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Environmental variables responsible for Zebu cattle thermal comfort acquisition.

Authors
  • Volpi, Denise1
  • Alves, Fabiana Villa2
  • da Silva Arguelho, Alan3
  • do Vale, Marcos Martinez4
  • Deniz, Matheus4
  • Zopollatto, Maity4
  • 1 Department of Animal Science, Federal University of Parana, 540 Funcionarios St., Curitiba, Parana, 80035050, Brazil. [email protected] , (Brazil)
  • 2 Embrapa Beef Cattle, Brazilian Agricultural Research Corporation, Campo Grande, Mato Grosso do Sul, Brazil. , (Brazil)
  • 3 Department of Animal Science, State University of Mato Grosso do Sul, Aquidauana, Mato Grosso do Sul, Brazil. , (Brazil)
  • 4 Department of Animal Science, Federal University of Parana, 540 Funcionarios St., Curitiba, Parana, 80035050, Brazil. , (Brazil)
Type
Published Article
Journal
International journal of biometeorology
Publication Date
Oct 01, 2021
Volume
65
Issue
10
Pages
1695–1705
Identifiers
DOI: 10.1007/s00484-021-02124-x
PMID: 33830324
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

The aim of this study was to estimate, using data mining, which microclimate and behavioral variables affect the behavior of animals to seek shaded or sunny areas. The experiment was carried out between January and May 2016 in an integrated crop-livestock-forest system. In this system, we defined two different areas: shaded and sunny. Microclimatic variables (At, BGt, RH, and WS) were measured in each area on 4 consecutive days per month. With these variables, we determined the bioclimatic indicators (THI, BGHI, HLI, MRT, RTL, and ETI). In addition, we calculated the absolute difference (Δ) by subtracting the value recorded in shaded areas from the value recorded in sunny areas for all microclimatic variables and bioclimatic indicators, except for WS. The behaviors (grazing, ruminating, and other activities), posture (standing or lying), and use of areas (shaded or sunny) of 38 Zebu cattle were recorded on 2 consecutive days per month. The data mining technique was applied for analysis in a classification task. The model correctly classified 76% of the instances with a Kappa statistic of 0.51 after features selection from the database. The ΔBGt was the most important feature in the model to classify the decision of Zebu cattle to seek another area or remain in a determined area. The model was built with seven classification rules, being one simple rule, composed of the interaction between ΔBGt and rumination; and other more complex rules, composed of the interactions among the ΔBGt, WS, and rumination. The preference of Zebu cattle to seek or remain in shaded or sunny areas was influenced by eight features: rumination, drinking water, WS, ΔBGt, MRT in shade, BGHI in sun, ΔBGHI, and HLI in sun. © 2021. ISB.

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