A Predictive Model for Spotted Wilt Epidemics in Peanut Based on Local Weather Conditions and the Tomato spotted wilt virus Risk Index

Abstract

Tomato spotted wilt virus (TSWV), a member of the genus Tospovirus (family Bunyaviridae), is an important plant virus that causes severe damage to peanut (Arachis hypogaea) in the southeastern United States. Disease severity has been extremely variable in individual fields in Georgia, due to several factors including variability in weather patterns. A TSWV risk index has been developed by the University of Georgia to aid peanut growers with the assessment and avoidance of high risk situations. This study was conducted to examine the relationship between weather parameters and spotted wilt severity in peanut, and to develop a predictive model that integrates localized weather information into the risk index. On-farm survey data collected during 1999, 2002, 2004, and 2005 growing seasons, and derived weather variables during the same years were analyzed using nonlinear and multiple regression analyses. Meteorological data were obtained from the Georgia Automated Environmental Monitoring Network. The best model explained 61% of the variation in spotted wilt severity (square root transformed) as a function of the interactions between the TSWV risk index, the average daily temperature in April (TavA), the average daily minimum temperature between March and April (TminMA), the accumulated rainfall in March (RainfallM), the accumulated rainfall in April (RainfallA), the number of rain days in April (RainDayA), evapotranspiration in April (EVTA), and the number of days from 1 January to the planting date (JulianDay). Integrating this weather-based model with the TSWV risk index may help peanut growers more effectively manage tomato spotted wilt disease.

Stability Analysis of Incidence of Tomato Spotted Wilt in Virginia-Type Peanut Cultivars and Breeding Lines

“…This variation in TSW incidence over years is well documented, but has not been fully explained by weather (Olatinwo et al, 2008) or evolution of the virus (Kaye et al, 2009). As a point of reference, the mean effect of Georgia Green, the standard TSWresistant runner-type cultivar, was actually slightly greater than zero (+0.05460.023, P50.0180), and its slope of regression did not differ from one (Table 4, Fig.…”

Weather-based Pest Forecasting for Efficient Crop Protection

“…Weather variables including temperature, rainfall, and relative humidity, have been tested and reported on extensively in many disease studies (Bailey et al, 1994;Nokes and Young, 1991;Wharton et al, 2008;Olatinwo et al, 2008Olatinwo et al, , 2009Olatinwo et al, , 2010. In some studies, individual computer programs have been developed based on various weather parameters to make predictions, while others studies have incorporated computer programs into commercial advisory equipment (Cu and Phipps, 1993;Grichar et al, 2005;Boyle, 1965, 1966;Linvill and Drye, 1995;Parvin et al, 1974;Shew et al, 1988;Wu et al, 1999).…”

“…In addition to temperature and precipitation, relative humidity is another weather variable that has been shown in many studies to be related to the development of fungal pathogens (Damicone et al, 1994;Boyle, 1965, 1966;Jewell, 1987;Olatinwo et al, 2008Olatinwo et al, , 2009Olatinwo et al, , 2011Shew et al, 1988;Wu et al, 1999). In monitoring the likelihood of infection initiation through sporulation of fungal spores, the available moisture on a leaf surface can be estimated using relative humidity, since it correlates with wetness of a leaf surface within a canopy.…”

“…The tobacco thrips (Frankliniella fusca Hinds) and the western flower thrips (Frankliniella occidentalis Pergande) are particularly important thrips species that have a significant economic impact on several crops in the southeastern United States (Olatinwo et al, 2008(Olatinwo et al, , 2009(Olatinwo et al, , 2011. The population peaks of important thrips in field crops and vegetables in the southeastern US mostly occur during the first and second week of May (McPherson et al, 1999;Pappu, 2000, 2004).…”

“…Weather variables also play a crucial role as inputs in models for predicting insect vector/pathogen population dynamics. For instance, weather patterns were shown to have a significant but indirect effect on the incidence of Tomato spotted wilt virus transmitted by thrips in peanut (Olatinwo et al, 2008(Olatinwo et al, , 2009). Several studies have also used weather parameters as a management tool for monitoring pests/vectors and diseases/pathogens in valuable crops (De Wolf and Isard, 2007;Magarey et al, 2007;Wharton et al, 2008).…”