Fusarium head blight is a worldwide fungal disease of small cereal grains such as wheat that affects the yield, quality, and safety of food and feed products. The current study was implemented to develop more efficient methods for optically detecting Fusarium-damaged (scabby) kernels from normal (sound) wheat kernels. Through development of a high-power pulsed LED (green and red) inspection system, it was found that Fusarium-damaged and normal wheat kernels have different reflected energy responses. Two parameters (slope and r2) from a regression analysis of the green and red responses were used as input parameters in linear discriminant analysis models. The examined factors affecting accuracy were the orientation of the optical probe, the color contrast between normal and Fusarium-damaged kernels, and the manner in which one LED's response is time-matched to the other LED. Whereas commercial high-speed optical sorters are, on average, 50% efficient at removing mold-damaged kernels, this efficiency can rise to 95% or better under more carefully controlled, kernel-at-rest conditions in the laboratory. The current research on free-falling kernels has demonstrated accuracies (>90% for wheat samples of high visual contrast) that approach those of controlled conditions, which will lead to improvements in high-speed optical sorters.