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Front. Sustain. Food Syst. | doi: 10.3389/fsufs.2018.00080

Comparison of methods for monitoring the body condition of dairy cows

 Matt Bell1*, Mareike Maak1, Marion Sorley1 and Robert Proud1
  • 1Department of Biosciences, University of Nottingham, United Kingdom

Dairy cows are known to mobilise body fat to achieve their genetic potential for milk production, which can have a detrimental impact on the health, fertility and survival of the cow. Better monitoring of cows with poor body condition (low or high body fat) will lead to improvements in production efficiencies and less wasted resources when producing milk from dairy cows. The aim of this study was to compare different methods for monitoring the body condition (body fat) of dairy cows. The methods used to measure body condition were: ultrasound scanner, manual observation, and a still digital image of the cow. For comparison, each measure was expressed as a body condition score (BCS) on a scale of extremely thin (1) to very fat (5) in quarter intervals. A total of 209 cows at various stages of lactation were assessed. Lin’s concordance correlation coefficient (CCC) and the root mean square prediction error (RMSPE) were used to compare the accuracy of methods. The average BCS across cows was 2.10 for ultrasound, 2.76 for manual and 2.41 for digital methods. The study found that both manual (r = 0.790) and digital (r = 0.819) approaches for monitoring cow body condition were highly correlated with ultrasound BCS measurements. After adjusting correlation coefficients for prediction bias relative to a 45 line through the origin, the digital BCS had a higher CCC of 0.789 when compared to the ultrasound BCS than the manual BCS with a CCC of 0.592. The digital BCS also had a lower prediction error (RMSPE = 28.3%) when compared with ultrasound BCS than the manual BCS (RMSPE = 42.7%). The prediction error for digital and manual BCS methods were similar for cows with a BCS of 2.5 or more (RMSPE = 20.5% and 19.0% respectively) but digital BCS was more accurate for cows of less than 2.5 BCS (RMSPE = 35.5% and 63.8% respectively). Digital BCS can provide a more accurate assessment of cow body fat than manual BCS observations, with the added benefit of more automated and frequent monitoring potentially improving the welfare and sustainability of high production systems.

Keywords: Cattle, body fat, Objective assessment, Health, wellbeing

Received: 24 Jul 2018; Accepted: 08 Nov 2018.

Edited by:

Will Peach, Royal Society for the Protection of Birds, United Kingdom

Reviewed by:

Yiorgos Gadanakis, University of Reading, United Kingdom
Emma L. Burns, Australian National University, Australia  

Copyright: © 2018 Bell, Maak, Sorley and Proud. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Matt Bell, Department of Biosciences, University of Nottingham, Loughborough, United Kingdom, matt.bell@nottingham.ac.uk