From Single Foods to Whole Diets: A Critical Framework for Protein Quality Assessment Accounting for Complementarity and Matrix Effects.

Accurate protein quality assessment is fundamental to food science and nutrition policy, yet the two dominant metrics, the Protein Digestibility-Corrected Amino Acid Score (PDCAAS) and the Digestible Indispensable Amino Acid Score (DIAAS), evaluate foods in isolation, identifying a single limiting indispensable amino acid (AA) per source. Although PDCAAS and DIAAS are broadly applicable, their single-food approach is especially limiting for plant-based proteins, where AA complementarity and food-matrix complexity are most pronounced. This single-food approach systematically underestimates protein adequacy in real-world diets, where diverse protein sources are consumed together and their AA profiles complement across meals and days. Compounding this limitation, food matrix composition, thermal processing, and product formulation reduce AA bioaccessibility relative to ingredient-level scores, as shown, for example, by in vitro DIAAS analyses of protein bars and processing losses of reactive lysine in plant-based products, effects single-food metrics cannot capture. This critical review synthesizes experimental evidence that protein quality is both additive and accurately predictable at the meal and dietary level, and proposes a whole-diet protein quality (WDPQ) framework that pools digestible indispensable AA contributions across daily intake to identify limiting AAs at the dietary rather than the single-food level. Applied to Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and pregnancy diets, as well as vulnerable populations, WDPQ yields corrected protein values 18%-30% higher than conventional single-food summation, materially altering assessments of dietary adequacy. The WDPQ framework is implementable using existing PDCAAS and DIAAS data and has implications for protein labeling, dietary guidelines, and the nutritional evaluation of plant-based food transitions.