Efficiency of metabolizable energy utilization for maintenance and gain and evaluation of Small Ruminant Nutrition System model in Santa Ines sheep
AUTOR(ES)
Regadas Filho, José Gilson Louzada, Pereira, Elzânia Sales, Villarroel, Arturo Bernardo Selaive, Pimentel, Patrícia Guimarães, Fontenele, Rildson Melo, Costa, Marcus Roberto Góes Ferreira, Maia, Iana Sérvulo Gomes, Sombra, Weberte Alan
FONTE
Revista Brasileira de Zootecnia
DATA DE PUBLICAÇÃO
2011-11
RESUMO
This study was carried out to estimate efficiencies of the utilization of metabolizable energy for maintenance (k m) and weight gain (k g) and to evaluate the Small Ruminant Nutrition System (SRNS) model in predicting dry matter intake and average daily gain of growing Santa Ines sheep. Twenty-four non-castrated Santa Ines sheep, at 50 days of age and with average body weight of 13.00 ± 0.56 kg, respectively, were used. After a 10-day adaptation period, four animals were slaughtered to be used as reference for estimating initial empty body weight and body composition of the other animals. The remaining animals were distributed in a random block design, with the treatments consisting of diets containing different levels of metabolizable energy (2.08, 2.28, 2.47 and 2.69 Mcal/kg of DM), with five replicates. The metabolizable energy use efficiencies for maintenance and for weight gain were calculated from the relationship between the dietary net energy for maintenance and gain and ME concentration in the diets. Evaluation of the SRNS model was performed by adjustment of simple linear regression model between the predicted (independent variable) and observed (dependent variable) values. The estimated energy use efficiency for maintenance (k m) was 0.70; and for gain weight (kg) it showed to be inversely proportional to the increase of metabolizable energy concentration in the diet. The dry matter intake predicted by the SRNS model did not statistically differ from that observed, but the model overestimated the average daily gain by 5.18%. Those results can contribute to the construction of a database, which could be condensed into several others in a predictive model of performance and feed planning for sheep reared in Brazil.
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