Fourier transformed near infrared (FT‐NIR) spectroscopy for the estimation of parameters in pretreated lignocellulosic materials for bioethanol production

Abstract

BACKGROUND In the bioethanol production process it is necessary to know the physical and chemical characteristics of pretreated material which may affect the enzymatic hydrolysis as well as the carbohydrates potential for fermentation. In the present study, prediction models were developed with Fourier transformed near infrared (FT‐NIR) spectroscopy and multivariate analysis for the cellulose crystallinity index (CrI), saccharification and ethanol yield, and glucan, hemicellulose and lignin content. Prediction models were generated using Eucalyptus globulus and Pinus radiata samples from different pretreatments such as bio pretreatment, kraft process, steam explosion, organosolv and biorganosolv process. RESULTS The calibration models obtained by partial least‐squares (PLS), presented high coefficients of calibration and validation determination. The predictive ability of the calibration models developed was evaluated in a set of external samples. The properties were predicted with a prediction error (RMSEP) of 0.02, 1.4 g L−1, 2.0%, 0.9%, 1.0% and 1.9% for CrI, ethanol yield, saccharification, lignin, hemicellulose and glucan content, respectively. CONCLUSION These results suggest that it is possible to construct models for these properties with a database involving pulps from different pretreatments. NIR spectroscopy predictions provide useful and economic tools for rapid analysis of the large number of samples required in the assessment of bioethanol production processes. © 2014 Society of Chemical Industry

Characterization of pre-treatments on wood chips prior to delignification by near infrared spectroscopy

“…This range includes several bands based on vibrations of C-H stretching (1 st OT) of aromatic, CH2 and CH3 bonds, phenolic O-H (1 st OT), and non-specified band at 5,522 cm -1 of lignin structures (Schwanninger et al 2011). Alternatively, the whole range of NIR spectroscopy (from 3,800-4,000 cm -1 to 10,000-12,000 cm -1 ) has been used to create multivariate prediction models (Kelley et al 2002;Monrroy et al 2015) for similar purposes in wood chemistry studies.…”

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

“…Later studies investigated calibration models for systems employing various NIR spectral pretreatments [4,5] alone or in combination with other multivariate analysis methods such as PCA [6] and SIMCA [7], or the interpretation of regression vectors or loading factors [8]. For chemically pretreated rice straw and Erianthus, we previously demonstrated a chemometric approach to the saccharification ratio, which is an important index for assessing pretreatment methods [9,10] All of the NIR spectra conducive to the acceptable calibration model were measured from residues that had strongly NIR-light absorbing and scattering properties, with a few sample preparation steps such as drying or molding.…”

Determination of Brachiaria Spp. Forage Quality by Near-Infrared Spectroscopy and Partial Least Squares Regression

“…4 Near-infrared spectroscopy (NIRS) combined with chemometric analysis is a useful and powerful technique used for the quality control of various raw materials and products in food, agricultural, pharmaceutical, and petrochemical industries, [5][6][7] e.g., in the chemical composition determination of bamboo and wood, 8,9 soil organic matter analysis, 10 wheat grain carbohydrate analysis, 11 chemical property determination of cellulosic pulps, 12 and material evaluation for bioethanol production. 13,14 In contrast to conventional analysis methods, NIRS has the advantages of being nondestructive, requiring a small sample size and a short analysis time, not using chemical reagents, being environmentally friendly (since no waste is generated), and allowing various parameters to be determined at-/on-line, offering a low-cost measurement alternative. 4,7,15 NIRS has a high potential for the determination of parameters of interest in the livestock industry.…”