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Luana Centorame, Thomas Gasperini, Alessio Ilari, Andrea Del Gatto and Ester Foppa Pedretti
Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, ...
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Zhiyang Li, Zhigang Nie and Guang Li
One of the crucial research areas in agricultural decision-making processes is crop yield prediction. This study leverages the advantages of hybrid models to address the complex interplay of genetic, environmental, and management factors to achieve more ...
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Lei Sun, Chongchong Yang, Jun Wang, Xiwen Cui, Xuesong Suo, Xiaofei Fan, Pengtao Ji, Liang Gao and Yuechen Zhang
Existing maize production is grappling with the hurdles of not applying nitrogen fertilizer accurately due to subpar detection accuracy and responsiveness. This situation presents a significant challenge, as it has the potential to impact the optimal yie...
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Zichao Wei, Xiangbei Wan, Wenye Lei, Kaikai Yuan, Miao Lu, Bin Li, Pan Gao, Huarui Wu and Jin Hu
Photosynthetic rate prediction models can provide guidance for crop photosynthetic process optimization, which has been widely used in the precise regulation of the protected environment. The photosynthetic capacity of crops continuously changes during t...
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Zhaoyang Tong, Shirui Zhang, Jingxin Yu, Xiaolong Zhang, Baijuan Wang and Wengang Zheng
The growth and yield of crops are highly dependent on irrigation. Implementing irrigation plans that are tailored to the specific water requirements of crops can enhance crop yield and improve the quality of tomatoes. The mastery and prediction of transp...
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