4.7 Article

A mechanistic thermal balance model of dairy cattle

Journal

BIOSYSTEMS ENGINEERING
Volume 209, Issue -, Pages 256-270

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2021.06.009

Keywords

Dairy cow; Thermal balance model; Heat stress

Funding

  1. W. K. Kellogg Endowment
  2. USDA National Institute of Food and Agriculture (Washington, DC) Multistate Research Project [NC2040]

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A dynamic model was developed to predict the thermal balance of Holstein dairy cattle, showing sensitivity to heat production, surface area, respiration, and sweating parameters. The model accurately simulated body temperatures under typical summer conditions in California, providing insights for the use of cooling strategies in dairy facilities.
A dynamic model describing the thermal balance of Holstein dairy cattle was developed. The model quantified the heat flow of five main nodes at the body core, top and bottom skin, and top and bottom coat of a dairy cow. Heat production by the animal and heat flows between the animal and the environment, including conduction, convection, evaporation and radiation, were calculated based on existing models and physical principles. The model requires information of climate, animal characteristics and location as inputs, and returns body core, skin and coat temperatures as outputs. The thermal balance model was evaluated through two datasets. The root mean squared error of prediction for body temperature was 1.16 degrees C and 0.40 degrees C for the two datasets, respectively. A simulation study was conducted based on a Holstein dairy cow with 600 kg of body weight and 25 kg of daily milk yield under a typical summer environment in California, USA for three days. The average simulated temperatures of body, top and bottom skin, and top and bottom coat were 40.9, 35.6, 35.9, 34.1 and 33.7 degrees C, respectively. A local and a global sensitivity analyses showed that heat production, surface area and the parameters relative to respiration and sweating were the most sensitive. The model is able to predict the dynamic change of body temperature under hot weather, and to guide the use of physical cooling strategies, such as shade, fans, sprinklers and cooling mats in dairy facilities. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of IAgrE.

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