SciELO - Scientific Electronic Library Online

 
vol.59 issue1HIGH SENSITIVITY METHOD FOR DETERMINATION OF TRACE CURCUMIN IN THE AQUEOUS PHASEDETERMINATION OF HEAVY METALS IN CHOAPA RIVER SEDIMENTS USING BCR SEQUENTIAL EXTRACTION PROCEDURE author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Journal of the Chilean Chemical Society

On-line version ISSN 0717-9707

Abstract

CASTILLO, ROSARIO DEL P et al. NIR SPECTROSCOPY APPLIED TO THE CHARACTERIZATION AND SELECTION OF PRE-TREATED MATERIALS FROM MULTIPLE LIGNOCELLULOSIC RESOURCES FOR BIOETHANOL PRODUCTION. J. Chil. Chem. Soc. [online]. 2014, vol.59, n.1, pp.2347-2352. ISSN 0717-9707.  http://dx.doi.org/10.4067/S0717-97072014000100022.

Lignocellulosic biomass (LB) has been recognized as potential raw for bioethanol production. To facility LB bioconversion a pretreatment is applied, followed by simultaneous or separated saccharification and fermentation (SSF or SHF, respectively) steps. Characterization of pretreated materials, needed to evaluate their ethanol yields, involves laborious and destructive methodologies. Therefore, saccharification is also time consuming and expensive step and some pretreated samples have not suitable characteristics to obtain high ethanol yields. Since bioethanol production aims to be a multivariable process respect to lignocellulosic resources, this work attempts to use NIR spectroscopy as alternative to wet chemical analysis to characterize samples from multiple pretreatments and lignocellulosic resources simultaneously and estimate their ethanol yield after a SSF process using multivariate calibration. Selection of suitable samples to obtain high ethanol yields using a classification method is also evaluated. Partial least squares (PLS) and discriminant partial least squares (PLS-DA) were used as calibration and classification techniques, respectively. Results showed ability of NIR spectroscopy to predict the chemical composition of samples and their ethanol yields, even if different lignocellulosic materials were used in the models, with low prediction errors and high correlation coefficients with reference methods (r>0,96) in PLS models and low misclassification rates (20- 30%) in classification models. Use of these models could facility the fast selection of high number of samples with suitable characteristics to obtain high ethanol yields and as predictive tool of these ethanol yields after a SSF process under controlled conditions.

Keywords : NIBS; bioethanol; simultaneous saccharification and fermentation (SSF); lignocellulosic biomass.

        · text in English     · English ( pdf )