Assessment of hyperspectral imaging system for poultry safety inspection

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 (565/517) performed very well with 96.4% accuracy and 147 false positives for detecting both feces (duodenum, ceca, colon) and ingesta contaminants.