Prediction of the digestible crude protein and protein digestibility of feed ingredients for rabbits from chemical analysis

Ninety-five data of individual feedstuffs, for which information on chemical analyses and crude protein digestibility (CPD) was available, were subject to sequential multiple linear regression analysis employing CPD and digestible crude protein (DCP) as dependent variables and chemical analysis as independent variables. The feedstuffs were classed separately into dry forages (n=26), cereals and cereal by-products (n=29), protein concentrates (n=18) and by-products (n=22) groups. The procedure followed in each of the groups was to utilize: (1) the feedstuffs in which the Van Soest fiber and the Weende analysis were simultaneously available, and (2) all feedstuffs with data of the variables selected in the first step. The CP content was the best single predictor of the DCP content of feeds, the best equation in terms of R2 was obtained in the total group: DCP (g kg−1)=−34.67+0.876×CP (g kg−1), R2=0.948, RSD=7.36, n=93. The addition of the ash content to sequential analysis improved the accuracy of DCP prediction, increasing the R2 up to 0.960. Acid detergent fiber was the second independent variable selected in the cereals and by-products groups, the R2 obtained was, respectively, higher (0.969) and lower (0.895) than that of general equation. The correlations among the independent variables employed and CPD were low. Only when in the total group the nitrogen linked to acid detergent fiber (N–ADF) measurement was included as independent variable (n=11) a high R2 (0.905) was obtained. The N–ADF content that included the heat-damaged protein and the nitrogen associated with lignin could be adequate to estimate the indigestible protein content of feeds. However, more data points would be necessary to confirm its accuracy, taking into account the non-uniformity in the distribution of current data.