Application of FT-NIR spectroscopy and FT-IR spectroscopy to Chinese rice wine for rapid determination of fermentation process parameters

Abstract

Effective fermentation monitoring is a growing need during the production of wine due to the rapid pace of change in the industry. Total reducing sugar, pH and amino acid nitrogen (AAN) are the three most important process variables indicating the status of the Chinese rice wine (CRW) fermentation process. In this study, the potential of near-infrared (NIR) spectroscopy and mid-infrared (MIR) spectroscopy as rapid tools to monitor the evolutions of these three chemical parameters involved in the CRW fermentation process was investigated and compared. The results demonstrated that compared with the partial least-squares (PLS) model based on the full spectrum, the model based on the spectra intervals selected by the synergy interval partial least-squares (SiPLS) algorithm had higher prediction accuracy. In addition, nonlinear models outperformed linear models in predicting fermentation parameters. After systemic comparison and discussion, it was found that for either models developed based on NIR spectra or models developed based on MIR spectra, SiPLS-support vector machine (SiSVM) models obtained the best result with the highest prediction precision. The overall results indicated that it was feasible to monitor the fermentation process of Chinese rice wine using NIR and MIR spectroscopy.