Prediction of starch content and ethanol yields of sorghum grain using near infrared spectroscopy

A rapid quantification method was developed and validated for nondestructive measurement of starch content and ethanol yield of 48 cultivars of sorghum grain using Fourier transform near infrared (FT-NIR) spectroscopy in diffuse reflectance mode. Multiplicative scatter correction (MSC), Savitzky-Golay derivative smoothing, and mean centering were used for processing the spectra of ground sorghum grain. The processed spectra were correlated with starch content and ethanol produced through simultaneous saccharification and fermentation (SSF) using partial least squares regression (PLSR). Spectral range and the number of factors were optimized for the lowest root mean square error of prediction (RMSEP), coefficient of determination (R²), and ratio of performance to deviation (RPD). The best PLSR models for starch content had RMSEP = 1.23%, R² = 0.94, and RPD = 2.66; likewise, models for ethanol yield had RMSEP =1.29 g/100 g grain, R² = 0.96, and RPD = 1.92.The models developed demonstrated FT-NIR analysis as a practical method for screening different sorghum grain varieties by estimating starch content and ethanol yield to provide a rapid measure of conversion efficiency.