Applications of artificial intelligence in the dairy Industry: From farm to product development

dc.contributor.authorKhanashyam A.C.
dc.contributor.authorJagtap S.
dc.contributor.authorAgrawal T.K.
dc.contributor.authorThorakkattu P.
dc.contributor.authorMalav O.P.
dc.contributor.authorTrollman H.
dc.contributor.authorHassoun A.
dc.contributor.authorRamesh B.
dc.contributor.authorManoj V.
dc.contributor.authorRathnakumar K.
dc.contributor.authorBekhit A.E.D.A.
dc.contributor.authorNirmal N.
dc.contributor.correspondenceKhanashyam A.C.
dc.contributor.otherMahidol University
dc.date.accessioned2025-08-24T18:18:44Z
dc.date.available2025-08-24T18:18:44Z
dc.date.issued2025-11-01
dc.description.abstractThe dairy industry faces increasing demand for enhanced productivity, sustainability, and innovation. Artificial Intelligence (AI) has emerged as a transformative tool capable of addressing these challenges by enabling data-driven decision-making across the dairy supply chain. AI integrates machine learning (ML), big data analytics (DA), and predictive algorithms (PA) to optimize processes, improve efficiency, and foster innovation. This review examines the diverse applications of AI in the dairy industry, including dairy farming, processing, and product development. In this context, an overview of AI, including ML, DA, and various algorithms used in these processes, is discussed. A major discussion has been provided on AI for animal performance (e.g., disease detection, reproductive management, milk yield enhancement, nutrition) and sustainable practices (e.g., emission control, precision farming). Furthermore, AI in dairy processing (quality control and process optimization) and product development (flavor and texture prediction, and customized products) has been developed. Finally, the challenges of AI integration, including data privacy, ethical considerations, and technical barriers, are reported. The findings indicate that AI revolutionizes traditional practices by enabling precise farming, energy-efficient processing, and the creation of customized, high-quality products. Despite its transformative potential, challenges, such as ethical concerns and technological limitations, must be addressed.
dc.identifier.citationComputers and Electronics in Agriculture Vol.238 (2025)
dc.identifier.doi10.1016/j.compag.2025.110879
dc.identifier.issn01681699
dc.identifier.scopus2-s2.0-105013289933
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/111806
dc.rights.holderSCOPUS
dc.subjectAgricultural and Biological Sciences
dc.subjectComputer Science
dc.titleApplications of artificial intelligence in the dairy Industry: From farm to product development
dc.typeReview
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105013289933&origin=inward
oaire.citation.titleComputers and Electronics in Agriculture
oaire.citation.volume238
oairecerif.author.affiliationUniversity of Minnesota Twin Cities
oairecerif.author.affiliationUniversity of Wisconsin-Madison
oairecerif.author.affiliationIcahn School of Medicine at Mount Sinai
oairecerif.author.affiliationChalmers University of Technology
oairecerif.author.affiliationUniversity of Otago
oairecerif.author.affiliationMahidol University
oairecerif.author.affiliationKansas State University
oairecerif.author.affiliationCranfield University
oairecerif.author.affiliationLunds Tekniska Högskola
oairecerif.author.affiliationGuru Angad Dev Veterinary and Animal Sciences University
oairecerif.author.affiliationUniversity of Aleppo
oairecerif.author.affiliationUniversity of Leicester School of Business
oairecerif.author.affiliationTKM Institute of Technology
oairecerif.author.affiliationSustainable AgriFoodtech Innovation and Research (SAFIR)

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