August
2008
, Volume
92
, Number
8
Pages
1,215
-
1,222
Authors
K. B. Duttweiler and
M. L. Gleason, Department of Plant Pathology, Iowa State University, Ames 50011;
P. M. Dixon, Department of Statistics, Iowa State University, Ames 50011;
T. B. Sutton, Department of Plant Pathology, North Carolina State University, Raleigh 27695;
P. S. McManus, Department of Plant Pathology, University of Wisconsin, Madison 53706; and
J. E. B. A. Monteiro, Department of Exact Sciences, ESALQ, University of São Paulo, Piracicaba, SP, Brazil
Affiliations
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RelatedArticle
Accepted for publication 28 April 2008.
Abstract
ABSTRACT
A warning system for sooty blotch and flyspeck (SBFS) of apple, developed in the southeastern United States, uses cumulative hours of leaf wetness duration (LWD) to predict the timing of the first appearance of signs. In the Upper Midwest United States, however, this warning system has resulted in sporadic disease control failures. The purpose of the present study was to determine whether the warning system's algorithm could be modified to provide more reliable assessment of SBFS risk. Hourly LWD, rainfall, relative humidity (RH), and temperature data were collected from orchards in Iowa, North Carolina, and Wisconsin in 2005 and 2006. Timing of the first appearance of SBFS signs was determined by weekly scouting. Preliminary analysis using scatterplots and boxplots suggested that cumulative hours of RH ≥ 97% could be a useful predictor of SBFS appearance. Receiver operating characteristic curve analysis was used to compare the predictive performance of cumulative LWD and cumulative hours of RH ≥ 97%. Cumulative hours of RH ≥ 97% was a more conservative and accurate predictor than cumulative LWD for 15 site years in the Upper Midwest, but not for four site years in North Carolina. Performance of the SBFS warning system in the Upper Midwest and climatically similar regions may be improved if cumulative hours of RH ≥ 97% were substituted for cumulative LWD to predict the first appearance of SBFS.
JnArticleKeywords
Additional keywords:disease forecasting, microclimate, ROC analysis
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© 2008 The American Phytopathological Society