Abstract
Actaea racemosa (black cohosh) has a history of traditional use in the treatment of general gynecological
problems. However, the plant is known to be vulnerable to adulteration with other
cohosh species. This study evaluated the use of shortwave infrared hyperspectral imaging
(SWIR-HSI) in tandem with chemometric data analysis as a fast alternative method for
the discrimination of four cohosh species (Actaea racemosa, Actaea podocarpa, Actaea pachypoda, Actaea cimicifuga) and 36 commercial products labelled as black cohosh. The raw material and commercial
products were analyzed using SWIR-HSI and ultra-high-performance liquid chromatography
coupled to mass spectrometry (UHPLC-MS) followed by chemometric modeling. From SWIR-HSI
data (920 – 2514 nm), the range containing the discriminating information of the four
species was identified as 1204 – 1480 nm using Matlab software. After reduction of
the data set range, partial least squares discriminant analysis (PLS-DA) and support
vector machine discriminant analysis (SVM-DA) models with coefficients of determination
(R2
) of ≥ 0.8 were created. The novel SVM-DA model showed better predictions and was
used to predict the commercial product content. Seven out of 36 commercial products
were recognized by the SVM-DA model as being true black cohosh while 29 products indicated
adulteration. Analysis of the UHPLC-MS data demonstrated that six commercial products
could be authentic black cohosh. This was confirmed using the fragmentation patterns
of three black cohosh markers (cimiracemoside C; 12-β,21-dihydroxycimigenol-3-O-L-arabinoside; and 24-O-acetylhydroshengmanol-3-O-β-D-xylopyranoside). SWIR-HSI in conjunction with chemometric tools (SVM-DA) could
identify 80% adulteration of commercial products labelled as black cohosh.
Key words
Actaea racemosa
- Ranunculaceae - shortwave infrared hyperspectral imaging - chemometrics - support
vector machine - quality control
