MODELING DOSE-RESPONSE RELATIONSHIPS IN BIOLOGICAL-CONTROL - PARTITIONING HOST RESPONSES TO THE PATHOGEN AND BIOCONTROL AGENT

Breeding plants to improve the effectiveness of biocontrol agents is a promising approach to enhance disease suppression by microorganisms. Differences in biocontrol efficacy among cultivars suggest there is ge netic variation for this trait within crop germplasm. The ability to q uantify host differences in support of biological control is influence d by variation in host response to the pathogen and the dose of pathog en and biocontrol agent applied to the host. To assess the contributio n of each of these factors to successful biocontrol interactions, we m easured disease over a range of pathogen (Pythium) and biocontrol agen t (Bacillus cereus UW85) inoculum doses. We fit dose-response models t o these data and used model parameter estimates to quantify host diffe rences in response to the pathogen and biocontrol agent. We first inoc ulated eight plant species separately with three species of Pythium an d evaluated three dose-response models for their ability to describe t he disease response to pathogen inoculum level. All three models fit w ell to at least some of the host-pathogen combinations; the hyperbolic saturation model provided the best overall fit. To quantify the host contribution to biological control, we next evaluated these models wit h data from a tomato assay, using six inbred tomato lines, P. torulosu m, and UW85. The lowest dose of pathogen applied revealed the greatest differences in seedling mortality among the inbred lines, ranging fro m 40 to 80%. The negative exponential (NE) pathogen model gave the bes t fit to these pathogen data, and these differences corresponded to mo del parameter values, which quantify pathogen efficiency, of 0.023 and 0.091. At a high pathogen dose, we detected the greatest differences in biocontrol efficacy among the inbred lines, ranging from no effect to a 68% reduction in mortality. The NE pathogen model with a NE bioco ntrol component, the NE/NE biocontrol model, gave the best fit to thes e biocontrol data, and these reductions corresponded to model paramete r values, which quantify biocontrol efficiency, of 0.00 and 0.038, res pectively. There was no correlation between the host response to the p athogen and biocontrol agent for these inbred lines. This work demonst rates the utility of epidemiological modeling approaches for the study of biological control and lays the groundwork to employ manipulation of host genetics to improve biocontrol efficacy.