The Malaysian Journal of Analytical Sciences Vol 12 No 1 (2008): 210 – 216

 

 

CLASSIFICATION OF CHILLI SAUCES: MULTIVARIATE PATTERN RECOGNITION USING SELECTED GCMS RETENTION TIME PEAKS OF CHILLI SAUCE SAMPLES

 

Low Kah Hin¹, Sharifuddin M. Zain¹, Mohd. Radzi Abas¹, Mustafa Ali Mohd²_.

 

¹Department of Chemistry, Faculty of Science,

²Shimadzu-UMMC Centre for Xenobiotics Studies, University of Malaya Medical Centre,

University Malaya, 50603, Kuala Lumpur, Malaysia

 

Abstract

As a preliminary work on the possibility of separating classes of chili sauces based on taste or customer preferences, organic compounds from different kinds of chili sauces of various brands were separated and analyzed by gas chromatography/mass spectrometry (GC/MS). It was found that these organic compounds do form a basis for separation of  different types of sauces.  The similarity and dissimilarity of chromatograms due to the organic composition of the chili sauces were explored by multivariate pattern recognition techniques based on cluster analysis (CA) and principal component analysis (PCA). Both CA and PCA results exhibit four linearly separable classes, namely general sauces, hot sauces, sauces with benzoic acid and sauces with garlic. It was concluded that by using chosen retention peaks in the chromatograms of various sauce samples as multivariate features, CA and PCA can be successfully used to reveal the natural clusters existing in chili sauces according to their organic composition.

 

Keywords: Chemometrics; Chili sauce; Principal component analysis; PCA; Cluster analysis

 

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