IDENTIFICATION OF SALMONELLA-INOCULATED BEEF USING A PORTABLE ELECTRONIC NOSE SYSTEM

Autor:	Sundar Balasubramanian, Suranjan Panigrahi, M. J. Marchello, Julie S. Sherwood, Catherine M. Logue
Rok vydání:	2005
Předmět:	education.field_of_study Electronic nose business.industry Population Cold storage Pattern recognition Quadratic classifier Linear discriminant analysis Microbiology Cross-validation Artificial intelligence Raw meat education business Bootstrapping (statistics) Mathematics
Zdroj:	Journal of Rapid Methods and Automation in Microbiology. 13:71-95
ISSN:	1745-4581 1060-3999
Popis:	A commercially available Cyranose-320TM (Cyrano Sciences, Pasadena, CA) conducting polymer–based electronic nose system was used to analyze the volatile organic compounds emanating from vacuum-packaged beef strip loins (Longissimus Lamborum) that were repackaged simulating retail store conditions and stored at 4 and 10°C after inoculating them with Salmonella Typhimurium. Two statistical techniques, i.e., linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA), were used to develop classification models from the collected sensor signals. The models were developed for the captured signals, which were scaled and not scaled. The performances of the developed models were validated by two different methods, leave-one-out cross validation and bootstrapping. The developed models classified the meat samples based on the Salmonella population into “No Salmonella” (microbial counts
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::964cc97a92ff74a926baac28b0f654ae https://doi.org/10.1111/j.1745-4581.2005.00011.x Zobrazit plný text záznamu Plný text ve formátu PDF