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Zhiqing Guo, Xiaohui Chen, Ming Li, Yucheng Chi and Dongyuan Shi
Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction me...
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Carlos Alberto Matias de Abreu Júnior, George Deroco Martins, Laura Cristina Moura Xavier, João Vitor Meza Bravo, Douglas José Marques and Guilherme de Oliveira
Image-based spectral models assist in estimating the yield of maize. During the vegetative and reproductive phenological phases, the corn crop undergoes changes caused by biotic and abiotic stresses. These variations can be quantified using spectral mode...
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Dexi Zhan, Yongqi Mu, Wenxu Duan, Mingzhu Ye, Yingqiang Song, Zhenqi Song, Kaizhong Yao, Dengkuo Sun and Ziqi Ding
Soil water content is an important indicator used to maintain the ecological balance of farmland. The efficient spatial prediction of soil water content is crucial for ensuring crop growth and food production. To this end, 104 farmland soil samples were ...
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Tao He, Wenya Zhang, Hanwen Zhang and Jinliang Sheng
In this study, mathematical models are used to estimate the emissions of livestock excreta (LE) generated by China?s livestock industry more accurately. Also, the spatial relationship between provinces is analyzed. LE emissions are predicted for the next...
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Srinivasagan N. Subhashree, C. Igathinathane, Adnan Akyuz, Md. Borhan, John Hendrickson, David Archer, Mark Liebig, David Toledo, Kevin Sedivec, Scott Kronberg and Jonathan Halvorson
Farmers and ranchers depend on annual forage production for grassland livestock enterprises. Many regression and machine learning (ML) prediction models have been developed to understand the seasonal variability in grass and forage production, improve ma...
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