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| Lovato,Gustavo Dias; Vale,Marcos Martinez do; Oliveira,Vladimir de; Klein,Daniela Regina; Branco,Tatiane. |
| ABSTRACT The objective of this study was to evaluate a growth model applied to adjust nutritional programs for growing and finishing pigs, in a commercial production context. The phase I (calibration) was conducted in a commercial pig production unit. The data were collected from a nutritional program, a feed program, and an animal profile. In experimental phase II, these data were entered in the InraPorc® model for simulations and to propose adjustments to the commercial nutritional program. Afterwards, the conventional nutritional program (CNP) and the adjusted nutritional program (ANP) were compared with InraPorc® simulation. Animal profile was collected by weighing 30% of pigs per stall and monitoring their feed intake in each stage. Four hundred and... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: InraPorc®; Modeling; Pig production; Temperature. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017000900755 |
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| Klein,Daniela Regina; Vale,Marcos Martinez do; Silva,Mariana Fernandes Ribas da; Kuhn,Micheli Faccin; Branco,Tatiane; Santos,Mauricio Portella dos. |
| 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... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Attribute selection; Classification tree; Data management; Data mining and information technology. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000400501 |
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