Aerial Drone-based Phenotyping and GWAS of Emergence and Late Blight Resistance in Tetraploid Potato

Solanum tuberosum L. is the world’s most important vegetable crop, and the development of improved cultivars by breeding is paramount for global food security. The efficacy of genomic prediction models accelerating breeding programs and genome-wide association studies (GWAS) depends on large, precise phenotypic training sets. These are often associated with inhibitory costs. However, recent advances in drone-based phenotyping and image analysis offer high-throughput low-cost alternatives that may facilitate the study of plant-associated phenotypes. Drone-based phenotypic data of potato plant emergence and late blight resistance collected in separate field plots at 2-6 temporal points across a growing season with a red-green-blue camera with replicates across 2-3 growing seasons were used in GWAS. The phenotypic output included 6,262 phenotypic observations of emergence and 6,972 observations of late blight resistance. 2,576 clones in an emergence panel and 1,520 clones in a late blight resistance panel were genotyped for 8,731 markers using a custom SNP array. The analysis yielded four significant quantitative trait loci (QTLs) for late blight resistance, aligning with known Rpi-gene clusters on chromosomes 4, 5, 7, and 9, and three significant minor-effect QTLs underpinning emergence. The rediscovery of previously known QTLs for late blight resistance demonstrates the reliability of the approach. The genomic regions flanking the emergence associations harbor several candidate genes, encoding proteins involved in plant growth and development, stress response, and compound trafficking pathways. Here, we demonstrate that GWAS in combination with high-throughput remote phenotyping technology can produce meaningful, precise results in commercial breeding populations of tetraploid potatoes.