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Analysis of HPLC fingerprints: discrimination of raw and processed Rhubarb samples with the aid of chemometrics

机译:HPLC指纹图谱分析:借助化学计量学对生大黄和加工大黄样品进行区分

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Chromatographic fingerprints of raw, wine-treated and braised rhubarb samples were obtained by liquid chromatography with a diode array detector (LC-DAD). Eight LC peaks were selected for fingerprint analysis, and six compounds were identified as gallic acid, emodin, chrysophanol, palmidin, rhein glucoside and desoxyrhaponticin. A data matrix of the chromatographic fingerprints from the three types of sample was submitted to principal component analysis (PCA) and this indicated that the three types of rhubarb were distinguished in the PC1versusPC2 space. Training, verification and prediction data sets of the three types of HPLC fingerprint were processed successfully by chemometrics data classification methods, K-nearest neighbor (KNN), linear discriminant analysis (LDA) and least squares support vector machines (LS-SVM), and these types of rhubarb sample were classified satisfactorily...
机译:用二极管阵列检测器(LC-DAD)通过液相色谱法获得未经处理,经葡萄酒处理和炖煮的大黄样品的色谱指纹图谱。选择了八个LC峰进行指纹分析,并鉴定出六种化合物,分别为没食子酸,大黄素,大黄酚,棕榈素,大黄酸葡萄糖苷和脱氧皂苷。将来自三种类型样品的色谱指纹图谱数据矩阵提交给主成分分析(PCA),这表明在PC1versusPC2空间中可以区分出三种大黄。通过化学计量学数据分类方法,K最近邻(KNN),线性判别分析(LDA)和最小二乘支持向量机(LS-SVM)成功处理了三种HPLC指纹的训练,验证和预测数据集这些类型的大黄样品被令人满意地分类...

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