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Título : | Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy |
Autor : | Fernandez, J. Luis Saez, Felicia Castro, Eulogio Manzanares, Paloma Ballesteros, Mercedes Negro, Mª Jose |
Palabras clave : | lignocellulosic components feedstock analysis near-infrared spectroscopy olive tree pruning |
Fecha de publicación : | 28-jun-2019 |
Editorial : | MPDI |
Citación : | J. L. Fernández, F. Sáez, E. Castro, P. Manzanares, M. Ballesteros and M. J. Negro. Determination of the Lignocellulosic Components of Olive Tree Pruning Biomass by Near Infrared Spectroscopy. Energies 2019, 12, 2497; doi:10.3390/en12132497 |
Resumen : | 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 o ers 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 di use 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
values over 0.5, except for lignin which showed lowest prediction accuracy. |
URI : | http://documenta.ciemat.es/handle/123456789/2959 |
ISSN : | 1996-1073 |
Aparece en las colecciones: | Artículos de Energía
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