The present study aimed to evaluate the digestion rate and nutritional quality of pig muscle proteins in relation to different meat processes (aging, mincing, and cooking). Under our experimental conditions, aging and mincing had little impact on protein digestion. Heat treatments had different temperature-dependent effects on the meat protein digestion rate and degradation potential. At 70 °C, the proteins underwent denaturation that enhanced the speed of pepsin digestion by increasing enzyme accessibility to protein cleavage sites. Above 100 °C, oxidation-related protein aggregation slowed pepsin digestion but improved meat protein overall digestibility. The digestion parameters defined here open new insights on the dynamics governing the in vitro digestion of meat protein. However, the effect of cooking temperature on protein digestion observed in vitro needs to be confirmed in vivo.

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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.