Multivariate curve resolution (MCR) methods are proposed to improve the analysisof volatile components of an Iranian rice sample (Domsiah) by headspace sampling coupled to gas chromatography-mass spectrometry. A total of 31 components was identified using similarity searches between mass spectra and mass spectrometry database. Then extended multivariate curve reso lution-alternating least squares (MCR-ALS) by applying proper constraints is used to obtain pure elution and mass spectral profiles for the components present in each peak cluster. The resolved components were identified by similarity searches using the NIST mass database and their percentage were calculated for qualita- tive and quantitative analysis, respectively. The number ofidentified components was extended to 82 by applying the MCR-ALS techniques. The main identified volatile chemicals that were f ound in an Iranian rice sample (Domsiah) were; nonanal (18.22%), hexanal (14.33%), 2-benzoyl-6,7-dimethoxy-4-methylidene-2H-1,3-benzothiazine (7.81%), epilophodione (7.023%), and 1-methyl-4-(1-methylethenyl)cyclohexene (6.61%).
