Evaluation of analytical and statistical approaches for predicting in vitro nitrogen solubility and in vivo pre-caecal crude protein digestibility of cereal grains in growing pigs.

Different analytical (enzyme system and near-infrared spectroscopy (NIRS)) and statistical (single and multiple regressions) approaches were used to predict in vivo standardized pre-caecal digestibility (PCD) of crude protein (CP) and amino acids (AA) in cereal grains for growing pigs as well as in vitro nitrogen (N) solubility. Furthermore, different chemical and physical characteristics were categorized (e.g. crude nutrients, AA, minerals, fibre components or combinations of these) and used for generating prediction equations. There were strong linear relationships (p < .05) between in vivo PCD of CP and essential AA and in vitro N solubility when grain species was considered as covariate in the model. Predicting in vivo PCD values using various chemical and physical characteristics produced inconsistent results among different grain species and AA and could therefore not be used for predicting PCD. It is possible to predict in vitro N solubility from chemical and physical characteristics for some grain species. However, the relationships between some of these categories and the in vitro N solubility were not consistent and not always causative or physiologically explainable. The R2 of NIRS for predicting in vitro N solubility was at a relatively high level (up to R2  = 0.80). This level of R2 indicates that a classification of the grain samples in, for example, high, medium and low in vitro N solubility levels is possible, but it does not allow for a quantitative prediction of the in vitro N solubility. In conclusion, the present database can be used for establishing a ranking of different cereal grain species for PCD of CP and essential AA values. However, it was not possible to create clear prediction equations for in vivo or in vitro digestibility values. Therefore, greater variation within grain species, for example due to different growing and harvesting conditions, is warranted for predicting PCD values of individual grain samples.

Determination of basal ileal endogenous losses and standardized ileal digestibility of amino acids in barley fed to growing pigs.

BACKGROUND: Basal ileal endogenous amino acid (AA) losses (IAAend) and standardized ileal digestibility (SID) values of cereal grains, such as barley, are apparently underestimated when determined according to the nitrogen (N)-free method. Regression analysis between the dietary apparent ileal digestible content (cAID) and total crude protein (CP) and AA can be considered as alternative approach to obtain more accurate values for IAAend and SID of AA in cereal grains. METHODS: Eight hulled barley genotypes were used, with barley being the only source of CP and AA in the assay diets. The diets contained 95 % as-fed of these eight barley genotypes each, ranging in CP content between 109.1 and 123.8 g/kg dry matter (DM). Nine ileally T-cannulated barrows, average body weight (BW) 30 ± 2 kg, were allotted to a row-column design comprising eight periods with 6 d each and nine pigs. On d 5 and the night of d 6 of every period, ileal digesta were collected for a total of 12 h. The IAAend and the SID were determined by linear regression analysis between cAID and total dietary CP and AA. RESULTS: There exist linear relationships between cAID and total CP and AA (P < 0.001). The IAAend of CP, Lys, Met, Thr and Trp amounted to 35.34, 1.08, 0.25, 1.02 and 0.38 g/kg DM intake (DMI), respectively, which are greater compared to average IAAend determined previously under N-free feeding conditions. The SID of CP, Lys, Met, Thr and Trp was 90, 79, 85, 79 and 86 %, respectively, and was greater when compared to tabulated values. Moreover, these SID values were greater than those reported in literature, based on correction of apparent ileal digestibility (AID) of CP and AA for their IAAend values. Summarized, the results of the present regression analysis indicate greater IAAend in barley-based diets compared to those obtained by N-free feeding. CONCLUSIONS: For low-protein feed ingredients like barley the regression method may be preferred over correction of AID values for their IAAend determined under N-free feeding conditions, as intercepts and slopes of the linear regression equations between cAID and total dietary CP and AA provide direct estimates of IAAend and SID of CP and AA in the presence of the assay feed ingredient.