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Research article2024Peer reviewedOpen access

Social network analysis to predict social behavior in dairy cattle

Marina, H.; Fikse, W. F.; Ronnegard, L.

Abstract

Dairy cattle are frequently housed in freestalls with limited space, affecting social interactions between individuals. Social behavior in dairy cattle is gaining recognition as a valuable tool for identifying sick animals, but its application is hampered by the complexities of analyzing social interactions in intensive housing systems. In this context, precision livestock technologies present the opportunity to continuously monitor dyadic spatial associations on dairy farms. The aim of this study is to evaluate the accuracy of predicting social behavior of dairy cows using social network analysis. Daily social networks were built using the position data from 149 cows over 14 consecutive days of the study period. We applied the separable temporal exponential random graph models to estimate the likelihood of formation and persistence of social contacts between dairy cows individually and to predict the social network on the subsequent day. The correlation between the individual degree centrality values, the number of established social contacts per individual, between the predicted and observed networks ranged from 0.22 to 0.49 when the structural information from network triangles was included in the model. This study presents a novel approach for predicting animal social behavior in intensive housing systems using spatial association information obtained from a real-time location system. The results indicate the potential of this approach as a crucial step toward the larger goal of identifying disruptions in dairy cows' expected social behavior.

Published in

JDS communications
2024, volume: 5, number: 6, pages: 608-612
Publisher: ELSEVIER

SLU Authors

UKÄ Subject classification

Animal and Dairy Science

Publication identifier

  • DOI: https://doi.org/10.3168/jdsc.2023-0507

Permanent link to this page (URI)

https://res.slu.se/id/publ/139508