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Mykhailo Lohachov, Ryoji Korei, Kazuo Oki, Koshi Yoshida, Issaku Azechi, Salem Ibrahim Salem and Nobuyuki Utsumi
This article investigates approaches for broccoli harvest time prediction through the application of various machine learning models. This study?s experiment is conducted on a commercial farm in Ecuador, and it integrates in situ weather and broccoli gro...
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Xiaobo Zhuang and Yaoming Li
Rice lodging not only brings trouble to harvesting but also reduces yield. Therefore, the effective identification of rice lodging is of great significance. In this paper, we have designed a bilinear interpolation upsampling feature fusion module (BIFF) ...
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Hua Yang, Xingquan Deng, Hao Shen, Qingfeng Lei, Shuxiang Zhang and Neng Liu
In recent years, the domain of diagnosing plant afflictions has predominantly relied upon the utilization of deep learning techniques for classifying images of diseased specimens; however, these classification algorithms remain insufficient for instances...
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Zhen Tan, Fengzhen Liu, Yongshan Wan, Suqing Zhu, Jing Zhang, Kun Zhang and Lu Luo
To reduce the application of phosphorus fertilizer and improve phosphorus efficiency in peanut (Arachis hypogaea L.) production, six peanut varieties with different phosphorus activation efficiencies were selected, and the root morphology, physiological ...
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Wenhong Ma, Zhouyang Yang, Xiaochen Qi, Yu Xu, Dan Liu, Housen Tan, Yongbin Li and Xuhai Yang
The production of the Korla fragrant pear is significant, but the optimal harvesting time is short; therefore, the reasonable use of mechanical arms for harvesting is conducive to promoting the sustainable development of the fragrant pear industry. The e...
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