Open AccessFlavor quality evaluation system of Xinjiang milk knots by using SOM neural network and the fuzzy AHP
Author(s) -
Wei Zhisheng,
Ma Xueping,
Zhan Ping,
Tian Honglei,
Li Kaixuan
Publication year - 2020
Publication title -
food science and nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 27
ISSN - 2048-7177
DOI - 10.1002/fsn3.1501
Subject(s) - flavor , knot (papermaking) , analytic hierarchy process , mathematics , fuzzy logic , artificial neural network , consistency (knowledge bases) , statistics , computer science , food science , artificial intelligence , biology , operations research , engineering , pulp and paper industry
Abstract Self‐made milk knots in Xinjiang Kazakh ethnic group were used as material to establish the quality assessment system of flavor quality. The fuzzy analytic hierarchy process based on the optimal consistency matrix was used to evaluate the quality of the samples qualitatively and quantitatively. Its result is consistent with the cluster analysis of the SOM neural network. The results showed that the milk knot samples of Altay had differences with the milk knot samples of Yili. The comprehensive evaluation system is feasible and can evaluate the quality of milk knot samples by flavor characteristics. This can provide a reference for further research on the origin of differences between two types of milk knot samples.