Abstract:

In order to evaluate the influence of temperature on near-infrared spectroscopy (NIRS) analysis models of Chinese
rice wine quality, NIR spectra of rice wine samples were collected at 5, 10, 15, 20, 25, 30 and 35 ℃, respectively. Calibration
models for the quantification of alcohol and total sugar contents in rice wine were developed by partial least square (PLS)
algorithm. The results indicated that the spectra of samples were affected by temperature. An obvious clustering tendency
was detected by principal component analysis (PCA) between samples at different temperatures. The prediction ability of the
calibration models was also influenced by temperature, but showing no consistent trend with temperature. The performance
of the multi-temperature calibration models was suitable for practical application with low relative error values. These results
provided a theoretical basis for rapid detection of rice wine quality as well as temperature correction by NIR spectroscopy.

Key words: temperature, near infrared spectroscopy (NIRS), partial least square, Chinese rice wine, quality