Real-Time Monitoring of Ethanol Fermentation Using Mid-Infrared Spectroscopy Analysis of the Gas Phase

The Fourier transform mid-infrared (FT-MIR) spectroscopy technique, with multivariate calibration by the partial least-squares (PLS) regression method, was used for real-time monitoring of the ethanol molar fraction in the gas phase during ethanol fermentation. The PLS model was obtained using a calibration set constructed of gas streams with different molar fraction proportions and the corresponding FT-MIR spectra. The molar fraction compositions were calculated by combining thermodynamic assumptions and mass balances. The proposed model presented excellent performance when the spectra were submitted to pretreatment using middle center (MC), smoothed moving average (SMA), and second derivative (secondD). The determination coefficient for the model revealed an excellent fit to the experimental data (R 2 = 0.999). The root-mean-square error of cross-validation (RMSECV) and the root-mean-square error of prediction (RMSEP) were less than 1.6 and 1.9% of the range of values, respectively, indicative of excellent predictive capacity. The high values of the range error ratio (RER = 52.52) and the ratio of the standard error of performance to the standard deviation (RPD = 17.54) provided further evidence of the excellent resolution of the model, which was used for carrying out quantitative analyses of ethanol in the gas phase. A set of fermentations performed in batch and fed-batch modes was used to evaluate the predictive capacity of the model. The data for the molar fraction of ethanol in the gas phase were used to estimate the ethanol and substrate concentrations in the liquid phase. The findings demonstrated that analysis of the gas phase using the FT-MIR/PLS technique is a reliable strategy for real-time monitoring of ethanol fermentation under different operational modes, without any sample manipulation.