The use of artificial intelligence for the prediction of productivity parameters in swine culture

• Autor(a) principal: Sangoi, Luiz Fernando
• Data de Publicação: 2016
• Outros Autores: Kessler, Alexandre de Mello, Neuenfeldt Junior, Álvaro Luiz, Siluk, Julio Cezar Mairesse, Ribeiro, Andrea Machado Leal, Soliman, Marlon
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/185851
• topic: Suinocultura; Produtividade; Competitividade; Inteligência artificial; Swine culture; Artificial neural networks; Competitiveness

In similar conditions of food handling and genetics, there are large differences in the final productivity of farms, resulting from inherent factors of the production system. This fact predisposes the need of studies on optimizing the rearing conditions of the farms, in order to verify the main limitations for the producers. Therefore, the present study aims to generate predictions of the swine productivity in the finishing phase, using variables related to their profiles and the production results achieved. 107 farmers belonging to a swine cooperative were considered in the study, located in 47 counties at the Taquari valley region, Brazil. Predictions were generated through the aid of neural networks, and the findings show that Artificial Neural Networks (ANN) can predict the productivity variables Feed Conversion, Mortality and Average Daily Gain for the proposed case.