Title: Partial least squares models for hyperspectral contaminant detection Authors
Submitted to: Near Infrared Spectroscopy International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: June 30, 2005
Publication Date: March 1, 2007
Citation: Lawrence, K.C., Windham, W.R., Park, B. 2007. Partial least squares models for hyperspectral contaminant detection. Proc. 12th International Conf. Near Infrared Spectroscopy. p.595-603. Technical Abstract: The United States of America food supply is one of the safest in the world. However, it is not free of pathogens. For the poultry industry, the Food Safety Inspection Service (FSIS) has regulatory responsiblity for food safety and has established a hazard analysis, critical control point system (HACCP) to reduce the number of pathogens in poultry products. The HACCP system requires meat-processing companies to identify critical control points (CCP) in their system and provide control to reduce hazards at the CCP. The objective of the paper was to investigate the use of broad-spectrum multivariate models with hyperspectral data for the detection of fecal contaminants on poultry carcasses.