Modelling the progress of light leaf spot (Pyrenopeziza brassicae ) on winter oilseed rape (Brassica napus ) in relation to leaf wetness and temperature

A - Papers appearing in refereed journals

Papastamati, K., Welham, S. J., Fitt, B. D. L. and Gladders, P. 2001. Modelling the progress of light leaf spot (Pyrenopeziza brassicae ) on winter oilseed rape (Brassica napus ) in relation to leaf wetness and temperature. Plant Pathology. 50 (2), pp. 154-164. https://doi.org/10.1046/j.1365-3059.2001.00551.x

AuthorsPapastamati, K., Welham, S. J., Fitt, B. D. L. and Gladders, P.
Abstract

A compartmental model was developed to describe the progress with time of light leaf spot (Pyrenopeziza brassicae) on leaves of winter oilseed rape (Brassica napus) during the autumn in the UK. Differential equations described the transition between the four compartments: healthy susceptible leaves. infected symptomless leaves, sporulating symptomless leaves and leaves with necrotic light leaf spot lesions, respectively The model was fitted to data on the progress of light leaf spot on winter oilseed rape at a single site during the autumn of the 1990-1991 season. Model parameters were used to describe rates of leaf appearance, leaf death, infection by airborne ascospores (primary inoculum) and infection by splash-dispersed conidiospores (secondary inoculum). Infection was dependent on sufficient leaf wetness duration. The model also included delay terms for the latent period between infection and sporulation and the incubation period between infection and the appearance of necrotic light leaf spot lesions. This modified SEIR model formulation gave a reasonable fit to the experimental data. Sensitivity analysis showed that varying the parameter accounting for the rate of infection by ascospores affected the magnitude of the curves after the start of the epidemic, whilst including a parameter for conidiospore infection improved the fit to the data. Use of ascospore counts from different sites and different years showed variation in spore release patterns sufficient to affect model predictions.

KeywordsAgronomy; Plant Sciences
Year of Publication2001
JournalPlant Pathology
Journal citation50 (2), pp. 154-164
Digital Object Identifier (DOI)https://doi.org/10.1046/j.1365-3059.2001.00551.x
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or code424
507
445
513
Collaborative statistical investigations into biological processes
Quantitative comparative plant disease epidemiology
Output statusPublished
PublisherWiley
ISSN0032-0862

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