Comparison of Fourier Transform Near-Infrared, Visible Near-Infrared, Mid-Infrared, and Raman Spectroscopy as Non-Invasive Tools for Transgenic Rice Discrimination

Abstract

<abstract> <bold><sc>Abstract. </sc></bold>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.