Prediction of Concentration of Animal Fat in Mixture with Vegetable Oil by Multivariate Calibration Associated with Spectrofluorimetry

Autor:	Erika M. de O. Ribeiro, Weidson Leal Silva, Alexandre Kamei Guimarães, Saionara Luna, Mariana Andrade Santos, Cristina M. Quintella, Marilena Meira, Gabriela Silva Cerqueira, Alexandre Lopes Del Cid
Rok vydání:	2013
Předmět:	Psychiatry and Mental health Biodiesel Animal fat Vegetable oil Fouling Chemistry Biodiesel production Principal component analysis Partial least squares regression Food science Raw material
Zdroj:	American Journal of Analytical Chemistry. :99-103
ISSN:	2156-8278 2156-8251
DOI:	10.4236/ajac.2013.42013
Popis:	Total spectrofluorimetry associated with Principal Component Analysis (PCA) was used to discriminate samples of vegetable oil and animal fat. In addition, a multivariate calibration model was developed that combines spectroflurimetry with Partial Least Squares (PLS) for prediction of concentration of animal fat in mixture with vegetable oil. The multivariate calibration model had an R2 value of 0.98098, which indicates the accuracy of the model. This method has potential application in the control of quality of raw material for production of biodiesel. The control of the concentration of animal fat is important because animal fat is more susceptible to oxidation than vegetable oil. Furthermore, high concentrations of animal fats may increase electricity costs for biodiesel production due to the high melting points of saturated fats that solidify at room temperature and cause the fouling and clogging of pipes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::18b5a1b5efef30c954536c12c6a2e57e https://doi.org/10.4236/ajac.2013.42013 Zobrazit plný text záznamu