TY - JOUR
T1 - Prediction of coumarin and ethyl vanillin in pure vanilla extracts using MID-FTIR spectroscopy and chemometrics
AU - Moreno-Ley, Cristina Montserrat
AU - Hernández-Martínez, Diana Maylet
AU - Osorio-Revilla, Guillermo
AU - Tapia-Ochoategui, Adriana Patricia
AU - Dávila-Ortiz, Gloria
AU - Gallardo-Velázquez, Tzayhri
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/5/15
Y1 - 2019/5/15
N2 - Fourier transform mid-infrared (MID-FTIR) spectroscopy coupled with chemometric analysis was used to identify and quantify coumarin (CMR) and ethyl vanillin (EVA) adulterations in pure vanilla extracts. Forty samples adulterated with CMR (0.25–10 ppm) and forty with EVA (0.25–10%) were prepared from pure vanilla extracts and characterized by MID-FTIR spectroscopy to develop chemometric models. Additionally, six commercial vanilla samples were analyzed. A soft independent modeling of class analogy (SIMCA) model was developed to identify and classify the purity from EVA-adulterated or CMR-adulterated samples. Prediction models for CMR or EVA content were developed using the principal component regression (PCR), partial least squares with single y-variables (PLS1), and with multiple y-variables (PLS2) algorithms. Moreover, the predictions of the best quantification chemometric model were compared with the results of a high-performance liquid chromatography-diode array detector (HPLC-DAD) method to evaluate the accuracy of the prediction. The PLS1 algorithm had better performance using 3 and 8 factors for EVA and CMR, respectively. The SIMCA model showed 100% recognition and rejections rates. The results demonstrate that adulteration of pure vanilla with EVA and CMR could be successfully predicted by the developed technique.
AB - Fourier transform mid-infrared (MID-FTIR) spectroscopy coupled with chemometric analysis was used to identify and quantify coumarin (CMR) and ethyl vanillin (EVA) adulterations in pure vanilla extracts. Forty samples adulterated with CMR (0.25–10 ppm) and forty with EVA (0.25–10%) were prepared from pure vanilla extracts and characterized by MID-FTIR spectroscopy to develop chemometric models. Additionally, six commercial vanilla samples were analyzed. A soft independent modeling of class analogy (SIMCA) model was developed to identify and classify the purity from EVA-adulterated or CMR-adulterated samples. Prediction models for CMR or EVA content were developed using the principal component regression (PCR), partial least squares with single y-variables (PLS1), and with multiple y-variables (PLS2) algorithms. Moreover, the predictions of the best quantification chemometric model were compared with the results of a high-performance liquid chromatography-diode array detector (HPLC-DAD) method to evaluate the accuracy of the prediction. The PLS1 algorithm had better performance using 3 and 8 factors for EVA and CMR, respectively. The SIMCA model showed 100% recognition and rejections rates. The results demonstrate that adulteration of pure vanilla with EVA and CMR could be successfully predicted by the developed technique.
KW - Adulteration
KW - Chemometrics
KW - Coumarin
KW - Ethyl vanillin
KW - MID-FTIR
KW - Vanilla extracts
UR - http://www.scopus.com/inward/record.url?scp=85059911820&partnerID=8YFLogxK
U2 - 10.1016/j.talanta.2019.01.033
DO - 10.1016/j.talanta.2019.01.033
M3 - Artículo
C2 - 30771933
SN - 0039-9140
VL - 197
SP - 264
EP - 269
JO - Talanta
JF - Talanta
ER -