Characterization of Sugar Reduction in Model Confectionary Gels Using Descriptive Analysis

Abstract

Successful sugar reduction in food products mimics the sensory and functional properties of the full sugar counterpart. The initial step of sugar reduction is to determine how the absence of sugar affects these properties. Descriptive analysis was conducted on four gel types (gelatin, ι-carrageenan, κ-carrageenan, and konjac glucomannan) and a range of sugar concentrations from 0-20% w/v to create a sensory profile of model confectionary gels for comparison to instrumental texture profile analysis data. The sensory descriptive data were analyzed using analysis of variance and principal component analysis. Correlation analysis, cluster analysis, and partial least squares regression (PLS-R) were used to compare and correlate sensory and instrumental data. Regardless of sugar concentration, sensory analysis primarily clustered samples by gelling agent type, such as in the case of konjac glucomannan consistently being characterized as chewy. Cohesion and gumminess were correlated highly with melt-in-mouth and a jiggly texture, while adhesion and fracturability were negatively correlated. In the PLS-R samples biplot, gelatin and iota carrageenan samples were located near these attributes indicating their aptness as descriptors. In conclusion, descriptive analysis provided a more discriminating method for characterizing model confectionary gels.

Keywords: carrageenan; descriptive analysis; gelatin; konjac glucomannan; sugar reduction.

Figure 1

Principal components analysis biplot of Factors 1 and 2 by the correlation matrix of mean 12 sensory attributes across the 20 model confectionary gel samples based on Gel Type. AT = aftertaste, G = gelatin, IC = ι-carrageenan, KC = κ-carrageenan, KGM = konjac glucomannan.

Figure 2

Principal components analysis biplot of Factors 1 and 2 by the correlation matrix of mean six sensory attributes across the 20 model confectionary gel samples based on sugar concentration. AT = aftertaste, G = gelatin, IC = ι-carrageenan, KC = κ-carrageenan, KGM = konjac glucomannan.

Figure 3

Dendrogram from agglomerative hierarchical cluster analysis (unweighted pair-group average method) of 20 model confectionary gel samples by sensory attributes based on gel type. Similarity based on Pearson correlation coefficient. G = gelatin, IC = ι-carrageenan, KC = κ-carrageenan, KGM = konjac glucomannan.

Figure 4

Dendrogram from agglomerative hierarchical cluster analysis (unweighted pair–group average method) of 20 model confectionary gel samples by sensory attributes based on sugar concentration. Similarity based on Pearson correlation coefficient. G = gelatin, IC = ι-carrageenan, KC = κ-carrageenan, KGM = konjac glucomannan.

Figure 5

Dendrogram from agglomerative hierarchical cluster analysis (unweighted pair-group average method) of 20 model confectionary gel samples by instrumental measurements. Similarity based on Pearson correlation coefficient. G = gelatin, IC = ι-carrageenan, KC = κ-carrageenan, KGM = konjac glucomannan.

Figure 6

Partial least squares regression biplot for Factors 1 and 2 for Instrumental Parameters (x-variable) and Sensory Texture Attributes (y-variable) on 20 model confectionary gels: (A) correlations on Factor 1 and Factor 2; (B) observations on axes Factors 1 and 2. G = gelatin, IC = ι-carrageenan, KC = κ-carrageenan, KGM = konjac glucomannan.