The effect of acid‐deamidated wheat gluten on the sensory profile and consumer acceptance of ice cream

Abstract

The effect of wheat gluten (WG) modified by acetic acid, tartaric acid and citric acid on sensory profile and consumer acceptance of ice cream was examined. A sensory profile of ice cream including six flavours and six textures descriptors was developed by quantitative descriptive analysis. Principal component analysis and confidence ellipse analysis results indicated that ice cream C2 (substitution of 20% of skim milk powder with citric acid-deamidated WG) was the most similar to ice cream control (Ctrl) (without aciddeamidated WG). Multiple factor analysis proved that physical viscosity and overrun properties were key factors affected the sensory texture properties of ice cream samples. External preference mapping indicated that consumer acceptance of Ctrl and C2 was the highest, and the inducing factors were 'sweetness', 'dairy flavour', 'fat feel', 'meltdown' and 'density' attributes. The C2 ice cream was suggested as a prototype for further development of ice cream with citric acid-deamidated WG.Acid-deaminated wheat gluten ice cream W. He et al.

Textural properties and consumer preference of functional milk puddings fortified with apricot kernel extracts

“…Calculated using the bootstrap procedure (Lee & Young, 1995), the 95% confidence ellipse for the pudding samples presented in Figure 1b allows the description of the similarity among the apricot kernel milk pudding samples by the overlap of their confidence ellipse (He et al, 2019). The confidence ellipse shows that S2 and the R sample were the most similar and could not be well discriminated based on the TPA results.…”

“…Thus, hedonic testing was conducted on P1–P12, and hedonic data were collected. EPM was set up through three steps, including grouping the consumer, creating the sensory map, and generating the preference map (He et al, 2019). Consumer segmentation was conducted to elucidate the eating perceptions and preferences of consumers (Sasaki et al, 2017).…”

“…To elucidate the effect of the attributes (Table 2) on consumer preference, EPM was conducted using the PREFMAP method on the sample score results determined by PCA on the first two principal components (X configuration) and the average overall acceptability scores of cluster means obtained by AHC (Y) (He et al, 2019).…”

“…EPM reduces the number of descriptive attributes into several components and then regresses consumer preference data onto the first few components (Yenket, Chambers IV, & Adhikari, 2011). Widely used in food product development, EPM can also relate consumer acceptance data, descriptive sensory data and/or instrumental data (He, Gasmalla, Yang, & Zhao, 2019;Ubeda, Callej on, Troncoso, & Morales, 2017).…”