Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: Pattern-recognition analyses for screening quality control purposes

被引：7
作者：
Flumignan, Danilo Luiz [1 ]
Boralle, Nivaldo [2 ]
de Oliveira, Jose Eduardo [1 ]
机构：
[1] Sao Paulo State Univ UNESP, Ctr Monitoring & Res Qual Fuels Biofuels Crude Oi, Inst Chem, Dept Organ Chem, BR-14800900 Sao Paulo, Brazil
[2] Sao Paulo State Univ UNESP, Dept Organ Chem, Inst Chem, BR-14800900 Sao Paulo, Brazil
来源：
TALANTA | 2010年 / 82卷 / 01期
关键词：
Brazilian commercial gasoline; Quality control; Carbon nuclear magnetic resonance; spectroscopic fingerprinting; Pattern-recognition multivariate SIMCA; ANP Regulation 309; BRAZILIAN GASOLINE; H-1-NMR SPECTROSCOPY; CHROMATOGRAPHIC DATA; GAS-CHROMATOGRAPHY; ADULTERATION; GC;
D O I：
10.1016/j.talanta.2010.04.058
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
In this work, the combination of carbon nuclear magnetic resonance ((13)C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized (13)C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：392 / 397
页数：6
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