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Pre-classification of residual oil and fat (OGR) for biodiesel application

Grant number: 15/09766-1
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): September 01, 2015
Effective date (End): February 28, 2017
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Ana Lúcia Gabas
Grantee:Daniel Rodrigues Valle Galhardi
Home Institution: Escola de Engenharia de Lorena (EEL). Universidade de São Paulo (USP). Lorena , SP, Brazil

Abstract

Actually, Brazil stands out for generating 40% of its energy from renewable energy sources, especially products from sugar cane and biofuel. Brazil's political strategy is world leading production, use and marketing of biofuels, and it is expected an exponential growth in production in the next years. This project aims to contribute to the development of a methodology for pre-assessment of residual oil and fat (OGR), from the frying food for the production of biofuel. It is known that the characteristics of the raw material directly influence the final quality of the biofuel. Thus, it will be used an electronic nose for classifying the origin of the OGR, which will be also characterized by analysis of acid value, color, peroxide, viscosity and density. This research is part of a larger project, funded by FAPESP (Proc. No 2014/25001-2), which will produce biodiesel from these different samples of OGR, which will be correlate with the quality indicators of biofuel. All the research that is carrying out will allow the optimization of the biodiesel production process, with considerable reduction in the analysis time and without using sophisticated and expensive equipment.

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SIQUEIRA, A. F.; MELO, M. P.; GIORDANI, D. S.; GALHARDI, D. R. V.; SANTOS, B. B.; BATISTA, P. S.; FERREIRA, A. L. G. Stochastic modeling of the transient regime of an electronic nose for waste cooking oil classification. Journal of Food Engineering, v. 221, p. 114-123, MAR 2018. Web of Science Citations: 2.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.