Does the face show what the mind tells? A comparison between dynamic emotions obtained from facial expressions and Temporal Dominance of Emotions (TDE)

Measuring food-evoked emotions dynamically during consumption can be done using explicit self-report methods such as Temporal Dominance of Emotions (TDE), and implicit methods such as recording facial expressions. It is not known whether or how dynamic explicit and implicit emotion measures correspond. This study investigated how explicit self-reported food-evoked emotions evaluated with TDE are related to implicit food-evoked emotions determined from facial expressions. Fifty-six participants evaluated six yogurts with granola pieces varying in size, hardness and concentration, using multiple bite assessment employing TDE for the first, third and fifth bite of consumption. Consumers were video recorded during each bite of consumption and facial expressions were analysed using FaceReader™. Happy, interested, disgusted and bored were similar descriptors measured explicitly and implicitly. Little overlap was observed regarding the type of emotion characterization by FaceReader™ and TDE. Products were mainly discriminated along the valence dimension (positive – negative), and directly reflected product discrimination in terms of liking. FaceReader™ further differentiated the least liked products from each other on arousal and negative facial expressions. Our results indicated little dynamics in food-evoked emotions within and between bites. Facial expressions seemed more dynamic within bites, while explicit food-evoked emotion responses seemed more dynamic between bites. We conclude that FaceReader™ intensities of emotions and dominance durations observed in TDE are not directly comparable and show little overlap. Moreover, food-evoked emotion responses were fairly stable from first to last bite and only very limited changes were observed using implicit and explicit emotions measures.</p

TimeSens - un logiciel Web pour l'acquisition et le traitement des données sensorielles

TimeSens est un nouveau logiciel dédié à l'acquisition et au traitement des données d'analyse sensorielle. TimeSens bénéficie de l'expérience et de l'expertise de ChemoSens, la plate-forme d'analyse sensorielle du CSGA. TimeSenspropose la plupart des protocoles standards de l'analyse sensorielle (profil, tests hédoniques, DTS), ainsi que des protocoles originaux (MATI, PSP). Les résultats collectés peuvent être analysés à l'aide de méthodes statistiques traditionnelles ou innovantes

Combining statistics and semantic for an automated data analysis of Free-Comment sensory description of products

Diaporama de 54 p.International audienceFree-Comment (FC) is a sensory characterization method where panelists are invited to describe the products using their own term by answering open-ended questions. Despite its benefits, notably its spontaneous and natural aspects, the method remains currently underused in practice. The main reason for that is likely to be the cumbersome and time-consuming extraction of relevant sensory information from the text. This presentation introduces a web-based application (accessible from any web browser) that fully automatizes the data analysis of FC data without requiring any coding. The relevant sensory information is extracted from the text using NLP tools combined with semantics. It results in descriptors classified and hierarchized according to an ontology. Then, an algorithm aggregates the descriptors having the same semantic meaning (same parent in the tree structure of the ontology) AND similar profiles of citations that maximize product discrimination. The descriptors are then encoded as check-all-that-apply data and analyzed using multiple-response chi-square related methods

Multi-attribute temporal descriptive methods in sensory analysis applied in food science: Protocol for a scoping review

International audienceBackground Sensory perception is a temporal phenomenon highly present in food evaluation. Over the last decades, several sensory analysis methods have been developed to determine how our processing of the stimuli changes during tasting. These methods differ in several parameters: how attributes are characterized (intensity, dominance or applicability), the number of attributes evaluated, the moment of sample characterization (simultaneously with the tasting in continuous or discrete time, retrospectively), the required panel (trained subjects or consumers), etc. At the moment, there is no systematic review encompassing the full scope of this topic. This article presents the protocol for conducting a scoping review on multi-attribute temporal descriptive methods in sensory analysis in food science. Methods The protocol was developed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews checklist. The research question was "how have multi-attribute temporal descriptive methods been implemented, used and compared in sensory analysis?". The eligibility criteria were defined using the PICOS (Population, Intervention, Comparator, Outcome, Study design) framework. This protocol details how the articles of the final review will be retrieved, selected and analyzed. The search will be based on the querying of two academic research databases (Scopus and Web of Science). The main topics reported in research involving sensory analyses methods will be identified and summarized in a data extraction form. This form (detailed in the protocol) will be used to report pertinent information regarding the objectives of the review. It could also be reused as a guideline for carrying out and reporting results of future research in a more standardized way. A quality appraisal process was derived from literature. It will be applied on the included articles of the review, and could also be re-used to ensure that future publications meet higher quality levels. Finally, for the sake of transparency, the limitations of the protocol are discussed

Multi-attribute temporal descriptive methods in sensory analysis applied in food science: protocol for a scoping review

Abstract: Background: Sensory perception is a temporal phenomenon highly present in food evaluation. Over the last decades, several sensory analysis methods have been developed to determine how our processing of the stimuli changes during tasting. These methods differ in several parameters: how attributes are characterized (intensity, dominance or applicability), the number of attributes evaluated, the moment of sample characterization (simultaneously with the tasting in continuous or discrete time, retrospectively), the required panel (trained subjects or consumers), etc. At the moment, there is no systematic review encompassing the full scope of this topic. This article presents the protocol for conducting a scoping review on multi-attribute temporal descriptive methods in sensory analysis in food science. Methods: The protocol was developed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews checklist. The research question was "how have multi-attribute temporal descriptive methods been implemented, used and compared in sensory analysis?". The eligibility criteria were defined using the PICOS (Population, Intervention, Comparator, Outcome, Study design) framework. This protocol details how the articles of the final review will be retrieved, selected and analyzed. The search will be based on the querying of two academic research databases (Scopus and Web of Science). The main topics reported in research involving sensory analyses methods will be identified and summarized in a data extraction form. This form (detailed in the protocol) will be used to report pertinent information regarding the objectives of the review. It could also be reused as a guideline for carrying out and reporting results of future research in a more standardized way. A quality appraisal process was derived from literature. It will be applied on the included articles of the review, and could also be re-used to ensure that future publications meet higher quality levels. Finally, for the sake of transparency, the limitations of the protocol are discussed

Decomposition of the level effect into overall and descriptor-specific components

International audienceDespite training, subjects in a descriptive panel can still differ in their use of the scale. Some subjects can score higher or lower than others (level effect) or spread more or less their scores on the scale (scaling effect). The scaling effect, as calculated in Brockhoff, Schlich, and Skovgaard (2015), was recently decomposed into an overall and a descriptor-specific component (Peltier, Visalli, &Schlich, 2015b). It was suggested that the overall component was related to psychological effect whereas the specific one was more related to a physiological one.This paper aims to extend this decomposition to the level effect. The overall level effect gives indications about the psychological component of the scoring level, which is obtained by averaging the level effects of all the descriptors, whereas the descriptor-specific component can reveal a subject's hyper-or hyposensitivity to a given descriptor and thus is related to the individual's physiological response. The relevance of this decomposition was demonstrated by a meta-analysis of 419 sensory profiling datasets.Finally, the summary table of performances MAM-CAP Table (Peltier, Brockhoff, Visalli, & Schlich, 2014) was improved in order to show both level and scaling effects (overall and specific) for facile monitoring of individual differences in the use of sensory scales by a panel

Multiplicative decomposition of the scaling effect in the Mixed Assessor Model into a descriptor-specific and an overall coefficients

In 1994, Brockhoff and Skovgaard presented the so-called assessor model, including a “scaling coefficient” expressing the predisposition of a panelist to spread more or less his scores than the panel on a given sensory descriptor. This paper discusses potential scaling causes, and then proposes a decomposition of the scaling coefficient into two components: (i) an overall scaling coefficient, independent of the descriptors, expressing a psychological trend of the panelist towards the scoring task in general; (ii) a corrected scaling coefficient for each descriptor, expressing specific sensitivity of the panelist to the descriptor. Applied to 187 sensory datasets, this decomposition showed that panelists over sixty years old and smokers tend to spread less their scores than other panelists regardless of the sensory modalities; further, the corrected scaling coefficients were more heterogeneous among panelists for aroma and flavor compared to texture and appearance sensory modalities

Corrigendum to “Concurrent vs immediate retrospective temporal sensory data collection: A case study on lemon-flavoured carbonated alcoholic drinks” [Food Qual. Pref. 101 (2022) 104629]

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Temporal drivers of liking by period: A case study on lemon-flavored carbonated alcoholic drinks with consumers in natural settings

International audienceKey driver analysis has long been used to identify important attributes that could positively or negatively contribute to product liking among target consumers. However, most studies focus only on how a desirable product should or should not be perceived, without considering when these perceptions dynamically occur during consumer interaction with the product. The objective of this study was to investigate drivers of liking with considerations of temporal descriptions collected from consumers having tasted full cans of four lemon-flavored carbonated alcoholic drinks at home. A total of 193 naive consumers were asked to check all applicable items from a check-all-that-apply list among eight attributes during three periods of perception- "in mouth before swallowing," "immediately after swallowing" and "aftertaste"-for three sips (1st, 4th, and 7th) of each can, using their own smartphones while tasting each drink at home. Drivers of liking were analyzed both with and without considering the temporality of the three periods. The results suggested that taking dynamic perceptions into account enables the capture of not only the drivers of liking at the precise moment of tasting, but also further details. The results also indicated that bitterness perceived in the mouth before swallowing and as an aftertaste negatively contributed to product liking, and that lemon aroma had the greatest positive contribution to product liking in the aftertaste period. These results suggest that "temporal drivers of liking by period" could add greater value for product development and marketing purposes