ABSTRACT
Soilborne wheat mosaic virus (SBWMV) and Wheat spindle streak mosaic virus (WSSMV) are putatively transmitted to small grains by the obligate parasite Polymyxa graminis, but little is known about environmental requirements for transmission and the resulting disease incidence. We planted susceptible wheat and triticale cultivars in field nurseries on different autumn dates in 3 years and observed the incidence of symptomatic plants in each following spring. Autumn postplanting environment explained most of the variation in disease caused by both viruses. Little apparent transmission, based on eventual symptom development, of either virus occurred after the average soil temperature dropped below 7°C for the remainder of the winter. To forecast disease, we tested an SBWMV transmission model in the field, based on laboratory results, that predicts opportunities for transmission based on soil temperature and soil moisture being simultaneously conducive. This model was predictive of soilborne wheat mosaic in 2 of 3 years. Zoospores of P. graminis have optimal activity at temperatures similar to those in the SBWMV transmission model. Furthermore, the matric potential threshold (as it relates to waterfilled pore sizes) in the SBWMV transmission model fits well with P. graminis as vector given the size restrictions of P. graminis zoospores. Conditions optimal for SBWMV transmission in the laboratory were not conducive for WSSMV transmission in the laboratory or for wheat spindle streak mosaic development in the field. This differential response to environment after emergence, as indicated by disease symptoms, may be due to virus-specific environmental conditions required to establish systemic infection via the same vector. Alternatively, the differential response may have been due to the involvement of a different vector in our WSSMV nursery than in our SBWMV nursery. Our results suggest that, as a control tactic for SBWMV or WSSMV, earliness or lateness of planting is less important in determining virus transmission and disease than the specific postplanting environment. Improved models based on the postplanting environment might predict virus-induced losses of yield potential, and in some cases, growers might avoid purchase of spring inputs such as pesticides and fertilizer for fields with greatly reduced yield potential.
