Presenter Information

James Harnly, USDAFollow

Document Type

Oral Presentation

Location

Oxford Convention Center, 102 Ed Perry Boulevard Oxford, MS 38655

Event Website

https://oxfordicsb.org/

Start Date

15-4-2024 1:00 PM

End Date

15-4-2024 1:15 PM

Description

One-class modeling based on soft independent modeling of class analogy (SIMCA) is a simple but powerful method for comparing the chemical composition of botanical materials using non-targeted chromatograms (GC, LC) or spectra (IR, MS, NIR, NMR). The methodology is available on any commercial chemometric platform. Authentication is based solely on the characteristics of the botanical material of interest. Detection of adulteration is determined for each variable and requires no identification of adulterants. Some highly characterized botanical reference materials (BRMs) may account for species, cultivar, and year and location of harvest while more generic BRMs may have minimal characterization. All of these factors can result in variability in the chemical composition that may lead to statistically significant differences when applying one-class modeling. Using flow injection mass spectrometry (FIMS), principal component analysis (PCA), and factorial multivariate analysis of variance (factorial mANOVA), statistically significant (95% confidence limit) differences in chemical composition were found between 4 sources of A. racemosa BRMs and between Actaea species. Interestingly, the variability of 6% of the mass variables were found to be quantitatively conserved (variability of

Comments

Supported by an Interagency Agreement with the Office of Dietary Supplements, National Institutes of Health.

Publication Date

April 2024

Accessibility Status

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Apr 15th, 1:00 PM Apr 15th, 1:15 PM

One-class modeling for the authentication of Actaea racemosa and evaluation of the variation between botanical reference materials

Oxford Convention Center, 102 Ed Perry Boulevard Oxford, MS 38655

One-class modeling based on soft independent modeling of class analogy (SIMCA) is a simple but powerful method for comparing the chemical composition of botanical materials using non-targeted chromatograms (GC, LC) or spectra (IR, MS, NIR, NMR). The methodology is available on any commercial chemometric platform. Authentication is based solely on the characteristics of the botanical material of interest. Detection of adulteration is determined for each variable and requires no identification of adulterants. Some highly characterized botanical reference materials (BRMs) may account for species, cultivar, and year and location of harvest while more generic BRMs may have minimal characterization. All of these factors can result in variability in the chemical composition that may lead to statistically significant differences when applying one-class modeling. Using flow injection mass spectrometry (FIMS), principal component analysis (PCA), and factorial multivariate analysis of variance (factorial mANOVA), statistically significant (95% confidence limit) differences in chemical composition were found between 4 sources of A. racemosa BRMs and between Actaea species. Interestingly, the variability of 6% of the mass variables were found to be quantitatively conserved (variability of

https://egrove.olemiss.edu/icsb/2024_ICSB/Schedule/3