Integrated electronic nose system for detection of Salmonella contamination in meat

A novel metal oxide based electronic nose system was designed and developed to detect Salmonella contamination in packaged meat (beef). This system contained an array of metal oxide detectors and custom made electronics for acquiring olfactory signature of the volatile organic compounds in the headspace of the meat packages produced by detector arrays. The acquired signals were processed using three wavelet packet transforms (WPT) for simultaneous noise reduction and compression. The coefficients of wavelet packets were used as features for developing statistical classification models using bootstrapped linear and quadratic discriminant analysis techniques. The average total classification accuracies for classifying Salmonella contaminated meat samples were higher than 82% with highest average accuracy of about 88%.