Blending Technology Based on HPLC Fingerprint and Nonlinear Programming to Control the Quality of Ginkgo Leaves

Abstract

The breadth and depth of traditional Chinese medicine (TCM) applications have been expanding in recent years, yet the problem of quality control has arisen in the application process. It is essential to design an algorithm to provide blending ratios that ensure a high overall product similarity to the target with controlled deviations in individual ingredient content. We developed a new blending algorithm and scheme by comparing different samples of ginkgo leaves. High-consistency samples were used to establish the blending target, and qualified samples were used for blending. Principal component analysis (PCA) was used as the sample screening method. A nonlinear programming algorithm was applied to calculate the blending ratio under different blending constraints. In one set of calculation experiments, the result was blended by the same samples under different conditions. Its relative deviation coefficients (RDCs) were controlled within ±10%. In another set of calculations, the RDCs of more component blending by different samples were controlled within ±20%. Finally, the near-critical calculation ratio was used for the actual experiments. The experimental results met the initial setting requirements. The results show that our algorithm can flexibly control the content of TCMs. The quality control of the production process of TCMs was achieved by improving the content stability of raw materials using blending. The algorithm provides a groundbreaking idea for quality control of TCMs.

Keywords: ginkgo leaves; high-performance liquid chromatography; natural herb blending; stoichiometry; traditional Chinese medicine quality control.

Figure 1

Ginkgo biloba HPLC-UV-ELSD chromatograms from 25 min to 60 min with peak designation.

Figure 2

Comparison of peak areas between different samples. (A) Samples of the same year from different origins. (B) Samples of different years from the same origin. (C) Samples of same years from the same origin. (D) Samples over 10 years, 2 years and 5 years from the same origin.

Figure 3

Radar diagram of ginkgo biloba target samples used for the target calculation.

Figure 4

Radar diagram of qualified samples acquired in the market.

Figure 5

PCA results for samples M1–M11, T1–T10, and the blended target.

Figure 6

Calculated results for the same samples under different constraints. different control constraints of C1, C2 and C3 was shown in Table 5.

Figure 7

Calculated results for different samples with the same constraints. different control constraints of C4, C5 and C6 was shown in Table 7.

Figure 8

Radar diagram of calculated and experimental results.