Authenticity Identification of Copaiba Oil Using a Handheld NIR Spectrometer and DD-SIMCA

Abstract

Copaiba oil (CO) is a non-timber forest product, obtained from the Copaifera genus, used in popular medicine, pharmaceutical, and cosmetic industries. The increasing demand and price of this oil also increased the occurrence of adulterations in commercial products and small providers in cooperatives. Nowadays, the GC-MS is the most suitable method used for quality control. However, the high cost of this technique is unfeasible for small traders and cooperatives. Considering the lack of alternative methods for CO analysis, this work presents an easy, direct, fast, and inexpensive method based on a handheld NIR spectrometer and a DD-SIMCA model for purity authentication. The training set was composed of 65 pure CO samples originated by 12 distinct sources of Copaifera sp. oil, 9 distinct commercial samples, binary and ternary mixtures among them. The validation was accomplished using 213 samples constituted by independent authentic samples, samples submitted to thermal stress, commercial samples with and without edible vegetable oil adulteration, and samples purposefully adulterated with edible oils (palm, olive, sunflower, coconut, and soybean). The optimized DD-SIMCA model showed 95% of sensitivity regarding the target class, where 5% the false-negative rate revealed the necessity of increasing the number of commercial samples in the training set. The specificity, related to samples not belonging to the target class, was 97.3%, showing that the model is highly effective to detect adulterated samples. The average efficiency of the method was 92.3%, revealing to be very promising for quality control and authenticity testing applications in small cooperatives.