Abstract #W225
Section: Nonruminant Nutrition
Session: Nonruminant Nutrition: Energy & fiber
Format: Poster
Day/Time: Wednesday 7:30 AM–9:30 AM
Location: Gatlin Ballroom
Session: Nonruminant Nutrition: Energy & fiber
Format: Poster
Day/Time: Wednesday 7:30 AM–9:30 AM
Location: Gatlin Ballroom
# W225
Fitting and validating prediction equations of metabolizable energy of meat and bone meal for pigs.
R. A. Castilho1, P. C. Pozza*2, N. T. E. Oliveira3, C. P. Sangali2, C. N. Langer4, R. V. Nunes3, 1Safeeds Nutrição Animal, Cascavel, Paraná, Brazil, 2Universidade Estadual de Maringá, Maringá, Paraná, Brazil, 3Universidade Estadual do Oeste do Paraná, Mchal Candido Rondon, Paraná, Brazil, 4Swine Production System, Quatro Pontes, Paraná, Brazil.
Key Words: chemical composition, feedstuff, model
Fitting and validating prediction equations of metabolizable energy of meat and bone meal for pigs.
R. A. Castilho1, P. C. Pozza*2, N. T. E. Oliveira3, C. P. Sangali2, C. N. Langer4, R. V. Nunes3, 1Safeeds Nutrição Animal, Cascavel, Paraná, Brazil, 2Universidade Estadual de Maringá, Maringá, Paraná, Brazil, 3Universidade Estadual do Oeste do Paraná, Mchal Candido Rondon, Paraná, Brazil, 4Swine Production System, Quatro Pontes, Paraná, Brazil.
The aim of this study was to fit and validate models to predict the metabolizable energy (ME) of meat and bone meal (MBM) for pigs. Thirty-two barrows (26.75 ± 1.45 kg) were allotted in a randomized blocks design with 8 treatments (7 MBM that replaced 20% the basal diet) and 4 replicates, to determine the ME. All MBM samples were analyzed for dry matter (DM), crude protein (CP), ether extract (EE), gross energy (GE), crude fiber (CF), mineral matter (MM), calcium (Ca) and phosphorus (P). The multiple linear regression models were adjusted using GE, CP, EE, MM, Ca and P as regressors (DM basis) using the ordinary least square method. To validate prediction equations, a database was compiled containing 48 pairs of observed and predicted ME. The 48 observed ME values were compiled from the literature and classified according to the scientific origin, resulting in 15 Brazilian data and 33 from international literature. The validity was initially assessed by adjusting the linear regression of 1st degree of the observed ME in function of the estimated ME, using the ordinary least squares. This procedure was adopted for the databases from the Brazilian, international and mixed literature. The validation of the estimated equations, as predictors of the linear ratio of ME, was checked by fitting a linear model of 1st degree of the predicted values (y = b0 + b1xi) of ME by the equations initially estimated in function of the observed values. The ME values of MBM ranged from 1645 to 2645 kcal/kg. The prediction equations ME1 = −4233.58 +0.4134GE +72P +89.62MM −159.06Ca (R2 = 0.90); ME2 = 2087.49 +0.3446GE +31.82MM −189.18Ca (R2 = 0.87); ME3 = 2140.13 +0.3845GE −112.33Ca (R2 = 0.86); ME4 = −346.58 +0.656GE (R2 = 0.80); and ME5 = 3221.27 +178.96EE −76.55MM (R2 = 0.82) were effective in predicting the ME of Brazilian MBM. However, there was no validation when using data obtained from international researches. In conclusion, the equations that efficiently estimates the ME of MBM for pigs in Brazilian conditions are ME1 = −4233.58 +0.4134GE +72CP + 89.62MM –159.06Ca and ME2 = 2087.49 +0.3446GE +31.82EE –189.18Ca.
Key Words: chemical composition, feedstuff, model