|QIN, JIANWEI - University Of Maryland|
|Chao, Kuanglin - Kevin Chao|
|KANG, SUKWON - National Academy Of Agricultural Science|
Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/5/2010
Publication Date: 1/18/2011
Citation: Qin, J., Chao, K., Kim, M.S., Kang, S., Jun, W. 2011. Detection of organic residues on poultry processing equipment surfaces by LED-induced fluorescence imaging. Applied Engineering in Agriculture. 27(1):153-161.
Interpretive Summary: 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. This study demonstrated that LED-induced fluorescence imaging technique is capable of detecting organic residues on stainless steel poultry processing equipment surfaces. High-power blue LEDs can excite organic residues on stainless steel surfaces to generate fluorescence emission spectra. Samples of common chicken residues 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 samples were determined. Multivariate data analysis was performed to differentiate the organic residues from the stainless steel 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. Development of such portable and sensitive image detection devices will provide poultry processors with useful tools to help improve operation efficiency and reduce cross-contamination risks by minimizing the presence of organic residues on processing equipment surfaces.
Technical Abstract: Organic residues on equipment surfaces in poultry processing plants can generate cross- contamination and increase the risk of unsafe food for consumers. This research was aimed to investigate the potential of LED-induced fluorescence imaging technique for rapid inspection of stainless steel processing equipment surfaces for the presence of organic residues. High-power blue LEDs with a spectral output at 410 nm were used as the excitation source for a line-scanning hyperspectral imaging system. Samples of common chicken residues 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. LED-induced fluorescence characteristics of the samples were determined. PCA (principal component analysis) was performed to analyze fluorescence spectral data. Two SIMCA (soft independent modeling of class analogy) models were developed to differentiate the organic residues from the stainless steel surfaces. Classification accuracies using 2-class (‘stainless steel’ and ‘organic residue’) and 4-class (‘stainless steel’, ‘fat’, ‘blood’, and ‘feces’) SIMCA models were 100% and 97.5%, respectively. Optimal selections for a single band and a band-pair for use in rapid residue detection were identified by correlation analysis. The single-band approach using the selected wavelength of 666 nm generated some false negative errors for chicken blood detection. Two-band ratio images using 503 and 666 nm (F503/F666) demonstrated great potential for detecting various chicken residues on stainless steel surfaces. This wavelength pair can be adopted for developing a LED-based hand-held fluorescence imaging device for inspecting poultry processing equipment surfaces.