Net energy （NE） is the most accurate and unbiased way in characterizing the energy content of feed. Comparatively speaking, research on NE prediction is still limited and under development. Therefore, it is importan...Net energy （NE） is the most accurate and unbiased way in characterizing the energy content of feed. Comparatively speaking, research on NE prediction is still limited and under development. Therefore, it is important to correctly assess NE for further study. In this study, an energy balance trial and a fasting metabolism trial were used to measure the net energy for production （NEp） and the net energy for maintenance （NEm）, respectively. Meanwhile, a backward method of multiple linear regression was applied to establish prediction equations for NE. The results showed that corn NE is about 2 times higher than that of soybean meal, due to the efficiency of ME （k） utilization by the ingredients. Meanwhile, AME and acid detergent fiber （ADF） were found to be better predictors for the NE of corn and soybean meal, respectively. Furthermore, Equations 1（R^2=0.993, RSD=0.0091） and 12 （R^2=0.999, RSD=0.0008） were found to be better prediction equations in multiple linear regression analyses for corn and soybean meal, respectively. However, considering the cost of the analytical procedures, the accuracy of the prediction （RSD）, and the additional variability or errors due to interlaboratory variance, Equation 4 （R^2=0.990, RSD=0.0109） and Equation 20 （R^2=0.996, RSD=0.0043） were better models for corn and soybean meal, respectively. Nevertheless, these equations for corn and soybean meal should be applied only under similar experimental conditions.展开更多
文摘Net energy （NE） is the most accurate and unbiased way in characterizing the energy content of feed. Comparatively speaking, research on NE prediction is still limited and under development. Therefore, it is important to correctly assess NE for further study. In this study, an energy balance trial and a fasting metabolism trial were used to measure the net energy for production （NEp） and the net energy for maintenance （NEm）, respectively. Meanwhile, a backward method of multiple linear regression was applied to establish prediction equations for NE. The results showed that corn NE is about 2 times higher than that of soybean meal, due to the efficiency of ME （k） utilization by the ingredients. Meanwhile, AME and acid detergent fiber （ADF） were found to be better predictors for the NE of corn and soybean meal, respectively. Furthermore, Equations 1（R^2=0.993, RSD=0.0091） and 12 （R^2=0.999, RSD=0.0008） were found to be better prediction equations in multiple linear regression analyses for corn and soybean meal, respectively. However, considering the cost of the analytical procedures, the accuracy of the prediction （RSD）, and the additional variability or errors due to interlaboratory variance, Equation 4 （R^2=0.990, RSD=0.0109） and Equation 20 （R^2=0.996, RSD=0.0043） were better models for corn and soybean meal, respectively. Nevertheless, these equations for corn and soybean meal should be applied only under similar experimental conditions.
