Applied Sciences (Jun 2022)

Development of an Algorithm for Rapid Herd Evaluation and Predicting Milk Yield of Mastitis Cows Based on Infrared Thermography

  • Artyom R. Khakimov,
  • Dmitriy Y. Pavkin,
  • Sergey S. Yurochka,
  • Maksim E. Astashev,
  • Igor M. Dovlatov

DOI
https://doi.org/10.3390/app12136621
Journal volume & issue
Vol. 12, no. 13
p. 6621

Abstract

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The aim of this study was to explore the possibility of assessing the health status of a cow’s udder using infrared thermography. We studied the effect of mastitis on cow milk yield, the effect of mastitis on udder surface skin temperature, and the dependence between severity of mastitis and udder temperature. We determined the presence of a significant relationship between the udder surface skin temperature and the milk yield of mastitis cows (Coefficient of determination = 0.886, linear Pearson correlation coefficient = −0.96), as well as the absence of a significant relationship between the udder surface skin temperature and the milk yield of healthy cows (Coefficient of determination = 0.029, linear Pearson correlation coefficient = 0.16). We substantiated the temperature ranges of the udder surface of healthy cows [32–35.9 °C] and mastitis [36.1–39 °C]. The obtained data made it possible to form an algorithm that allows a quick assessment of the herd for the presence of udder disease, using infrared images of the udder surface skin temperature.

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