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Headspace Gas Chromatography‐Mass Spectrometry and Electronic Nose Analysis of Volatile Compounds in Canned Alaska Pink Salmon Having Various Grades of Watermarking
Author(s) -
Oliveira Alexandra C.M.,
Crapo Charles A.,
Himelbloom Brian,
Vorholt Carey,
Hoffert Jennifer
Publication year - 2005
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/j.1365-2621.2005.tb11486.x
Subject(s) - electronic nose , mass spectrometry , chemistry , gas chromatography–mass spectrometry , chromatography , gas chromatography , digital watermarking , linear discriminant analysis , mathematics , artificial intelligence , computer science , statistics , image (mathematics)
Volatiles in canned pink salmon, produced from different degrees of skin watermarked raw material and stored for 2 and 9 mo, were characterized and compared using static headspace gas chromatography analysis coupled to a mass spectrometer (SHGCMS). Sulfur‐containing compounds comprised 30% to 50% of the total volatiles and tended to decrease with increasing degrees of skin watermarking, and dimethyl sulfide was the most abundant compound of this class of molecules. A few alcohols, aldehydes, ketones, and furans were also identified. Forward stepwise general discriminant analysis (FSGDA) was used to investigate prediction models based on degree of skin watermarking. The 2‐ and 9‐mo models using SHGCMS showed 92.5% and 93.75% correct classifications, respectively. The ability of the Cyranose 320, a hand‐held electronic nose (EN), to differentiate these grades of watermarking in the canned samples was also tested. EN analysis using FSGDA resulted in models with 90% and 92.5% correct classifications for the 2‐ and 9‐mo samples, respectively. Overall, results indicate that the watermarking grades studied are not readily distinguishable from each other by either method of analysis.