This study introduces temporal rate-all-that-apply (TRATA) as a new temporal sensory method. It was inspired by rate-all-that-apply (RATA) and temporal check-all-that-apply (TCATA), but is most similar to multiple-attribute time intensity (MATI) in that the TRATA method allows for simultaneous rating of attribute intensities over time. Only attributes that are perceived are scaled. In this case study, the TRATA method was
Temporal ranking for the characterization and better discrimination of protein beverages with different sweeteners
This study proposes the application of ranking to temporal product evaluation to differentiate attribute dominances over time. The ability of the proposed method to discriminate sensory differences was compared to temporal check-all-that-apply (TCATA), a discriminating temporal method for capturing the temporal profile of food and beverage products.
Analyzing data using the chance-corrected beta-binomial model: Parameter estimates and their confidence regions
Data arising from replicated sensory discrimination test methods with a correct response are often modelled using the chance-corrected beta-binomial distribution. The model can provide maximum likelihood estimates of the mean proportion of correct responses in the population (and discriminal distances under Thurstonian assumptions) and of the assessor heterogeneity (overdispersion). Both of these parameters are estimated with uncertainty. Previously uncertainty associated
Analysis of sensory check-all-that-apply (CATA) data which includes the evaluation of a single ideal product
When evaluating samples in sensory tests, consumers are sometimes asked not only about real samples but also about imagined ideal products. Check-all-that-apply (CATA) questions are one way to understand consumers’ perceptions of products and their ideal product. We propose the following statistical analyses of consumer CATA data: (i) confidence intervals for head-to-head comparisons based on CATA data; (ii) panel (dis)agreement
A retail simulation study for investigating product choice and choice satisfaction: A case study involving kombucha
Kombucha is a fermented tea that is rapidly growing in popularity in the United States. As part of a larger consumer study conducted in Portland, Oregon, kombucha consumers (n=1303, 68% female, aged 18-86, USA)participated in an online retail simulation test. They evaluated 9 commercial products (bottle images) and made choice selections in a retail simulation.
Segmenting consumers based on food choice motivation and product benefit expectations: A case study involving Kombucha
Kombucha is a fermented beverage that is rapidly growing in popularity in the United States. As part of a larger consumer study conducted in Portland, Oregon, kombucha consumers (n=230) participated in a retail simulation in a central location test. They evaluated 9 commercial products, made choice selections, and were prompted with questions related to food choice motivations, product expectations and
Brettanomyces spoilage in wine is due to the production of metabolites, which together create a distinctive ‘Bretty’ aroma and flavor profile. The objective of this study was to assess the influence three wine flavor matrices have on consumer perception and acceptance of wines containing high and low concentrations of Brettanomyces-metabolites. A commercial Shiraz wine was altered through additions of whiskey
Light-struck taints in wine develop when they are exposed to sunlight and elevated temperature. Affected wines undergo a colour change, a decrease in fruit flavours and a development of off-flavours that have been described as cooked cabbage and/or corn nuts. This poses a problem in retail stores that have a large number of external facing windows that can potentially expose
From a sensory perspective, sparkling wines are highly complex products. Carbonation imparts characteristic mouthfeel effects that include tingling and other sensations, and may trigger gustatory, olfactory, trigeminal, and auditory perceptions as well.
Dominance rates arising from temporal dominance of sensations (TDS) data are almost always plotted and understood with reference to chance and significance lines. Chance lines are fully determined by the number of attributes, and represent what we might expect if poor reading but task-engaged monkeys picked the attributes. Significance lines are conventionally based on the 95% upper confidence limit for