Estimating digestible energy values of feeds and diets and integrating those values into net energy systems

The California Net Energy System (CNES) used a combination of measured and tabular metabolizable energy (ME) values and changes in body composition gain to determine net energy requirements for maintenance and gain and their corresponding dietary concentrations. The accuracy of the CNES depends on the accuracy of the feed ME values. Feed or diet ME values can be measured directly but are expensive and require specialized facilities; therefore, most ME values are estimated from digestible energy (DE) values, which are often estimated from the concentration of total digestible nutrients (TDN). Both DE and TDN values are often from tables and not based on actual nutrient analysis. The use of tabular values eliminates important within-feed variation in composition and digestibility. Furthermore, the use of TDN to estimate DE does not account for important variation in the gross energy value of feeds. A better approach would be to estimate DE concentration directly from nutrient composition or in vitro (or in situ) digestibility measurements. This approach incorporates within-feed variation into the energy system and eliminates the issues of using TDN. A widely used summative equation based on the commonly measured feed fractions (ash, crude protein, neutral detergent fiber, and fat) has been shown to accurately estimate DE concentrations of many diets for cattle; however, deficiencies in that equation have been identified and include an overestimation of DE provided by fat and an exaggerated negative effect of intake on digestibility. Replacing the nonfiber carbohydrate term (which included everything that was not measured) in the equation with measured starch concentration and residual organic matter (i.e., nonfiber carbohydrate minus starch) should improve accuracy by accounting for more variation in starch digestibility. More accurate estimates of DE will improve the accuracy of ME values, which will ultimately lead to more accurate NE values.