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Jingming Wu, Tiecheng Bai and Xu Li
Chlorophyll content is highly susceptible to environmental changes, and monitoring these changes can be a crucial tool for optimizing crop management and providing a foundation for research in plant physiology and ecology. This is expected to deepen our ...
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Minghua Li, Yang Liu, Xi Lu, Jiale Jiang, Xuehua Ma, Ming Wen and Fuyu Ma
The accurate assessment of nitrogen (N) status is important for N management and yield improvement. The N status in plants is affected by plant densities and N application rates, while the methods for assessing the N status in drip-irrigated cotton under...
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Jian Liu, Shihui Yu, Xuemei Liu, Guohang Lu, Zhenbo Xin and Jin Yuan
In-field in situ droplet deposition digitization is beneficial for obtaining feedback on spraying performance and precise spray control, the cost-effectiveness of the measurement system is crucial to its scalable application. However, the limitations of ...
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Huizhong Xiong, Xiaotong Gao, Ningyi Zhang, Haoxiong He, Weidong Tang, Yingqiu Yang, Yuqian Chen, Yang Jiao, Yihong Song and Shuo Yan
A novel deep learning model, DiffuCNN, is introduced in this paper, specifically designed for counting tobacco lesions in complex agricultural settings. By integrating advanced image processing techniques with deep learning methodologies, the model signi...
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Xinyu Jia, Xueqin Jiang, Zhiyong Li, Jiong Mu, Yuchao Wang and Yupeng Niu
The occurrence of pests at high frequencies has been identified as a major cause of reduced citrus yields, and early detection and prevention are of great significance to pest control. At present, studies related to citrus pest identification using deep ...
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