Date of Award

Summer 8-23-2019

Level of Access

Open-Access Thesis

Language

English

Degree Name

Master of Science (MS)

Department

Biological Sciences

Advisor

Seanna Annis

Second Committee Member

David Yarborough

Third Committee Member

Jianjun Hao

Additional Committee Members

Ek Han Tan

Abstract

Blueberry rust caused by Thekopsora minima is a common disease in wild blueberry (Vaccinium angustifolium) and other Vaccinium genera. Understanding the spore dispersal pattern and disease cycle of fungal pathogens in wild blueberry is crucial for the development of a more efficient disease management program. Molecular assays for rapid detection and quantification of Thekopsora minima were developed to be incorporated with a spore trap sampling method and weather data collection to examine spore dispersal pattern and production in three different fields: Blueberry Hill Farm in Jonesboro, East Machias, and Spring Pond in Deblois, Maine, in three years 2014, 2015 and 2017. A total of fifteen primer sets for PCR assays and one set of six Loop-mediated isothermal amplification assay (LAMP) primers developed from the internal transcribed spacer (ITS) regions of T. minima were tested for specificity and sensitivity towards T. minima DNA. There was one primer set (TMITS2F and TMITS2GR) that was specific to rust in both PCR and qPCR assay and could detect down to about 20 copies of DNA. Lower DNA level detection (about 2 copies) is possible but often nonreproducible. The LAMP assays results were found to be not reproducible. The qPCR with the two primers TMITS2F and TMITS2GR was used to quantify rust spores in the spore trap tape DNA extracted by a Phenol-Chloroform method. Weather factors including temperature and leaf wetness duration (LWD) were collected using weather stations and button loggers placed in the fields. Calculated weekly sums of LWD and optimal temperature (17oC to 22oC) hour for uredinia production (TH) and weekly averages of other weather factors were analyzed with the weekly spore count numbers using a linear mixed model with the random effects from weeks, fields and years. There was a significant correlation between spore counts using a compound microscope and the qPCR method. There was no clear pattern of temperature, TH and LWD effects on spore numbers quantified by qPCR or microscopy. A linear mixed model (LMM) for disease severity in 2017 testing the effects of log of spore number quantified by qPCR assays, average temperature, LWD, and the random effects of weeks and fields, found that both temperature and LWD had significant negative effects on the disease severity (pT. minima. This relationship could be due to the time required for spores to germinate and cause disease. The proposed preliminary models for disease severity and weather variables, as well as the relationship between the spore number and disease severity need to be tested with data from more years and fields to confirm the results. Nevertheless, the establishment of the molecular assay and predicting models for spore number in this study could be a useful tool for future research on disease management and development of a disease warning strategy for T. minima in wild blueberry.

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