Peer-Reviewed Journal Details
Mandatory Fields
Ofarrell, M; Sheridan, C; Lewis, E; Flanagan, C; Kerry, JF; Jackman, N
Ieee Sensors Journal
Online optical fiber sensor for detecting premature browning in ground beef using pattern recognition techniques and reflection spectroscopy
Optional Fields
artificial neural network backpropagation learning food processing industry multilayer perceptrons online color measurement optical fiber sensors premature browning detection principal component analysis self organizing maps spectral classification weighted distance fuzzy logic class membership COLOR CLASSIFICATION QUALITY SYSTEM FOOD
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.
Grant Details