Chemometrics-assisted voltammetric method for simultaneous determination of vanillin and ethyl maltol in food samples
NI Yong-niana
Abstract
NI Yong-niana
Abstract
A differential pulse stripping voltammetry(DPSV) method for simultaneous determination vanillin and ethyl maltol in food samples was developed.Both of these two food additives gave well-defined oxidation peaks at glass carbon electrode in medium of pH=10.12 Britton-Robinson buffer,and serious overlapped voltammograms were observed.In the optimum experimental conditions selected,the linear ranges of vanillin and ethyl maltol were 0.4-6.4 and 0.2-7.6 μg·mL-1,respectively,and their corresponding limits of detection(LOD) were 0.28 and 0.11 μg·mL-1.In this paper,chemometrics methods:such as principal component regression(PCR),partial least squares(PLS),first-derivative principal component regression(DPCR),and first-derivative partial least squares(DPLS),were applied to resolve the overlapped voltammograms.The calibration models were established,which were then applied to predict the composition of an unknown sample set.The prediction performance was compared.It was found that PCR gave better results than other methods.The method proposed in our paper could be applied to determine these two flavoring enhancers in some real food samples,validated by high-performance liquid chromatography(HPLC) technique.
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A differential pulse stripping voltammetry(DPSV) method for simultaneous determination vanillin and ethyl maltol in food samples was developed.Both of these two food additives gave well-defined oxidation peaks at glass carbon electrode in medium of pH=10.12 Britton-Robinson buffer,and serious overlapped voltammograms were observed.In the optimum experimental conditions selected,the linear ranges of vanillin and ethyl maltol were 0.4-6.4 and 0.2-7.6 μg·mL-1,respectively,and their corresponding limits of detection(LOD) were 0.28 and 0.11 μg·mL-1.In this paper,chemometrics methods:such as principal component regression(PCR),partial least squares(PLS),first-derivative principal component regression(DPCR),and first-derivative partial least squares(DPLS),were applied to resolve the overlapped voltammograms.The calibration models were established,which were then applied to predict the composition of an unknown sample set.The prediction performance was compared.It was found that PCR gave better results than other methods.The method proposed in our paper could be applied to determine these two flavoring enhancers in some real food samples,validated by high-performance liquid chromatography(HPLC) technique.
Key concepts: Maltol, Chemometrics, Chemistry, Principal component regression, Partial least squares regression, Chromatography, Voltammetry, Detection limit