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Organ3DNet: A deep network for segmenting organ semantics and instances from dense plant point cloudsLi, D.; Huang, J.; Zhao, B.; Wen, W. Organ3DNet：一种用于从密集植物点云中分割器官语义和实例的深度网络。Artif. Intell. Agric. 2025, 16, 342–364. [Google Scholar] [CrossRef]
Li, Dawei; Huang, Jiali; Zhao, Boyuan; Wen, Weiliang.png)
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收藏 Prediction of wheat stem biomass using a new unified model driven by phenological variable under remote-sensed canopy vegetation index constraints利用受遥感冠层植被指数约束的基于生育期变量的新统一模型预测小麦茎生物量Chen, Weinan; Yang, Guijun; Meng, Yang; Feng, Haikuan; Wen, Hongrui; Tang, Aohua; Zhang, Jing; Yang, Hao; Li, Heli; Xu, Xingang; Li, Changchun; Li, Zhenhong 分享 收藏 LPNet: A lightweight progressive network for calyx-aware apple pose estimation in orchard environments王, W.; 朱, L.; 赵, B.; 高, J.; 崔, X.; 韩, Z.; 赵, S. LPNet: 一种轻量级渐进网络，用于果园环境下的基于calyx-aware的苹果姿态估计。Artif. Intell. Agric. 2026, 16, 672–694. [Google Scholar] [CrossRef]Wang, Wenbei; Zhu, Licheng; Zhao, Bo; Gao, Jianbo; Cui, Xuezhi; Han, Zhenhao; Zhao, Siyuan 分享 收藏 Utilizing interpretable machine learning algorithms and multiple features from multi-temporal Sentinel-2 imagery for predicting wheat fusarium head blight王, H.; 阮, C.; 赵, J.; 王, Y.; 李, Y.; 董, Y.; 黄, L. 利用可解释机器学习算法和多时相Sentinel-2影像的多特征预测小麦 Fusarium 头部枯萎病. Artif. Intell. Agric. 2026, 16, 224–239. [Google Scholar] [CrossRef]Wang, Hui; Ruan, Chao; Zhao, Jinling; Wang, Yunran; Li, Ying; Dong, Yingying; Huang, Linsheng 分享 收藏 Early detection of wheat powdery mildew: A multi-source in situ remote sensing approach enabled by stacked ensemble learningSong, L.; Zhao, J.; Li, Y.; Liu, L.; Duan, J.; He, L.; Wang, Y.; Guo, T.; Feng, W. 小麦白粉病的早期检测：一种基于堆叠集成学习的多源现场遥感方法. Artif. Intell. Agric. 2026, 16, 124–138. [Google Scholar] [CrossRef]Song, Li; Zhao, Jiliang; Li, Yahui; Liu, Linru; Duan, Jianzhao; He, Li; Wang, Yonghua; Guo, Tiancai; Feng, Wei 分享 收藏 Energy-saving and stability-enhancing control for unmanned distributed drive electric plant protection vehicle based on active torque distribution徐文祥; 朱永军; 肖明华; 刘梦娜; 叶丽丽; 杨玉平; 刘志. 基于主动扭矩分配的无人分布式驱动电动植保车节能与稳定性提升控制. 人工智能农业, 2026, 16, 495–513. [Google Scholar] [CrossRef]Xu, Wenxiang; Zhu, Yejun; Xiao, Maohua; Liu, Mengnan; Ye, Liling; Yang, Yanpeng; Liu, Ze 分享 收藏 CTGNN: UAV-satellite cross-domain transfer learning for monitoring oat growth in China's key production areasCTGNN：UAV-卫星跨域迁移学习在中国主要产区监测燕麦生长Zhang, Pengpeng; Yang, Yadong; Zang, Huadong; Zeng, Zhaohai; Lu, Bing; Shang, Jiali; Tan, Changwei; Sun, Shuchang; Xu, Zhuo; Ge, Junyong 分享 收藏 
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