A predictive model for carpogenic germination of Sclerotinia sclerotiorum

• Published in: Phytopathology 2010-06, Vol.100 (6), p.S89-S89
• Main Authors: Nepal, A, del Rio Mendoza, LE
• Format: Article
• Language: English
• Subjects: Sclerotinia sclerotiorum
• ISSN: 0031-949X

A predictive model for carpogenic germination (CG) of S. sclerotiorum was developed using soil moisture data. Two types of soils from Fargo (Fargo Silty clay) and Kindred (Aylmer-Bantry fine Sand), ND were mixed in proportions of 1:0, 2:1, 1:1, 1:2, and 0:1 v/v to create different textures. Sclerotia were buried in samples from each soil texture set at constant 100%, 75%, 50% or 25% soil saturation; or to conditions fluctuating back and forth between 100 to 0; 75 to 0; 50 to 0; and 25 to 0% saturation with 25% saturation intervals. Samples were incubated at 14/18C day/night for 82 days. CG was recorded at five-day intervals. CG data were expressed as binary values using 15 and 20% CG as thresholds. This data was split into two portions, one was used for model development using logistic regression analysis and the other was left for model validation. The area under cumulative moisture curve and rate of moisture accumulation were calculated for every time interval in all treatments and used, along with percentage of clay and silt, as predictor variables for the model. The best model had c = 0.96. When the model was validated using the independent data set, it produced a true negative proportion of 73% and a true positive proportion of 100% for an overall accuracy of 85%. Field validation of this model will be discussed.