Modelling aeciospore release, dispersal and disease transmission to inform wheat rust management

Bueno Sancho, Vanessa (2020) Modelling aeciospore release, dispersal and disease transmission to inform wheat rust management. Doctoral thesis, University of East Anglia.

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Abstract

Wheat rust pathogens have been threatening agriculture all through history and they currently cause big economic loses every year. Investigating how these pathogens are able to spread and the key aspects of host-pathogen dynamics is vital for the design of appropriate control strategies. Two of the most damaging pathogens that require more careful monitoring are Puccinia graminis tritici (Pgt), that causes wheat stem rust, and Puccinia striiformis f. sp. tritici (Pst), cause of wheat yellow rust. Here, I have studied the process of aeciospore dispersal for Pgt, beginning with aeciospore release. Aeciospore release was recorded using high-speed videography and the velocity of ejection was estimated. Aeciospores are observed to release in clusters to achieve greater distances and their ejection is not affected by the temperatures tested here (5-37oC). Humidity is the key factor in aeciospore release, and it leads to their increase in volume, which was also measured in this thesis. A model of how this occurs is also proposed here. The dispersal process of Pgt aeciospores is also investigated, by evaluating the number of aeciospores that can be produced in barberry bushes. A Gaussian Plume model is used to predict how far aeciospores can travel, including real-time weather data gather using an API. This model was included into a user-friendly website to make the model accessible to the widest demographic. This tool can help identify the barberry bushes that present a higher risk and thus prioritise them for careful monitoring. Finally, the dynamics of Pst population in the UK at a field level is studied here. To do so, I developed a quick method for genotyping Pst-infected wheat samples collected from the field to determine which race they belong to. Using this method, I analysed samples collected all through the wheat growing season (December-June) for two consecutive years (2015-16 and 2016-17). Results indicate that one race (Warrior -) has become predominant in the UK and that seasonality for different races is observed. However, the presence of Pst races in one season was not indicative of prevalence of the same race in following seasons. In summary, this thesis provides tools to improve wheat rust management, both for stem and yellow rust at different levels. First, by trying to predict Pgt aeciospore release and dispersal to avoid future epidemics and secondly, with a quick genotyping method that can lower the costs of yellow rust surveillance.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Biological Sciences
Depositing User: Nicola Veasy
Date Deposited: 06 Oct 2021 15:16
Last Modified: 06 Oct 2021 15:16
URI: https://ueaeprints.uea.ac.uk/id/eprint/81582
DOI:

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