Terahertz Spectroscopic Identification of Roast Degree and Variety of Coffee Beans.

ABSTRACT: In this study, terahertz time-domain spectroscopy (THz-TDS) was proposed to identify coffee of three different varieties and three different roasting degrees of one variety. Principal component analysis (PCA) was applied to extract features from frequency-domain spectral data, and the extracted features were used for classification prediction through linear discrimination (LD), support vector machine (SVM), naive Bayes (NB), and k-nearest neighbors (KNN). The classification effect and misclassification of the model were analyzed via confusion matrix. The coffee varieties, namely Catimor, Typica 1, and Typica 2, under the condition of shallow drying were used for comparative tests. The LD classification model combined with PCA had the best effect of dimension reduction classification, while

SUBMITTER: Huang L 

PROVIDER: S-EPMC10855191 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature