Fusarium head blight (FHB) infection results in Fusarium damaged kernels (FDK) that normally reduce grain yield and quality. As the deoxynivalenol (DON) mycotoxin in FDK is toxic upon consumption, FDK is a major grading factor at Canadian grain terminals. The disease has recently caused severe economic losses in the wheat industry. Developing genetic resistance to FDK through improving resistance to Fusarium infection is essential to reduce losses of grain yield and quality. However, selecting for resistance and understanding the genetics depends on the assessment of FDK which has been a bottleneck as FDK is conventionally quantified by a human observer estimating the percentage visually. The conventional method is slow, labor-intensive, and innately prone to human error. Improving FHB resistance is in dire need of a fast and consistent FDK assessment technique to allow reliable screening, as well as enhancing the resolution of the genetic factors associated with FDK resistance. The wheat breeding and pathology programs at the the Swift Current Research and Development Centre-Agriculture and Agri-food Canada explored the application of the VibeQM3 image analyzer as a new alternative method of measuring FDK to limit subjectivity and increase throughput. The Vibe QM3, developed by Vibe Imaging Analytics, is a digital imaging platform which, with a custom developed calibration model, is capable of analyzing kernels by differentiating FDK from healthy kernels by utilizing 3,000 color pixels. A validation of the Vibe QM3 calibration model involved processing 21 wheat samples harvested from FHB inoculated nurseries that we subjected to FDK assessment using manual visual count and image analysis. The VibeQM3-estimated FDK was highly correlated with the manually scored FDK (r=0.91, P<0.001), which suggested that digital imaging is an FDK assessment alternative that will improve the consistency, accuracy, and effectiveness of FDK phenotyping in wheat breeding.