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.