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Phytochemical Fingerprints of Copaiba Oils (Copaifera multijuga Hayne) Determined by Multivariate Analysis
Authors:Paula Cristina Souza Barbosa  Larissa Silveira Moreira Wiedemann  Raquel da Silva Medeiros  Paulo de Tarso Barbosa Sampaio  Gil Vieira  Valdir Florêncio da Veiga‐Junior
Affiliation:1. Departamento de Química, Universidade Federal do Amazonas, Av. General Rodrigo Octávio, N° 6200, CEP 69079‐000, Manaus‐AM, Brazil (phone/fax: +55‐92‐33052817);2. Instituto Nacional de Pesquisas da Amaz?nia, Av. André Araújo, N° 2936, Aleixo, CEP 69060‐001, Manaus‐AM, Brazil
Abstract:Oils of various species of Copaifera are commonly found in pharmacies and on popular markets and are widely sold for their medicinal properties. However, the chemical variability between and within species and the lack of standardization of these oils have presented barriers to their wider commercialization. With the aim to recognize patterns for the chemical composition of copaiba oils, 22 oil samples of C. multijuga Hayne species were collected, esterified with CH2N2, and characterized by GC‐FID and GC/MS analyses. The chromatographic data were processed using hierarchical cluster analysis (HCA) and principal component analysis (PCA). In total, 35 components were identified in the oils, and the multivariate analyses (MVA) allowed the samples to be divided into three groups, with the sesquiterpenes β‐caryophyllene and caryophyllene oxide as the main components. These sesquiterpenes, which were detected in all the samples analyzed in different concentrations, were the most important constituents in the differentiation of the groups. There was a prevalence of sesquiterpenes in all the oils studied. In conclusion, GC‐FID and GC/MS analyses combined with MVA can be used to determine the chemical composition and to recognize chemical patterns of copaiba oils.
Keywords:Copaifera multijuga  Copaiba oil  Oleoresin  Multivariate analysis (MVA)  Hierarchical cluster analysis (HCA)  Principal component analysis (PCA)
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