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Panax quinquefolius  L ( P. quinquefolius  L) samples grown in the United States and China were analyzed with high performance liquid chromatography-mass spectrometry (HPLC-MS). Prior to classification, the two-way data sets were subjected to pretreatment including baseline correction and retention time (RT) alignment. Principal component analysis (PCA) and projected difference resolution (PDR) metrics were used to evaluate the data quality and the pretreatment effects. A fuzzy rule-building expert system (FuRES) classifier was used to classify the  P. quinquefolius  L samples grown in the United States and China with the optimized partial least-squares (o-PLS) classifier as the positively biased control method. A classification rate as high as 98 ± 3% with FuRES was obtained after baseline correction and RT alignment, which is equivalent to the result obtained by using the positively biased o-PLS control method (98 ± 3%). RT alignment improved the classification rates for both FuRES and o-PLS classifiers (18% improvement for the FuRES classification rate and 10% improvement for the o-PLS classification rate with baseline correction). From the rule obtained to classify the  P. quinquefolius  L samples grown in the United States and China, peaks were identified that can be prospective biomarkers for differentiating samples from different growth regions. HPLC-MS with chemometric analysis has the potential to be used as an authentication method for  P. quinquefolius  L grown in China and the United States.

analytical chemistry

Classification of Cultivation Locations of Panax quinquefolius L Samples using High Performance Liquid Chromatography–Electrospray Ionization Mass Spectrometry and Chemometric Analysis