Abstract: This study aimed to establish an accurate model based on fingerprint information fusion of characteristic volatile compounds and infrared spectrum for identifying the geographical origin of rice. A total of 20, 19 and 15 rice samples respectively collected from Panjin, Sheyang and Wuchang were analyzed for their volatile compounds by gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectra of these samples were recorded. Analysis?of variance (ANOVA) was employed to screen out the characteristic volatile components and characteristic infrared spectra, which were combined to establish a fingerprint information fusion model by partial least squares discriminant analysis (PLS-DA). The results showed that the identification accuracy of the fingerprint information fusion model was 97.4%, which was increased by 4.5% and 8.5% compared with individual infrared spectrum (92.9%) and volatile fingerprints (88.9%), respectively. Therefore, the PLS-DA information fusion model is feasible to identify the geographical origin of rice with high accuracy.

Key words: geographical indication rice, geographical origin identification, gas chromatography-mass spectrometry (GC-MS), Fourier transform infrared spectroscopy, partial least squares-discriminant analysis (PLS-DA)