Inspection of citrus canker is crucial due to its fast spread, high damage potential, and massive impact on export and domestic trade. This research was aimed to develop a prototype for real-time citrus canker detection. An inspection module was developed on a one-line commercial fruit sorting machine. Twenty tungsten halogen spotlights coupled with an aluminum dome painted with white diffuse paint provided reflectance illumination to the fruits in the detection chamber. The camera unit was a two-band spectral imaging system, which mainly consisted of a beamsplitter, two bandpass filters with central wavelengths at 730 and 830 nm, and two identical monochrome cameras. Using an exposure time of 10 ms, the imaging system can capture narrowband images without blurring from samples moving at a speed of 5 fruits/5. Spatial resolution of the acquired images was 2.3 pixels/mm. Real-time image processing and classification algorithms were developed based on a two-band ratio approach (i.e., R830/R730). The system was tested using 360 grapefruits with normal surface, canker lesions, and other peel diseases and defects. The overall classification accuracy was 95.3%, demonstrating that the methodology as well as the hardware and the software are effective and suitable for real-time citrus canker detection. Greasy spot, melanose, and sooty mold could generate false positive errors for the fruits without canker. The current system setup was limited to a single perspective view of the fruits. Future work will be conducted with an emphasis on whole surface inspection of each fruit. (C) 2011 Elsevier Ltd. All rights reserved.