A NOVEL HYBRID CLUSTERING AND ENSEMBLE LEARNING FRAMEWORK FOR AGRICULTURAL CROP RECOMMENDATION
提出聚类加集成学习的混合框架，用土壤气候数据做作物推荐。
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Precision Agriculture Using AI for Crop Yield Prediction and Disease Detection: A Comprehensive Review of Machine Learning and Deep Learning Approaches for Sustainable, Data-Driven Farming
综述机器学习与深度学习在作物产量预测和叶片病害检测中的应用与挑战。
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Image-Based Soil Nutrient Prediction Using Machine Learning and Deep Learning Models
用土壤图像结合机器学习与深度学习模型预测氮磷钾含量。
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Architecture diverse TabNet ensemble for crop type classification using harmonized multisource soil data（基于多源土壤数据融合的架构多样性TabNet集成作物类型分类）
构建架构多样性TabNet集成，用多源土壤数据分类7类作物。
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Artificial intelligence in food safety: a bibliometric and empirical synthesis of emerging technologies and research frontiers
对2021-2025年2782篇文献做文献计量，梳理AI与食品安全交叉研究趋势。
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A growing challenge: stakeholder perceptions of AI and ML applications in U.S. agriculture
通过问卷与访谈调查美国农业利益相关者对AI/ML应用的认知与障碍。
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Machine Learning-based Prediction of SVI Parameter in Maize: A Comparative Study and Feature Importance Analysis
用四种机器学习模型基于39个玉米基因型盐胁迫发芽数据预测幼苗活力指数SVI。
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Groundwater Potential Mapping in Northwestern Nigeria: A Comparison of the Analytic Hierarchy Process and Galileo-Enhanced CAT-XGB
对比专家驱动AHP与遥感基础模型增强的CAT-XGB集成，用于尼日利亚西北部地下水潜力制图。
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Applications of Artificial Intelligence in Soil Characterization and Agriculture: A Systematic Review
系统综述2018-2026年196项AI用于土壤特性与农业的研究。
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Impervious Surface Classification Using Artificial Intelligence from Remote Sensing Imagery, Part I: Evaluation of Machine Learning Algorithms
用Landsat与Sentinel-2影像和三种机器学习算法自动分类胡志明市不透水面并监测15年变化
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Comparative Performance of Machine Learning and Deep Learning Algorithms for Agricultural Land Mapping in Anambra State, Nigeria
比较RF、SVM、ANN、CNN在尼日利亚农业用地制图中的表现
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A Hybrid Model for Crop Yield Prediction Using Recurrent Neural Networks and Explainable Artificial Intelligence
用LSTM结合可解释AI预测肯尼亚玉米产量，兼顾精度与透明度。
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Machine Learning for Surface Water Quality Management in Malaysia: Integrating Physicochemical Parameters, Nutrient Loads, Land Use, Hydrological Conditions, and Anthropogenic Pressure
构建马来西亚地表水质机器学习框架，融合多源环境数据实现分类、预测与污染事件检测。
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A Systematic Study of Supervised and Ensemble Learning Approaches for Crop Selection in Smart Agriculture
系统综述2016-2026年24项作物推荐研究，比较四类机器学习方法并指出基准精度已趋饱和。
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Machine learning models combined with feature importance methods for honey yield classification: A replicable approach
构建可复现工作流，用气候变量与机器学习分类蜂蜜产量。
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Crop recommendation in precision agriculture: a systematic literature review of methods, trends, and challenges（精准农业中的作物推荐：方法、趋势与挑战系统综述）
系统综述129篇2020-2026年文献，梳理精准农业作物推荐的方法、趋势与挑战。
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YieldVision: Model-Driven Decision Support System for Crop Yield Prediction
提出YieldVision决策支持系统，用RF、LSTM及混合模型预测作物产量并部署应用。
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Research on the Inversion Method of Total Phosphorus Concentration in Water Bodies Based on PSO-Adam-BP Neural Network Model
用PSO-Adam-BP神经网络结合Sentinel-2影像反演白洋淀总磷浓度。
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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。
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A Novel Data-Driven Framework for Stubble Burning Detection Using NASA FIRMS and Machine Learning
提出基于NASA FIRMS与机器学习的数据驱动框架，用于检测秸秆焚烧。
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