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Comparison of Rate-All-That-Apply and Descriptive Analysis for the Sensory Profiling of Wine
- Source :
- American Journal of Enology and Viticulture. 69:12-21
- Publication Year :
- 2017
- Publisher :
- American Society for Enology and Viticulture, 2017.
-
Abstract
- The aim of this work was to investigate how useful the Rate-All-That-Apply (RATA) method with naive consumers is to profile a wide range of wines and how the sensory profiles obtained compare with those of classic descriptive analysis (DA). For this purpose, we conducted two studies. Study 1 presents preliminary work comparing the discrimination ability of RATA, undertaken by 84 naive consumers, with a traditional DA with 11 trained panelists. The vocabulary lists remained the same across the two methods, and the assessment was based on a set of six red table wines (from six different varieties). Study 2 aimed to further elucidate the discrimination ability of RATA with 71 naive consumers compared with traditional DA. It expanded on Study 1 by increasing the number of samples assessed (12 white table wines from six varieties) and by varying the vocabulary between methods (RATA used a generic white wine attribute list and the DA used a panel-generated attribute list). In addition, similarity of sample configuration in the sensory space between RATA and DA was assessed by means of multiple factor analysis (MFA) and regression vector (RV) coefficients. The results of both studies revealed that RATA and DA are highly similar in sample discrimination ability (in terms of number of attributes significantly discriminating among samples). Furthermore, the MFA indicated high agreement in sample configuration between RATA and DA, reinforced by highly significant RV coefficients of 0.97 for Study 1 and 0.92 for Study 2. Overall, this observation supports a trend toward more consumer-centric approaches for sensory profiling and suggests that RATA could be a valid, accurate, and rapid addition to existing profiling methods used for wine.
- Subjects :
- Wine
Vocabulary
Descriptive statistics
media_common.quotation_subject
Sensory system
04 agricultural and veterinary sciences
Horticulture
040401 food science
0404 agricultural biotechnology
Statistics
Multiple factor analysis
Profiling (information science)
Food Science
Mathematics
media_common
Regression vector
Subjects
Details
- ISSN :
- 00029254
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- American Journal of Enology and Viticulture
- Accession number :
- edsair.doi...........6031d2d615bc39d0bf9a7a978b80d092