Vicky Anand1, Priyadarshani Rajput1, Tatiana Minkina1, Saglara Mandzhieva1, Santosh Kumar2, Avnish Chauhan3, Vishnu D. Rajput1,*
Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1339-1365, 2025, DOI:10.32604/phyton.2025.063927
- 29 May 2025
Abstract The digital revolution in agriculture has introduced data-driven decision-making, where artificial intelligence, especially machine learning (ML), helps analyze large and varied data sources to improve soil quality and crop growth indices. Thus, a thorough evaluation of scientific publications from 2007 to 2024 was conducted via the Scopus and Web of Science databases with the PRISMA guidelines to determine the realistic role of ML in soil health and crop improvement under the SDGs. In addition, the present review focused to identify and analyze the trends, challenges, and opportunities associated with the successful implementation of ML in… More >
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