目的 基于藥材粉末顏色數(shù)字化分析建立一種不同生長方式黃芩Scutellaria baicalensis的快速鑒別方法，同時建立一種黃芩主要藥效成分含量的準確預測模型。方法 采用分光測色儀測定黃芩樣品粉末顏色亮度值（L^*）、紅綠色值（a^*）、黃藍色值（b^*），并計算總色值（E^*）；采用HPLC測定黃芩樣品中4個主要藥效成分（黃芩苷、漢黃芩苷、黃芩素、漢黃芩素）的含量，基于色度值并結(jié)合多元統(tǒng)計分析及機器學習算法，建立可區(qū)分不同生長方式黃芩的定性判別模型、主要藥效成分的定量預測模型。結(jié)果 不同生長方式黃芩的黃芩素和漢黃芩素含量具有顯著差異（P＜0.05）；黃芩藥材粉末色度值與有效成分含量具有相關(guān)性（除a^*與黃芩苷、漢黃芩苷含量無顯著相關(guān)性外，其他因素之間P＜0.05）；基于色度值并結(jié)合機器學習算法構(gòu)建的黃芩生長方式判別模型中，隨機森林分類器結(jié)合十倍交叉驗證法的分類準確率最高，為100%；并在基于色度值構(gòu)建的主要藥效成分含量預測模型中，4種成分的預測值與實測值的相關(guān)系數(shù)均大于0.97。結(jié)論 通過藥材粉末的色度值建立的定性判別及定量預測分析方法具有快速、準確、可及的優(yōu)點，為揭示黃芩“辨色論質(zhì)”的科學內(nèi)涵提供理論依據(jù)。

Objective In order to establish a rapid method for distinguishing different growth modes of Huangqin (Scutellariae Radix) based on digital analysis of the color of the herbal powder, and to establish an accurate prediction model for the main active components of Scutellariae Radix based on the color of the herbal powder. Methods The L^*(luminance), a^*(red-green), b^*(yellow-blue) colorimetric values and E^*(total color) of the powder color of Scutellariae Radix were measured using a spectrophotometer, and the contents of flavonoid components (baicalin, wogonoside, baicalein, and wogonin) were determined by HPLC. Based on the colorimetric values, combined with multivariate statistical analysis and machine learning algorithms, a qualitative discriminant model for different growth modes of Scutellariae Radix and a quantitative prediction model for four main active components were established. Results There were significant differences in the contents of flavonoid components baicalein and wogonin between different cultivation methods of Scutellariae Radix (P < 0.05). The colorimetric values of the powdered herb were correlated with the content of effective components (except a^* was not significantly correlated with baicalin and wogonin contents, P < 0.05). In the model for discriminating the growth patterns of Scutellariae Radix based on colorimetric values and integrated with machine learning algorithms, the Random Forest classifier combined with ten-fold cross-validation achieved the highest classification accuracy of 100%. Furthermore, the main active component content prediction model based on chromaticity values showed that the correlation coefficients between the predicted values and the measured values of the four effective components were all greater than 0.97. Conclusion The qualitative and quantitative prediction analysis method established by using the chromaticity value of the herbal powder has the advantages of rapidity, accuracy, and accessibility, providing theoretical basis for revealing the scientific connotation of "distinguishing colors to judge quality" of Scutellariae Radix.

R286.2

山西省2022-2023年度中醫(yī)藥科技創(chuàng)新工程項目[2100601中醫(yī)（民族醫(yī)）藥專項];2023年北中醫(yī)基本科研業(yè)務(wù)費（揭榜掛帥）重點項目立項（2023-JYB-JBQN-058）