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Data mining as a hatchery process evaluation tool
Klein, Daniela Regina; Vale, Marcos Martinez do; Silva, Mariana Fernandes Ribas da; Kuhn, Micheli Faccin; Branco, Tatiane; Santos, Mauricio Portella dos.
Afiliação
  • Klein, Daniela Regina; Universidade Federal de Santa Maria. Depto. de Zootecnia. Santa Maria. BR
  • Vale, Marcos Martinez do; Universidade Federal do Paraná. Depto. de Zootecnia. Curitiba. BR
  • Silva, Mariana Fernandes Ribas da; Universidade Federal do Rio Grande do Sul. Depto. de Zootecnia. Porto Alegre. BR
  • Kuhn, Micheli Faccin; Universidade Federal de Santa Maria. Depto. de Zootecnia. Santa Maria. BR
  • Branco, Tatiane; Universidade Estatual de Campinas. Faculdade de Engenharia Agrícola. Depto. de Construções Rurais e Ambiência. Campinas. BR
  • Santos, Mauricio Portella dos; Universidade Federal de Santa Maria. Depto. de Zootecnia. Santa Maria. BR
Sci. agric ; 77(4): e20180074, 2020. tab, ilus
Article em En | VETINDEX | ID: biblio-1497865
Biblioteca responsável: BR68.1
Localização: BR68.1
ABSTRACT
The hatchery is one of the most important segments of the poultry chain, and generates an abundance of data, which, when analyzed, allow for identifying critical points of the process . The aim of this study was to evaluate the applicability of the data mining technique to databases of egg incubation of broiler breeders and laying hen breeders. The study uses a database recording egg incubation from broiler breeders housed in pens with shavings used for litters in natural mating, as well as laying hen breeders housed in cages using an artificial insemination mating system. The data mining technique (DM) was applied to analyses in a classification task, using the type of breeder and house system for delineating classes. The database was analyzed in three different ways original database, attribute selection, and expert analysis. Models were selected on the basis of model precision and class accuracy. The data mining technique allowed for the classification of hatchery fertile eggs from different genetic groups, as well as hatching rates and the percentage of fertile eggs (the attributes with the greatest classification power). Broiler breeders showed higher fertility (> 95 %), but higher embryonic mortality between the third and seventh day post-hatching (> 0.5 %) when compared to laying hen breeders eggs. In conclusion, applying data mining to the hatchery process, selection of attributes and strategies based on the experience of experts can improve model performance.
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