Sclerotinia sclerotiorum is a pathogenic fungus that infects around 400 species of host plants. Stem rot disease caused by this fungus is economically disastrous for Brassica napus cultivators in Sweden. Due to the lack of disease resistant cultivars, disease management has been solely dependent on fungicide application. The current disease prediction models are not scientifically accurate and take into account factors such as weather, previous disease incidence, and conomic effects which often result in unnecessary and excessive use of fungicides by cultivators. Real-Time Polymerase Chain Reaction has proven to be the fastest, most accurate and reliable technique for detecting plant pathogens as it gives an idea about disease severity by measuring pathogen concentration in environmental samples. Reproducible and able qPCR assays have the potential of being the main principle on which more scientifically accurate plant disease prediction and management models an be developed. The aim of this study was to validate a previously established qPCR assay to detect S. sclerotiorum. An absolute quantification experiment was performed by using plasmid DNA cloned with a target gene as template. Further, three different qPCR machines were compared to make a plausible conclusion regarding their sensitivity and efficiency in detecting minuscule amounts of DNA from the environment. While a solid conclusion could not be reached regarding the sensitivity of each of these machines, this study pointed out some basic trends about each machine that may help researchers in selecting the most efficient qPCR system when working with detection of plant pathogens.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-20265 |
Date | January 2021 |
Creators | Patil, Neeraj |
Publisher | Högskolan i Skövde, Institutionen för biovetenskap |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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