Statistical Analysis between Analytical and Sensory Data of Coffee Aroma

Kouji Wada, Yoshinori Tanaka, Mitsuya Shimoda, Yutaka Osajima, Seiichi Ohgama

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The relationship between gas chromatographic (GC) data and sensory data was analyzed in 31 arabica coffee samples by multivariate analysis, and the aroma profiles of the samples were characterized. Using principal component analysis (PCA) for GC data, the samples were classified into six groups. The relationships between the principal components obtained by PCA and sensory data were linear by Quantification Theory 1. On the basis of partial correlation coefficients, the effects of the terms used in sensory evaluation on the first and second principal component were clarified.

Original languageEnglish
Pages (from-to)1485-1491
Number of pages7
JournalNippon Nōgeikagaku Kaishi
Issue number9
Publication statusPublished - 1989

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Food Science
  • Chemistry (miscellaneous)
  • Medicine (miscellaneous)


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