• multivariate statistical analysis;
  • SIFT-MS;
  • vanilla;
  • vanillin

Abstract:  Vanilla beans have been shown to contain over 200 compounds, which can vary in concentration depending on the region where the beans are harvested. Several compounds including vanillin, p-hydroxybenzaldehyde, guaiacol, and anise alcohol have been found to be important for the aroma profile of vanilla. Our objective was to evaluate the performance of selected ion flow tube mass spectrometry (SIFT-MS) and Fourier-transform infrared (FTIR) spectroscopy for rapid discrimination and characterization of vanilla bean extracts. Vanilla extracts were obtained from different countries including Uganda, Indonesia, Papua New Guinea, Madagascar, and India. Multivariate data analysis (soft independent modeling of class analogy, SIMCA) was utilized to determine the clustering patterns between samples. Both methods provided differentiation between samples for all vanilla bean extracts. FTIR differentiated on the basis of functional groups, whereas the SIFT-MS method provided more specific information about the chemical basis of the differentiation. SIMCA's discriminating power showed that the most important compounds responsible for the differentiation between samples by SIFT-MS were vanillin, anise alcohol, 4-methylguaiacol, p-hydroxybenzaldehyde/trimethylpyrazine, p-cresol/anisole, guaiacol, isovaleric acid, and acetic acid. ATR-IR spectroscopy analysis showed that the classification of samples was related to major bands at 1523, 1573, 1516, 1292, 1774, 1670, 1608, and 1431 cm−1, associated with vanillin and vanillin derivatives.

Practical Application:  Fourier transform infrared attenuated total reflectance and selected ion flow tube mass spectrometry have shown to be quick and reliable methods for analyzing vanilla extracts which could be utilized as a quality assurance tool in the fragrance, flavoring, and food industries.