McNish, Ian2021-04-122021-04-122020-12https://hdl.handle.net/11299/219305University of Minnesota Ph.D. dissertation. 2020. Major: Applied Plant Sciences. Advisor: Kevin Smith. 1 computer file (PDF); 199 pages + 8 supplementary files.Plant diseases are often described as the interaction of a plant, a pathogen, and the environment. For a disease to develop, there must be a susceptible plant, a virulent pathogen, and an environment amenable to disease. This concept is useful to explain the presence or absence of a disease, but many important questions and ideas in plant pathology, plant genomics, plant phenomics, and plant cultivar development are also dependent on time. A pathogen population changes over time, by a process of selection, to defeat the resistances deployed in crop cultivars. The genetic architecture of disease resistance changes as a plant grows from a seedling to an adult plant, matures, and dies. The visual and spectral signature of plant stress and disease also changes as the plant grows and the disease develops. Finally, plant breeders attempt to limit the damage diseases cause by quickly improving plant populations and deploying disease resistant plant cultivars. The dimension of time has been well-explored in some areas of plant science such as gene expression, but time is often overlooked in plant breeding, quantitative genetics, and phenomics. Crown rust, caused by the fungal pathogen Puccinia coronata f. sp. avenae Erikss. (Pca), is a dynamic and devastating disease of cultivated oat (Avena sativa L.). In this research, I found that the North American Pca population has gained many virulences over the past thirty years and that the Pca isolates collected in recent years are capable of defeating a surprisingly high number of crown rust resistance genes. I found that the genetic architecture of crown rust resistance changed throughout the growing season. Many resistance loci were detected briefly, sometimes just for a couple of days, and few loci were detected at many points in time. I found that the spectral signature of disease and plant stress changed throughout the season and that the predictive value of the collected data was greatest for adult plants before senescence. Finally, I found that quantitative resistance to crown rust could be rapidly improved in an oat population, but the race-specificity of that resistance was difficult to determine. If plant breeders understand how time influences the composition of pathogen populations, the observations they make, the analyses they perform, and the technologies they develop, then they will be more capable of improving complex plant traits like disease resistance.enOatPlant breedingPlant genomicsPlant pathologyPlant phenomicsQuantitative geneticsThesis or Dissertation