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Multivariate fatty acid and fatty alcohol profile of mullet bottarga
Author(s) -
Scano Paola,
Rosa Antonella,
Mereu Simone,
Piras Cristina,
Atzeri Angela,
Dessi M. Assunta
Publication year - 2010
Publication title -
european journal of lipid science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 94
eISSN - 1438-9312
pISSN - 1438-7697
DOI - 10.1002/ejlt.201000321
Subject(s) - mugil , polyunsaturated fatty acid , mullet , docosahexaenoic acid , eicosapentaenoic acid , food science , chemistry , fatty acid , gas chromatography , multivariate statistics , tuna , chromatography , biology , biochemistry , fish <actinopterygii> , mathematics , fishery , statistics
Mullet bottarga is a food delicacy obtained by salting and drying the intact roes of mullet ( Mugil spp.). The fatty acid and fatty alcohol compositions of different samples of bottarga were studied by means of gas chromatography (GC) and multivariate analysis (MVA). High percentages of beneficial n‐3 PUFA, among which docosahexaenoic acid (DHA) (22:6 n‐3 , 11.9%) and eicosapentaenoic acid (EPA) (20:5 n‐3 , 8.6%), were detected. Differences in the concentrations of unsaturated FA and FAL were observed among samples, while saturated components showed little variations. On the other hand, the total contents of saturated, monounsaturated and polyunsaturated components were similar. The principal component analysis loadings bi‐plot showed that n‐6 PUFA concentrations were inversely correlated to those of n‐3 PUFA, except for DHA that showed no correlations. Correlations between FAL concentrations were also observed. Furthermore, integrating our GC data with those from the literature on mullet and tuna bottarga, the MVA showed that both bottarga typologies exhibit a similar trend in the FA distribution and that 16:0 and 16:1 n‐7 FA are the variables with the highest discriminant power. In this work, we demonstrated the usefulness of the application of MVA to GC data to extract meaningful information otherwise hidden in the amount of data.