目的 基于多指标定量结合化学模式识别技术、加权逼近理想解排序法（technique for order preference by similarity to an ideal solution，TOPSIS）与灰色关联度分析（grey relational analysis，GRA）法融合模型评价不同产地宽叶荨麻Urtica laetevirens质量。方法 收集主要产地20批宽叶荨麻，采用HPLC法检测原儿茶酸、绿原酸、咖啡酸、阿魏酸、金丝桃苷、芦丁、槲皮素、芹菜素、山柰酚、木犀草素、胡萝卜苷、β-谷甾醇的含量，并检查浸出物、总灰分和酸不溶性灰分。结合化学模式识别技术探讨不同产地宽叶荨麻之间的差异性，筛选导致不同产地宽叶荨麻质量差异的主要标志性成分，以各指标的VIP值为权重，构建加权TOPSIS模型，进而与GRA法融合，对20批宽叶荨麻质量进行排序。结果 在建立的HPLC条件下，原儿茶酸、绿原酸、咖啡酸、阿魏酸、金丝桃苷、芦丁、槲皮素、芹菜素、山柰酚、木犀草素、胡萝卜苷、β-谷甾醇分别在0.21～10.50、1.15～57.50、0.28～14.00、0.46～23.00、3.35～167.50、4.47～223.50、1.70～85.00、0.14～7.00、0.37～18.50、0.79～39.50、0.65～32.50、1.31～65.50 µg/mL线性关系良好，建立的方法重复性良好，仪器精密度高，70%甲醇超声提取的宽叶荨麻供试品溶液24 h内稳定性良好，各成分平均加样回收率分别为98.43%、97.91%、98.24%、99.06%、100.03%、99.68%、100.01%、97.81%、98.92%、98.23%、96.77%、98.34%，RSD在0.73%～1.86%。各成分质量分数分别为0.066～0.129、0.270～0.577、0.093～0.184、0.164～0.281、1.440～2.465、1.911～3.204、0.331～1.188、0.036～0.106、0.078～0.209、0.187～0.456、0.196～0.418、0.383～0.613 mg/g，浸出物、总灰分和酸不溶性灰分含量分别为14.3%～31.5%、7.3%～16.2%、0.5%～3.4%，显示批次间质量差异较大。化学模式识别技术将20批宽叶荨麻样品分为3组，其中源于四川、甘肃和云南样品S1～S8、源于广西、贵州和湖南样品S9～S14、源于青海和西藏样品S15～S20各为一组，呈明显的地域性，区分各样品质量差异的标志性成分为芦丁、金丝桃苷、槲皮素、绿原酸、木犀草素和β-谷甾醇。加权TOPSIS与GRA法融合模型分析结果显示20批样品的综合相对贴近度在0.285 4～0.673 6，其中源于青海和西藏S15～S20样品的综合相对贴近度分别为0.652 2、0.663 3、0.628 3、0.673 6、0.597 0、0.583 7，高于其他批次，质量相对较优。结论 建立的多指标定量方法稳定可靠，可用于完善宽叶荨麻质量标准；化学模式识别联合加权TOPSIS与GRA法融合模型全面科学地评价了不同产地宽叶荨麻的质量状况，为宽叶荨麻质量分析和评价奠定基础。

Objective To evaluate the quality of Urtica laetevirens from different producing areas based on multi-index quantification, combined with chemical pattern recognition technology, weighted TOPSIS and grey relational analysis(GRA) fusion model. Methods A total of 20 batches of U. laetevirens were collected from the main producing areas. The contents of protocatechuic acid, chlorogenic acid, caffeic acid, ferulic acid, hyperoside, rutin, quercetin, apigenin, kaempferol, luteolin, daucosterol, β-sitosterol were detected by HPLC, and the extract, total ash and acid-insoluble ash were examined. Combined with chemical pattern recognition technology, the differences between U. laetevirens from different producing areas were discussed, and the main landmark components leading to the quality differences of U. laetevirens from different producing areas were screened. The weighted TOPSIS model was constructed with the VIP value of each index as the weight, and then integrated with the GRA method to rank the quality of 20 batches of U. laetevirens. Results Under the established HPLC conditions. The linear ranges of protocatechuic acid, chlorogenic acid, caffeic acid, ferulic acid, hyperoside, rutin, quercetin, apigenin, kaempferol, luteolin, daucosterol, β-sitosterol showed a good linear relationship within the range of 0.21—10.50, 1.15—57.50, 0.28—14.00, 0.46—23.00, 3.35—167.50, 4.47—223.50, 1.70—85.00, 0.14—7.00, 0.37—18.50, 0.79—39.50, 0.65—32.50, 1.31—65.50 μg/mL, respectively. The established method had good repeatability and high instrument precision. The stability of the sample solution of nettle extracted by 70% methanol ultrasonic extraction was good within 24 h. The average recovery rates of each component were 98.43%, 97.91%, 98.24%, 99.06%, 100.03%, 99.68%, 100.01%, 97.81%, 98.92%, 98.23%, 96.77% and 98.34%, respectively. The RSD was between 0.73% and 1.86%. The contents of various components were 0.66—0.129, 0.270—0.577, 0.093—0.184, 0.164—0.281, 1.440—2.465, 1.911—3.204, 0.331—1.188, 0.036—0.106, 0.078—0.209, 0.187—0.456, 0.196—0.418, 0.383—0.613 mg/g, The contents of extract, total ash and acid-insoluble ash were 14.3%—31.5%, 7.3%—16.2%, 0.5%—3.4%, respectively. It showed that the quality difference between batches was large. The 20 batches of U. laetevirens samples were divided into three groups by chemical pattern recognition technology, among them, S1—S8 from Sichuan, Gansu and Yunnan, S9-S14 from Guangxi, Guizhou and Hunan, and S15—S20 from Qinghai and Xizang were each group, showing obvious regional characteristics. The marker components that distinguish the quality differences of each sample were rutin, hyperoside, quercetin, chlorogenic acid, luteolin and β-sitosterol. The analysis results of weighted TOPSIS and GRA fusion model showed that the comprehensive relative closeness of 20 batches of samples was between 0.285 4 and 0.673 6. The comprehensive relative closeness of S15—S20 samples from Qinghai and Xizang were 0.652 2, 0.663 3, 0.628 3, 0.673 6, 0.597 0 and 0.583 7, respectively, which was higher than that of other batches, and the quality was relatively better. Conclusion The established multi-index quantitative method is stable and reliable, which can be used to perfect the quality standard of U. laetevirens. The chemical pattern recognition combined with weighted TOPSIS and GRA fusion model comprehensively and scientifically evaluated the quality of U. laetevirens from different producing areas, laying a foundation for the quality analysis and evaluation of U. laetevirens.

R282.6

国家自然科学基金项目（81560806）；青海省“昆仑英才·高端创新创业人才”计划（K9923143）