Fine tuning artificial Rhizoctonia inoculation methods to improve disease pressure using DNA-based quantification.

Abstract

Rhizoctonia solani is a major pathogen plaguing sugar beet production. This pathogen causes crown and root rot leading to plant death and reduced yields. Many breeding efforts across the world use artificially inoculated disease nurseries to evaluate germplasm for resistance. These fields are typically in rotation with other crops and inoculated at a set rate to induce disease. The general assumption is that there is little to no Rhizoctonia in the soil, but by measuring the baseline pressure, we can accurately apply inoculum at an optimized rate. Understanding baseline disease pressure is critical for adjusting inoculum to achieve uniform disease pressure from year to year. In this study, we conducted an inoculum dosage curve experiment using commercial check varieties with six different application rates. This results from this trial will guide the optimization of inoculum application rate to ensure even uniform disease pressure across years. Soil samples were taken from this experiment, as well as from the site of the recurring USDA-ARS Fort Collins Rhizoctonia solani nursery, to quantify pre- and post-inoculation pathogen load. Using qPCR we can distinguish the levels of Rhizoctonia in the soil for different stages within our testing year as well as our crop rotation. Gaining information on the baseline levels of disease within our nurseries allows for more accurate selection and evaluation of germplasm for Rhizoctonia Crown and Root Rot resistance.