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ARS Home » Research » Publications at this Location » Publication #153587


item Park, Bosoon
item Lawrence, Kurt
item Windham, William
item Smith, Douglas

Submitted to: Journal of Food Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/21/2005
Publication Date: 6/22/2005
Citation: Park, B., Lawrence, K.C., Windham, W.R., Smith, D.P. 2005. Performance of hyperspectral imaging system for poultry surface contaminant detection. Journal of Food Engineering.

Interpretive Summary: Identification and separation of poultry carcasses contaminated by feces and/or ingesta are very important steps for the federal poultry safety inspection program to protect consumers from a potential source of food poisoning when pathogens enter the food chain. Development of accurate and reliable science-based inspection tools to ensure safe production of poultry processing is an important issue for the Hazard Analysis, Critical Control Point (HACCP) compliance. We developed a state-of-the-art hyperspectral imaging system for the detection of fecal and ingesta contaminants on the surface of broiler carcasses. The system provides potential science-based surface contaminant detection suitable for use in poultry slaughter houses. This paper reports the performance of a hyperspectral imaging system including several different models to identify fecal and ingesta contaminants. With high accuracy, the system separated contaminated carcasses (feces and ingesta) from non-contaminated carcasses during poultry processing.

Technical Abstract: A hyperspectral imaging system demonstrated potential to detect surface fecal and ingesta contaminants on poultry carcasses. Hyperspectral data were analyzed with four pre-processing methods considering two parameters: calibration and 20-nm spectral smoothing. A band-ratio image-processing algorithm, using band equation including 2-wavelengths (565 nm / 517 nm) and 3-wavelengths (576 nm - 616 nm)/(529 nm - 616 nm) equations, was then applied to each pre-processed method that included applying a background mask to the ratio of images, and finally applying a fecal threshold. Based on a high accuracy of 96.2% for predicting surface contaminants and significantly less false positives on the 64 birds measured, the calibrated smooth method was considered the best pre-processing method for contaminant detection. In conjunction with an appropriate image-processing algorithm, the hyperspectral imaging system is an effective technique for the identification of fecal and ingesta contaminants on poultry carcasses. Specifically, band ratio with 2-wavelength equation performed very well with 96.4% accuracy and 147 false positives for detecting both feces (duodenum, ceca, and colon) and ingesta contaminants.