Identification of animal species in ground meat mixtures by multivariate analysis of isoelectric focusing protein profiles

The present work investigates the possibility of constructing a multivariat e calibration model to predict the composition of ground meat with respect to animal species, based on intensity profiles from isoelectric focusing of water-soluble proteins in mixtures of ground meat. Samples containing vari ous amounts of beef, pork and turkey meat were analyzed by isoelectric focu sing in immobilized pH-gradients. The gels were photographed and the images transferred to a digital format. The digital images were processed in orde r to reduce background and optimize signal strength. Resulting gel profiles were analyzed by multivariate re,regression allowing the determination of sample composition with prediction errors close to 10%.