Implementing artificial intelligence and machine learning algorithms for optimized crop management: a systematic review on data-driven approach to enhancing resource use and agricultural sustainability

Implementing artificial intelligence and machine learning algorithms for optimized crop management: a systematic review on data-driven approach to enhancing resource use and agricultural sustainability

<p>Artificial intelligence (AI) and machine learning (ML) are transforming agriculture by enabling data-driven decisions that elevate productivity and sustainability. This review synthesises 95 studies published between 2013 and 2023 that evaluate applications across crop monitoring, yield pre...

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Bibliographic Details
Main Author: Okechukwu Paul-Chima Ugwu (21578037) (author)
Other Authors: Fabian C. Ogenyi (21578049) (author), Esther Ugo Alum (20880703) (author), Val Hyginus Udoka Eze (21578043) (author), Mariam Basajja (22188196) (author), Jovita Nnenna Ugwu (21578040) (author), Chinyere N. Ugwu (21578046) (author), Regina Idu Ejemot-Nwadiaro (15245416) (author), Michael Ben Okon (21578052) (author), Simeon Ikechukwu Egba (22438849) (author), Uti Daniel Ejim (22438852) (author)
Published: 2025
Subjects:
Medicine
Biotechnology
Ecology
Science Policy
Plant Biology
Information Systems not elsewhere classified
Artificial intelligence (AI)
machine learning (ML)
precision agriculture
neural networks
crop yield prediction
smart irrigation and sustainable farming
Artificial Intelligence
Computer Science (General)
Computer Engineering
Databases
Information & Communication Technology (ICT)
Computing & IT Security
Software Engineering & Systems Development
Supercomputing
Networks
Plant Engineering & Maintenance
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