Characterization of commercial chili sauce varieties according to their chemical and physical properties using chemometric methods
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Abstract
Different varieties of chili sauces that are commercially available in Malaysia were randomly collected and their physical and chemical parameters were determined. Initially, pattern recognition techniques were applied in order to categorize the chili sauce varieties. With the aid of principal component analysis and cluster analysis, it is possible to visualize the clustering tendencies of the different varieties of chili sauces where four major clusters, namely chili sauces, general chili ketchups, hot/garlic added ketchups, and Thai ketchups have been successfully partitioned. Color and taste parameters have been found to be the most discriminating variables among them. With the K-nearest neighbor technique, a good prediction of chili sauces’ categories could be achieved. With appropriate customer preference survey, it would be possible to map these characteristics to the preferences. This would certainly help producers of chili sauces in upgrading the quality and taste of their products.
Keywords
Characterization Chemometric Chili Sauces Ketchup Cluster analysis K-nearest neighbors Multivariate Pattern recognition Principal component analysisNotes
Acknowledgments
This work was financially supported by the Vote F UM.AC/UPDiT (Geran PJP)/2004/F0186/2004A from the University of Malaya.
References
- 1.P.J. Molnar, Food Qual. Prefer. 6, 185–190 (1995)CrossRefGoogle Scholar
- 2.M.E. Otero-Losada, Physiol. Behav. 78(3), 415–425 (2001)CrossRefGoogle Scholar
- 3.E. Vangdal, Acta Agric. Scand. 35, 41–47 (1985)CrossRefGoogle Scholar
- 4.P.J. Fellers, Food Technol. 75, 68–75 (1991)Google Scholar
- 5.F.G. Mitchell, G. Mayer, W. Biasi, Acta Hortic. 297, 617–625 (1991)Google Scholar
- 6.R.G.L. de Guevara, J.E. Pardo-Gonzalez, J. Agric. Food Chem. 44, 2049–2052 (1996)CrossRefGoogle Scholar
- 7.L.A. Berrueta, R.M. Alonso-Salces, K. Heberger, J. Chromatogr. A 1158, 196–214 (2007)CrossRefGoogle Scholar
- 8.M.B. Kiziloz, O. Cumhur, M. Kilic, Food Hydrocolloids 23, 1596 (2009)CrossRefGoogle Scholar
- 9.Malaysian Standard MS 1120:2004, Sauces—sampling and test methods (First Revision) (2004)Google Scholar
- 10.G.L. Miller, Anal. Chem. 31, 426 (1959)CrossRefGoogle Scholar
- 11.Malaysian Standard MS 532:1995. Specification for red chili sauce (Second Revision) (1995)Google Scholar
- 12.N. Takada, P.E. Nelson, J. Food Sci. 48, 1460–1462 (1983)CrossRefGoogle Scholar
- 13.ASTA, Official analytical method of the American spice trade association, 2nd edn. (ASTA, USA, 1986)Google Scholar
- 14.J. Sall, A. Lehman, L. Ceighton, A guide to statistics and data analysis using JMP ® and JMP IN ® software (SAS Institute Inc., Thomson LearningTM, Duxbury, 2001)Google Scholar
- 15.K.R. Beebe, R.J. Pell, M.B. Seasholtz, Chemometrics: a practical guide (Wiley, New York, 1998)Google Scholar
- 16.K.V. Mardia, J.T. Kent, J.M. Bibby, Multivariate analysis (Academic Press, London, 1979), pp. 213–254Google Scholar
- 17.P.M. Padin, R.M. Pena, S. Garcia, R. Iglesias, S. Barro, C. Herrero, Analyst 126, 97–103 (2001)CrossRefGoogle Scholar
- 18.W.R. Dillon, Multivariate analysis (Wiley, New York, 1984), pp. 157–208Google Scholar
- 19.J. Riu, R. Bro, Chemometrics Intell Lab Syst 65(1), 35–49 (2003)CrossRefGoogle Scholar
- 20.A.A. Wahab, MARDI Res. Bull. 12(3), 290–297 (1984)Google Scholar
- 21.B.G. Green, Chemesthesis: pungency as a component of flavor. Trends Food Sci. Technol. 7(12), 415–420 (1996)CrossRefGoogle Scholar