Use of decision trees from the Globe Temperature and Humidity Index to mitigate heat stress in light laying hens
Keywords:Laying Poultry Farming; Climatic Extremes; Data Mining; Egg Production; Sustentabilidade.
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.
Albuquerque, R. (2004). Tópicos importantes na produção de poedeiras comerciais. Avicultura Industrial, 1121, (95), 53-56.
Buffington, C. S., Collier, R. I., Canton, G. H., (1981). Shade management system heat stress for dairy cows in hot, humid climates. Transations of the ASAE, St. Joseph, 26, n. (6),1798-1802.
Camilo, C. O., Silva, J. C. (2009). Mineração de Dados: Conceitos, Tarefas, Métodos e Ferramentas. Relatório Técnico. Instituto de Informática Universidade Federal de Goiás.
Carvalho, L. C., Romano, G. G., Ivo, M. A., Rodrigues, R. F. (2017). Bem-estar na produção de galinhas poedeiras- Revisão de Literatura. Revista Científica de Medicina Veterinária, 28(1), 1-14.
Carvalho, T. (2020). Estresse térmico em poedeiras: definição do estresse e consequências fisiológicas. Agroceres. Retrieved 14 april from: https://agroceresmultimix.com.br/blog/estresse-termico-em-poedeiras-definicao-do-estresse-e-consequencias-fisiologicas/.
Damasceno, F. A., Gomes, R. C. C., Tinôco, I. F., Souza, F. F. (2010). Mudanças climáticas e suas influências na produção avícola. PUBVET, Londrina. 4, (28), ed. 133, art 901.
Fayyad, U, Piatetsky-Shapiro, G, Smyth, P. (1996). From data mining to knowledge discovery: an overview. Artficial Intelligence Magazine, 17(1), 37-54.
Frank, E., Hall, M. A., Witten, I. H. (2016). The Weka Workbench. Online Appendix for "Data Mining: Practical Machine Learning Tools and Techniques", Morgan Kaufmann, Fourth Edition.1-128.
Kochetov, V. (2018). Overview of different approaches to solving problems of Data Mining. Procedia Computer Science. 123(1), 234-239.
Lawrence, M. G. (2005). The relationship between relative humidity and the dewpoint temperature in moist air. American Meteorological Society. Bulletin, Boston, 225- 233.
Lima, E. S., Souza, Z. M., Montanari, R., Oliveira, S. R. M., Lovera, L. H., Farhate, C. V. V. (2017). Classification of the initial development of eucaliptus using data mining techniques. CERNE, Lavras, 23, (2), 201-208.
Nardone, A., Ronchi, B., Lacetera, N., Bernabucci, U. (2006). Climatic effects on productive traits in livestock. Veterinary Research Communications, 30(1), 75-81.
Pereira, D. F. (2011). Ambiência em frangos de corte. In: CONFERÊNCIA APINCO 2011 DE CIÊNCIA E TECNOLOGIA AVÍCOLAS, Santos. Anais. Campinas-SP: Fundação APINCO de Ciência de Tecnologia Avícolas-FACTA. 113-122.
Pereira, D. F., Vale, M. M., Zevolli, B. R., Salgado, D. D. (2010). Estimating mortality in laying hens as the environmental temperature increases. Brazilian Journal of Poultry Science, 12(4), 265-271.
Riquena, R. S., Pereira, D. F., Vale, M. M., Salgado, D. A. (2019). Mortality prediction of laying hens due to heat waves. Revista Ciência Agronômica, 50((1), 18-26.
Rodrigues, V. C., Vieira, F. M. C., Silva, I. J. O. (2013). Mineração de dados para estimativas de mortalidade pré-abate de frangos de corte. Archivos de zootecnia 62(239), 470.
Salgado, D. D., Nääs, I. A. (2010). Avaliação de risco à produção de frango de corte do Estado de São Paulo em função da temperatura ambiente. Engenharia Agrícola, Jaboticabal, v. 30, n.3, p. 367-376.
Silva, J. H. V., Jordão Filho, J., Silva, E. L., Ribeiro, M. L. G., Furtado, D. A. (2005). Efeito do bebedouro e da densidade de alojamento no desempenho de frangos de corte em alta temperatura. Revista Brasileira de Engenharia Agrícola e Ambiental, 9(1), 636-641.
UBA - União Brasileira de Avicultura. (2008). Protocolo de bem-estar para aves poedeiras. São Paulo: UBA.
Vale, M. M., Moura, D. J., Nääs, I. A., Pereira, D. F. (2010). Characterization of Heat Waves Affecting Mortality Rates of Broilers Between 29 Days and Market Age. Brazillian Journal of Poultry Science. 12(4), 279-285.
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Copyright (c) 2021 Maria Elena Silva Montanhani; Érik dos Santos Harada; Mario Mollo Neto; Silvia Regina Lucas de Souza; Ricardo da Fonseca; Leda Gobbo de Freitas Bueno
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