Evaluation of Near-Infrared and Mid-Infrared Spectroscopy for the Determination of Routine Parameters in Chinese Rice Wine

Journal of Food Processing and Preservation

Volumn 41, Issue 3, 2017, Pages

  Shen, Fei ^a   Wu, Qifang ^a   Wei, Yingqi ^a   Liu, Xiao ^a   Tang, Peian ^a  

^a NANJING UNIVERSITY OF FINANCE AND ECONOMICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FOOD PRODUCTS; INFORMATION USE; INFRARED SPECTROSCOPY; LEAST SQUARES APPROXIMATIONS; PH; REGRESSION ANALYSIS; SPECTROSCOPIC ANALYSIS; WINE;

CHEMOMETRIC METHOD; COMPARATIVE STUDIES; CONTENT DETERMINATION; MID-INFRARED SPECTROSCOPY; NONDESTRUCTIVE DETECTION; PARTIAL LEAST SQUARES REGRESSION MODELS; QUALITY PARAMETERS; SPECTROSCOPIC METHOD;

INFRARED DEVICES;

EID: 84994461700     PISSN: 01458892     EISSN: 17454549     Source Type: Journal    
DOI: 10.1111/jfpp.12952     Document Type: Article

References (38)

1. Bellon-Maurel, V. and Mcbratney, A. 2011. Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils – Critical review and research perspectives. Soil Biol. Biochem. 43, 1398–1410.
2. Chen, L.J., Xing, L. and Han, L.J. 2009. Quantitative determination of nutrient content in poultry manure by near infrared spectroscopy based on artificial neural networks. Poultry Sci. 88, 2496–2503.
3. Contreras, A., Hidalgo, C., Henschke, P.A., Chambers, P.J., Curtin C. and Varela, C. 2014. Evaluation of non-saccharomyces yeasts for the reduction of alcohol content in wine. Appl. Environ. Microb. 80, 2623–2632.
4. Cozzolino, D., Cynkar, W., Shah, N. and Smith, P. 2011. Technical solutions for analysis of grape juice, must, and wine: the role of infrared spectroscopy and chemometrics. Anal. Bioanal. Chem. 401, 1475–1484.
5. Cozzolino, D., Dambergs, R.G., Janik, L., Cynkar, W.U. and Gishen, M. 2006. Analysis of grapes and wine by near infrared spectroscopy. J. Near Infrared Spec. 14, 279–289.
6. Cozzolino, D., Smyth, H.E. and Gishen, M. 2003. Feasibility study on the use of visible and near-infrared spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins. J. Agric. Food Chem. 51, 7703–7708.
7. Cuadrad, M.U., Castro, M.D.L., Juan, P.M.P. and Gémez-Nieto, M.A. 2005. Comparison and joint use of near infrared spectroscopy and Fourier transform mid infrared spectroscopy for the determination of wine parameters. Talanta 66, 218–224.
8. Dambergs, R., Gishen, M. and Cozzolino, D. 2015. A review of the state of the art, limitations, and perspectives of infrared spectroscopy for the analysis of wine grapes, must, and grapevine tissue. Appl. Spectrosc. Rev. 50, 261–278.
9. Drivelos, S.A. and Georgiou, C.A. 2012. Multi-element and multi-isotope-ratio analysis to determine the geographical origin of foods in the European Union. TrAC Trends Anal. Chem. 40, 38–51.
10. Filho, P.A.C. 2009. Rapid determination of sucrose in chocolate mass using near infrared spectroscopy. Anal. Chim. Acta 631, 206–211.
11. Fragoso, S., Aceña, L., Guasch, J., Busto, O. and Mestres, M. 2011. Application of FT-MIR spectroscopy for fast control of red grape phenolic ripening. J. Agric. Food Chem. 59, 2175–2183.
12. Friedel, M., Patz, C.D. and Dietrich, H. 2013. Comparison of different measurement techniques and variable selection methods for FT-MIR in wine analysis. Food Chem. 141, 4200–4207.
13. Garde-Cerdan, T., Lorenzo, C., Alonso, G.L. and Salinas, M.R. 2012. Review of the use of near infrared spectroscopy to determine different wine parameters: discrimination between wines. Curr. Bioact. Compd. 8, 353–369.
14. Ginjom, I., D'Arcy, B., Caffin, N. and Gidley, M. 2011. Phenolic compound profiles in selected Queensland red wines at all stages of the wine-making process. Food Chem. 125, 823–834.
15. Gishen, M., Dambergs, R. G., & Cozzolino, D. 2005. Grape and wine analysis – Enhancing the power of spectroscopy with chemometrics. Aust. J. Grape Wine Res. 11, 296–305.
16. Herrmann, S., Mayer, J., Michel, K. and Ludwig, B. 2009. Predictive capacity of visible-near infrared spectroscopy for quality parameter assessment of compost. J. Near Infrared Spectrosc. 17, 289–301.
17. Kokaly, R.F. and Clark, R.N. 1999. Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote Sens. Environ. 67, 267–287.
18. Kelebek, H., Selli, S., Canbas, A. and Cabaroglu, T. 2009. HPLC determination of organic acids, sugars, phenolic compositions and antioxidant capacity of orange juice and orange wine made from a Turkish cv. Kozan. Microchem. J. 91, 187–192.
19. Niu, X.Y., Shen, F., Yu, Y.F., Yan, Z., Xu, K., Yu, H.Y. and Ying, Y.B. 2008. Analysis of sugars in Chinese rice wine by Fourier transform near-infrared spectroscopy with partial least-squares regression. J. Agric. Food Chem. 56, 7271–7278.
20. Ohira, S.I., Kuhara, K., Shigetomi, A., Yamasaki, T., Kodama, Y., Dasgupta, P.K. and Toda, K. 2014. On-line electrodialytic matrix isolation for chromatographic determination of organic acids in wine. J. Chromatogr. A 1372, 18–24.
21. Oliveira, G.A., Castilhos, F., Renard, C.M.G.C. and Bureau, S. 2014. Comparison of NIR and MIR spectroscopic methods for determination of individual sugars, organic acids and carotenoids in passion fruit. Food Res. Int. 60, 154–162.
22. Patz, C.D., Blieke, A., Ristow, R. and Dietrich, H. 2004. Application of FT-MIR spectrometry in wine analysis. Anal. Chim. Acta 513, 81–89.
23. Que, F., Mao, L.C., Zhu, C.G. and Xie, G.F. 2006. Antioxidant properties of Chinese yellow wine, its concentrate and volatiles. LWT – Food Sci. Technol. 39, 111–117.
24. Shen, F., Li, F., Liu, D., Xu, H., Ying, Y. and Li, B. 2012. Ageing status characterization of Chinese rice wines using chemical descriptors combined with multivariate data analysis. Food Control 25, 458–463.
25. Shen, F., Niu, X.Y., Yang, D.T., Ying, Y.Y., Li, B.B., Zhu, G.Q., Wu, J. 2010. Determination of amino acids in Chinese rice wine by Fourier transform near-infrared spectroscopy. J. Agric. Food Chem. 58, 9809–9816.
26. Shen, F., Ying, Y.B., Li, B.B., Zheng, Y.F., & Hu, J.G. 2011. Prediction of sugars and acids in Chinese rice wine by mid-infrared spectroscopy. Food Res. Int. 44, 1521–1527.
27. Shen, F., Yang, D.T., Ying, Y.B., Li, B.B., Zheng, Y.F. and Jiang, T. 2012. Discrimination between Shaoxing wines and other Chinese rice wines by near-infrared spectroscopy and chemometrics. Food Bioprocess Technol. 5, 786–795.
28. Smit, I., Pfliehinger, M., Binner, A., Großmann, M., Horst, W. J. and Löhnertz, O. 2014. Nitrogen fertilisation increases biogenic amines and amino acid concentrations in Vitis vinifera var. Riesling musts and wines. J. Sci. Food Agric. 94, 2064–2072.
29. Soares, R.D., Welke, J.E., Nicolli, K.P., Zanus, M., Caramão, E.B., Manfroi, V. and Zini, C.A. 2015. Monitoring the evolution of volatile compounds using gas chromatography during the stages of production of Moscatel sparkling wine. Food Chem. 183, 291–304.
30. Wang, Y.Q., Ye, D.Q., Zhu, B.Q., Wu, G.F., & Duan, C.Q. 2014. Rapid HPLC analysis of amino acids and biogenic amines in wines during fermentation and evaluation of matrix effect. Food Chem. 163, 6–15.
31. Wold, S., Sjostrom, M. and Eriksson, L. 2001. PLS-regression: a basic tool of chemometrics. Chemometr Intell. Lab. Syst. 58, 109–130.
32. Wu, Z.Z., Xu, E.B., Long, J., Wang, F., Xu, X.M., Jin, Z.Y. and Jiao, A.Q. 2015a. Use of attenuated total reflectance mid-infrared spectroscopy for rapid prediction of amino acids in Chinese rice wine. J. Food Sci. 80, C1670–C1679.
33. Wu, Z.Z., Long, J., Xu, E.B., Wu, C.S., Wang, F., Xu, X.M., Jin, Z.Y. and Jiao, A.Q. 2015b. Application of FT-NIR spectroscopy and FT-IR spectroscopy to Chinese rice wine for rapid determination of fermentation process parameters. Anal. Methods 7, 2726–2737.
34. Wu, Z.Z., Xu, E.B., Long, J., Zhang, Y.J., Wang, F., Xu, X.M., Jin, Z.Y. and Jiao, A.Q. 2015c. Monitoring of fermentation process parameters of Chinese rice wine using attenuated total reflectance mid-infrared spectroscopy. Food Control 50, 405–412.
35. Wu, Z.Z., Xu, E.B., Long, J., Pan, X.W., Xu, X.M., Jin, Z.Y. and Jiao, A.Q. 2016. Comparison between ATR-IR, Raman, concatenated ATR-IR and Raman spectroscopy for the determination of total antioxidant capacity and total phenolic content of Chinese rice wine. Food Chem. 194, 671–679.
36. Yu, H.Y., Ying, Y.B., Fu, X.P. and Lu, H.S. 2006. Quality determination of Chinese rice wine based on Fourier transform near infrared spectroscopy. J. Near Infrared Spectrosc. 14, 37–44.
37. Zeaiter, M., Roger, J.M. and Bellon-Maurel, V. 2005. Robustness of models developed by multivariate calibration. Part II: The influence of pre-processing methods. TrAC Trends Anal. Chem. 24, 437–445.
38. Zhu, X.G., Li, G.Y. and Shan Y. 2015. Prediction of Cadmium content in brown rice using near-infrared spectroscopy and regression modelling techniques. Int. J. Food Sci. Technol. 50, 1123–1129.