Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens (Research, Society and Development, 2021)
Laying poultry is constantly evolving, with the use of technologies that help the producer to obtain better productivity and, allied to this, the commitment to the welfare of the birds. One of the environmental factors that directly affect these issues is the heat stress that can affect birds due to hot flashes. To mitigate these negative effects, bioclimatic monitoring is carried out, this survey can be used for analyzes that will provide a better view, as is the case with data mining that generates decision trees. Therefore, the objective of this study was to develop decision trees using the data mining tool, as a subsidy for warning systems from the Black Globe Temperature and Humidity Index (BGTHI), mitigating the damage that can be caused by climatic extremes in the production and quality of laying eggs. For this purpose, a data set of three aviaries located in the city of Bastos-SP, collected in the summer season of 2013/2014, was used. These data were selected and organized in Excel® spreadsheets and the BGTHI was calculated, classifying them in comfort bands, after being processed with the Weka® software with J48 algorithm (C4.5) performing data mining. The decision trees generated for each aviary showed a similar behavior, with two branches classified as comfortable or warm, and the BGTHI value was very close, differing only in decimal places. For aviaries A1 and A2 excellent Kappa coefficients were obtained, whereas in A3 this coefficient did not obtain a good classification.