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Liang Zhong, Xueyuan Chu, Jiawei Qian, Jianlong Li and Zhengguo Sun
With the rapid development of China?s industrialization and urbanization, the problem of heavy metal pollution in soil has become increasingly prominent, seriously threatening the safety of the ecosystem and human health. The development of hyperspectral...
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Jiying Kong, Zhenhai Luo, Chao Zhang, Min Tang, Rui Liu, Ziang Xie and Shaoyuan Feng
The fraction of absorbed photosynthetically active radiation (FPAR), which represents the capability of vegetation-absorbed solar radiation to accumulate organic matter, is a crucial indicator of photosynthesis and vegetation growth status. Although a si...
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Roei Grimberg, Meir Teitel, Shay Ozer, Asher Levi and Avi Levy
Since leaf temperature (LT) is not a trivial measurement, deep-neural networks (DNN) and machine learning (ML) models were evaluated in this study as tools for estimating foliage temperature. Two DNN methods were used. The first DNN used convolutional la...
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Naji Mordi Naji Al-Dosary, Abdulwahed Mohamed Aboukarima and Saad Abdulrahman Al-Hamed
The focal objective of the current research is to apply artificial neural network (ANN) and multiple linear regression (MLR) methods for modeling the performance attributes of a mechanization unit (tractor-chisel plow) during the plowing process under bo...
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Severino Segato, Giorgio Marchesini, Luisa Magrin, Barbara Contiero, Igino Andrighetto and Lorenzo Serva
Estimating the dry matter losses (DML) of whole-plant maize (WPM) silage is a priority for sustainable dairy and beef farming. The study aimed to assess this loss of nutrients by using net-bags (n = 36) filled with freshly chopped WPM forage and buried i...
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