Submitted to: Journal of Food Process Engineering
Publication Type: Peer reviewed journal
Publication Acceptance Date: 6/18/2004
Publication Date: 8/1/2005
Citation: Park, B., Lawrence, K.C., Windham, W.R., Smith, D.P. 2005. Multispectral imaging system for fecal and ingesta detection on poultry carcasses. Journal of Food Process Engineering. 27(5):311-327. Interpretive Summary: Identification and separation of poultry carcasses contaminated by feces and/or ingesta are very important to protect the consumer from a potential source of food poisoning where pathogens can enter the food chain. Development of high speed and reliable science-based inspection systems to ensure safe production of poultry processing is an important issue for Hazard Analysis, Critical Control Point (HACCP) compliance. We developed a multispectral imaging system to detect fecal and ingesta contaminates on the surface of poultry carcasses. The system provides the basic engineering design suitable for use in poultry processing plants. This paper reports on the system components including an industrial-scale prototype, the real-time imaging software used for fecal detection, and the accuracy of the system. Overall the system was able to identify 96.8% of the fecal and ingesta contaminants.
Technical Abstract: A multispectral imaging system including a common aperture camera with three optical trim filters (515.4, 566.4 and 631 nm), which were selected by visible/NIR spectroscopy and validated by a hyperspectral imaging system, was developed for a real-time, on-line poultry inspection application. The algorithms developed by a hyperspectral imaging system were employed for multispectral image analysis to validate the accuracy of fecal and ingesta detection for real-time poultry processing. Multispectral imaging could be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses with a processing speed of approximately 251 msec or 3.99 frames/sec. The multispectral imaging system developed in this research could be used for real-time, on-line detection of fecal and ingesta contaminants on poultry carcasses. The overall accuracy to identify fecal and ingesta contaminates was 96.8% and the prediction accuracy to identify each contaminate were 92.4% for duodenum and 98% for ceca, colon, and ingesta. However, even though the system had high accuracy to detect fecal and ingesta contaminates, it identified 156 false contaminants on the 72 birds imaged. These false positive results must be reduced prior to implementing the system into the poultry processing line.