Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/11682
Título: Using data mining to identify factors that influence the degree of leg injuries in broilers
Título(s) alternativo(s): Uso de mineração de dados para identificação de fatores que influenciam o grau de lesões de perna em frangos de corte
Palavras-chave: Árvore de decisão
Avicultura
Gait score
Decision trees
Aviculture
Data do documento: 2012
Editor: Associação Brasileira de Engenharia Agrícola
Citação: CORDEIRO, A. F. da S. et al. Using data mining to identify factors that influence the degree of leg injuries in broilers. Engenharia Agrícola, Jaboticabal, v. 32, n. 4, p. 642-649, jul./ago. 2012.
Resumo: Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.
URI: http://repositorio.ufla.br/jspui/handle/1/11682
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