|Authors: ||V. Philion, M. Trapman|
|Keywords: ||apple, pear, blossom, epidemiology, simulation, logistic regression |
Fire blight caused by Erwinia amylovora is a sporadic disease that can cause major damage and important tree loss in many apple and pear growing regions.
Many infections occur when suitable weather conditions are met during bloom period.
Timely applications of antibiotics or biocontrol agents during this period can dramatically reduce disease severity.
Consequently, a number of forecasting systems have been developed to help to predict disease outbreaks based on these criteria.
Unfortunately, these systems can generate false positive warnings, because the inoculum pressure in orchards was not sufficient to cause disease, the models could overestimate pathogen growth, or the cultivar was less susceptible.
Conversely, models can also generate false negative prognoses under conditions considered marginal for bacterial growth or when localised wetness events cannot be recorded adequately.
The RIMpro-erwinia model addresses some of these problems by including recent findings on bacterial growth and infection through a simulation approach.
The software calculates bacterial growth and the possibility of infection on each individual daily flower cohorts.
Epiphytic bacterial growth calculations are based on a nonlinear model that accounts for low temperature growth.
Flower infection is predicted based on population size during wetness events.
Flower cohorts not meeting the colonization and infection criteria are discarded from calculations as they age.
Preliminary data collected since 2007 suggest that this approach improves blight prediction compared to Cougarblight and MaryblytTM models.
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