Rapid quality identification of the whole wine-steamed process of Polygonati Rhizome by chromaticity and near-infrared spectroscopy

Abstract

In order to quickly determine the processing degree and quality of Polygonati Rhizome (PR), the rapid qualitative and quantitative model for the whole steaming process was established in this study. Firstly, the contents and the chromaticity value of polysaccharide, saponin, 5-hydroxymethyl furfural (5-HMF), 5-hydroxymaltol, polygonatine A, fructose, glucose, sucrose, and the chromaticity value in 98 batches of PR during the whole processing were determined. The chromaticity value was used to establish the qualitative discrimination model of the whole steaming process by partial least squares-discriminant analysis (PLS-DA). Then, the near-infrared (NIR) spectra of all samples were collected to establish the NIR qualitative discriminant model. The samples of four different processing stages, raw products, less processed products, finished processed products, and over processed products, were well distinguished in two qualitative models, and the model validation results were good. Finally, the chromaticity value, the content, and NIR spectra were imported into TQ Analyst software. After screening the pretreatment methods, the optimal pretreatment method combined with partial least squares (PLS) was selected to establish the NIR quantitative model of 11 indicators. The correlation coefficient of models was above 0.9, indicating that the model had high prediction accuracy. Through the establishment of the qualitative discriminant model, the different processing degrees of PR could be accurately distinguished, and the NIR quantitative prediction model could accurately predict the content and the chromaticity value, which provided a scientific basis for the quality identification of PR in the whole process of processing.