Identification of geographical origins of soybean pastes using headspace gas chromatography-mass spectrometry by selecting sample-descriptive components with an Incremental Association Markov Blanket

Abstract

The identification of geographical origins of soybean pastes using headspace gas chromatography-mass spectrometry was attempted in this study. Since soybean paste was odor-rich, 36 components were identified in the imported and domestic soybean samples. t-Test, variable importance in projection (VIP), and Incremental Association Markov Blanket (IAMB) were employed to select proper components that could effectively discriminate the two sample groups. The discrimination accuracies were below 87.3 % when all 36 components were fed for either LDA, k-NN, or SVM. When the five t-test-selected components or six VIP score-selected components were employed, the accuracies improved to 95.2–96.2 %. The IAMB selected three different components were 3-methylbutanal, 4-methylnonane, and 2,3-pentanedione, and the correlations among their peak areas were not significant. This suggests that these three components were independently relevant for the discrimination. The accuracy obtained using these three components was superior, 97.7 %, as undescriptive and/or redundant components for the discrimination were excluded.