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.
Keywords: Ambience; Bos taurus indicus; Data mining; Heat stress; Knowledge discovery in databases; Precision livestock farming.
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