Visualization of temporal differences between dominant perceptions in temporal dominance of sensations (TDS) and temporal check-all-that-apply (TCATA) perceptions using dominance-highlighted TCATA (dTCATA) curves

The temporal dominance of sensations (TDS) method measures dynamic changes of panelists’ attention to the sensory attributes of products. The temporal check-all-that-apply (TCATA) method measures all sensory attributes perceived at each moment of an evaluation. However, unlike in TDS, significant levels cannot be calculated in TCATA. This study proposes the use of dominance-highlighted TCATA (dTCATA) curves, which are highlighted TCATA curves that show significant time periods for the TDS data of different panels. Twelve R&D panelists evaluated five commercial corn soups using the TCATA method. Then, 125 consumer panelists evaluated the same products using the TDS method. The dTCATA curves showed TCATA curves for all attributes for each product evaluated by the R&D panel highlighted with the dominance rates identified by the consumer panel in the TDS evaluation. For example, for product 1, some attributes (sweet, viscosity) showed relatively high citation proportions in the TCATA evaluations of the R&D panel and significant dominance rates in the TDS evaluations of the consumer panel. In contrast, consommé flavor showed relatively low citation proportions in TCATA but significant dominance rates in TDS. By merging TDS and TCATA data, we could compare consumers’ dominant sensations with the evaluations of R&D panelists. This comparison could provide useful insights to product developers. In some cases, we observed attributes with significant dominance rates that were under-identified by the R&D panel in TCATA. This could suggest that most of the R&D panel may not have perceived these attributes; therefore, during product development, these attributes should be carefully considered.     

Alternating temporal dominance of sensations and liking scales during the intake of a full portion of an oral nutritional supplement

Measurement of liking with consumers is often performed on a single sip or mouthful of the product and results in a single liking score that does not necessarily reflect the liking over consumption of a whole product. A dynamic approach could provide this type of information. Thus, obtaining reasons why the liking score is changing over consumption could help to gain insights for product improvement. Recently, Thomas, Visalli, Cordelle, and Schlich (2015) suggested collecting with the same consumers liking scores dynamically and Temporal Dominance of Sensations (TDS) during mono-intakes of flavored cheeses, in two independent sessions. This new type of sensory data has been analysed at individual level to identify “temporal drivers of liking” for each product.The present paper further develops this method consisting of collecting TDS and dynamic liking data in the same session and during the consumption of the full portion of a product. The products used to experiment this new method were two commercial oral nutritional supplements (ONS) assessed by 65 consumers over two lab sessions separated by one week.The protocol consisted of a TDS evaluation of 5 flavor, 2 texture and 3 taste sensations during each sip, immediately followed by a liking scale. This protocol was repeated over sips. This method, named “Alternated Temporal Drivers of Liking” (A-TDL), required that consumers record liking changes and do TDS over sips during food consumption. Results showed that one of the two ONS was more liked than the other and consumed in a larger volume resulting in a higher energy intake. In contrast, the other product resulted in a stronger thirst and presented more negative temporal drivers of liking (dry, metallic, filming) over the consecutive sips.     

Investigating temporal sensory data via a graph theoretic approach

A graph theoretic approach is applied to investigate perception dynamics in the Sensometrics 2018 Data Analysis Workshop data sets. First, temporal check-all-that-apply (TCATA) data are investigated: ten sensory attributes are modelled as vertices and concurrent perception as edges, the size and width of each corresponding to the momentary elicitations and the concurrent elicitations, respectively. A temporal dominance of sensations (TDS) data set does not lend itself as readily to this type of analysis because the task for each assessor involves selection of only one dominant attributes at a time. For this reason, TDS data sets considered in this workshop are (re-)analyzed within localized temporal ranges, considering dominance elicitations within localized temporal ranges to be adjacent-dominant. In TDS by Modality (M-TDS), assessors taste the sample to evaluate the five taste and flavour attributes via TDS, then retaste the sample to evaluate the five texture attributes via TDS. M-TDS results from these two separate tasting timelines are adjoined as if they arose from a single evaluation timeline, which ignores systematic biases that may be introduced by the evaluation protocol (e.g. texture attributes are always evaluated with carryover effects from the first tasting). Data from each of these temporal sensory method are then analyzed using a graph theoretic approach. Cliques and attribute structures are identified. TCATA and TDS results are more similar to one another than either is to M-TDS results. Implications of method choice and various data pre-processing decisions are discussed.     

Exploring the common and unique variability in TDS and TCATA data – A comparison using canonical correlation and orthogonalization

Temporal Dominance of Sensations (TDS) and Temporal Check-all-that-Apply (TCATA) from three different case studies are compared by means of canonical correlation analysis, orthogonalization and principal component analysis of the vertically unfolded data (which means that the matrices compared have samples*timepoints in the rows and attributes in the columns). The multivariate analyses decompose the datasets into common and distinct components. The results showed that the major part of the variation is common between the two methods for the cases investigated, but that there were subtle differences showing better discrimination for TCATA than TDS. TDS showed a more complex data structure and more unique variation. The unique variation in TDS is, however, difficult to interpret. The methods are more different towards the end of the mastication, this can be explained both by the difficulty of assessors to agree on the dominant attributes at the bolus stage for TDS, and that assessors may forget to unclick attributes in TCATA. This work builds on recent methodological studies on temporal methods that aim to better understand differences among methodologies and ultimately to identify what methods could be better for answering different objectives.     

Temporal methods: Are we comparing apples and oranges?

A workshop held at the 2018 Sensometrics conference in Montevideo aimed at a data-based comparison between three temporal methods, namely Temporal Check-All-That-Apply (TCATA), Temporal Dominance of Sensations (TDS), and Temporal Dominance of Sensations by Modality (MTDS). Data on 8 yoghurts designed following a full-factorial design have been evaluated using the three protocols. In this paper, we compare the data obtained with regard to discriminative power and highlight potential pitfalls when making significance-based comparisons. TCATA is found to provide overall highest discrimination, while for special purposes, the other methods may have advantages. We further compare the dominance and selection rates from the methods, addressing the arbitrariness of necessary standardizations. Finally, we compare results from correspondence analyses with trajectories, showing noteworthy differences between the protocols. In the discussion, it is argued that a reasonable comparison between the methods might not be possible or even reasonable, as they address quite different concepts. Rather than being considered as alternatives for the same objective, they should better be considered as complimentary, addressing different project needs.     

Temporal dominance of emotions: Measuring dynamics of food-related emotions during consumption

Mapping food-evoked emotions in addition to sensory profiling is topical. In sensory profiling, the Temporal Dominance of Sensation (TDS) method focuses on the assessment of the temporal evolution of dominant sensory attributes over time. We hypothesize that food-evoked emotions also show temporal dynamics that can be related to dynamic sensory perception. This study assessed temporal dynamics of sensory and emotional attributes during chocolate tasting. We used TDS to determine dynamic sensory properties of dark chocolates providing a list of 10 sensory attributes. Comparably, Temporal Dominance of Emotions (TDE) was assessed by replacing the sensory attributes with 10 emotional attributes. Sixty-two participants assessed TDS and TDE of five commercially available dark chocolates (plain and flavoured). Multivariate comparisons (Hotelling test) showed significant differences between products based on the dominance duration of sensory (p < 0.05) and emotional attributes (p < 0.05). TDS difference curves revealed products to differ based on their dominant sensory attributes, with different attributes peaking at different time moments. TDE difference curves showed that products also differed in the temporal distribution of dominant emotional attributes. Comparing the average dominance rates between plain dark and flavoured dark chocolates revealed that for flavoured dark chocolates mainly flavour attributes and positive/active emotions were perceived as salient whereas for plain dark chocolates textural as well as taste attributes were dominant accompanied by more negative/non-energetic emotions. A joint CVA plot on the duration of dominance for sensory and emotional attributes per product revealed that temporal evolution of sensory – and emotional attributes was related. This suggests a mutual reciprocity between those two entities (sensory and emotional attributes) resulting in more complex, richer product characterization. In conclusion, these findings show TDE to be a promising new venue in characterising food-evoked emotions in relation to sensory profiling.     

Sugar reduction in probiotic chocolate-flavored milk: Impact on dynamic sensory profile and liking

Reducing the sugar content of processed products has been claimed to be one of the most efficient strategies for decreasing sugar intake. The present work aimed at studying the influence of sugar reduction on the dynamic sensory profile and consumers' liking of probiotic chocolate-flavored milks using a novel temporal methodology, and to evaluate two alternatives (vanilla flavor and thaumatin) to attenuate the sensory changes caused by sugar reduction. Probiotic chocolate-flavored milks were formulated with different reductions in added sugar (0, 20, 40 and 60%). Vanilla flavor and thaumatin were added to the sugar-reduced samples at two concentrations. Samples were evaluated by trained assessors using Temporal check-all-that-apply (TCATA). Additionally, consumers evaluated the dynamic sensory profile of a subset of the samples using TCATA and indicated their overall liking using a 9-point hedonic scale. Results from the present work showed that the main effect of sugar reduction on the dynamic sensory profile of the probiotic chocolate-flavored milks was related to changes in sweetness, bitterness and thickness. A reduction in added sugar of 20% led to changes in sweetness intensity, which were perceived by both trained assessors and consumers. However, consumers' liking was not significantly affected by sugar reduction up to 40%. The addition of vanilla flavor at suprathreshold concentrations was not efficient in increasing sweetness perception in chocolate-flavored milks with the lowest sugar reduction percentage, suggesting that it may not be a feasible alternative for reducing sugar in this product category. These results suggest that in many situations sugar content of food products could be decreased without a relevant impact on consumers' sensory and hedonic perception.     

Influence of fading duration on TCATA evaluation

Temporal Check All that Apply (TCATA) is a dynamic sensory evaluation technique in which participants select the terms they consider apply at each moment from a list of attributes and deselect them when they no longer apply. TCATA Fading is a variant that facilitates the TCATA task by making term deselection automatic and progressive over.a period of a few seconds. The aim of the present work was to assess the influence of fading duration on the TCATA Fading task and results. Three studies evaluated two fading durations (4 s vs 8 s in Study 1 and 2, and 3 s vs 6 s in Study 3), using commercial cooked ham, a strawberry-flavoured dessert and orange juice, and compared task performance, TCATA curves and sensory trajectories. Longer fading times resulted in TCATA curves with higher citation proportions, in which differences among samples lasted slightly longer. TCATA curves and trajectories provided very similar information on differences in dynamic sensory perception of the products. Fading duration seems to be not critical when using values within a “reasonable” range, which can be determined in preliminary essays. Ideally it would be advisable to choose the shorter fading time in the range to avoid possible overestimation of the duration of sensations and “filling gaps” procedure to compensate the increase in gap events due to delay in reselection. This is the first paper to show the implications of duration of fading in TCATA evaluation.     

Powerful visualization of product-attribute associations for temporal data

Temporal Check-All-That-Apply (TCATA) extends classical Check-All-That-Apply (CATA) by adding a temporal dimension to the evaluation. Because TCATA extends CATA, an obvious visualization of product-attribute associations over time is to treat product x time combinations as individual observations and then use classical Correspondence Analysis (CA) to visualize the associations. Often the CA results and visualization emphasize the chronological features. However, this approach could lead to misinterpretations as time is not just a feature but also a confound. Because of time, all products might show convergence to, e.g., off flavor, which is produced only by a few observations that provide a relative but not an absolute peak in this attribute.Therefore, we suggest alternative CA approaches to analyze TCATA data that emphasize (Canonical CA, CanCA) or remove (Escofier’s Conditional CA, ConCA) temporal effects. Generally, CanCA was designed to analyze CA data in the presence of row and column covariates; it is related to canonical correlation analysis. When there is only one set of covariates (e.g., row), CanCA is more akin to redundancy analysis. Here, we use external row information – time and product – to emphasize the overall temporal profile applying to all products. CanCA nicely displays the main product differences within the attribute space. CanCA better emphasizes than CA the unique properties of each product over time. Escofier’s conditional CA (ConCA) removes confounding effects such as time. ConCA provides two features for TCATA: (1) effects adjusted for time and (2) more appropriate measures of strength of association that can be used with CA for better visualization.We exemplify the proposed methods by means of data from a study on orange squashes. The relevance of off flavor is (correctly) found to be largely de-emphasized compared to standard CA: CanCA shows off flavor as an average effect because of time and ConCA shows off flavor does not contribute to the overall effect. Together CanCA and ConCA facilitate a richer, more detailed, and potentially more accurate interpretation of the data. The approaches can be equally used for Temporal Dominance of Sensations (TDS) data.