Direct prediction of bioethanol yield in sugar beet pulp using near infrared spectroscopy

Abstract

Sugar beets are a raw material for the production of sugar and ethanol. The decision on which end product to pursue could be facilitated by fast and reliable means of predicting the potential ethanol yield from the beets. A Near Infrared (NIR) Spectroscopy-based approach was tested for the direct prediction of the potential bioethanol production from sugar beets. A modified partial least squares (MPLS) regression model was applied to 125 samples, ranging from 21.9 to 31.0 gL(-1) of bioethanol in sugar beet brei. The samples were analyzed in reflectance mode in a Direct Contact Food Analyser (DCFA) FOSS-NIRSystems 6500 monochromator, with standard error of cross validation (SECV), standard error of prediction (SEP), coefficient of determination (r(2)) and coefficient of variation (CV) of 0.51, 0.49, 0.91 and 1.9 gL(-1), respectively. The NIR technique allowed direct prediction of the ethanol yield from sugar beet brei (i.e. the product obtained after sawing beets with a proper machine) in less than 3 min.