Open AccessA Degree-Day Model for the Latent Period of Stagonospora nodorum Blotch in Winter Wheat
Author(s) -
Ashley Zearfoss,
Christina Cowger,
P. S. Ojiambo
Publication year - 2011
Publication title -
plant disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.663
H-Index - 108
eISSN - 1943-7692
pISSN - 0191-2917
DOI - 10.1094/pdis-09-10-0651
Subject(s) - biology , winter wheat , period (music) , degree day , botany , glume , poaceae , degree (music) , horticulture , agronomy , physics , acoustics , thermodynamics
Stagonospora nodorum blotch (SNB), which is caused by Stagonospora nodorum, occurs frequently in the southeastern United States, and severe epidemics can lead to substantial yield losses. To develop a model for the progress of SNB based on the effects of temperature on the latent period of the pathogen, batches of two winter wheat cultivars, AGS 2000 and USG 3209, were inoculated with S. nodorum at weekly intervals for 16 weeks. After 72 h of incubation, inoculated plants were exposed to outdoor conditions where temperatures ranged from –6.6 to 35.8°C, with a mean batch temperature ranging from 9.7 to 24.7°C. Latent period, expressed as time from inoculation until the first visible lesions with pycnidia, ranged from 13 to 34 days. The relationship between the inverse of the latent period and mean temperature was best described by a linear model, and the estimated thermal time required for the completion of the latent period was 384.6 degree-days. A shifted cumulative gamma distribution model with a base temperature of 0.5°C significantly (P < 0.0001) described the relationship between increasing number of lesions with pycnidia and accumulated thermal time. When latent period was defined as time to 50% of the maximum number of lesions with pycnidia (L50), the model estimated L50 as 336 and 326 degree-days above 0.5°C for AGS 2000 and USG 3209, respectively. The relationship between 1/L50 and mean temperature was also best described using a linear model (r 2 = 0.93, P < 0.001). This study provides data that link disease progress with wheat growth, which facilitates accurate identification of thresholds for timing of fungicide applications.