Skip to main content
ARS Home » Research » Publications at this Location » Publication #252010

Title: Detection of organic residues on food processing equipment surfaces by spectral imaging method

item QIN, JIANWEI - University Of Maryland
item Jun, Won
item Kim, Moon
item Chao, Kuanglin - Kevin Chao

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 4/1/2010
Publication Date: 4/5/2010
Citation: Qin, J., Jun, W., Kim, M.S., Chao, K. 2010. Detection of organic residues on food processing equipment surfaces by spectral imaging method [abstract]. International Society for Optics and Photonics Symposium. 7676:76760801-76760803.

Interpretive Summary:

Technical Abstract: Organic residues remaining attached to equipment surfaces during poultry processing operations can potentially generate cross-contamination and thus increase the risk of unsafe food for consumers. Current pre-operational sanitation monitoring mainly relies on human visual inspection, which is subjective, labor-intensive, and time-consuming. There is a need to develop a rapid, accurate, and non-invasive method for monitoring the processing line for the food industry. One goal of the presentation is to illustrate a fluorescence imaging technique for rapid inspection of organic residues on poultry processing equipment surfaces. High-power blue LEDs with a spectral output at 410 nm were used as the excitation source for a line-scanning hyperspectral imaging system. Common chicken residue samples including fat, blood, and feces from ceca, colon, duodenum, and small intestine were prepared on stainless steel sheets. Fluorescence emission images were acquired from 120 samples (20 for each type of residue) in the wavelength range of 500-700 nm. Fluorescence characteristics of the tested samples were determined. Multivariate data analysis was performed to differentiate organic residues from stainless steel poultry processing equipment surfaces. Key wavelengths for differentiating residues from stainless steel were identified for use in developing LED-based hand-held fluorescence imaging devices for inspection of poultry processing equipment. This presentation will present the algorithms used to identify the key wavelengths to detect organic residues on poultry processing equipment surfaces, experimental results that provide the scientific basis of the device, and identification of components, needed to build a commercially-usable device.