Statistical analysis between analytical and sensory data of coffee aroma.

  • WADA Kouji
    Department of food Science and Technology, Faculty of Agriculture, Kyushu University
  • TANAKA Yoshinori
    Department of food Science and Technology, Faculty of Agriculture, Kyushu University
  • SHIMODA Mitsuya
    Department of food Science and Technology, Faculty of Agriculture, Kyushu University
  • OHGAMA Seiichi
    Key Coffee Co., Nishishimbashi
  • OSAJIMA Yutaka
    Department of food Science and Technology, Faculty of Agriculture, Kyushu University

Bibliographic Information

Other Title
  • コーヒーの香りに関する研究 X  コーヒー香気の機器分析データと官能検査データの統計的解析
  • コーヒー コウキ ノ キキ ブンセキ データ ト カンノウ ケンサ データ ノ

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Abstract

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.

Journal

  • Nippon Nōgeikagaku Kaishi

    Nippon Nōgeikagaku Kaishi 63 (9), 1485-1491, 1989

    Japan Society for Bioscience, Biotechnology, and Agrochemistry

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