1611, 2022

Evaluation of complementary numerical and visual approaches for investigating pairwise comparisons after principal component analysis

John Castura/ November 16, 2022/ Oral Presentation/ 0 comments

We propose and evaluate numerical and visual methods for investigating paired comparisons after principal component analysis (PCA). PCA results can be visualized to facilitate an understanding of the relationships between the products and the sensory attributes. But identifying and visualizing significant product differences in multiple PCs simultaneously is not straightforward. A benefit of the proposed methods is that they provide

0911, 2022

Clustering consumers based on their hedonic responses

John Castura/ November 9, 2022/ Oral Presentation/ 0 comments

Consumers are diverse in their product perceptions. But within the consumer population there are often consumer segments whose product perceptions are relatively homogeneous. To discover these consumer segments, consumers’ product-related responses are submitted to a cluster analysis. The particular cluster analysis is chosen by the researcher. But the choice of clustering algorithm can have profound consequences on the clustering solution

0310, 2022

Investigating the temporality of binary taste interactions in blends of sweeteners and citric acid in solution

John Castura/ October 3, 2022/ Peer-reviewed Paper/ 0 comments

This study investigated sweet–sour taste interactions in novel sweeteners using a 3 × 2 factorial design consisting of Sweetening System (three levels: sucrose; d-allulose; and a blend of d-allulose and Monk fruit extract) and Acidity (two levels: with or without citric acid). 110 untrained Chinese subjects participated using the temporal check-all-that-apply (TCATA) method. Mixed-model ANOVA was conducted to investigate the effect of

0310, 2022

Identifying temporal sensory drivers of liking of biscuit supplemented with brewer’s spent grain

John Castura/ October 3, 2022/ Poster/ 0 comments

Brewer’s spent grain (BSG), a by-product of the brewing industry, has great potential as a valuable food additive. BSG is particularly rich in protein and fibre content which makes it an ideal nutritional fortifier for biscuits. However, adding BSG in biscuits can lead changes in sensory perception and consumer acceptance. This study explores the temporal sensory profiles and drivers/inhibitors of

0310, 2022

Screening as a tool to increase consumer data quality

John Castura/ October 3, 2022/ Poster/ 0 comments

We developed and tested a strategy to improve data quality in consumer tests by dropping consumers based on their screener responses. A key question was whether test outcomes were improved enough to justify the extra effort of having this screening step. To do this investigation, we made an online test in which respondents answered a short screener followed by a

2405, 2022

Temporal ranking for characterization and improved discrimination of protein beverages

John Castura/ May 24, 2022/ Peer-reviewed Paper/ 0 comments

We propose a new temporal sensory method called temporal ranking (TR) in which assessors indicate and rank the three most noticeable sensations at every time point. The TR method was compared to temporal-check-all-that-apply (TCATA) in two trained-panel studies, one study involving six ready-to-mix (RTM) protein beverages and one study involving seven ready-to-drink (RTD) protein beverages. In each study, the same

0403, 2022

Clustering consumers based on product discrimination in check-all-that-apply (CATA) data

John Castura/ March 4, 2022/ Peer-reviewed Paper/ 0 comments

Consumers can be clustered based on their product-related check-all-that-apply (CATA) responses. We identify two paradoxes that can occur if these clusters are derived from conventional similarity coefficients. The first paradox is that clustering similar consumers can nullify within-cluster sensory differentiation of products. The second paradox is that consumers who check many attributes yet disagree can be clustered together, whereas consumers

0102, 2022

Discriminability and uncertainty in principal component analysis (PCA) of temporal check-all-that-apply (TCATA) data

John Castura/ February 1, 2022/ Peer-reviewed Paper/ 0 comments

Temporal check-all-that-apply (TCATA) data can be summarized and explored using principal component analysis (PCA). Here we analyze TCATA data on Syrah wines obtained from a trained sensory panel. We evaluate new and existing methods to explore the uncertainty in the PCA scores. To do so, we use the bootstrap procedure to obtain many virtual panels from the real panel’s data.