title: Detection of adulteration in fresh and frozen beefburger products by beef offal using mid-infrared ATR spectroscopy and multivariate data analysis.
abstract: A series of authentic and offal-adulterated beefburger samples was produced. Authentic product (36 samples) comprised either only lean meat and fat (higher quality beefburgers) or lean meat, fat, rusk and water (lower quality product). Beef offal adulterants comprised heart, liver, kidney and lung. Adulterated formulations (46 samples) were produced using a D-optimal experimental design. Fresh and frozen-then-thawed samples were modelled, separately and in combination, by a classification (partial least squares discriminant analysis) and class-modelling (soft independent modelling of class analogy) approach. With the former, 100% correct classification accuracies were obtained separately for fresh and frozen-then-thawed material. Separate class-models for fresh and frozen-then-thawed samples exhibited high sensitivities (0.94 to 1.0) but lower specificities (0.33-0.80 for fresh samples and 0.41-0.87 for frozen-then-thawed samples). When fresh and frozen-then-thawed samples were modelled together, sensitivity remained 1.0 but specificity ranged from 0.29 to 0.91. Results indicate a role for this technique in monitoring beefburger compliance to label.
authors.affiliation: Teagasc Food Research Centre Ashtown, Department of Food Chemistry and Technology, Ashtown, Dublin 15, Ireland.
authors.forename: Ming
authors.initials: M
authors.lastname: Zhao
authors.forename: Gerard
authors.initials: G
authors.lastname: Downey
authors.forename: Colm P
authors.initials: CP
authors.lastname: O'Donnell
mesh_terms: D000818:Animals; D002417:Cattle; D016002:Discriminant Analysis; D063427:Food Quality; D061353:Food Storage / Q000379:methods*; D005615:Freezing; D016018:Least-Squares Analysis; D008461:Meat Products / Q000032:analysis*; D015999:Multivariate Analysis; D013055:Spectrophotometry, Infrared
keywords: Adulteration; Authenticity; Beefburger; Class-modelling; Discrimination; Offal