COMPARISON OF FOURIER TRANSFORM NEAR-INFRARED, VISIBLE NEAR-INFRARED, MID-INFRARED, AND RAMAN SPECTROSCOPY AS NON-INVASIVE TOOLS FOR TRANSGENIC RICE DISCRIMINATION

Spectroscopic techniques combined with multivariate analysis have been proven to be effective tools for the discrimination of objects with similar properties. In this work, a comparison of various spectroscopic techniques for identifying genetically modified organisms (GMOs) was performed, including Fourier transform near-infrared (FT-NIR), visible near-infrared (VIS-NIR), mid-infrared (MIR), and Raman spectroscopy. Transgenic rice (Huahui-1) and its parent (Minghui 63) were chosen as subjects in this study. The obtained spectra were analyzed using three common chemometrics methods: principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), and discriminant analysis (DA). The highest classification accuracy (100%) was obtained using Raman (applying PLSDA model) and VIS-NIR (applying DA and PLSDA model) spectroscopy The accuracies obtained by MIR and FT-NIR reached 96.7% (using DA model) and 95.7% (using PLSDA model), respectively These results indicate that FT-NIR, VIS-NIR, Raman, and MIR spectroscopy together with chemometrics methods could be effective in differentiating transgenic rice.