Predicting Metabolizable Energy of Normal Corn from its Chemical Composition in Adult Pekin Ducks
2008
Zhao, F. | Zhang, H.F. | Hou, S.S. | Zhang, Z.Y.
Two experiments were conducted to establish an ME content prediction model for normal corn for ducks based on the grain's chemical composition. In Experiment 1, observed linear relationships between the determined ME content of 30 corn calibration samples and proximate nutrients, acid detergent fiber (ADF), and neutral detergent fiber (NDF) were used to develop an ME prediction model. In Experiment 2, 6 samples of corn selected at random from the primary corn-growing regions of China were used for testing the accuracy of ME prediction models. The results indicated that the AME, AMEn, TME, and TMEn were negatively correlated with crude fiber (r = -0.905), ADF (r = -0.915), and NDF (r = -0.95) contents, and moderately correlated with gross energy (GE; r = -0.55) content in corn calibration samples. In contrast, no significant correlations were found for CP, ether extract, and ash contents. According to the stepwise regression analysis, both NDF and GE were found to be useful for the ME prediction models. Because the maximum absolute difference between the in vivo ME determinations and the predicted ME values was 61 kcal/kg, it was concluded that, for White Pekin ducks, the latter could be used to predict the ME content of corn with acceptable accuracy.
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