ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS

Jonathan Masasi (), John N. Ng’ombe and Blessing Masasi
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Jonathan Masasi: Department of Agribusiness, Applied Economics and Agriscience Education, North Carolina A&T State University, Greensboro, NC 27411, USA
John N. Ng’ombe: Department of Agribusiness, Applied Economics and Agriscience Education, North Carolina A&T State University, Greensboro, NC 27411, USA
Blessing Masasi: Department of Natural Resources and Environmental Design, North Carolina A&T State University, Greensboro, NC 27411, USA

Big Data In Agriculture (BDA), 2024, vol. 6, issue 2, 113-116

Abstract: Artificial intelligence (AI) presents an opportunity to offer innovative solutions to long-standing challenges in agriculture. This review study provides an overview of AI applications in agriculture, focusing on its applications to predict and monitor crop growth rate and yield, climate change and weather patterns, pests and diseases management, weed management, animal production, agricultural machinery, crop irrigation, and soil management, and crop fertilization. AI technologies, including machine learning, computer vision, and precision agriculture, are explored. This review highlights the significant potential of AI to improve agricultural productivity, efficiency, and sustainability. Furthermore, the challenges and limitations of AI adoption in agriculture, including data quality and availability, infrastructure requirements, and ethical considerations, are also discussed. Overall, this study demonstrates the transformative power of AI in agriculture and highlights the need for continued research and investment in this critical field to build more resilient and sustainable agricultural production systems.

Keywords: Artificial intelligence; agriculture; machine learning; deep learning (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnbda:v:6:y:2024:i:2:p:113-116

DOI: 10.26480/bda.02.2024.113.116

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