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Universidade Estadual Paulista (UNESP) 2014

Modelo computacional para previsão de mortalidade de galinhas poedeiras em função de ondas de calor e tipologia dos aviários

Riquena, Rodrigo da Silva

Titre : Modelo computacional para previsão de mortalidade de galinhas poedeiras em função de ondas de calor e tipologia dos aviários

Computational model for prediction of laying hens mortality due to heat waves and avian typology

Auteur : Riquena, Rodrigo da Silva

Université de soutenance : Universidade Estadual Paulista (UNESP)

Grade : Mestre em Agronegócio e Desenvolvimento. 2014

Résumé
Mortality in the production of laying hens is a concern for producers and constitutes a considerable economic loss. Some climatic events, such as heat waves, are directly related to increase of mortality. The aim of this work was to relate the occurrence of heat waves with laying hens mortality, considering the effect of two different typologies of shed used in egg production. Daily mortality data were obtained from two aviaries located in the city of Bastos-SP for the period from October 2014 to January 2016. To standardize the collection of information, a tool was created to record daily mortality on the farm. The climate data were obtained from two meteorological stations located in the cities of Tupã-SP and Rancharia-SP for the period from 2010 to 2015. The heat waves were classified in the climatic database using different definitions of the literature. Mortality and climate data were related in a single database and were classified into normal and high mortality according to the lineage manual. After being related the data were taken to mining, the technique used was the CRISP-DM using the algorithm J48. The classification for INMET heat waves was the most adequate for region. It was possible to associate the occurrences of heat wave to the increase of laying hens mortality and the constructive variables of the aviaries influence the mortality and production. The classification tree generated accurately identified 71% of occurrences of high mortality and 95% of all mortality data. The classification tree allowed to relate the increase in laying mortality as a function of heat waves and allows a forecast of when there is a higher chance of high mortality occur

Mots Clés : Mineração de dados Avicultura de postura Mudanças climáticas Zootecnia de precisão Data mining Poultry farming Climate changes Animal husbandry

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