Regression Equations of Energy Values of Corn, Soybean Meal, and Wheat Bran Developed by Chemical Composition for Growing Pigs

Simple Summary In pig production, feed represents a large part of the total cost, and available energy in feedstuff represents the greatest proportion of this cost. In China, corn, soybean meal (SBM), and wheat bran (WB) are the principal ingredients in diets of pigs because these feedstuffs are widely available in China, have highly available energy, and are generally economical. In practice, the actual digestible energy (DE) and metabolizable energy (ME) of corn, SBM, and WB are unknown. The experimental determination of DE or ME values is expensive, time consuming, and labor intensive. Regression equations to estimate DE and ME in feed ingredients based on chemical composition can be a useful tool in feed ingredient evaluation. Thus, the objectives of this study were to evaluate a wide variety of corn, SBM, and WB to generate the regression equation for DE and ME and to evaluate and compare the energy content of various corn, SBM, and WB samples. A range of regression equations were developed in the present study, and proved adequate to reliably predict the DE and ME of commercially available corn, SBM, and WB for growing pigs. The application of these regression equations is expected to optimize productivity and maximize profits for pork producers. The objectives of this study were to determine the chemical compositions, digestible energy (DE), and metabolizable energy (ME) in corn, soybean meal (SBM) and wheat bran (WB) fed to growing pigs, and to develop regression equations for predicting DE and ME. Three separate experiments were conducted to determine DE and ME of corn, SBM, and WB. The DE and ME in corn were determined directly using 10 barrows allotted to a replicated 5 x 5 Latin square design, and the diets were formulated with one of 10 corn samples. The DE and ME in SBM and WB were determined by difference using two corn basal diets and 10 corn-SBM or 10 corn-SBM-WB diets, which were allotted to a replicated 6 x 6 Latin square design. Ten corn samples were obtained from the main corn producing areas of China. Ten SBM samples were obtained from nine different crushing facilities in nine provinces in China. Ten WB samples were collected from different feed mills of China. Samples were analyzed for dry matter (DM), crude protein (CP), ether extract (EE), ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), gross energy (GE), and soluble carbohydrates (SCHO). The best-fit equations for corn were DE (MJ/kg DM) = 20.18 - 0.76 x EE (%) and ME (MJ/kg DM) = 5.74 + 1.11 x DE (MJ/kg DM) - 0.33 x CP (%) - 0.07 x SCHO (%). The best-fit equations for SBM were DE (MJ/kg DM) = 42.91 - 3.43 x Ash (%) - 0.20 x NDF (%) + 0.09 x ADF (%) and ME (MJ/kg DM) = -21.67 + 0.89 x DE (MJ/kg DM) - 1.06 x GE (MJ/kg DM). The best-fit equations for WB were DE (MJ/kg DM) = -7.09 + 1.54 x CP (%) - 0.25 x NDF (%) - 0.32 x ADF (%) + 0.23 x Ash (%) and ME (MJ/kg DM) = 0.02 + 0.96 x DE (MJ/kg DM). The chemical composition of corn, SBM, and WB can vary substantially from zone to zone, resulting in considerable variation in its available energy value for pig. The DE and ME of corn, SBM and WB for growing pigs can be predicted based on their chemical compositions.