Automated seedling vigor estimation in cucumbers using digital image processing
用YOLOv8检测黄瓜真叶并结合多元回归，实现幼苗活力指数无损预测。
数字农业与前沿技术
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A Multi-Task Stacked Ensemble and IoT-Enabled Decision Support System for Precision Fertigation in Smallholder Agriculture
构建多任务堆叠集成模型与物联网决策支持系统，实现小农户精准水肥一体化。
AgriMAC: An Attention Based Multimodal Deep Clustering Framework for Rice Health Assessment
提出无监督多模态聚类框架AgriMAC，融合无人机NDVI、IoT土壤与气象数据评估水稻健康。
AshGdNutDefAM: Machine-learning-based multi-feature framework for nutrient deficiency detection and classification in Ash gourd Plant
提出AshGdNutDefAM多特征机器学习框架，自动检测和分类冬瓜缺镁缺铁症状。
基于无人机多光谱图像和VGG21模型的小麦渍害调控效果识别方法
用无人机多光谱图像和VGG21模型识别小麦渍害调控效果。
A comprehensive review of deep learning methods for weed classification in precision agriculture
综述2018-2025年深度学习杂草分类方法，分析技术瓶颈并给出改进建议。
Advances in Bioacoustics Sensing and Signal Processing Technologies
综述生物声学传感与信号处理进展，涵盖医疗、生态与农业应用。
AI-enabled UAV-based Soil Organic Carbon Mapping in Arid Environments: A Pilot Study Protocol
提出一套无人机高光谱结合AI的干旱区土壤有机碳制图标准化试点方案。
Assessing spatial suitability and climate resilience of agroforestry systems in the Indian Himalaya of Uttarakhand using remote sensing and artificial neural networks
结合遥感、GIS与人工神经网络评估印度喜马拉雅地区农林复合系统的空间适宜性与气候韧性。
Rule-driven functional zoning index prediction for sustainable agricultural landscapes design based on multimodal fusion deep learning
构建规则驱动农业景观功能分区指数，并用多模态融合深度学习实现自动预测。
Deep learning-driven multisource remote sensing image fusion: Advances, challenges, and future directions
综述深度学习多源遥感图像融合方法、挑战与未来方向。
A Hybrid CNN–Transformer–LSTM Deep Learning Framework for Automated Cotton Disease Detection
提出CNN-Transformer-LSTM混合框架，实现棉花叶片病害自动识别。
Zenodo (CERN European Organization for Nuclear Research)·9月18日 · 周五65 分 论文农业AI与大模型智慧农业 / 农业物联网2 个信源同时报道 阅读 3
A CNN-Based Approach for Leaf Disease Prediction in Smart Agriculture
用CNN对植物叶片病害进行自动识别，在基准数据集上取得92%准确率。
Zenodo (CERN European Organization for Nuclear Research)·9月18日 · 周五0 分 论文农业AI与大模型智慧农业 / 农业物联网2 个信源同时报道 阅读 1
**The Hidden Physical Cost of Artificial Intelligence: A Materials Science and Engineering Optimization Perspective on AI Infrastructure, Resource Constraints, and Sustainable Innovation in India**
揭示AI并非云端无形，而是依赖电力、水和关键矿产的实体基础设施，并以印度为例探讨可持续创新。
A REAL-TİME AI-DRİVEN AGRİCULTURAL ROVER INTEGRATİNG PLANT DİSEASE DETECTİON AND GEO-REFERENCED SOİL MOİSTURE ANALYSİS
开发实时AI农业机器人，集成植物病害检测与地理参考土壤湿度分析。
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering·9月18日 · 周五72 分 论文水资源与灌溉智慧农业 / 农业物联网阅读 2
An artificial intelligence-based stacking ensemble framework for smart irrigation pump control using IoT sensor data
提出基于堆叠集成学习的灌溉泵ON/OFF预测框架，用物联网传感器数据实现智能灌溉控制。
A quantum-inspired multi-objective learning framework for real-time sustainable aquaculture water quality prediction
提出量子启发多目标优化网络Q-AQUAOptNet，实现水产养殖水质实时预测。
Precision Diagnosis of Apple Leaf Diseases Across Infection Stages via Web-Based Analysis
提出基于YOLOv8-MHSA与SAM的网页系统，实现苹果叶片病害多感染阶段实时检测与分级。
Field-scale prediction and spatial mapping of tractor tractive efficiency in tillage operations using machine learning
Field-scale prediction and spatial mapping of tractor tractive efficiency in tillage operations using machine learning。Precision Agriculture
MMTA-ACDD: Multi-teacher online adaptive learning and multimodal augmentation synergy for robust crop disease detection
提出多教师在线自适应与多模态增强框架，提升作物病害实时检测模型在动态环境下的鲁棒性。