Prediction of Phyllosticta citricarpa using an hourly infection model and validation with prevalence data from South Africa and Australia

Magarey, Roger D., Hong, Seung Cheon, Fourie, Paul H., Christie, David N., Miles, Andrew K., Schutte, Gerhardus C. and Gottwald, Timothy R. (2015) Prediction of Phyllosticta citricarpa using an hourly infection model and validation with prevalence data from South Africa and Australia. Crop Protection, 75 104-114. doi:10.1016/j.cropro.2015.05.016


Author Magarey, Roger D.
Hong, Seung Cheon
Fourie, Paul H.
Christie, David N.
Miles, Andrew K.
Schutte, Gerhardus C.
Gottwald, Timothy R.
Title Prediction of Phyllosticta citricarpa using an hourly infection model and validation with prevalence data from South Africa and Australia
Formatted title
Prediction of Phyllosticta citricarpa using an hourly infection model and validation with prevalence data from South Africa and Australia
Journal name Crop Protection   Check publisher's open access policy
ISSN 0261-2194
Publication date 2015-09-01
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.cropro.2015.05.016
Open Access Status
Volume 75
Start page 104
End page 114
Total pages 11
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Collection year 2016
Language eng
Formatted abstract
An hourly infection model was used for a risk assessment of citrus black spot (CBS) caused by Phyllosticta citricarpa. The infection model contained a temperature-moisture response function and also included functions to simulate ascospore release and dispersal of pycnidiospores. A validation data set of 18 locations from South Africa and Australia was developed based on locations with known citrus black spot prevalence. An additional 67 sites from Europe and the United States with unknown prevalence were also identified. The model was run for each location with 9 years of hourly weather data from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) database. The infection scores for the sites with known prevalence where ranked and a threshold for suitability in a given year was derived from the average score of the lowest ranked moderate prevalence site. The results of the simulation confirm that locations in Florida were high risk while most locations in California and Europe were not at risk. The European location with the highest risk score was Andravida, Greece which had 67% of years suitable for ascosporic infection but only 11% of years were suitable for pycnidiosporic infection. There were six other sites in Europe that had frequency of years suitable for ascosporic infection greater than 22% including Pontecagnano, Italy; Kekrya, Greece; Reggio Calabria, Italy; Cozzo Spadaro, Italy; Messina, Italy; and Siracusa, Italy. Of these six sites only Reggio Calabria had a frequency of years suitable for pycnidiosporic infection greater than 0%. These six sites are predicted to have prevalence similar or less than Messina, South Africa, i.e. low and occasional. Other sites in Europe would best be described as likely to have no prevalence based on very low simulated scores for both spore types. Although Andravida had a similar risk of infection to moderate locations in South Africa there was a difference in the seasonality of infection periods. The ascosporic infection period score was similar between the two sites, but Andravida had a much lower pycnidiosporic infection score in the middle of the period of fruit susceptibility than Addo, South Africa. In Europe favorable climatic conditions are discontinuous, i.e., there is a low frequency of suitable seasons. This raises doubts about the ability of the pathogen to persist at a location and cause disease loss when favorable seasons reoccur. These results suggest that Europe is less suitable for CBS than suggested by an earlier study produced by the European Food Safety Authority using a similar model. The findings from our model simulations suggest that only a few isolated locations in the extreme south of Europe are likely to have a low to marginal risk of P.citricarpa establishment.
Keyword Modeling
Risk analysis
Validation
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Alliance for Agriculture and Food Innovation
Official 2016 Collection
 
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