Back to Search Start Over

Essential Oil Composition and DNA Barcode and Identification of Aniba species (Lauraceae) Growing in the Amazon Region.

Authors :
Xavier, Júlia Karla A. M.
Maia, Leonardo
Figueiredo, Pablo Luis B.
Folador, Adriana
Ramos, Alessandra R.
Andrade, Eloísa H.
Maia, José Guilherme S.
Setzer, William N.
da Silva, Joyce Kelly R.
De Martino, Laura
Source :
Molecules; Apr2021, Vol. 26 Issue 7, p1914, 1p
Publication Year :
2021

Abstract

Lauraceae species are widely represented in the Amazon, presenting a significant essential oil yield, large chemical variability, various biological applications, and high economic potential. Its taxonomic classification is difficult due to the accentuated morphological uniformity, even among taxa from a different genus. For this reason, the present work aimed to find chemical and molecular markers to discriminate Aniba species collected in the Pará State (Brazil). The chemical composition of the essential oils from Aniba canelilla, A. parviflora, A. rosaeodora, and A. terminalis were grouped by multivariate statistical analysis. The major compounds were rich in benzenoids and terpenoids such as 1-nitro-2-phenylethane (88.34–70.85%), linalool (15.2–75.3%), α-phellandrene (36.0–51.8%), and β-phellandrene (11.6–25.6%). DNA barcodes were developed using the internal transcribed spacer (ITS) nuclear region, and the matK, psbA-trnH, rbcL, and ycf1 plastid regions. The markers psbA-trnH and ITS showed the best discrimination for the species, and the phylogenic analysis in the three- (rbcL + matK + trnH − psbA and rbcL + matK + ITS) and four-locus (rbcL + matK + trnH − psbA + ITS) combination formed clades with groups strongly supported by the Bayesian inference (BI) (PP:1.00) and maximum likelihood (ML) (BS ≥ 97%). Therefore, based on statistical multivariate and phylogenetic analysis, the results showed a significant correlation between volatile chemical classes and genetic characteristics of Aniba species. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14203049
Volume :
26
Issue :
7
Database :
Complementary Index
Journal :
Molecules
Publication Type :
Academic Journal
Accession number :
149715668
Full Text :
https://doi.org/10.3390/molecules26071914