Simultaneous Spectrometric Determination of Caffeic Acid, Gallic Acid, and Quercetin in Some Aromatic Herbs, Using Chemometric Tools
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R2, and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918?18.055, 9.014?23.825, and 9.040?13.350 mg/g of dry sample, respectively.
Abstract
The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R2, and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918?18.055, 9.014?23.825, and 9.040?13.350 mg/g of dry sample, respectively.
참고문헌 (39)
- Diaz-Garcia, M. C., , Food Chem, 138, pp.938~ (2013)
- Belajova, E, , J. Food Nutr. Res, 51, pp.117~ (2012)
- Marti, R., , Food Chem, 169, pp.169~ (2015)
- Benkaci-Ali, F., , Chem. Nat. Comp, 47, pp.925~ (2012)
- Shamuratov, B. A., , Chem. Nat. Comp, 39, pp.597~ (2003)
- Pedroza, M. A., , CyTA-J. Food, 10, pp.225~ (2012)
- Boggia, R., , Food Chem, 140, pp.735~ (2013)
- Amelin, V. G., , J. Anal. Chem, 71, pp.82~ (2016)
- Barros, L., , Plant Foods Hum. Nutr, 67, pp.229~ (2012)
- De Paepe, D., , Food Chem, 136, pp.368~ (2013)
- Helmja, K., , Electrophoresis, 29, pp.3980~ (2008)
- Wang, Y., , Anal. Methods, 5, pp.6051~ (2013)
- Barbosa, S., , J. Agric. Food Chem, 68, pp.591~ (2020)
- Sakakibara, H., , Food Chem, 51, pp.571~ (2003)
- Rebwar, O. H., , J. Iran. Chem. Soc, 15, pp.1603~ (2018)
- Abbasi-Tarighat, M., , Food Chem, 138, pp.991~ (2013)
- Aguerssif, N., , J. Trace Elem. Med. Biol, 22, pp.175~ (2008)
- De Carvalho, B. M. A., , Food Chem, 174, pp.1~ (2015)
- Ivanovic, M., , Acta Chim. Slov, 63, pp.661~ (2016)
- Kachbi, A., , Curr. Anal. Chem, 6, pp.88~ (2010)
- Kavsek, D., , Acta Chim. Slov, 60, pp.375~ (2013)
- Divya, O., , J. Appl. Spectrosc, 80, pp.326~ (2013)
- Korany, M. A., , Spectrochim. Acta Part A: Mol. Biomol. Spectrosc, 143, pp.281~ (2015)
- Moghadam, M. R., , Spectrochim. Acta Part A: Mol. Biomol. Spectrosc, 135, pp.929~ (2015)
- Zolgharnein, J., , J. Anal. Chem, 70, pp.148~ (2015)
- Chanda, S., , J. Chemom, 33, pp.1~ (2019)
- De Jong, S, , Chemom. Intell. Lab. Syst, 18, pp.251~ (1993)
- Geladi, P., , Anal. Chim. Acta, 185, pp.1~ (1986)
- Meloun, M., , Analyst, 127, pp.433~ (2002)
- Wise, B. M., "Eigenvector Research", ~ (2006)
- Wold, S., , Chemom. Intell. Lab. Syst, 58, pp.109~ (2001)
- Cornell, J. A., "Experiments with Mixtures: Designs, Models, and the Analysis of Mixture Data", pp.1~ (2002), John Wiley, and Sons
- Ghasemi, J., , Anal. Chim. Acta, 510, pp.121~ (2004)
- Proestos, C., , Food Chem, 95, pp.664~ (2006)
- Wang, H., , Food Chem, 87, pp.307~ (2004)
- Bilyk, A., , J. Agric. Food Chem, 33, pp.226~ (1985)
- Lugast, A., , Acta Alim, 29, pp.345~ (2000)
- Justesen, U., , Food Chem, 73, pp.245~ (2001)
- Trichopoulou, A., , Food Chem, 70, pp.319~ (2000)