Fat-salty sensory interactions in model cheeses: multivariate analysis of a compilation of data from different projects organised in the BaGaTeL database

The food industry needs to develop new strategies to formulate well-balanced products in terms of nutritional and environmental requirements and sensory acceptability by consumers. The BaGaTeL database has been built, guided by a process and observation ontology in food science, PO² ontology, to integrate data on dairy foods composition process, nutritional and sensory properties, using a consensual model and a shared structured vocabulary. We searched the database, using specific queries, for samples for which data of composition, rheological properties and sensory profile analysis were available. However, the composition and structure of the dairy products and the measured variables are often very different, which do not allow a direct comparison of the data. Thus, we made a selection of 68 model cheeses from 6 different projects made with different compositions (fat, protein, minerals, and water). A principal component analysis (PCA) performed on this set of samples revealed that the sensory hardness was better explained by a low moisture-in-non-fat-content than by a high protein content as was often suggested and that the intensity of salty taste was not only linked to salt content but was also modulated by cheese composition. Considering a subgroup of 22 samples from 3 projects, in which fat perception was also measured, a partial least square analysis revealed that fat perception was not only explained by fat content but was also highly influenced by salty taste, and that salty taste was more correlated with fat perception than with sodium ions content, highlighting sensory fat-salty interactions.