Hyperspectral Imaging and Support Vector Machine: A Powerful Combination to Differentiate Black Cohosh (Actaea racemosa) from Other Cohosh Species

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

• References

• 1 Hernlund E, Svedbom A, Ivergård M, Compston J, Cooper C, Stenmark J, McCloskey EV, Jönsson B, Kanis JA. Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 2013; 8: 136
• 2 Borrelli F, Ernst E. Black cohosh (Cimicifuga racemosa) for menopausal symptoms: a systematic review of its efficacy. Pharmacol Res 2008; 58: 8-14
• 3 Rossouw JE, Anderson GL, Prentice RL. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the womenʼs health initiative randomized controlled trial. J Am Med Assoc 2002; 288: 321-333
• 4 Qiu F, McAlpine JB, Krause EC, Chen SN, Pauli GF. Pharmacognosy of black cohosh: the phytochemical and biological profile of a major botanical dietary supplement. Prog Chem Org Nat Prod 2014; 99: 1-68
• 5 Blumenthal M, Lindstrom A, Ooyen C, Lynch ME. Herb supplement sales increase 4.5 % in 2011. HerbalGram 2012; 95: 60
• 6 Geller SE, Studee L. Botanical and dietary supplements for menopausal symptoms: what works, what does not?. J Womens Health 2005; 14: 634-649
• 7 Kim CD, Lee WK, Lee MH, Lee YK, Roh SS. Inhibition of mast cell-dependent allergy reaction by extract of black cohosh (Cimicifuga racemosa). Immunopharmacol Immunotoxicol 2004; 26: 299-308
• 8 Bodinet C, Freudenstein J. Influence of Cimicifuga racemosa on the proliferation of estrogen receptor-positive human breast cancer cells. Breast Cancer Res Treat 2002; 76: 1-10
• 9 Niblen T, Freudenstein J. Concomitant administration of an isopropanolic extract of black cohosh and tamoxifen in the in vivo tumor model of implanted RUCA-I rat endometrial adenocarcinoma cells. Toxicol Lett 2004; 150: 271-275
• 10 Jiang B, Ma C, Motley T, Kronenberg F, Kennelly EJ. Phytochemical fingerprinting to thwart black cohosh adulteration: a 15 Actaea species analysis. Phytochem Analysis 2011; 22: 339-351
• 11 Wood M. Black Cohosh. In: Gladstar R, Hirsch P. eds. Planting the Future: Saving our medicinal Herbs. Rochester: Healing Arts Press; 2000: 64-71
• 12 Davis J, Dressler A. Black cohosh (Actaea racemosa L.). Mountain Horticultural Crops 2013; 455: 1-7
• 13 Verbitski SM, Gourdin GT, Ikenouye LM, Mcchesney JD, Hildreth J. Detection of Actaea racemosa adulteration by thin layer chromatography and combined thin layer chromatography-bioluminescence. J AOAC Int 2008; 91: 268-275
• 14 AHPA (American Herbal Products Association). Black cohosh (Actaea racemosa syn. Cimicifuga racemosa) root/rhizome. Available at. http://www.ahpa.org/Resources/TechnicalGuidance/ScientificAffairs/BotanicalAuthenticationProgram/BlackCohoshRoot.aspx Accessed May 1, 2016
• 15 BHMA (British Herbal Medicine Association). Unregistered black cohosh product associated with liver failure: this must not happen again. Press release, No 1002805, England; 2012.
• 16 Betz JM, Anderson L, Avigan MI, Barnes J, Farnsworth NR, Gerden B, Henderson L, Kennelly EJ, Koetter U, Lessard S, Dog TL, Mclaughlin M, Naser B, Osmers RGW, Pellicore LS, Senior JR, Breemen RBV, Wuttke W, Cardellina II JH. Black cohosh: considerations of safety and benefit. Nutr Today 2009; 44: 155-161
• 17 Avula B, Ali Z, Khan IA. Chemical fingerprinting of Actaea racemosa (black cohosh) and its comparison study with closely related Actaea species (A. pachypoda, A. podocarpa and A. ruba) by HPLC. Chromatographia 2007; 66: 757-762
• 18 Foster S. Exploring the peripatetic maze of black cohosh adulteration: a review of the nomenclature, distribution, chemistry, market status, analytical methods and safety. HerbalGram 2013; 98: 32-51
• 19 Turker-Kaya S, Huck CW. A review of mid-infrared and near-infrared imaging: principles, concepts and applications in plant tissue analysis. Molecules 2017; 22: E168
• 20 Vidal M, Amigo JM. Pre-processing of hyperspectral images: essentials steps before image analysis. Chemometr Intell Lab 2012; 117: 138-148
• 21 Manley M, Du Toit F, Geladi P. Tracking diffusion of conditioning water in single wheat kernels of different hardnesses by near infrared hyperspectral imaging. Anal Chim Acta 2011; 686: 64-75
• 22 Ma C, Kavalier AR, Jiang B, Kennelly EJ. Metabolic profiling of Actaea species extracts using high performance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry. J Chromatogr A 2011; 1218: 1461-1476
• 23 Geladi P, Grahn H, Manley M. Data Analysis and Chemometrics for hyperspectral Imaging. In: Šašić S, Ozaki Y. eds. Raman, infrared, and near infrared chemical Imaging. Hoboken: John Wiley and Sons; 2010: 93-107
• 24 Brereton RG, Lloyd GR. Partial least square discriminant analysis: taking the magic away. J Chemometr 2014; 28: 213-225
• 25 Williams P, Geladi P, Fox G, Manley M. Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis. Anal Chim Acta 2009; 653: 121-130
• 26 Burges CJC. A tutorial on support vector machine for pattern recognition. Data Min Knowl Disc 1998; 2: 121-167
• 27 Hsu CW, Chang CC, Lin CJ. A practical Guide to support Vector Classification. Taipei: Department of Computer Science, National Taiwan University; 2010: 1-16