Prediction of the total and standardized ileal digestible amino acid contents from the chemical composition of soybean meals of different origin in broilers

The objective of this experiment was to determine total amino acid (TAA) content, standardized ileal digestibility (SID) of crude protein, and standardized ileal amino acid digestibility in 9 sources of soybean meal (SBM) of different origin and to subsequently establish equations for predicting the TAA content and concentration of standardized ileal digestible amino acids (SIDAA) based on their protein content and other proximate components. Concentration of SIDAA of the samples was also predicted using TAA values. A total of 160 1-day-old male broiler chicks were randomly assigned to 10 dietary treatments consisted of 9 semipurified diets containing one SBM (200 g of crude protein/kg) as the only source of dietary amino acid (AA) and one N-free diet to determine endogenous ileal AA flow. The birds were fed with a standard diet from 0 to 18 D of age, and experimental diets were fed from 19 to 24 D of age. The fitness of the models of the study was tested using the adjusted coefficient of determination (R(2)) value, P-value regression and coefficients, and standard error of prediction (SEP). The coefficient of SID for Lys and Cys among SBM varied from 86.7 to 96.3 and 74.1 to 89.3, respectively, with significant difference (P < 0.05). In equations based on protein content, the adjusted R(2) value ranged from 40.7 (Ile) to 99.6 (Met) and 37.2 (Met + Cys) to 99.6 (Met) for TAA content and concentration of SIDAA, respectively. Inclusion of other proximate components of test samples (e.g., crude fiber, neutral detergent fiber, acid detergent fiber, ash, gross energy, and so on) into the regression equation increased the adjusted R(2) value and decreased the SEP. The results of linear regression revealed that it is possible to satisfactorily estimate the TAA content and concentration of SIDAA of SBM through its protein content and other proximate components, but the prediction equations based on other proximate components were more accurate in terms of reflecting the measured results; however, additional time and costs were associated with this approach. It is also possible to estimate the concentration of SIDAA through TAA values with reasonable accuracy and lower SEP.