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目的利用化学计量学方法分析陈皮挥发性成分差异,鉴别其不同产地与种源。方法通过GC-MS获取5个不同产地不同植物种源的10批新会陈皮和15批陈皮药材共有成分峰面积数据,结合主成分分析、聚类分析及人工神经网络三种化学计量学方法进行鉴别区分。结果通过主成分分析及聚类分析可将新会地区茶枝柑样品与其他产地另两个品种样品大致分为两大类,重庆地区大红袍样品又与台州和桂林地区的蜜柑样品各自聚为一小类;依据共有成分峰面积数据建立人工神经网络模型,对新会陈皮和非新会陈皮样本、3个不同品种陈皮样本进行识别区分,训练和预测的准确率均为100%。结论 GC-MS结合化学计量学方法能够作为鉴别不同产地不同种源新会陈皮药材和陈皮药材的一种手段,为新会陈皮的质量控制提供依据。
OBJECTIVE: To analyze the differences of volatile components of Chenpi by using chemometric methods and to identify their different origins and provenances. Methods GC-MS was used to obtain the peak area data of common components of 10 batches of Xinhui tangerine peel and 15 tangerine peel herbs from 5 provenances of different origins. Principal component analysis, cluster analysis and artificial neural network were used to perform the three chemometric methods Identification of distinction. Results By principal component analysis and cluster analysis, the samples of Citrullaia indica from Xinhui area and the other two cultivars from other producing areas were broadly divided into two groups. Samples of Dahongpao from Chongqing and samples from Citrus sinensis of Taizhou and Guilin were clustered respectively A small class. According to the peak area data of the common components, an artificial neural network model was established to distinguish and distinguish the three different varieties of tangerine peel samples of Xinhui tangerine peel and non-Xinhui tangerine peel samples. The accuracy of training and prediction was 100%. Conclusion GC-MS combined with chemometric method can be used as a means to identify the different provenances of Xinhui dried tangerine peel and dried tangerine peel herbs in different provenances, and provide the basis for the quality control of Xinhui tangerine peel.