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Effects of Environmental Factors on Development of Pyrenopeziza brassicae (Light Leaf Spot) Apothecia on Oilseed Rape Debris

April 2001 , Volume 91 , Number  4
Pages  392 - 398

T. Gilles , B. D. L. Fitt , and M. J. Jeger

First and second authors: Institute of Arable Crops Research, Rothamsted, Harpenden, Herts AL5 2JQ, U.K.; and third author: Wye College, University of London, Ashford, Kent TN25 5AH, U.K.


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Accepted for publication 10 January 2001.
ABSTRACT

The development of Pyrenopeziza brassicae (light leaf spot) apothecia was studied on petiole debris from artificially infected oilseed rape leaves incubated at temperatures from 6 to 22°C under different wetness regimes and in 16 h light/8 h dark or continuous darkness. There was no significant difference between light treatments in numbers of apothecia that developed. Mature apothecia developed at temperatures from 5 to 18°C but not at 22°C. The rate of apothecial development decreased as temperature decreased from 18 to 5°C; mature apothecia were first observed after 5 days at 18°C and after 15 days at 6°C. Models were fitted to estimates of the time (days) for 50% of the maximum number of apothecia to develop (t1; model 1, t1 = 7.6 + 55.8(0.839)T) and the time for 50% of the maximum number of apothecia to decay (t2; model 2, t2 = 24.2 + 387(0.730)T) at temperatures (T) from 6 to 18°C. An interruption in wetness of the petiole debris for 4 days after 4, 7, or 10 days of wetness delayed the time to observation of the first mature apothecia for ≈4 days and decreased the number of apothecia produced (by comparison with continuous wetness). A relationship was found between water content of pod debris and electrical resistance measured by a debris-wetness sensor. The differences between values of t1 predicted by model 1 and observed values of t1 were 1 to 9 days. Model 2 did not predict t2; apothecia decayed more quickly under natural conditions than predicted by model 2.


Additional keywords: ascoma development , ascospores , Cylindrosporium concentricum , exponential model , forecasting .

The American Phytopathological Society, 2001