Authentication of Garcinia fruits and food supplements using DNA barcoding and NMR spectroscopy

Quantification of adulteration in traded ayurvedic raw drugs employing machine learning approaches with DNA barcode database

Adulteration of expensive raw drugs with inferior taxa has become a routine practice, conceding the quality and safety of derived herbal products. In this regard, the study addresses the development of an integrated approach encompassing DNA barcode and HPTLC fingerprinting to authenticate chiefly traded ayurvedic raw drugs in south India [viz. Saraca asoca (Roxb.) Willd., Terminalia arjuna (Roxb. ex DC.) Wight and Arn., Sida alnifolia L. and Desmodium gangeticum (L.) DC.] from its adulterants. Consortium of Barcode of Life (CBOL) recommended DNA barcode gene regions viz. nuclear ribosomal-Internal Transcribed Spacer (nrDNA-ITS), maturase K (matK), ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (rbcL) and psbA-trnH spacer regions along with HPTLC profiling were experimented and a reference database was created. Further, an integrated analytical approach employing genetic distance-based Maximum Likelihood phylogenetic tree and Artificial Intelligence (AI)based Machine Learning Algorithms (MLA)-Waikato Environment for Knowledge Analysis (WEKA) and Barcoding with Logic (BLOG) were employed to prove efficacy of DNA barcode tool. Even though, among the four barcodes, psbA-trnH (S. alnifolia and its adulterants, T. arjuna and its adulterants) or ITS region (S. asoca and its adulterants, D. gangeticum and its adulterants) showed highest inter specific divergences in the selected Biological Reference Materials (BRMs), rbcL or matK barcode regions alone were successful for authentication of traded samples. The automated species identification techniques, WEKA and BLOG, experimented for the first time in India for raw drug validation, could achieve rapid and precise identification. A national certification agency for raw drug authentication employing an integrated approach involving a DNA barcoding tool along with standard organoleptic and analytical methods can strengthen and ensure safety and quality of herbal medicines in India.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03001-5.

The efficacy of machine learning algorithm for raw drug authentication in Coscinium fenestratum (Gaertn.) Colebr. employing a DNA barcode database

Medicinal plants are a valuable resource for traditional as well as modern medicine. Consequently huge demand has exerted a heavy strain on the existing natural resources. Due to over exploitation and unscientific collection most of the commercially traded ayurvedic plants are in the phase of depletion. Adulteration of expensive raw drugs with inferior taxa has become a common practice to meet the annual demand of the ayurvedic industry. Although there are several recommended methods for proper identification varying from the traditional taxonomic to organoleptic and physiochemical, it is difficult to authenticate ayurvedic raw drugs available in extremely dried, powdered or shredded forms. In this regard, the study addresses proper authentication and illicit trade in Coscinium fenestratum (Gaertn.) Colebr. using CBOL recommended standard barcode regions viz. nuclear ribosomal-Internally Transcribed Spacer (nrDNA- ITS), maturase K (matK), ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (rbcL), and psbA-trnH spacer regions. Further, an integrated analytical approach employing Maximum Likelihood phylogenetic tree and Machine Learning Approach, Waikato Environment for Knowledge Analysis was employed to prove efficacy of the method. The automated species identification technique, Artificial Intelligence uses the ability of computers to build models that can receive the input data and then conduct statistical analyses which significantly reduces the human labour. Concurrently, scientific management, restoration, cultivation and conservation measures should be given utmost priority to reduce the depletion of wild resources as well as to meet the rapidly increasing demand of the herbal industries.

Pitfalls and promises of raw drug identification techniques in the ayurvedic industry: an overview

India, with a rich heritage of floral diversity, is well-known for its medicinal plant wealth and is the largest producer of medicinal herbs in the world. Ethnobiological Survey of Ministry of Environment and Forests (MOEF) could identify 8000 plant species utilized in various systems of medicine with approximately 25,000 effective herbal formulations. The extensive consumption to meet demand-supply ratio exerts a heavy strain on the existing resources. This subsequently led to the adulteration and substitution of medicinal plants with look-alike species. The consumer's faith on herbal medicine is in the phase of decline due to the extremities in adulteration/substitution and ensuing consequences. It is imperative to bring forth universally acceptable standard tools to authenticate raw drugs before being processed further into formulations. A vast array of techniques such as physical, chemical (analytical), biochemical, anatomical, organoleptic, and recently emerged DNA based molecular methods are widely used for plant species authentication. In recent years, DNA barcoding has made remarkable progress in the field of medicinal plants research. DNA metabarcoding is the latest development for qualitative evaluation of the herbal formulations, whereas for quantitative analysis, combination of pharmacognostic, pharmacovigilance and analytical methods are inevitable for authentication. This review addresses the overall strengths and shortcomings of the existing as well as recently emerged techniques in authenticating ayurvedic raw drugs.