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Dexin Wei, Chongyou Wu, Lan Jiang, Gang Wang and Hui Chen
At present, Chinese corn grain harvesters lack cleaning loss monitoring. Cleaning parameters cannot be automatically adjusted, and the loss rate is high. In view of the above problems, a cleaning loss monitoring sensor is designed, composed of a metal im...
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Genlan Han, Jiang Wang, Haiyan Zhao, Dan Wang, Yanyan Duan, Ruihua Han, Meng?en Nie, Lijie Zhao and Huiling Du
The effect of nitrogen and zinc treatment on quality and yield was studied to provide a theoretical basis for generating high-quality and high-yielding foxtail millet. In the years 2021?2022, ?Jingu 21? was utilized as the test material in a split-plot d...
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Jinkai Guo, Xiao Xiao, Jianchi Miao, Bingquan Tian, Jing Zhao and Yubin Lan
In order to achieve accurate detection of mature Zanthoxylum in their natural environment, a Zanthoxylum detection network based on the YOLOv5 object detection model was proposed. It addresses the issues of irregular shape and occlusion caused by the gro...
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Du?an Dunderski, Goran Jacimovic, Jovan Crnobarac, Jelena Viskovic and Dragana Latkovic
In this study, we aimed to evaluate the feasibility of digital image analysis (DIA) as a substitute for standard analysis (SA) in assessing corn ear traits in agrotechnical field trials. Accurate and timely prediction of corn yield through corn ear trait...
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Hongcheng Li, Rong Zeng, Zhiyou Niu and Junqi Zhang
Clarifying the maize kernel movement during the crushing process is critical for improving the design and optimization of the impact mill. Rather than through experiments, maize kernel movement can be quantitatively analyzed through the discrete element ...
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