Validating prediction equations of metabolizable energy of soybean meal for growing pigs

Abstract

The aim of this study was to evaluate equations to predict the metabolizable energy (ME) of soybean meal (SBM) for swine. Seven SBM were used, which were analyzed for dry matter, crude protein, ether extract, neutral detergent fiber (NDF), acid detergent fiber (ADF), ash, calcium, phosphorus, solubility in potassium hydroxide (KOH) and urease index. To determine the ME of SBM, 32 barrows, with an average initial weight of 29.01 ± 3.64 kg, were used and distributed in a randomized blocks design, with seven treatments and four replicates. To validate the prediction equations, linear regression models were adjusted, using observed values of ME (metabolism trial) as a function of the estimated ME (obtained by applying the chemical composition of the SBM in selected equations found in the literature). The existence of regression was evaluated by the “t” test, partially applied to each parameter (?0 and ?1). The validation of the prediction models of first degree was obtained by accepting the joint null hypothesis ?0 = 0 and ?1 = 1. The equations ME = 5.42 - 17.2FDN - 19.4MM + 0.709GE and ME= 1099 + 0.740GE - 5.5MM - 3.7NDF are effective for estimating the ME of SBM for growing pigs.

Keywords

• Chemical composition
• Linear regression
• Validation.