ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS
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...
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| Format: | Article |
| Language: | English |
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Zibeline International Publishing
2024-07-01
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| Series: | Big Data in Agriculture |
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| Online Access: | http://bigdatainagriculture.com/paper/issue22024/2bda2024-113-116.pdf |
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| author | Jonathan Masasi John N. Ng’ombe Blessing Masasi |
| author_facet | Jonathan Masasi John N. Ng’ombe Blessing Masasi |
| author_sort | Jonathan Masasi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-43da9e4aa727445ca4eb119b328d79f9 |
| institution | Kabale University |
| issn | 2682-7786 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Zibeline International Publishing |
| record_format | Article |
| series | Big Data in Agriculture |
| spelling | doaj-art-43da9e4aa727445ca4eb119b328d79f92025-02-06T03:47:30ZengZibeline International PublishingBig Data in Agriculture2682-77862024-07-016211311610.26480/bda.02.2024.113.116ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONSJonathan Masasi0John N. Ng’ombe1Blessing Masasi2Department of Agribusiness, Applied Economics and Agriscience Education, North Carolina A&T State University, Greensboro, NC 27411, USADepartment of Agribusiness, Applied Economics and Agriscience Education, North Carolina A&T State University, Greensboro, NC 27411, USADepartment of Natural Resources and Environmental Design, North Carolina A&T State University, Greensboro, NC 27411, USAArtificial 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.http://bigdatainagriculture.com/paper/issue22024/2bda2024-113-116.pdfartificial intelligenceagriculturemachine learningdeep learning |
| spellingShingle | Jonathan Masasi John N. Ng’ombe Blessing Masasi ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS Big Data in Agriculture artificial intelligence agriculture machine learning deep learning |
| title | ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS |
| title_full | ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS |
| title_fullStr | ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS |
| title_full_unstemmed | ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS |
| title_short | ARTIFICIAL INTELLIGENCE IN AGRICULTURE: CURRENT TRENDS AND INNOVATIONS |
| title_sort | artificial intelligence in agriculture current trends and innovations |
| topic | artificial intelligence agriculture machine learning deep learning |
| url | http://bigdatainagriculture.com/paper/issue22024/2bda2024-113-116.pdf |
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