In recent years, there has been a surge in recognition and demand for traditional Chinese medicine (TCM) [1], [2], [3]. However, the quality of TCM is influenced by numerous factors, such as the origin of medicinal materials, harvest season, and processing methods, resulting in inconsistent quality. An imperfect quality control system further impedes the internationalization and modernization of TCM [4]. Developing an appropriate quality control system is, therefore, a paramount and formidable challenge for better utilizing the natural treasure trove of TCM [5,6].

Currently, the quality control of TCM has evolved beyond analyzing basic index components, such as the use of HPLC fingerprints to evaluate various medicinal materials [7], [8], [9], [10], [11], [12], [13]. It is necessary to as far as possible ensure the purity of chromatographic peak. The commonly used method currently is to compare the UV absorption at each time point of the chromatographic peak to identify the purity of the peak. However, it can only be analyzed online and is often used for the analysis of simple components, rather than for the TCM with complex components. Therefore, it is particularly important to find a simple and rapid method for determining the purity of TCM fingerprint peaks. The purity of fingerprint peaks is mainly determined by two factors, namely the HPLC separation conditions and the intrinsic difference of the chemical components in the sample. Under suitable separation conditions, the purity of the fingerprint peak is only related to the chemical components in the sample. This article presents a simple and effective method for checking the purity of fingerprint peaks by the double wavelength absorption coefficient ratio fingerprint (DWAR). Furthermore, the variability of the sample can result in uncertainty in the reference fingerprint (RFP), and the lack of research on the reliability of the fingerprint can directly impact the credibility of the evaluation results [14]. Therefore, this study established a reliability study to ensure the credibility of the number distribution, content distribution ratio, and overall content difference of chemical fingerprints.

HPLC only detects substances under specific extraction and separation conditions, which poses a significant problem for TCM, where multiple components work in concert, and the characteristic information of total active compounds cannot be ascertained only by HPLC [15]. Fortunately, electrochemical (EC) technology, particularly the classic B-Z oscillating reaction system [16], has become increasingly popular in fields such as food safety, environmental protection, and TCM detection [17], [18], [19]. Unlike HPLC, the EC mainly reacts with the overall electroactive component information in the sample, experiment does not require any extraction and separation, can be applied to various phases and dosage forms, and is often used to identify TCM and distinguish their origin [20,21]. Similarity analysis is an indispensable strategy for TCM to monitor the quality of all components. However, current EC analysis only focuses on the profile of the curve and induction period parameters, while research on the induction period, which contains a wealth of information, is relatively scarce [22]. This makes it challenging to conduct in-depth qualitative and quantitative analyses of samples. To address this limitation, this study proposes the use of electrochemical fingerprint (ECFP) obtained by the valley integrated method to obtain full stage information, leading to more accurate qualitative and quantitative analysis of samples.

In parallel, DSC analysis, which monitors the thermal behavior of samples with all components, has a significant impact in various fields [23]. In the food industry [24], it is primarily used for studying protein denaturation and carbohydrate stability. In the pharmaceutical industry [25], it is mainly employed for the characterization of solid components and their stability. It provides information on the sample's thermal properties, commonly expressed by parameters such as melting and degradation temperature, glass transition temperature, melting and crystallization enthalpy, polymorphism, and purity. Akin to electrochemistry, the heat flow curve with fingerprint information is more valuable for further qualitative and quantitative analysis of samples. This study employs a fixed-point merger method to convert the DSC curve into the form of virtual chromatographic peaks, successfully utilizing all heat flow rate changes to assist in data analysis.

This study proposes a series of strategies for the more scientific application of HPLC fingerprints and a more accurate reflection of sample quality. Firstly, the DWAR is used to verify peak purity, while the dual-wavelength fusion fingerprint (DWFFP) is used to avoid the limitations of a single wavelength. The reliability of the fingerprint is also verified. In addition, the four components were accurately quantified, and the sample were analyzed by the EC fingerprint and DSC QFP. Finally, the mean method was used to comprehensively evaluate the sample. This strategy can provide new ideas for the quality control of TCM, help to improve the competitiveness of TCM, and promote the modernization of TCM more effectively.