Development of Digital Image Analysis Protocol for High-Throughput Phenotyping of Fruiting Traits in Vitis

Matthew D. Clark , University of Minnesota, St. Paul, MN
Alexander Quentin Susko , University of Minnesota, St. Paul, MN
Soon Li Teh , University of Minnesota, St. Paul, MN
Genetic mapping of fruit traits in grapevine (Vitis spp.) is important for enabling marker assisted breeding (MAB) that combines disease resistance and fruit quality traits for cultivar development.  The development of image analysis protocols with ImageJ and MATLAB software can expedite the phenotyping of traits that are destructive in nature, difficult to measure by hand, or rely on numerous replicates for increased precision.  Digital image phenotyping allows samples to be analyzed when convenient and maximizes the number of data points from a single image.  Measurements were made on berry color and berry size and correlated with hand measurements.  Observations were made on single clusters for branched shoulder and bunch density.  The traits were genetically mapped in a F1 population of 120 individuals using genotype by sequencing markers.  Signficant QTL for fruit color attributes were mapped to linkage group (LG) 2 from 54-63.2 cM.  A significant QTL for the presence of a branched shoulder was mapped to LG 18 with a LOD score of 3.2.