Discussing the present, past, and future of Machine learning techniques in livestock farming: A systematic literature review
Rita Roy, Manish Mohan Baral, Surya Kant Pal, Santosh Kumar, Subhodeep Mukherjee, Bhaswati Jana
Abstract
The digital revolution of livestock production has converted various planning functions into artificially intelligent systems to obtain information from different sources. Machine learning (ML), a subset of artificial intelligence, has a high potential for handling multiple difficulties for the organisations of information-based systems. The current study provides insights on ML in livestock farming by comprehensively reviewing recent academic articles using keyword combinations and in full compliance with PRISMA guidelines. This article extracted 216 articles from the literature review and, after the proper selection process, only considered 144 articles for further study. This study presents the past, present, and future of ML in livestock farming. This study will act as a source of information in both the research world and industry to know the future of ML in livestock production.