Cercospora leaf spot, caused by the fungus Cercospora beticola, is a major fungal sugar beet disease worldwide and the cause of significant yield losses. The disease is most successfully countered by the introduction of genetic tolerance into elite sugar beet hybrids. To this end, breeding programs require high quality biological assays allowing discrimination of minor differences between plants within a segregating population. In this study, we describe the successful implementation of image analysis software in the bioassays for quantification of necrotic lesions at different stages of the C. beticola infection process, allowing selection on minor phenotypic differences during the sugar beet breeding process for C. beticola resistance. In addition, we developed a real-time PCR assay for the quantification of C. beticola pathogen biomass in infected beet canopy. We show that the use of both techniques, even in an early stage of infection, fine-tunes current bioassays, allowing more accurate and efficient selection of resistant breeding material.