17E-2 |
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R. D. PHILLIPS1, D. R. Clark2, F. K. Saalia1, and Y. -H. Tuan3. (1) Dept. of Food Science & Technology, Univ. of Georgia, 1109 Experiment St., Melton Bldg., Griffin, GA 30223-1797, (2) Food Science and Technology, University of Georgia, 1109 Experiment St., Griffin, GA 30223, (3) Department of Restaurant Management, Kuang Wu Institute of Technology and Commerce, Taipei, Taiwan Developing an entirely in vitro method for predicting overall protein nutritional quality would save much time and money. The objective of this study was to extend previous use of PDCAAS and AAACAAS values derived from studies in swine to predict overall protein nutritional quality in terms of the saturation kinetics model that relates protein intake to subject response Casein, cowpea, whole sorghum, extruded cowpea, and extruded sorghum were sequentially digested with pepsin, then pancreatin for 0, 2, 4, 6, 8, and 12 hours in dialysis tubes (MWCO=1000 kD). Dialysates were analyzed for nitrogen by the Dumas, and for amino acids by the AccQTag method. The resulting data were fitted to the Hill equation and coefficients including Dmax or Amax determined. Digestibility/availability at 24 (D24, A24) were also calculated. PDCAAS for Dmax and D24 and AAACAAS for A24 were calculated. These values were regressed against saturation kinetics (SK) coefficients, n and K0.5 from previous studies in swine. In some cases Dmax was closer to swine protein digestibility values, while in others D24 was closer. A24 values varied considerably among amino acids and protein sources, as was observed in a previous study in swine. Linear relationships between in vitro PDCAAS (Dmax, D24) and SK n and K.5 values determined in swine were found. AAACAAS (A24) values exhibited a curvilinear relationship with n and K.5. Predicted n and K.5 values were used to generate SK curves and compared to curves from swine data. AAACAAS(24) produced the closest agreement followed by PDCAAS(24). Although considerable more work would be required to validate this approach, it appears that an entirely in vitro approach to predicting overall protein quality is possible. The SK model allows predicting protein quality at all possible intakes, making it more powerful than one-value scores.
Session 17E, Food Chemistry: Proteins
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