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dc.contributor.authorMata Sánchez, Jesús
dc.contributor.authorPérez Jiménez, José A.
dc.contributor.authorDíaz Villanueva, Manuel Jesús 
dc.contributor.authorSerrano, Antonio
dc.contributor.authorNúñez, Nieves
dc.contributor.authorLópez-Giménez, Francisco J.
dc.contributor.otherIngeniería Química y Tecnología de Alimentoses_ES
dc.date.accessioned2024-09-24T14:11:36Z
dc.date.available2024-09-24T14:11:36Z
dc.date.issued2015
dc.identifier.issn0960-1481
dc.identifier.urihttp://hdl.handle.net/10498/33332
dc.description.abstractThe use of biofuels is a key factor in this transition away from fossil fuels. Today, biofuels are only a small share of world total energy supply. The characterization of biomass is a substantial improvement in the valorization of these resources, allowing a rational and controlled use of its energy potential. Therefore, a fast, reliable and cheap analytical technique is mandatory in order to increase the quality control of these products in the bioenergetic industry and enable comprehensive traceability of raw materials and processes in pursuit of a better use of resources. Near-Infrared (NIR) spectroscopy is eligible for the development of quality control systems of products and processes in accordance with the new demands taking into account their high response speed, low cost per sample, absence of sample preparation, versatility for the analysis of many different products and parameters. NIR spectroscopy prediction model for determination of quality parameters such us moisture, gross energetic value, ash content, volatile fraction content, and elemental composition (Carbon, Hydrogen, and Nitrogen) from ground and dried olive residues have been obtained. High accuracy in prediction for a test set has been achieved for all the parameters (R2 > 0.7) except for Hydrogen content. As expected, Standard Error of Prediction (SEP) for ground samples is better than dried samples except for moisture content. This study illustrates the possibility of using the NIR technique in combination with multivariate data analysis to predict economically important properties of olive byproducts for energetic uses.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceRenewable Energy, Vol. 74, 2015, pp. 599-605es_ES
dc.subjectNear infrared spectroscopyes_ES
dc.subjectChemometricses_ES
dc.subjectEnergetic useses_ES
dc.subjectOlive stonees_ES
dc.subjectOlive tree pruninges_ES
dc.subject“Orujillo”es_ES
dc.titleAssessment of near infrared spectroscopy for energetic characterization of olive byproductses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.renene.2014.08.066
dc.type.hasVersionAMes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Esta obra está bajo una Licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional