Comparing Visual and Image Analysis Techniques to Quantify Fusarium Basal Rot Severity in Mature Onion Bulbs

Abstract

Development of resistant cultivars for Fusarium basal rot (FBR), a fungal disease caused by the soil-borne fungus Fusarium oxysporum f.sp. cepae (FOC), is a major breeding goal for onion breeding programs around the world. Currently, the selection of FBR-resistant bulbs is based on a visual interval or category scale, which is an entirely subjective method. This study aimed to develop an objective approach using digital image analysis to quantify symptom development in the basal plate of dormant bulbs. Digital image analyses were performed after artificially inoculating dormant bulbs of eighty-five United States Department of Agriculture (USDA) Allium cepa accessions with a virulent FOC isolate, ‘CSC-515’. An analysis with confocal microscopy identified bright blue–green autofluorescence from FOC-infected tissue, effectively differentiating diseased from healthy tissue. Visual scoring of the FBR symptom was aided by stereo fluorescence microscopic images captured using a green fluorescence protein dual filter to quantify accurately FBR severity in the basal plate tissue. An automatic stepwise image segmentation method was developed that was relatively more accurate than a visual estimation. This method exhibited comparable reliability and precision to visual scoring, but it tended to underestimate FOC infection. To our best knowledge, this is the first comprehensive study to investigate the potential use of image analysis as a viable alternative to conventional visual scoring for FBR symptom development. This method could be used for developing resistant cultivars for onion breeding programs in the near future.