Application of a precision nutrition tool for growing and finishing pigs
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 thirty-two pigs with an average initial body weight of 21.9 kg were used in a completely randomized design. There were no differences between treatments, the pig performance was affected by temperature conditions, and the fat thickness was 8% higher for CNP than ANP. In conclusion, the model has advantages to adjust growing and finishing pig nutrition programs and improve environmental and economic aspects.
Main Authors: | , , , , |
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Format: | Digital revista |
Language: | English |
Published: |
Sociedade Brasileira de Zootecnia
2017
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Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017000900755 |
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Summary: | 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 thirty-two pigs with an average initial body weight of 21.9 kg were used in a completely randomized design. There were no differences between treatments, the pig performance was affected by temperature conditions, and the fat thickness was 8% higher for CNP than ANP. In conclusion, the model has advantages to adjust growing and finishing pig nutrition programs and improve environmental and economic aspects. |
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