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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Applications of an electronic nose in the prediction of oxidative stability of stored biodiesel derived from soybean and waste cooking oil

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Author(s):
Vidigal, Igor G. [1] ; Siqueira, Adriano F. [2] ; Melo, Mariana P. [2] ; Giordani, Domingos S. [1] ; da Silva, Maria L. C. P. [1] ; Cavalcanti, Eduardo H. S. [3] ; Ferreira, Ana L. G. [2]
Total Authors: 7
Affiliation:
[1] Univ Sao Paulo, Escola Engn Lorena, Dept Engn Quim, BR-12602810 Lorena, SP - Brazil
[2] Univ Sao Paulo, Escola Engn Lorena, Dept Ciencias Basicas & Ambientais, BR-12602810 Lorena, SP - Brazil
[3] Inst Nacl Tecnol LACOR INT, Lab Corrosao & Protecao, BR-20081312 Rio De Janeiro, RJ - Brazil
Total Affiliations: 3
Document type: Journal article
Source: FUEL; v. 284, JAN 15 2021.
Web of Science Citations: 3
Abstract

Waste cooking oil (WCO) is a valuable feedstock for the synthesis of biodiesel but the product exhibits poor oxidative stability. Techniques available for assessing this parameter are generally expensive and time-consuming, hence the purpose of this study was to develop and validate a rapid and reliable predictive system based on signals from the sensors of a commercial hand-held e-nose instrument. Biodiesels were synthesized from soybean oil and six samples of WCO, and their physicochemical characteristics and oxidative stabilities determined before and after storage in different types of containers for 30 or 60 days at room temperature or 43 degrees C. Linear regression models were constructed based on principal component analysis of the signals generated by all 32 e-nose sensors and stochastic modeling of signal profiles from individual sensors. The regression model with principal components as predictors was unable to explain the oxidative stability of biodiesels, while the regression model with stochastic parameters (combining signals from 11 sensors) as predictors showed an excellent goodness of fit (R-2 = 0.91) with a 45-sample training set and a good quality of prediction (R-2 = 0.84) with a 18-sample validation set. The proposed e-nose system was shown to be accurate and efficient and could be used to advantage by producers/distributors of biodiesel in the assessment fuel quality. (AU)

FAPESP's process: 18/16156-3 - Study on the main constraining variables affecting biofuel quality: from production to storing
Grantee:Ana Lúcia Gabas
Support Opportunities: Program for Research on Bioenergy (BIOEN) - Regular Program Grants
FAPESP's process: 17/25340-0 - Study of oxidative stability for a quality of biofuel
Grantee:Igor Gomes Vidigal
Support Opportunities: Scholarships in Brazil - Master