Application of GPA and PLSR in correlating sensory and chemical data sets

Seo Jin Chung, Hildegarde Heymann, Ingolf U. Grün

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


This paper discusses the application of various multivariate statistical procedures to understand the relationship between sensory and instrumental flavor profiles. Ice cream with varying fat levels was used as the vehicle for the flavor compounds in the experiment. Chemical and sensory flavor profiles were obtained by modified dynamic headspace analysis and descriptive analysis, respectively. Chromatographic peak areas of flavor-volatiles were used as the variables for the chemical data set. Initially, principal component analysis and canonical variate analysis were performed separately on the chemical and sensory data sets to explore the structure of each set. Flavor volatiles were then further studied to investigate their impact on the sensory profile of ice cream using general procrustes analysis and partial least squares regression analysis. The results from the two statistical analysis methods are compared and discussed. Additionally, the effect of log-transformation of chemical data on the overall chemical-sensory relationship was evaluated within each statistical method.

Original languageEnglish
Pages (from-to)485-495
Number of pages11
JournalFood Quality and Preference
Issue number5-6
StatePublished - Jul 2003


  • General procrustes analysis
  • Ice cream
  • Low fat
  • Partial least squares regression analysis
  • Sensory-instrumental correlations


Dive into the research topics of 'Application of GPA and PLSR in correlating sensory and chemical data sets'. Together they form a unique fingerprint.

Cite this