Computer Science > Artificial Intelligence
[Submitted on 3 May 2023 (v1), last revised 26 Sep 2024 (this version, v2)]
Title:Empowering Agrifood System with Artificial Intelligence: A Survey of the Progress, Challenges and Opportunities
View PDF HTML (experimental)Abstract:With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages. Recently, artificial intelligence (AI) techniques such as deep learning (DL) have demonstrated their strong abilities in various areas, including language, vision, remote sensing (RS), and agrifood systems applications. However, the overall impact of AI on agrifood systems remains unclear. In this paper, we thoroughly review how AI techniques can transform agrifood systems and contribute to the modern agrifood industry. Firstly, we summarize the data acquisition methods in agrifood systems, including acquisition, storage, and processing techniques. Secondly, we present a progress review of AI methods in agrifood systems, specifically in agriculture, animal husbandry, and fishery, covering topics such as agrifood classification, growth monitoring, yield prediction, and quality assessment. Furthermore, we highlight potential challenges and promising research opportunities for transforming modern agrifood systems with AI. We hope this survey could offer an overall picture to newcomers in the field and serve as a starting point for their further research. The project website is this https URL.
Submission history
From: Di Wang [view email][v1] Wed, 3 May 2023 05:16:54 UTC (7,975 KB)
[v2] Thu, 26 Sep 2024 13:34:35 UTC (10,749 KB)
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