1. GC Fingerprints Coupled to Pattern-Recognition Multivariate SIMCA Chemometric Analysis for Brazilian Gasoline Quality Studies
- Author
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Danilo Luiz Flumignan, José Eduardo Dutra de Oliveira, and Rafael Rodrigues Hatanaka
- Subjects
Multivariate statistics ,business.industry ,Chemistry ,Organic Chemistry ,Clinical Biochemistry ,Pattern recognition ,Biochemistry ,Analytical Chemistry ,law.invention ,Chemometrics ,law ,Principal component analysis ,Pattern recognition (psychology) ,Flame ionization detector ,Gas chromatography ,Artificial intelligence ,Gasoline ,business - Abstract
ASTM D6729 gas chromatographic fingerprinting coupled to pattern-recognition multivariate soft independent modeling of class analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality. SIMCA, was performed on gas chromatographic fingerprints to classify the quality of representative commercial gasoline samples selected by hierarchical cluster analysis and collected over a 5 month period from gas stations in Sao Paulo State, Brazil. Following an optimized ASTM D6729 gas chromatographic-SIMCA algorithm, it was possible to correctly classify the majority of commercial gasoline samples. The method could be employed for rapid monitoring to discourage adulteration.
- Published
- 2009
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