|Scherm, Harold - UNIV OG GEORGIA|
Submitted to: International Rhizoctonia Symposium
Publication Type: Abstract Only
Publication Acceptance Date: August 4, 2008
Publication Date: August 20, 2008
Citation: Copes, W.E., Scherm, H. 2008. Risk of Rhizoctonia Web Blight Development on Container-Grown Azalea. International Rhizoctonia Symposium 20-22 August 2008, Berlin (d) p.35. Technical Abstract: Rhizoctonia web blight, caused by binucleate Rhizoctonia spp., is an annual problem in the southern United States on container-grown azaleas (Rhododendron spp.) that receive daily irrigation. Disease progress was assessed weekly from mid-May to early October in blocks of nursery-grown plants at four locations in both 2006 and 2007. Disease severity was assessed by scoring each plant (>395) per block and by more detailed counts of the number of blighted leaves on subsets of 15 randomly selected plants per block. Disease onset occurred from mid-July to mid-August. Disease severity peaked between late August and mid-September, after which it declined due to defoliation of affected leaves and regrowth of new, uninfected leaves. Based on the relative increase in the log-transformed number of infected leaves per plant from disease onset to the peak of the disease progress curve, weekly assessment periods were classified as having rapid (>10% increase), intermediate (0 to 10%), or slow (<0%) disease progress. Three-day moving averages (MAs) of various weather variables were calculated, and lagged values (by 5 days) of the MAs were used in an attempt to predict these disease progress periods. Of the periods assessed as slow disease progress, 92.3% (24 of 26) met at least one of the following criteria for the lagged MAs: min. temperature <20'C, max. temperature >35'C, avg. temperature >28'C, or avg. vapor pressure deficit <2.5 hPa. One or more of these same criteria were met in only 3 of 16 (18.5%) assessment periods with rapid disease progress, indicating that periods with rapid vs. slow disease progression could be distinguished reasonably well based on weather. However, weather variables were not useful in separating periods with either rapid or slow disease progress from intermediate progress. Thus, weather variables might be most useful when used in a negative prognosis approach to predict disease risk as being "not low" or "not high".