TY - JOUR
T1 - Harnessing digital twins: transforming livestock supply chain management: a comprehensive review
AU - Ellahia, Rizwan Matloob
AU - Ali, Mahmood
AU - Ali Shah, Syed Adeel
AU - Qureshi, Muhammad Azeem
AU - Gulzar, Saba
AU - Wood, Lincoln C.
AU - Ahmed Bekhit, Alaa El-Din
PY - 2026/1/10
Y1 - 2026/1/10
N2 - This review examines the integration of digital twin (DT) technology in livestock supply chain management, with particular attention to cattle and dairy systems, emphasizing stakeholder perspectives and its role in advancing sustainability and agricultural productivity. Positioned within the frameworks of Industry 4.0 and Agriculture 4.0, DT adoption offers opportunities for precision farming by enhancing decision-making, transparency, and efficiency. Stakeholders including farmers, distributors, government agencies, technology developers, and consumers acknowledge DTs’ potential benefits but also highlight concerns related to cost, technical expertise, data privacy, scalability, and infrastructure readiness. The review evaluates the effectiveness of DTs in improving livestock management through health monitoring, disease prevention, behavior and sentience analysis, environmental control, productivity optimization, waste reduction, and cyber-physical system integration. Additional applications include colostrum management, teat shape classification, virtual livestock farms, pasture monitoring, predictive modeling, and integrated farm data, demonstrating their transformative role in food production systems and sustainable agriculture. A conceptual framework has been developed to illustrate the essential contributions of DT technology across the livestock sector, aiming to guide researchers and practitioners in understanding applications and identifying future directions for effective implementation. Despite promising advances, barriers to large-scale adoption persist, particularly in developing regions where issues of data availability, high costs, and technological complexity hinder deployment. Future research should focus on strengthening model robustness and developing interdisciplinary frameworks to address diverse contexts, thereby improving the generalizability and practical utility of DT technology in livestock, dairy, and broader agricultural systems.
AB - This review examines the integration of digital twin (DT) technology in livestock supply chain management, with particular attention to cattle and dairy systems, emphasizing stakeholder perspectives and its role in advancing sustainability and agricultural productivity. Positioned within the frameworks of Industry 4.0 and Agriculture 4.0, DT adoption offers opportunities for precision farming by enhancing decision-making, transparency, and efficiency. Stakeholders including farmers, distributors, government agencies, technology developers, and consumers acknowledge DTs’ potential benefits but also highlight concerns related to cost, technical expertise, data privacy, scalability, and infrastructure readiness. The review evaluates the effectiveness of DTs in improving livestock management through health monitoring, disease prevention, behavior and sentience analysis, environmental control, productivity optimization, waste reduction, and cyber-physical system integration. Additional applications include colostrum management, teat shape classification, virtual livestock farms, pasture monitoring, predictive modeling, and integrated farm data, demonstrating their transformative role in food production systems and sustainable agriculture. A conceptual framework has been developed to illustrate the essential contributions of DT technology across the livestock sector, aiming to guide researchers and practitioners in understanding applications and identifying future directions for effective implementation. Despite promising advances, barriers to large-scale adoption persist, particularly in developing regions where issues of data availability, high costs, and technological complexity hinder deployment. Future research should focus on strengthening model robustness and developing interdisciplinary frameworks to address diverse contexts, thereby improving the generalizability and practical utility of DT technology in livestock, dairy, and broader agricultural systems.
U2 - 10.1080/23311932.2025.2611196
DO - 10.1080/23311932.2025.2611196
M3 - Review article
SN - 2331-1932
VL - 12
JO - Cogent Food and Agriculture
JF - Cogent Food and Agriculture
IS - 1
M1 - 2611196
ER -