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Dania Tamayo-Vera, Xiuquan Wang and Morteza Mesbah
The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current ut...
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Chengmin Li, Haoyu Deng, Guoxin Yu, Rong Kong and Jian Liu
Nudging the adoption of agricultural green production technologies (AGPTs) by cotton farmers is a practical need to implement the national ?green development? strategy. Based on the micro-survey data of 502 cotton farmers, this paper empirically analyzed...
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Jianlei Qiao, Yonglu Lv, Yucai Feng, Chang Liu, Yi Zhang, Jinying Li, Shuang Liu and Xiaohui Weng
At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and superv...
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Roberto Barbetti, Irene Criscuoli, Giuseppe Valboa, Nadia Vignozzi, Sergio Pellegrini, Maria Costanza Andrenelli, Giovanni L?Abate, Maria Fantappiè, Alessandro Orlandini, Andrea Lachi, Lorenzo Gardin and Lorenzo D?Avino
A WebGis tool called GoProsit has been developed to support winegrowers in planning a new sustainable vineyard and in the identification of high-quality terroir in Tuscany, Central Italy, by providing various information on soils, climate, hydrological r...
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Lu Wang, Cunjie Yan, Wenqi Zhang and Yinghu Zhang
Exploring the crop production water footprint and their driving factors is of significant importance for management of agricultural water resources. However, how do we effectively assess the total agricultural water consumption and explore the significan...
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