Ionic valency influences oral processing by changing salivary behavior and merits more attention since little is known. In this study, the influence of three ionic valences (monovalent, divalent and trivalent), ionic strength and epigallocatechin gallate (EGCG) on lubricating properties of saliva were investigated. Tribological measurements were used to characterize the lubrication response of KCl, MgCl2, FeCl3, and AlCl3 in combination with EGCG to the ex vivo salivary pellicle. KCl at 150 mM ionic strength provided extra lubrication via hydration lubrication. Contrarily, trivalent salts aggregated together with the salivary mucins via ionic cross-link interactions, which led to a decrease in salivary lubrication. FeCl3 and AlCl3 affected the salivary lubrication differently, which was attributed to changes in the pH. Finally, in presence of EGCG, FeCl3 interacted with EGCG via chelating interactions, preventing salivary protein aggregation. This resulted in less desorption of the salivary film, retaining the lubrication ability of salivary proteins.
Characteristics of a food product are the backbone of sensory research and it is essential to describe the food flavor with well-defined and agreed-upon concepts. This paper reviews the current bibliography related to taste/flavor perception, with a particular focus on mouthfeel. A summary of the current mouthfeel vocabularies is given and research approaches are evaluated. A general mouthfeel model is presented that overarches product categories and has shown its use in practice. The intention is to contribute to an increased understanding of taste and flavor and mouthfeel sensations. This paper reveals the ambiguity of terms that are regularly used in literature. This is influenced by different focus in research. Three classes of research related to mouthfeel are identified: (1) product oriented (molecular attributes), (2) product/human oriented (human interface: receptors, saliva, chewing, etc.) and (3) human oriented (after swallowing). For the future of research in flavor of foods and beverages, it is essential to have consensus on the definitions of relevant concepts and to have a model (classification) based on an approach that is generally accepted. A mouthfeel model is potentially a powerful tool for food producers and researchers alike since it can be used to classify food based on the differences in food composition. Generalist descriptors that can be used to describe mouthfeel in foods and beverages can improve the communication between diverse audiences and contribute to the understanding of taste, flavor and particularly mouthfeel.
General introduction 11 1 pH values additionally increase friction.The disruption of the salivary film is dependent on the interaction of salivary proteins with polyphenols where aggregate formation occurs.Chapter 6 elaborates on the effect of mineral salts on the lubrication behavior of human saliva.Different cationic valences were studied where trivalent salts cause loss of lubrication behavior while monovalent salts improve lubrication.Additionally, the interaction between phenols and cationic valences indicates that trivalent salt interacts with phenolic components which provide inhibition of lubrication loss.The application of the mouthfeel model is presented in chapter 7. Commercial beers were analyzed, both chemically and sensorially.Using a chemometric application, sensorial parameters were found to be highly correlated with instrumental techniques regarding the molecular characteristics of beers.The general discussions on the studies described, as well as final conclusions, are formulated in chapter 8. References
Beer is one of the most consumed alcoholic beverages in the world. Classification of beer helps the consumer to find a preferred beer. Sensory assessments of taste are commonly done by sensory panels and therefore susceptible to subjectivity. Mouthfeel is an important parameter for the total perception of beer flavor. Three dimensions of mouthfeel are distinguished: contracting, coating, and drying. In this study 24 beer samples were evaluated chemically. The data were matched with sensorial data obtained from a trained panel. Different chemical analyses were performed; total acidity (TA), total flavonoids (TF), total polyphenols (TPC), total sugars (TS), color, pH, carbon dioxide content, ethanol, bitterness units (BU) and total iso-α-acids (TIA). The data were analyzed by performing several statistical techniques such as analysis of variance, principal component analysis, agglomerative hierarchical cluster analysis and multiple factor analysis. Sensory data obtained from trained panelists on the different mouthfeel attributes correlated with the data found instrumentally. The drying dimension could be expressed using the TPC, BU, TIA and pH. Contracting compounds correlated positively with TA and negatively with pH. As expected, ethanol was strongly associated with burning sensations and carbon dioxide with carbonation. The results of this experiment indicate that commercial beers can be classified into three mouthfeel attributes: drying, coating and contracting. The Principal Component Analysis (PCA) in this study confirmed the dimensions of the mouthfeel model and identified drying and coating as opposites, contracting forces interact on these dimensions. Moreover, these attributes were shown to be quantifiable by instrumental analysis which suggests that a data-driven approach based on mouthfeel could reduce subjectivity in the analysis of taste.