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Research Article Open access CC BY 4.0

Evaluation of the Chemical Variability and Phytochemical Analysis among Indian Germplasm of Acorus calamus Linn Using GC- MS and FTIR

Avani Kasture, R. Krishnamurthy

European Journal of Medicinal Plants · pp. 1–11 · Published 22 Jun 2016

10.9734/EJMP/2016/25774

Abstract

The present study was carried out to characterize the bioactive constituents present in essential oil using Fourier transform infrared spectroscopy (FTIR) spectrophotometer and Gas Chromatography –Mass Spectroscopy (GCMS) and evaluation of chemical variability in twenty accessions of Acorus calamus,  collected from India, and data collected were subjected to principle component analysis. The essential oils were scanned and FTIR analysis indicated the presence of groups such as - C – H stretching,  Aldehydic – C – H stretching,  Benzene C = C stretching, C – O stretching, Tetra substituted benzene. The GC-MS analysis results revealed the presence of four different compounds namely β-asarone, α-asarone, shyobunone and epicedrol. The main compound observed in all the accessions was β-asarone. Principal component analysis revealed that the first three principal components accounted for 47.80% of the total variation among the accessions. The first component had high positive loadings from epicedrol (0.925), shyobunone (0.659) and α-asarone (0.591) and high negative loadings from β-asarone (-0.953). Most of the variation was accounted for by the first principal component (20.97%). The dendogram generated by the UPGMA cluster analysis grouped the twenty accessions into two distinct clusters. The study indicated that there is moderate phytochemical variation within the population evaluated. Chemical compositions were moderately influenced by factors such as plant origins, soil and geographical region, medicinal parts, and storage environment. Hence, this study proposes a base of using A. calamus as herbal alternative for the synthesis of various therapeutic agents.

Acorus calamus β-asarone GC-MS essential oil composition principal component analysis (PCA) chemical variability

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