Artificial Neural Networks for Chicks Body Mass Prediction

 

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Detalles Bibliográficos
Autores: Ponciano-Ferraz, Patricia Ferreira, Yanagi Junior, Tadayuki, Hernández Julio, Yamid Fabián, e-Silva-Ferraz, Gabriel Araújo, Cecchin, Daiane
Formato: artículo original
Estado:Versión publicada
Fecha de Publicación:2019
Descripción:The thermal environment inside a broiler house has a great influence on animal welfare and productivity during the production phase. Thus, the aim of this study was to predict body mass of chicks from 2 to 21 days of age when subjected to different intensities (27, 30, 33 and 36°C) and duration (1, 2, 3 and 4 days starting on the second day of life) using artificial neural networks (ANN). This experiment was conducted at Lavras, MG, Brazil. It was used 210 chicks of both sexes, from 1st to 22nd days of life. The chicks were raised inside four climate-controlled wind tunnels. Daily the weight of all the chicks was measured to know the daily body masses. The input variables were dry-bulb air temperature, duration of thermal stress, chick age, and the output variable was the daily body mass of chicks. A database containing 840 records was used to train (70% of data), validate (15%) and test (15%) of models based on artificial neural networks (ANN). Between these models, the ANN was accurate in predicting the BM of chicks from 2 to 21 days of age after they were subjected to the input variables, and it had an R2 of 0.9992 and a standard error of 5,23 g. This model enables the simulation of different scenarios that can assist in managerial decision-making, and it can be embedded in the heating controls.
País:RepositorioTEC
Institución:Instituto Tecnológico de Costa Rica
Repositorio:RepositorioTEC
Lenguaje:Español
OAI Identifier:oai:repositoriotec.tec.ac.cr:2238/11920
Acceso en línea:https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4266
https://hdl.handle.net/2238/11920
Access Level:acceso abierto
Palabra clave:Animal welfare
artificial intelligence
chicks
thermal comfort
Bienestar animal
inteligencia artificial
pollitos
confort térmico