A novel approach to discriminate transgenic from non-transgenic soybean oil using FT-MIR and chemometrics

- FT-MIR-coupled with PLS-DA were used to discriminate soybean oil samples.
- Results show that FT-MIR coupled PLS-DA can provide reliable results.
- Compared to traditional method (PCR), this methodology is fast and reliable.

A methodology was developed to distinguish transgenic from non-transgenic soybean oils samples by using FT-MIR spectroscopy coupled with discrimination techniques, including Soft Independent Modeling of Class Analogies (SIMCA), Support Vector Machine-Discriminant Analysis (SVM-DA) and Partial Least Squares-Discriminant Analysis (PLS-DA). The discrimination success rate of these three methods was compared, and different types of preprocessing were investigated. Based on the results, the best option was PLS-DA with a 100% rate of discrimination, independent of the preprocessing method used.