Development of Detection Systems for the Sporangia of Peronospora Destructor

A monoclonal antibody that recognises components of the wall of sporangia of Peronospora destructor was raised. Tests using spores of higher fungi and other species of mildew demonstrated the specificity of the monoclonal. The antibody was used to develop lateral flow devices for sporangia of P. destructor. A competitive lateral flow format was developed which could detect onion downy mildew sporangia. Five-microliter gold anti-mouse IgM solution pre-mixed with 10 μl of P. destructor monoclonal antibody (EMA 242) proved the optimal concentration for detection of sporangia of P. destructor when applied to sample pads of lateral flow devices. Limits of approximately 500 sporangia of P. destructor could be detected by the absence of a test line on the lateral flow device within test samples. Using a scanning densitometer improved the sensitivity of detection. Further development and validation of the test is required if it is to be used for risk assessments of onion downy mildew in the field.

Field Evaluation of a Competitive Lateral-flow Assay for Detection of Alternaria brassicae in Vegetable Brassica Crops

On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.