Detection and characterization of adulterants in baru and soursop oils

Abstract

The presence of vegetable oils in the pharmaceutical and cosmetic industries boosts their production and commercialization, maximizing the economic potential, however to increase profits, vegetable oils with high added value are the target of adulteration practices. This negatively affects the quality of the product and compromises the bioactive properties of these oils. The objective of this study was to build partial least squares regression models to identify baru oil and soursop oil samples adulterated with soybean oil. For data collection the oils samples were characterized using portable near-infrared spectrometer and Fourier-transform infrared spectrometer. These techniques were chosen because both provide information about the functional groups of chemical compounds, however portable equipment, being cheaper, presents signals with lower spectral resolution. Thus, the objective of the work is also to verify if the results using both equipment are similar. The developed regression models were effective; however, the near-infrared technique presented some limitations in the identification of soursop oil. This is because for the construction of his model it was necessary to use a smaller number of variables and levels of adulteration. Nevertheless, high R² values and relatively low errors were obtained for all models, making it possible to identify the adulteration.
 
 Pratica Application: Adulteration analysis of baru and soursop oils by infrared spectroscopy and portable equipment