Coupled stepwise PLS-VIP and ANN modeling for identifying and ranking aroma components conforming palatability of cheddar cheese

Morita, A., Araki, T., Ikegami, S., Okaue, M., Sumi, M., Ueda, R., and Sagara, Y. 2015.

Coupled stepwise PLS-VIP and ANN modeling for identifying and ranking aroma components conforming palatability of cheddar cheese
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CiNii
J-STAGE

Food Science and Technology Research 21: 175-186. (査読有)


Abstract

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.