Validation of an Automated Body Condition Scoring System Using 3D Imaging

Niall O’ Leary, Lorenzo Leso, Frank Buckley, Jonathon Kenneally, Diarmuid McSweeney and Laurence Shalloo
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Niall O’ Leary: Hincks Centre For Entrepreneurial Excellence, Cork Institute of Technology, Cork, T12 P928 Co. Cork, Ireland
Lorenzo Leso: Department of Agricultural, Food and Forestry Systems, University of Florence, 50145 Firenze, Italy
Frank Buckley: Moorepark Animal & Grassland Research and Innovation Centre, Teagasc, Fermoy, P61 C997 Co. Cork, Ireland
Jonathon Kenneally: Moorepark Animal & Grassland Research and Innovation Centre, Teagasc, Fermoy, P61 C997 Co. Cork, Ireland
Diarmuid McSweeney: Unit 2, True North Technologies, Shannon Business Centre, Shannon, V14 YT99 Co. Clare, Ireland
Laurence Shalloo: Moorepark Animal & Grassland Research and Innovation Centre, Teagasc, Fermoy, P61 C997 Co. Cork, Ireland

Agriculture, 2020, vol. 10, issue 6, 1-8

Abstract: Body condition scores (BCS) measure a cow’s fat reserves and is important for management and research. Manual BCS assessment is subjective, time-consuming, and requires trained personnel. The BodyMat F (BMF, Ingenera SA, Cureglia, Switzerland) is an automated body condition scoring system using a 3D sensor to estimate BCS. This study assesses the BMF. One hundred and three Holstein Friesian cows were assessed by the BMF and two assessors throughout a lactation. The BMF output is in the 0–5 scale commonly used in France. We develop and report the first equation to convert these scores to the 1–5 scale used by the assessors in Ireland in this study ((0–5 scale × 0.38) + 1.67 → 1–5 scale). Inter-assessor agreement as measured by Lin’s concordance of correlation was 0.67. BMF agreement with the mean of the two assessors was the same as between assessors (0.67). However, agreement was lower for extreme values, particularly in over-conditioned cows where the BMF underestimated BCS relative to the mean of the two human observers. The BMF outperformed human assessors in terms of reproducibility and thus is likely to be especially useful in research contexts. This is the second independent validation of a commercially marketed body condition scoring system as far as the authors are aware. Comparing the results here with the published evaluation of the other system, we conclude that the BMF performed as well or better.

Keywords: Body condition score; cows; automated; validation; precision technology (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
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