Discrimination between Chinese rice wines of different geographical origins by NIRS and AAS

The feasibility of near infrared spectroscopy (NIRS) for discrimination between Chinese rice wine of different geographical origins (Shaoxing and Jiashan, China) is presented in this research. NIR spectra were collected in transmission mode in the wavelength range of 800–2500 nm. Qualitative analysis models were developed based on partial least squares regression (PLSR). The prediction performance of calibration models in different wavelength range was also investigated. The best models gave a 100% classification of wines of the two geographical origins in the range of 1300–1650 nm. The content of trace metals (potassium, magnesium, zinc, and iron) was also investigated to classify wines of the two categories by atomic absorption spectroscopy (AAS). The AAS results were in agreement with NIRS, with 100% classification for wines of the two categories. In addition, the correlation between NIRS and AAS was also investigated by PLSR. Potassium and magnesium were well predicted by quantitative models based on NIR spectra and AAS data. The correlation coefficient of calibration (Rcal) for potassium and magnesium were 0.958 and 0.885, respectively, and the correlation coefficient of validation (Rval) were 0.861 and 0.700, respectively. The results demonstrated that NIRS technique could be used as a rapid method for classification of geographical origin of Chinese rice wine, and AAS could be used as an alternative technique or to validate the discrimination results.