Modelling the daily progress of light leaf spot epidemics on winter oilseed rape (Brassica napus), in relation to Pyrenopeziza brassicae inoculum concentrations and weather factors
Ecological Modelling(2002)
Abstract
The progress of light leaf spot (Pyrenopeziza brassicae) epidemics on winter oilseed rape was monitored in 1998/99 and 1999/2000 at Rothamsted, and weather factors and P. brassicae ascospore concentrations were recorded daily. The data sets, which consisted of numbers of ‘apparently healthy’ leaves, leaves with P. brassicae sporulation and dead leaves, were analysed using a structured population model with four compartments to investigate the effects of presence of P. brassicae inoculum (ascospores and conidiospores) and weather factors on the progress of light leaf spot on winter oilseed rape leaves. The model consists of ordinary differential or delay-differential equations to describe the rates of change per unit time in numbers of healthy susceptible leaves, infected leaves with no sporulation, leaves with sporulation, dead leaves (the four compartments) and the length of the latent period (which is temperature-dependent). The model allows for production of new susceptible leaves and leaf birth rate is assumed to be linearly dependent on temperature. The model incorporates an infection criterion depending on temperature and leaf wetness duration (expressed as rain duration). Rates of transition between the four compartments are related to rates of infection of ‘susceptible leaves’, sporulation of ‘infected leaves’ to produce ‘sporulating leaves’ and death of leaves from these three compartments. Parameter values were estimated by fitting the model to the data sets. The model fitted the disease progress data equally well in both seasons. The model fitting suggested that disease progress could be described only if both ascospore and conidiospore numbers were included. When either of the parameters representing the rates of infection by ascospores or conidiospores was eliminated, the model did not fit the data well. The sum of the model outputs for the first two leaf compartments was compared to the recorded numbers of ‘apparently healthy’ leaves; the fit to the data was better in 1999/2000 than in 1998/99. An assumption that the leaf birth rate changed around the time stem extension began (GS 2,0) improved the fit of the model. Seasonal variations in temperature had a large effect on the length of the latent period, which increased when mean daily temperatures were less than 5°C.
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Key words
Pyrenopeziza brassicae,Model,Inoculum,Weather factors,Infection criterion,Latent period
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