Start Date: Jan 23, 2011
End Date: Jul 04, 2011
The Environmental Microbial and Food Safety Laboratory (EMFSL) multispectral imaging system will be fine-tuned to meet the rigors of use in a processing plant. Detection algorithms for both the EMFSL Vis/NIR spectrophotometric system and the multispectral imaging system will be upgraded so that they are able to automatically compensate for changes in environmental conditions (seasonal, geographical, etc.) and feed affecting the poultry being processed. An automated control system that improves the integration of EMFSL detection systems with commercial operations will be developed. The EMFSL poultry inspection systems and a system being developed by ARS in Athens, Georgia to detect fecal contamination on poultry carcasses will be integrated. Development, evaluation, validation and refinement of techniques for detecting feces and defects on fruits and vegetables will be continued. Problems of implementing new systems that use EMFSL techniques, or integrating these techniques with existing systems in commercial use or under development in other ARS facilities, will be addressed. The laboratory results where reflectance and fluorescence imaging methods were successfully used to detect feces on apples will be the basis for the design of more practical systems. The results obtained for apples will be used to develop systems to detect feces on other fresh and fresh-cut produce. Portable/wearable imaging devices will be designed to assist inspectors by highlighting areas with thin contaminants, much of which would not be easily spotted by the naked eye. Optimal wavelengths for detection using visually enhanced direct viewing (e.g., binoculars), reflectance imaging techniques, or fluorescence imaging techniques will be established. These results will be used to design, construct, and validate inexpensive portable/wearable devices. The devices will be designed to detect the presence of animal fecal matter and then will be expanded to include detection of other organic materials that can harbor pathogen growth. Strategic inspection models in which data are shared among multiple inspectors using portable devices and integrated with wireless image/voice communication capabilities will also be developed. Results from the development of apple inspection systems will be used to develop systems to detect feces on other fresh and fresh-cut produce.