Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy

Fernández, José Luis; Sáez, Felicia; Castro, Eulogio; Manzanares, Paloma; Ballesteros, Mercedes; Negro, María José

doi:10.3390/en12132497

Open AccessFeature PaperArticle

Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy

by

José Luis Fernández

¹,

Felicia Sáez

¹,

Eulogio Castro

²,

Paloma Manzanares

¹,

Mercedes Ballesteros

¹ and

María José Negro

^1,*

¹

Biofuels Unit, Energy Department, Research Centre for Energy, Environment and Technology (CIEMAT), Complutense Av, 22, 28040 Madrid, Spain

²

Department of Chemical, Environmental and Materials Engineering, University of Jaén, Campus Las Lagunillas, 23071 Jaén, Spain

^*

Author to whom correspondence should be addressed.

Energies 2019, 12(13), 2497; https://doi.org/10.3390/en12132497

Submission received: 30 May 2019 / Revised: 25 June 2019 / Accepted: 26 June 2019 / Published: 28 June 2019

(This article belongs to the Special Issue Biorefinery Based on Olive Biomass)

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Abstract

The determination of chemical composition of lignocellulose biomass by wet chemistry analysis is labor-intensive, expensive, and time consuming. Near infrared (NIR) spectroscopy coupled with multivariate calibration offers a rapid and no-destructive alternative method. The objective of this work is to develop a NIR calibration model for olive tree lignocellulosic biomass as a rapid tool and alternative method for chemical characterization of olive tree pruning over current wet methods. In this study, 79 milled olive tree pruning samples were analyzed for extractives, lignin, cellulose, hemicellulose, and ash content. These samples were scanned by reflectance diffuse near infrared techniques and a predictive model based on partial least squares (PLS) multivariate calibration method was developed. Five parameters were calibrated: Lignin, cellulose, hemicellulose, ash, and extractives. NIR models obtained were able to predict main components composition with R²_cv values over 0.5, except for lignin which showed lowest prediction accuracy.

Keywords: lignocellulosic components; feedstock analysis; near-infrared spectroscopy; olive tree pruning

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MDPI and ACS Style

Fernández, J.L.; Sáez, F.; Castro, E.; Manzanares, P.; Ballesteros, M.; Negro, M.J. Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy. Energies 2019, 12, 2497. https://doi.org/10.3390/en12132497

AMA Style

Fernández JL, Sáez F, Castro E, Manzanares P, Ballesteros M, Negro MJ. Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy. Energies. 2019; 12(13):2497. https://doi.org/10.3390/en12132497

Chicago/Turabian Style

Fernández, José Luis, Felicia Sáez, Eulogio Castro, Paloma Manzanares, Mercedes Ballesteros, and María José Negro. 2019. "Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy" Energies 12, no. 13: 2497. https://doi.org/10.3390/en12132497

APA Style

Fernández, J. L., Sáez, F., Castro, E., Manzanares, P., Ballesteros, M., & Negro, M. J. (2019). Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy. Energies, 12(13), 2497. https://doi.org/10.3390/en12132497

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Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy

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