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Xiaoyu Yin, Jia Li, Jingyi Wu, Ruihan Cao, Siqian Xin and Jianxu Liu
Geographical indications (GIs) mitigate information asymmetry in agri-food transactions by providing consumers with origin and quality information. This paper explores the impact of GIs on rural development in China by examining agricultural output and f...
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Suji Zhu, Bo Wang, Shiqi Pan, Yuting Ye, Enguang Wang and Hanping Mao
Currently, the multi-machine collaboration of agricultural machinery is one of the international frontiers and a topic of research interest in the field of agricultural equipment. However, the multi-machine cooperative operation of agricultural machinery...
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Zihao Zhu and Yonghua Xie
Black soil plays an important role in maintaining a healthy ecosystem, promoting high-yield and efficient agricultural production, and conserving soil resources. In this paper, a typical black soil area of Keshan Farm in Qiqihar City, Heilongjiang Provin...
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Arturs Kempelis, Inese Polaka, Andrejs Romanovs and Antons Patlins
Urban agriculture presents unique challenges, particularly in the context of microclimate monitoring, which is increasingly important in food production. This paper explores the application of convolutional neural networks (CNNs) to forecast key sensor m...
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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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Ibrahim Abdoul Nasser and Elhadi Adam
Urbanisation is the process whereby cities are transformed into large sprawling areas. Urbanisation combined with a continuous increase in population makes food security crucial for sustainable development. Urbanisation poses a threat to agricultural lan...
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Qingyan Wang, Longzhi Sun and Xuan Yang
Rice yield is essential to global food security under increasingly frequent and severe climate change events. Spatial analysis of rice yields becomes more critical for regional action to ensure yields and reduce climate impacts. However, the understandin...
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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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Anderson Carvalho, Daniel Riordan and Joseph Walsh
This study presents a newly developed edge computing platform designed to enhance connectivity between edge devices and the cloud in the agricultural sector. Addressing the challenge of synchronizing a central database across 850 remote farm locations in...
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