Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

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

Khanashyam, Anandu Chandra ; Jagtap, Sandeep LU orcid ; Agrawal, Tarun Kumar ; Thorakkattu, Priyamvada ; Malav, Om Prakash ; Trollman, Hana ; Hassoun, Abdo ; Ramesh, Bharathi ; Manoj, Vishnu and Rathnakumar, Kaavya , et al. (2025) In Computers and Electronics in Agriculture 238.
Abstract
The 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... (More)
The 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. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Computers and Electronics in Agriculture
volume
238
article number
110879
pages
12 pages
publisher
Elsevier
external identifiers
  • scopus:105013289933
ISSN
0168-1699
DOI
10.1016/j.compag.2025.110879
language
English
LU publication?
yes
id
cf0d8f54-9e4b-4663-ab07-67ab72dcf80f
date added to LUP
2025-08-14 10:32:32
date last changed
2025-09-25 03:35:08
@article{cf0d8f54-9e4b-4663-ab07-67ab72dcf80f,
  abstract     = {{The 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.}},
  author       = {{Khanashyam, Anandu Chandra and Jagtap, Sandeep and Agrawal, Tarun Kumar and Thorakkattu, Priyamvada and Malav, Om Prakash and Trollman, Hana and Hassoun, Abdo and Ramesh, Bharathi and Manoj, Vishnu and Rathnakumar, Kaavya and Bekhit, Alaa El-Din A and Nirmal, Nilesh}},
  issn         = {{0168-1699}},
  language     = {{eng}},
  month        = {{08}},
  publisher    = {{Elsevier}},
  series       = {{Computers and Electronics in Agriculture}},
  title        = {{Applications of artificial intelligence in the dairy Industry : from farm to product development}},
  url          = {{http://dx.doi.org/10.1016/j.compag.2025.110879}},
  doi          = {{10.1016/j.compag.2025.110879}},
  volume       = {{238}},
  year         = {{2025}},
}