Development of a Statistical Workflow for Screening Protein Extracts Based on Their Nutritional Composition and Digestibility: Application to Elderly - Angéline Duval; Thierry Sayd; Laurent Aubry; Claude De Oliviera Ferreira; Vincenza Ferraro; Véronique Sante-Lhoutellier (Foods, 2020)
The objective of the study is to develop a workflow to screen protein extracts and identify their nutritional potential as high quality nutritional culinary aids for recipes for the elderly. Twenty-seven protein extracts of animal, vegetable, and dairy origin were characterized. We studied their fate by monitoring static in vitro digestion, mimicking the physiological digestion conditions of the elderly. At the end of the gastric and intestinal phase, global measurements of digestibility and antioxidant bioactivities were performed. The statistical analysis workflow developed allowed: (i) synthesizing the compositional and nutritional information of each protein extract by creating latent variables, and (ii) comparing them. The links between variables and similarities between protein extracts were visualized using a heat map. A hierarchical cluster analysis allowed reducing the 48 quantitative variables into 15 qualitative latent variables (clusters). The application of the k-means method on each cluster enable to classify the protein extracts by level. This defined level was used as categorical value. Multiple correspondence analysis revealed groups of protein extracts with varied patterns. This workflow allowed the comparison/hierarchization between protein extracts and the creation of a tool to select the most interesting ones on the basis of their nutritional quality.