Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5792418 | Meat Science | 2013 | 7 Pages |
The combination of 1H NMR lipid profiling with multivariate analysis was applied to differentiate irradiated and non-irradiated beef. Two pattern recognition chemometric procedures, stepwise linear discriminant analysis (sLDA) and artificial neural networks (ANNs), provided a successful discrimination between the groups investigated. sLDA allowed the classification of 100% of the samples into irradiated or non-irradiated beef groups; the same result was obtained by ANNs using the 1Â kGy irradiation dose as discriminant value suggested by the network. Furthermore, sLDA allowed the classification of 81.9% of the beef samples according to the irradiation dose (0, 2.5, 4.5 and 8Â kGy). 1H NMR lipid profiling, coupled with multivariate analysis may be considered a suitable and promising screening tool for the rapid detection of irradiated meat in official control of food.
⺠New techniques to detect the irradiation treatment of foods could be helpful. ⺠1H NMR lipid profiling may be considered a promising tool to detect irradiated beef. ⺠This approach could be developed as a procedure for the official control of food.