Modeling Temporal Progress of Verticillium Wilt Epidemics in Cotton

Wednesday, January 6, 2016: 4:30 PM
Galerie 1 (New Orleans Marriott)
Xiaoxiao Liu , Department of Plant and Soil Science, Texas Tech University
Jason Woodward , Department of Plant and Soil Science, Texas Tech University
Terry Wheeler , Texas A&M AgriLife Research
Cotton (Gossypium hirsutum L.) is an economically important crop in the Texas High Plains. Reduced yield and fiber quality induced by Verticillium wilt, caused by Verticillium dahliae Kleb., is capable of causing substantial losses. Partially resistant cultivars is most commonly used for management of the disease; however, other production practices such as irrigation, reduced seeding rates and crop rotation are known to affect the disease. A small plot field experiment was conducted using a split-plot design with three replications at the Texas Tech University Quaker Farm. Whole plots consisted of seeding rate (1, 2, 3, 4, 5 or 6 seeds foot-1) and the cultivars Deltapine 1212 B2RF, NexGen 4111 RF, Fibermax 2484 B2F, and All-Tex Nitro-44 B2RF served as sub-plots. Results indicated that seeding rate and cultivar affected disease incidence. Medium (3-4 seeds foot-1) and high (5-6 seeds foot-1) seeding rates significantly (P < 0.05) decreased the foliar disease incidence compared to the low seeding rates (1-2 seeds foot-1). Area under Disease Progress Curve (AUDPC) showed a similar trend as the final foliar disease incidence rating. The partially resistant cultivars NexGen 4111 RF, Fibermax 2484 B2F, and All-Tex Nitro-44 B2RF exhibited lower foliar disease incidence (5.8%, 3.3%, and 6.1%) relative to the susceptible control Deltapine 1212 B2RF (10.8%). In addition, among the partially resistant cultivars, Fibermax 2484 B2F was superior to others in view of Verticillium wilt resistance. Five growth models (exponential, monomolecular, Gompertz, logistic, and Weibull) were used to simulate the temporal disease development and evaluate the effectiveness of the management practices on retarding disease epidemic rate. The Gompertz model was identified as the model with the highest coefficient of determination (R2) of 0.843. High seeding rates and partially resistant cultivars not only decreased the disease incidence significantly (P < 0.05) but also slowed the rate of disease increase.