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Title: THE IMPACT OF DIETARY PROTEIN SOURCE ON OBSERVED AND PREDICTED METABOLIZABLE ENERGY OF DRY EXTRUDED DOG FOODS

Author
item YAMKA, R. - UNIV. OF KENTUCKY
item MCLEOD, K. - UNIV. OF KENTUCKY
item HARMON, D. - UNIV. OF KENTUCKY
item Freetly, Harvey
item SCHOENHERR, W. - HILL'S PET NUTRITION

Submitted to: Journal of Animal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/9/2006
Publication Date: 1/2/2007
Citation: Yamka, R.M., McLeod, K.R., Harmon, D.L., Freetly, H.C., Schoenherr, W.D. 2007. The impact of dietary protein source on observed and predicted metabolizable energy of dry extruded dog foods. Journal of Animal Science. 85(1):204-212.

Interpretive Summary: Two replicated 4 x 4 Latin square experiments were designed to determine the metabolizable energy (ME) content of eight foods containing different protein sources. The major protein sources included low-oligosaccharide whole soybeans, 2 low-oligosaccharide low-phytate whole soybeans, 2 conventional soybean meals, and low-ash poultry meal, low-oligosaccharide low-phytate soybean meal or conventional whole soybeans. The digestible energy content of all foods ranged from 3624 to 4244 kcal/kg DM. The ME content of all foods ranged from 3,463 to 4,233 kcal/kg DM. The observed ME data was then used to test the accuracy of the modified Atwater's equation. We found that the modified Atwater equation consistently under predicted ME compared to observed ME. Therefore our second objective was to use individual data to develop an equation based on chemical composition of the food to predict ME content of the foods. A multivariate regression analysis was used to predict ME content based on chemical composition. Two initial models were fit to the data. Model 1 included CP, EE and crude fiber (CF). Because the foods varied in protein sources and the ratio of total amino acid (TAA) to nonamino acid CP (NAA) ranged from 3.5 to 14.4, we hypothesized that accounting for the proportion of TAA and NAA in CP would improve the fit of the model. Therefore, Model 2 included TAA, NAA, EE and CF. Defining CP in terms of TAA and NAA improved the r2 of the model from 0.46 to 0.79. Models 3 and 4 replaced the CF term with acid detergent fiber (ADF) and neutral detergent fiber (NDF). Model 3 included CP, EE, NDF, and ADF and Model 4 included TAA, NAA, EE, NDF and ADF. Similarly, defining CF in terms of NDF and ADF improved the r2 of Model 2 from 0.79 to 0.82. Residual analysis suggests that by replacing the CF term in Model 2 with ADF and NDF in Model 4 there was an improvement in prediction of ME content. By splitting CP into TAA and NAA fractions we have further defined the chemical composition of the food. These data suggest that defining protein composition improves the ability to predict ME content of dog foods.

Technical Abstract: Fifty-five balance trials were designed to determine the metabolizable energy (ME) content of eight foods containing different protein sources. The major protein sources tested included low-oligosaccharide whole soya beans, 2 low-oligosaccharide low-phytate whole soya beans, 2 conventional soya bean meals, low-ash poultry meal, low-oligosaccharide low-phytate soya bean meal or conventional whole soya beans. The ME content of all foods ranged from 14.5 to 17.7 MJ/kg DM. The first objective was to utilize the observed ME data and test the accuracy of the modified Atwater's equation. We found that the modified Atwater equation generally under predicted ME compared to observed ME (residual mean = 1.0 MJ/kg). Therefore our second objective was to use individual data to develop an equation based on chemical composition of the food to predict ME content of the foods. A multivariate regression analysis was used to predict ME content based on chemical composition. Five models were fit to the data. Model 1 included crude protein (CP), ether extract (EE) and crude fiber (CF). Because the foods varied in protein sources and the ratio of total amino acid (TAA) to non-amino acid CP (NAA) ranged from 3.5 to 14.4, we hypothesized that accounting for the proportion of TAA and NAA in CP would improve the fit of the model. Therefore, Model 2 included TAA, NAA, EE and CF. Defining CP in terms of TAA and NAA improved the r2 of the model from 0.46 to 0.79. Models 3, 4 and 5 replaced the CF term with acid detergent fiber (ADF), neutral detergent fiber (NDF) and hemi-cellulose (HEM). Model 3 included TAA, NAA, EE and NDF. Model 4 included TAA, NAA, EE, ADF and HEM. Model 5 included TAA, NAA, EE and HEM. Defining dietary fiber in terms of HEM improved the r2 of Model 2 from 0.79 to 0.81. Residual analysis suggests that replacing the CF term with HEM (Model 5) improved prediction of ME content. By fractionating CP into TAA and NAA fractions we have further defined the chemical composition of the food. These data suggest that defining protein composition greatly improves the accuracy of predicting ME content of dog foods.