Examining the interplay between artificial intelligence and the agri-food industry

IF 8.2 Q1 AGRICULTURE, MULTIDISCIPLINARY Artificial Intelligence in Agriculture Pub Date : 2022-01-01 DOI:10.1016/j.aiia.2022.08.002
Abderahman Rejeb , Karim Rejeb , Suhaiza Zailani , John G. Keogh , Andrea Appolloni
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引用次数: 19

Abstract

Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of AI on agri-food resources and educates practitioners on the significance of knowledge-based and smart agriculture. We utilised bibliometric analysis to investigate the present state of the art and emerging trends in the relationship between AI and the agri-food industry. The research identified three distinct growth phases and the most prevalent AI strategies in the industry. In addition, we analysed key trends and offered researchers and practitioners insightful recommendations for future research. Using resource-based view (RBV) as the theoretical lens, this study established a framework emphasising the long-term effects of AI on various agri-food resources and proposed several research propositions. In addition, AI-related obstacles have been identified and categorised into four major categories. Lastly, the originality of the article lies in its numerous research suggestions and recommendations for advancing the AI field in the agri-food industry.

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研究人工智能与农业食品行业之间的相互作用
人工智能(AI)以惊人的速度发展,并改变了许多经济部门。然而,对于人工智能如何改善农业食品行业,目前还缺乏全面的了解。此外,关于人工智能对农业食品资源的影响以及教育实践者关于知识农业和智慧农业的重要性的研究也明显缺乏。我们利用文献计量学分析来调查人工智能与农业食品工业之间关系的现状和新兴趋势。该研究确定了三个不同的增长阶段和行业中最流行的人工智能战略。此外,我们还分析了主要趋势,并为研究人员和从业者提供了有见地的建议。本研究以资源基础观(resource-based view, RBV)为理论视角,构建了一个强调人工智能对各种农业食品资源的长期影响的框架,并提出了若干研究命题。此外,人工智能相关的障碍已被确定并分为四大类。最后,文章的独创性在于其众多的研究建议和建议,以推进农业食品行业的人工智能领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Artificial Intelligence in Agriculture
Artificial Intelligence in Agriculture Engineering-Engineering (miscellaneous)
CiteScore
21.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊最新文献
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