Free-comment outperformed check-all-that-apply in the sensory characterisation of wines with consumers at home

Abstract Check-All-That-Apply (CATA) is a popular method used for collecting word-based sensory descriptions from consumers. Free-Comment (FC), as a response to open-ended questions, is an interesting alternative because it removes biases due to the use of a predefined list of descriptors. In the context of a home used test (HUT), FC enables subjects to express themselves more naturally. The present study investigated the relevance of the use of FC at home for word-based sensory description of a set of products. Two groups of 60 consumers of red wines characterised four French red wines from different terroirs performing either a CATA task or a FC task. The two sensory tasks were performed at home according to sensory modality: visual, olfactory and gustatory. The first objective was to investigate whether a FC protocol can be successfully conducted at home and whether it enables the characterisation and discrimination of a set of products. The second objective was to investigate whether extrinsic sensory information affects FC descriptions. The third objective was to investigate whether CATA and FC provide comparable information in the HUT context. The results show that an FC protocol is feasible at home and that the extrinsic sensory information did not affect FC descriptions. FC enabled better characterisation and discrimination of the products than CATA. A new test of product differences based on the total bootstrap procedure was proposed to compare FC and CATA.

[1]  H. Goldstein,et al.  The Graphical Presentation of a Collection of Means , 1995 .

[2]  Michael Greenacre,et al.  Clustering the rows and columns of a contingency table , 1988 .

[3]  G. Jager,et al.  Taste matters most: Effects of package design on the dynamics of implicit and explicit product evaluations over repeated in-home consumption , 2019, Food Quality and Preference.

[4]  Sylvie Chollet,et al.  Invited review Quick and dirty but still pretty good: a review of new descriptive methods in food science , 2012 .

[5]  Michael Greenacre,et al.  Tying up the loose ends in simple, multiple, joint correspondence analysis , 2006 .

[6]  Morten Meilgaard,et al.  Sensory Evaluation Techniques , 2020 .

[7]  Ronan Symoneaux,et al.  Using the free comments method for sensory characterisation of Cabernet Franc wines: Comparison with classical profiling in a professional context , 2013 .

[8]  J. Sieffermann,et al.  Consumer texture descriptions of a set of processed cheese , 2015 .

[9]  Betina Piqueras-Fiszman,et al.  Comparison of Rate-All-That-Apply (RATA) and Descriptive sensory Analysis (DA) of model double emulsions with subtle perceptual differences , 2017 .

[10]  Sébastien Lê,et al.  Nudging consumers for relevant data using Free JAR profiling: An application to product development , 2020 .

[11]  D. Hout,et al.  A novel two-step rating-based ‘double-faced applicability’ test. Part 1: Its performance in sample discrimination in comparison to simple one-step applicability rating , 2017 .

[12]  Ronan Symoneaux,et al.  Comment analysis of consumer’s likes and dislikes as an alternative tool to preference mapping. A case study on apples , 2012 .

[13]  D. Valentin,et al.  Reducing the sodium content without modifying the quality of beef burgers by adding micronized salt. , 2019, Food research international.

[14]  Conor M. Delahunty,et al.  Descriptive sensory analysis: past, present and future , 2001 .

[15]  G. Hough,et al.  Influence of temperature and light exposure on sensory shelf-life of a commercial sunflower oil , 2001 .

[16]  S. Jaeger,et al.  CATA questions for sensory product characterization: Raising awareness of biases , 2013 .

[17]  R. Boakes,et al.  The knowing nose: the role of knowledge in wine expertise , 2002 .

[18]  Jean-Xavier Guinard,et al.  How do consumer hedonic ratings for extra virgin olive oil relate to quality ratings by experts and descriptive analysis ratings , 2011 .

[19]  Margaret A. Brandt,et al.  Texture Profile Method , 1963 .

[20]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[21]  Simone Mueller,et al.  The relative influence of packaging, labelling, branding and sensory attributes on liking and purchase intent: Consumers differ in their responsiveness , 2010 .

[22]  Pieter A. D. Musters,et al.  Text analysis of open-ended survey responses : a complementary method to preference mapping , 2003 .

[23]  John C. Castura,et al.  Check-All-That-Apply Questions , 2014 .

[24]  M. Pelchat,et al.  Consumer sensory perception of cheese depends on context: A study using comment analysis and linear mixed models , 2014 .

[25]  Carolina Chaya,et al.  The influence of sensory and packaging cues on both liking and emotional, abstract and functional conceptualisations , 2013 .

[26]  P. Schlich,et al.  Accounting for the dimensionality of the dependence in analyses of contingency tables obtained with Check-All-That-Apply and Free-Comment , 2020 .

[27]  R. Symoneaux,et al.  Mixed Profiling: A new tool of sensory analysis in a professional context. Application to wines , 2017 .

[28]  Vani R. Henderson,et al.  Yes–no Answers versus Check-all in Self-Administered Modes: A Systematic Review and Analyses , 2015 .

[29]  Gastón Ares,et al.  Comparison of check-all-that-apply and forced-choice Yes/No question formats for sensory characterisation , 2014 .

[30]  Gastón Ares,et al.  Sensory profiling, the blurred line between sensory and consumer science. A review of novel methods for product characterization , 2012 .

[31]  S. Cairncross,et al.  Flavor Profiles: A New Approach to Flavor Problems , 2008 .

[32]  Gastón Ares,et al.  Use of an open-ended question to identify drivers of liking of milk desserts. Comparison with preference mapping techniques , 2010 .

[33]  N. Hatton.  ASKING QUESTIONS , 1979, The Medical journal of Australia.

[34]  F. Netto,et al.  Examining the role of regional culture and geographical distances on the representation of unfamiliar foods in a continental-size country , 2020 .

[35]  G. Ares,et al.  Trained vs. consumer panels for analytical testing: Fueling a long lasting debate in the field , 2017 .

[36]  Marine Cadoret,et al.  Construction and evaluation of confidence ellipses applied at sensory data , 2013 .

[37]  R. Singleton,et al.  Sensory Evaluation by Quantitative Descriptive Analysis , 2008 .

[38]  Jolene D. Smyth,et al.  Comparing Check-All and Forced-Choice Question Formats in Web Surveys , 2006 .