An automated poultry carcass inspection system will help the poultry processing industry to provide better chickenproducts for the consumer while minimizing potential economic losses. The objective of this research was to investigate thepotential of a color-based sensing technique suitable for rapid automated inspection for wholesomeness of chickens in thevisible region. Spectra, in the range of 400 to 867 nm, of veterinarian-selected carcasses, 400 wholesome and332 unwholesome, were collected from a high-speed kill line using a visible/near-infrared spectrophotometer system.CIELUV color differences characterizing wholesome and unwholesome chicken samples were calculated as a simple distanceformula and used to classify individual samples. Results showed that the greatest color differences occurred for wavebandcombinations at (508 nm, 426 nm), (560 nm, 426 nm), and (640 nm, 420 nm). Full-spectrum classification achieved accuraciesof 85%, 86%, 84%, and 82% for wholesome validation samples, wholesome testing samples, unwholesome validationsamples, and unwholesome testing samples, respectively. Using the (560 nm, 426 nm) waveband combination, classificationaccuracies of 91%, 92%, 90%, and 90% were achieved for wholesome validation samples, wholesome testing samples,unwholesome validation samples, and unwholesome testing samples, respectively. The potential of using CIELUV colordifferences to differentiate between wholesome and unwholesome chickens was demonstrated, and the straightforwardcalculation involved suggest that the method is suitable for rapid automated online sorting of chicken carcasses.