Rapid Quantification Analysis of Alcohol during the Green Jujube Wine Fermentation by Electronic Nose

Abstract

In order to explore the applicability of electronic nose technique for alcohol dynamic change, electronic nose was used to predict the alcohol content of the green jujube wine fermentation. The principal component regression (PCR) and multiple linear regression (MLR) were applied to establish the forecast model of the alcohol content. The results showed that the response values of sensors S1, S8, S3, S5 and S4 were the largest among the 10 sensors and changed significantly during 7 days of fermentation. The linear simulation equation was established by using the MLR to predict the alcohol content and the R2 value was 0.949, and the RMSEC was 0.974. The model shows the better predict alcohol content correlation (R2=0.946) and RMSEP (1.016). The results show that it is feasible to use the electronic nose system to analyses alcohol content dynamic chance of the green jujube wine fermentation, and electronic nose technique provides a method for rapid quantification analysis of alcohol of wine fermentation.