potato Leaf Disease Detection and Severity Assessment for Smart Agriculture in Bangladesh。Research Square
From Visual Words to Vision Transformers: Dual Approaches to Water Stress Classification in Maize
比较Swin Transformer与手工特征BPNN在玉米水分胁迫RGB图像分类中的表现，两者均达