Food Science and Technology Research
Online ISSN : 1881-3984
Print ISSN : 1344-6606
ISSN-L : 1344-6606
Original papers
Coupled Stepwise PLS-VIP and ANN Modeling for Identifying and Ranking Aroma Components Contributing to the Palatability of Cheddar Cheese
Airi Morita Tetsuya ArakiShoma IkegamiMisako OkaueMasahiro SumiReiko UedaYasuyuki Sagara
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2015 年 21 巻 2 号 p. 175-186

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A consumer-oriented methodological approach for the quality evaluation of Cheddar cheese as a typical fermented food was developed. Datasets were obtained from gas chromatography/olfactometry (GC/O) analysis and sensory evaluation of 10 Cheddar cheese samples. The GC/O analysis identified 43 aroma components under the categories of 14 aroma descriptors. Consumer evaluation of palatability was performed by 59 housewives. Factor analysis of the GC/O data identified aroma descriptors that have positive or negative correlations with palatability scores. Twelve aroma components were prioritized using stepwise partial least-squares regression with variable importance in projection (PLS-VIP). An artificial neural network (ANN) model was constructed to demonstrate the nonlinear relationships among the raw GC/O data of the samples and the palatability scores. Coupling stepwise PLS-VIP and ANN resulted in successful identification and ranking of aroma components contributing to the palatability of Cheddar cheese, and in modeling their nonlinear relationships.
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© 2015 by Japanese Society for Food Science and Technology

This article is licensed under a Creative Commons [Attribution-NonCommercial-ShareAlike 4.0 International] license.
https://creativecommons.org/licenses/by-nc-sa/4.0/
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