Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Improving communication of sensory profiling results – an illustration

Improving communication of sensory profiling results – an illustration Much sensory research focuses on an initial analysis of sensory descriptor data followed by a principal component analysis (PCA) of the sensory descriptors. This paper illustrates an alternative approach of conducting PCA and then applying analysis of variance (ANOVA) to the extracted principal components. The approach is applied to data from a case study quantifying the sensory characteristics of a sous vide vegetable product during storage. In the case study, 11 out of 18 descriptors were significantly influenced by product. Using the alternative approach, however, three out of six principal components were significantly influenced by product. The alternative approach, therefore, provided a more concise presentation of results and one that was consistent with the analysis of the original descriptors. It is hoped that this approach could improve interpretation and subsequent communication of sensory profiling results and help to bridge the gap between core and wider product development activities. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png British Food Journal Emerald Publishing

Improving communication of sensory profiling results – an illustration

Download PDF
11 pages

Loading next page...
 
/lp/emerald-publishing/improving-communication-of-sensory-profiling-results-an-illustration-FV0iURuePI
Publisher
Emerald Publishing
Copyright
Copyright © 2004 Emerald Group Publishing Limited. All rights reserved.
ISSN
0007-070X
DOI
10.1108/00070700410539789
Publisher site
See Article on Publisher Site

Abstract

Much sensory research focuses on an initial analysis of sensory descriptor data followed by a principal component analysis (PCA) of the sensory descriptors. This paper illustrates an alternative approach of conducting PCA and then applying analysis of variance (ANOVA) to the extracted principal components. The approach is applied to data from a case study quantifying the sensory characteristics of a sous vide vegetable product during storage. In the case study, 11 out of 18 descriptors were significantly influenced by product. Using the alternative approach, however, three out of six principal components were significantly influenced by product. The alternative approach, therefore, provided a more concise presentation of results and one that was consistent with the analysis of the original descriptors. It is hoped that this approach could improve interpretation and subsequent communication of sensory profiling results and help to bridge the gap between core and wider product development activities.

Journal

British Food Journal – Emerald Publishing

Published: Jun 1, 2004

Keywords: Product development; Data reduction

References

  • Quantitative descriptive analysis (QDA) – utilising the human instrument
    Armstrong, G.A.
  • Sous vide products
    Armstrong, G.A.
  • British Standard Guide to Design of Test Rooms for Sensory Analysis of Food – BS7183
    British Standards Institutue
  • Statistical analysis of sensory profiling data. Graphs for presenting results (PCA and ANOVA)
    Chabanet, C.
  • Consumer preference for the sensory characteristics of bottled beer
    Delahunty, C.; Caulfield, B.
  • Applying sensory information in the food industry – making your products better
    Eicher, N.
  • A case study of the use of experimental design and multivariate analysis in product improvement
    Ellekjaer, M.R.; Iiseng, M.A.; Naes, T.
  • Workshop on the statistical analysis of sensory profiling data: randomization/permutation/ANOVA
    Kunert, J.
  • Sensory Evaluation of Food – Principles and Practices
    Lawless, H.T.; Heymann, H.
  • Statistical Methodology for the Analysis and Interpretation of Sensory Profile and Consumer Acceptability Data – Technical Memorandum No. 536
    McEwan, J.A.
  • Sensory Evaluation Techniques
    Meilgaard, M.; Civille, G.V.; Carr, B.T.
  • Mapping consumer preference for the sensory and packaging attributes of Cheddar cheese
    Murray, J.M.; Delahunty, C.M.
  • Statistical analysis of sensory profiling data: data reduction and generalised procrustes analysis
    Peron, L.
  • A comparison of multivariate approaches to sensory analysis and the prediction of acceptability
    Popper, R.D.; Risvik, E.; Martens, H.; Martens, M.
  • Current practices and applications of descriptive methods
    Powers, J.J.
  • Consumer Sensory Testing for Product Development
    Resurreccion, A.V.A.
  • Top 10 trends to watch and work on
    Sloan, A.E.
  • Making sense of sensory analysis
    Spooner, M.
  • Applied multivariate statistics for the social sciences
    Stevens, J.
  • Sensory evaluation practices
    Stone, H.; Sidel, J.
  • Descriptive analysis
    Stone, H.; Sidel, J.
  • Quantitative descriptive analysis: developments, applications and the future
    Stone, H.; Sidel, J.
  • Using Multivariate Statistics
    Tabachnick, B.G.; Fidell, L.S.
  • Variable selection in PCA in sensory descriptive and consumer data
    Westad, F.; Hersleth, M.; Lea, P.; Martens, H.
  • Quantitative descriptive analysis
    Zook, K.L.; Pearce, J.H.