Rapid Evaluation of Qingpi Products Using E-Eye, Fast GC e-Nose, and FT-NIR

Current standards for identifying the characteristics of Qingpi (QP) primarily depend on traditional empirical methods, which are both time-consuming and labor-intensive. Therefore, there is significant potential for developing a rapid and nondestructive identification method.

This work aims to realize fast and effective identification of QP and its processed products, to provide a basis for quality assurance and monitoring of QP and its processed products, and to provide reference for guiding the practical work of traditional Chinese medicine (TCM) identification.

In this study, we employed three advanced technologies-electronic eye (E-eye), fast gas chromatography electronic nose (Fast GC e-nose), and Fourier transform near-infrared (FT-NIR) spectroscopy-to analyze the color, odor, and absorbance of QP samples.

The E-eye digitized the appearance color of various QP samples, and subsequent discriminant analysis, combined with statistical methods, confirmed the feasibility of the discriminant function obtained. Additionally, the Fast GC e-nose provided valuable odor information, identifying 18 distinct odor components. Based on variable importance in projection (VIP) analysis, four components were hypothesized as potential odor markers for distinguishing QP raw products (SQP) from vinegar processed products (CQP). According to the accuracy of the support vector machine (SVM) classification model, the NIR preprocessing method is screened. Alongside SVM, three classification models are chosen for simultaneous evaluation and verification. Notably, the test set recognition rate for all four classification models reached 100%.

E-eye, Fast GC e-nose, and NIR technology enable rapid, nondestructive identification and preliminary quality evaluation of QP products.