Abstract

Multiple samples (117) of sweet sorghum stalk particles were analysed qualitatively and quantitatively during solid-state fermentation using near infrared spectroscopy and chemometrics methods. The study indicated that the samples could be identified to the lag phase, exponential phase or stationary phase of the ethanol fermentation process by discriminant analysis of a principal component analysis (PCA) model. The first principal component score of PCA could be used to predict the extent of reaction, regardless of the value of parameters, such as pH value and sugar, ethanol and water content. The r² values of multivariate regression models for mass fractions of sugar, alcohol and water, and pH were 0.93, 0.94, 0.87 and 0.95, respectively. The root mean standard errors of prediction for mass fractions of sugar, alcohol and water, and pH were 0.013, 0.006, 0.008 w w⁻¹ and 0.15, respectively. The partial least squares regression of the value of pH had the best fit of the four parameters. Near infrared spectroscopy could be used successfully in process monitoring of solid-state fermentation of sweet sorghum stalks.

© 2015 The Author(s)

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