Abstract
Rosewood essential oil is a high value-added forest product obtained from the Aniba rosiodora Ducke species, native to the Amazon. The chemical constitution is rich in linalool, an important compound with fixative properties, but is the whole chemical profile that grants rosewood oil its unique aroma highly valued by the perfumery and cosmetic industries. However, due to intense exploitation for decades, A rosiodora is currently an endangered species and is part of Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), being that the trade and export of its essential oil are allowed only from managements authorized areas. Despite its efficiency for chemical characterization, GC–MS analysis is not available for most cooperatives and small producers and does not allow in situ measurements. On the other hand, near infrared spectroscopy (NIRS) can perform a fast, direct, low-cost, nondestructive analysis using handheld equipments. In this work, a new method for the direct and rapid analysis of this essential oil using near-infrared spectroscopy and data-driven soft independent modeling of class analogy (SIMCA) was developed for rosewood essential oil authentication. The sampling was conducted in different Brazillian states, covering industries, small cooperatives, local producers, and commercial products. All samples were characterized by GC–MS analysis to certify their purity and authenticity. NIRS measurements were performed without any sample treatment and data modeling was accomplished to ensure a representative validation. The representative sampling revealed that there is a significant variation among the samples declared as rosewood oil in the Brazilian market. The method has shown 98% efficiency in the analysis of authentic and commercial samples from different origins, indicating that it can be a green alternative for authentication purposes for export and quality control.
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