Coping with matrix effects in headspace solid phase microextraction gas chromatography using multivariate calibration strategies

被引:17
作者
Ferreira, Vicente [1 ]
Herrero, Paula [1 ]
Zapata, Julian [2 ]
Escudero, Ana [1 ]
机构
[1] Univ Zaragoza, Lab Aroma Anal & Enol, Aragon Inst Engn Res I3A, Dept Analyt Chem,Fac Sci, E-50009 Zaragoza, Spain
[2] Univ Antioquia, Fac Ciencias Exactas & Nat, Inst Quim, Medellin, Colombia
关键词
Multivariate calibration; HS-SPME-GC-MS; PLSR; Volatile compounds; MASS SPECTROMETRIC ANALYSIS; VOLATILE COMPOUNDS; QUANTITATIVE-DETERMINATION; MICRO-EXTRACTION; SPARKLING WINES; RED WINES; GC-MS; AROMA; QUANTIFICATION; FERMENTATION;
D O I
10.1016/j.chroma.2015.06.058
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
SPME is extremely sensitive to experimental parameters affecting liquid-gas and gas-solid distribution coefficients. Our aims were to measure the weights of these factors and to design a multivariate strategy based on the addition of a pool of internal standards, to minimize matrix effects. Synthetic but real-like wines containing selected analytes and variable amounts of ethanol, non-volatile constituents and major volatile compounds were prepared following a factorial design. The ANOVA study revealed that even using a strong matrix dilution, matrix effects are important and additive with non-significant interaction effects and that it is the presence of major volatile constituents the most dominant factor. A single internal standard provided a robust calibration for 15 out of 47 analytes. Then, two different multivariate calibration strategies based on Partial Least Square Regression were run in order to build calibration functions based on 13 different internal standards able to cope with matrix effects. The first one is based in the calculation of Multivariate Internal Standards (MIS), linear combinations of the normalized signals of the 13 internal standards, which provide the expected area of a given unit of analyte present in each sample. The second strategy is a direct calibration relating concentration to the 13 relative areas measured in each sample for each analyte. Overall, 47 different compounds can be reliably quantified in a single fully automated method with overall uncertainties better than 15%. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:30 / 41
页数:12
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