Author(s)

Zhiwen Yang ¹

Affiliation(s)

¹ Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering, Yibin, 644000, China

Corresponding Author

Zhiwen Yang

ABSTRACT

In order to achieve accurate identification of GC-MS Baijiu mapping data, the sparse principal component analysis (SPCA) of GC-MS Baijiu mapping data is achieved by introducing the elastic net penalty function and ridge regression to restrict the sparse principal components on the basis of the principal component analysis method. The sparse principal components are fed into different classifiers for classification and identification, and a Baijiu quality classification model is established. Through comparison experiments, it was demonstrated that sparse principal components better represented the information of different characteristics of liquor, and the classification recognition accuracy after classification was higher, and the recognition rates of SPCA+KNN, SPCA+DT, SPCA+SVM, and SPCA+BP reached 62%, 89%, 97% and 100%; the differences of sparse principal components of GC-MS profiles of different grades of liquor were greater than the differences of principal components, and the sparse principal components of GC-MS profiles of liquor was a nonlinear relationship. The established sparse principal component-based Baijiu quality evaluation model can effectively realize the evaluation of Baijiu grades, which provides a more effective and objective method for the control of Baijiu quality and grade identification.

KEYWORDS

Baijiu recognition; sparse principal component analysis; GC-MS map; elastic net penalty

CITE THIS PAPER

Zhiwen Yang, Classification Technology of GC-MS Map Data of Baijiu Based on Sparse Principal Components. Advances in Food Science and Human Nutrition (2023) Vol.5: 52-59. DOI: http://dx.doi.org/10.23977/afshn.2023.050107.

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Sponsors, Associates, and Links

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• Journal of Modern Crop Science
  
  
• Plant Nutrition & Soil Science International
  
  
• Agricultural Mechanization, Electrification and Automation
  
  
• Food Chemistry, Processing, and Storage
  
  
• Botany and Zoology Frontiers