Recent Trends of Machine Learning Techniques on The Growth of Agricultural Sector of Assam

Abstract

The agricultural sector in Assam, India, holds immense potential for economic growth and rural development. However, harnessing this potential requires tackling challenges like low productivity, resource scarcity, and climate change. Machine learning (ML) emerges as a promising tool to address these hurdles and transform Assam’s agricultural sector. This review investigates the potential of machine learning (ML) techniques in driving agricultural growth within the specific context of the Assam’s economy. Utilizing comprehensive search within Scopus and Web of Science databases from 2015 to 2023, and following the PRISMA guidelines, we analyzed 37 relevant articles. Our examination focuses on the multifaceted applications of ML across various agricultural domains in Assam, encompassing crop yield prediction, soil health analysis and economic growth. The review highlights successful ML- driven interventions in Assam’s agricultural sector, showcasing their ability to improve resource efficiency, optimize crop management, and enhance market access. This review provides valuable insights for policymakers, researchers, and farmers seeking to leverage the power of ML for a more sustainable and prosperous Assam’s agricultural landscape.