Line monitoring by near-infrared chemometric technique for potential ethanol production from hydrothermally treated Eucalyptus globulus

Abstract

This study reports a method that combines near-infrared (NIR) measurements with multivariate analysis to predict the saccharification efficiency of hydrothermally pretreated Eucalyptus globulus during ethanol conversion. Optimization of the NIR data with or without spectral treatment determined the best calibration model in the region 10000–4000cm−1 of the original spectra, with an RMSEP of 2.08% and Rp2 of 0.99. By investigating the regression coefficient to understand the key regions and chemical components, for original and multiplicative scatter correction (MSC)-treated spectra, the water absorption and higher wavenumber regions were important. For the second derivative spectra, the regression model was constructed based on the CH overtone vibrations (6050–5500cm−1). The regression coefficient demonstrated that the removal of hemicellulose resulted in higher lignin content, which might affect the biomass properties in terms of water absorption and enhanced enzymatic hydrolysis evaluated by dinitrosalicylic acid (DNS) method. For a higher throughput system, aqueous sample analysis was performed using an immersion probe equipped with an InGaAs detector, which generated an acceptable calibration model having RMSEP of 4.25% and Rp2 of 0.94. These results show the great potential of NIR spectroscopy for achieving fast, accurate, and nondestructive analysis, and its highly adaptability for maintaining an ethanol bioconversion system.TGS, triglycine sulfate