Open Collections

Reich, Jonathan

University of British Columbia

Many economically important agricultural plant pathogens are spread on air currents; as a result, monitoring the air for fungal spores could help predict epidemics and therefore prevent losses due to disease. This thesis describes the coupling of air sampling and molecular identification and quantification methods to both (i) characterize the air fungal microbiome, with an emphasis on regionally important plant pathogens, and (ii) describe and predict the occurrence of a specific pathogen and disease in southern Alberta: the fungus Sclerotinia sclerotiorum, causal agent of white mould in dry bean. For the first objective, Illumina amplicon sequencing of the internal transcribed spacer (ITS1) region was performed on air samples collected across Alberta. This approach was able to simultaneously detect many airborne plant pathogens, in contrast to currently employed methods that only detect a single pathogen. Furthermore, there was some evidence that read abundance was reflective of biological abundance, since certain fungal genera were found in greater levels in samples collected in their host crops compared to nonhost crops. For the second objective, quantitative PCR (qPCR) was used to quantify ascospores of S. sclerotiorum from spore samplers placed in commercial dry bean fields in Alberta, Manitoba, and Ontario over four growing seasons. In-field weather stations collected a range of variable data, and disease surveys were performed to assess white mould levels. Disease incidence was most significantly associated with dry bean cultivar, with Pinto beans having, on average, the greatest disease levels compared to Great Northern, Yellow, Red, and Black. Due to the wide range of disease intensity observed, disease was not associated with ascospore levels or most environmental variables. Daily ascospore counts were not correlated strongly with most environmental variables but were strongly correlated with the numbers of ascospores released the previous day. This research lays the groundwork for future work in multi-pathogen identification using new DNA sequencing technologies. Furthermore, it provides insights into the dynamics underlying ascospore dispersal and the development of white mould epidemics in dry bean crops.

Text; Dataset

2023-04-19

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/84330

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/