Probability of Identification: Adulteration of American Ginseng with Asian Ginseng

Author:

Harnly James1,Chen Pei1,Harrington Peter de B2

Affiliation:

1. U.S. Department of Agriculture, Agricultural Research Service, Food Composition and Methods Development Laboratory, Beltsville Human Nutrition Research Center, Building 161, BARC-East, Beltsville, MD 20705

2. Clippinger Laboratories, Center for Intelligent Chemical Instrumentation, Ohio University, Department of Chemistry and Biochemistry, Athens, OH 45701

Abstract

Abstract The AOAC INTERNATIONAL guidelines for validation of botanical identification methods were applied to the detection of Asian Ginseng [Panax ginseng (PG)] as an adulterant for American Ginseng [P. quinquefolius (PQ)] using spectral fingerprints obtained by flow injection mass spectrometry (FIMS). Samples of 100% PQ and 100% PG were physically mixed to provide 90, 80, and 50% PQ. The multivariate FIMS fingerprint data were analyzed using soft independent modeling of class analogy (SIMCA) based on 100% PQ. The Q statistic, a measure of the degree of non-fit of the test samples with the calibration model, was used as the analytical parameter. FIMS was able to discriminate between 100% PQ and 100% PG, and between 100% PQ and 90, 80, and 50% PQ. The probability of identification (POI) curve was estimated based on the SD of 90% PQ. A digital model of adulteration, obtained by mathematically summing the experimentally acquired spectra of 100% PQ and 100% PG in the desired ratios, agreed well with the physical data and provided an easy and more accurate method for constructing the POI curve. Two chemometric modeling methods, SIMCA and fuzzy optimal associative memories, and two classification methods, partial least squares-discriminant analysis and fuzzy rule-building expert systems, were applied to the data. The modeling methods correctly identified the adulterated samples; the classification methods did not.

Publisher

Oxford University Press (OUP)

Subject

Pharmacology,Agronomy and Crop Science,Environmental Chemistry,Food Science,Analytical Chemistry

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