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Using Modelling to Optimise the Use of Biological Control Agents Against Soil-Borne Plant Pathogens


Type

Thesis

Change log

Authors

Mitchell, Sarah Joanne 

Abstract

There is considerable interest in the use of biological control agents as a control strategy against plant pathogens. However, significant variability in their success at pathogen suppression across field trials has resulted in them often not being seen as commercially viable. This thesis uses mathematical modelling to explore the interactions between a soil- borne biocontrol agent, a soil-borne pathogen, and the roots of a host plant. Understanding the dynamics of these organisms in more detail can allow us to optimise the use of biological control agents.

We construct a model that focuses on the roots of a plant and whether they are infected by a pathogen or colonised by a biocontrol agent, as well as including any free-living pathogen and biocontrol agent in the surrounding soil. Although this model can be used across multiple systems, this thesis focuses on modelling the infection of winter wheat by Gaeumannomyces graminis var. tritici and suppression by the biocontrol agent 2,4-DAPG fluorescent Pseudomonas spp. Parameter values are obtained for the model through fitting it to data from this system.

Application timing and amount of application were both found to affect the ability for a biocontrol agent to suppress a pathogen. Including a break crop into a simulation had a negative impact on both the pathogen and biocontrol agent, suggesting that combining multiple strategies for epidemic suppression may not always be effective. Planting a crop with even spaces between plants, or in rows with 12cm between each row, was found to reduce epidemic severity more than if rows were spaced further apart for the first year of an epidemic. However, large-scale dispersal of free-living material between growing seasons from agricultural machinery reduced any benefit of specific spatial arrangements of a crop in the second year of an epidemic. Aggregation of the pathogen and biocontrol agent were found to affect epidemic severity, with the greatest reduction from a highly aggregated pathogen and a uniformly distributed biocontrol agent. We suggest that a greater focus on optimising application, as well as a detailed understanding of how the spatial dynamics of a biocontrol agent and pathogen can affect this application, may enhance the success of biocontrol agents and allow them to be seen as a viable control strategy.

Description

Date

2021-04-30

Advisors

Cunniffe, Nik J

Keywords

Computational biology, Mathematical biology

Qualification

Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge
Sponsorship
Biotechnology and Biological Sciences Research Council (1804491)
BBSRC