DETECTION OF ERWINIA AMYLOVORA IN ORCHARDS USING QUANTITATIVE PCR AND LATERAL-FLOW IMMUNOGRAPHY

Disease forecasting models that predict flower infection risk are routinely used to decide the necessity and timing of fire blight control products.
Model optimization could improve growers’ decision-making and reduce avoidable controversial antibiotic applications.
Current models measure climatic and host phenological parameters, but continue to rely upon assumptions of pathogen inoculum presence.
Simple methods that can deliver accurate measurements of pathogen inoculum potential by monitoring populations in specific orchards would potentially avert unnecessary applications of control products.
We evaluated a lateral-flow immunographic strip (Ea AgriStrip, Bioreba, Rheinach, Switzerland) and quantitative PCR (qPCR) for detection of E. amylovora on asymptomatic flowers with artificial pathogen inoculation and under natural disease pressure.
Both methods have the advantage of rapid detection without culturing the pathogen.
While qPCR consistently detected E. amylovora in orchards throughout the flowering period, the immunoassay was less sensitive but simpler to use and had the advantage of delivering results within 15 minutes.
Results indicate that immunoassay methods offer a conservative estimation of pathogen inoculum potential corresponding to realistic need for application of control products.

XII International Workshop on Fire Blight

A. Braun-Kiewnick, A. Lehmann, B. Duffy, T. Dreo, M. Ravnikar, V.O. Stockwell

apple, real-time PCR, quantification, Erwinia amylovora

https://doi.org/10.17660/ActaHortic.2011.896.7