Application of detection of process parameters in the Chinese rice wine by NIRS

The feasibility of NIRS was investigated to rapidly detect the total acid and alcohol in the fermentation process of Chinese rice wine. The detection of key parameters is of importance in the fermentation process of Chinese rice wine,however,it is largely time- consuming and laborious.In this paper,synergy interval partial least squares combined with the genetic algorithm( si PLS- GA) was put forward to estimate fermentation process parameters in Chinese rice wine,and the cross- validation method was used to select the optimal PLS factors and the variables.The results showed that the best prediction result was achieved by si PLS- GA using 5 and 8 factors in modeling the total acid and alcohol.By employing the best model,the prediction correlation coefficients( Rp) of the total acid and alcohol were 0.9177 and 0.9803,respectively,and the root mean square errors for prediction( RMSEP) were 0.2132 and 0.7816 respectively.Comparing with the results showed that NIRS combined with si PLSGA can achieve good performance in detection of the content of total acid and alcohol in the fermentation process of Chinese Rice wine.