(P11-014-24) Optimizing Protein Food Sources Combinations To Achieve Protein and Nutrient Quality in a Plant-Based Meal

Objectives: To use a nonlinear programming approach to determine optimal combinations of protein sources delivering high protein and nutrient quality in a plant-based meal, with breakfast as a case study.

Methods: Protein sources including information on protein, sum of amino acids, indispensable amino acid (IAA) profile, amino acid score and protein digestibility were used to calculate the protein digestibility corrected amino acid score (PDCAAS). The protein sources (N=56) were clustered into three groups based on their IAA profiles, namely “lysine-limiting” (cereals, oats, bread etc.), “methionine-limiting” (fava, split peas, lentils etc.) and “non-limiting” (eggs, milk, soya products etc.) respectively. Thereafter, a non-linear optimization model was developed to maximize PDCAAS as close to 1 as possible (optimal protein quality) with a constraint of at least 10% protein contribution each from “lysine-limiting” and “methionine-limiting” protein sources and a variable (10-80%) contribution from the “non-limiting” cluster to ensure a diversity of protein sources. Nutrient quality constraints critical to a balanced plant-based meal such as energy, protein, dietary fiber, iron, calcium, and zinc were added to the model based on the international breakfast research initiative.

Results: There were 5616 combinations from ingredients originating from the three clusters to reach a PDCAAS of 1. The optimal contribution allowing to meet PDCAAS of 1 while meeting the nutrient constraints was between 30-40% from “non-limiting”, 10% from “lysine-limiting” and 50-60% from “methionine-limiting” protein sources. An example of such a combination includes oat, fava bean and soya milk in the proportions of 10-60-30%, respectively.

Conclusions: This optimization methodology allows identifying combinations of up to three protein sources and proportions to reach the optimal protein and nutrient quality in a plant-based breakfast. These combinations can be used to identify high quality plant protein products and meals. Further work is needed to apply this methodology to other eating occasions.

Funding Sources: This research is funded by Nestlé Research.