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This paper examines the design of an optical fiber sensor that monitors ground beef online, as it cooks, in order to determine the quality of the meat; in particular, if premature browning has occurred. The experimental work involved cooking fresh meat and meat that has been stored in a freezer for, one week, one month and three months, and recording the reflected spectra and temperature during the cooking process in order to develop a classifier, based on pattern recognition techniques that can determine premature browning and the degree to which the meat has been cooked. A comparison of this sensor is made with traditional research methods of detecting premature browning, to demonstrate that it would be more commercially viable as an online solution. |
