Adaptation of the Forecasting Model DOWNCAST for Determination of Downy Mildew Epidemics of Oilseed Poppy in Tasmania, Australia

Abstract

Peronospora cristata, causing downy mildew, has become an economically important pathogen of oilseed poppy (Papaver somniferum) since its first record in Tasmania in 1996. DOWNCAST, originally developed for downy mildew of onion, was evaluated for its ability to predict sporulation and infection of poppy by P. cristata. To assess the influence of the parameters within DOWNCAST, two modifications (POPCAST1 and POPCAST2) of the standard DOWNCAST model were also developed and tested. Initial accuracy of determination of sporulation events by DOWNCAST was 75%, while POPCAST1 (but not POPCAST2) was a significantly more accurate predictor of sporulation events (86%) than DOWNCAST (v 2 = 5.74, P = 0.025). This increase in accuracy was attributed to increasing both the rainfall threshold inhibitory to sporulation from 0.2 to 3.0 mm, and the relative humidity threshold for induction and development of sporulation from 95% to 96%. While DOWNCAST, POP-CAST1 and POPCAST2 had accuracies of infection determination of 65%, 80% and 75%, respectively, chi-squared analysis indicated no significant difference between models. Preliminary field evaluation indicated that POPCAST1 and POPCAST2 were more sensitive in detecting early infection events than DOWNCAST. Field observations indicated that conditions are frequently conducive for downy mildew spread, therefore the ability to predict early season infection events would allow growers to reduce initial infection rates, and thus inoculum loads later in the season. POPCAST1 and POP-CAST2 represent a significant step towards the development of a predictive model for downy mildew in poppy crops.

Role of oospores as primary inoculum for epidemics of downy mildew caused by Peronospora arborescens in opium poppy crops in Spain

“…A constant temperature of 16°C was more favourable for seedling infection than 20°C. Scott et al (2008) suggested a range of 2–26°C and a threshold of 96% relative humidity for prediction of early season infection events of opium poppy downy mildew caused by P. cristata in Tasmania. These environmental conditions were satisfied in the present microplot experiments.…”

“…Despite the importance of opium poppy downy mildew worldwide, little was previously known in Spain and elsewhere about the epidemiology of the disease. Published research on opium poppy downy mildew is scarce and has focused mainly on resistance to the pathogen in varieties of P. somniferum (Bajpai et al ., 1999; Dubey et al ., 2009), spatiotemporal analysis and forecasting of epidemics in Tasmania (Scott et al ., 2003, 2008), and molecular detection and genetic diversity of the pathogen (Scott et al , 2004; Landa et al ., 2007; Montes‐Borrego et al, 2009). As a consequence, the biology of the pathogen and epidemiology of the disease are as yet poorly understood.…”

Short communication: Local infection of opium poppy leaves by Peronospora somniferi sporangia can give rise to systemic infections and seed infection in resistant cultivars

“…Downy mildew (DM) caused by either of the biotrophic, obligate oomycetes Peronospora somniferi Voglmayr and Peronospora meconopsidis Mayor (Voglmayr et al, 2014) poses an important economic constrain on opium poppy (Papaver somniferum L.) crops worldwide (Kapoor, 1995;Landa et al, 2007;Scott et al, 2008). Attacks by the disease are also of social significance because opium poppy is the only source of codeine, morphine and thebaine drugs for the pharmaceutical industry, which are key components for alleviation of chronic pain associated with cancer diseases.…”

Development of Forecasting System for Onion Downy Mildew in Egypt

“…This study suggested that the ODM-Cast model criteria could be used to initiate the fungicide program at the time of the first sporulation-infection period, according to accurate and successful prediction of both primary infection and the daily disease infection potential (DDIP) by the ODM-Cast model developing and validating in two onion growing seasons during (2006/2007 and 2007/2008). Worldwide, many scientific considerable efforts has gone in the study of forecasting models for the simulation of onion downy mildew development towards better disease management with less human and environment hazards (Jesperson and Sutton, 1987;Battilani et al, 1995;De Visser, 1998;Harper, 1998;Friedrich et al, 2003;Gilles et al, 2004 andScott et al, 2008).…”

“…Recent innovations in weather data collection, the use of onsite realtime automated (Telemetry) weather station to collect hourly plant canopy microclimate data via telephone modems or by radio telemetry to personal computers, and then the data need to be run through the computer forecasting simulation models. Several studies have been conducted around the world to forecast the appropriate time for the fungicide applications to wisely control onion downy mildew with no hazards to the human and environment and to avoid the misuse of such unnecessary applications at the same time (Jesperson and Sutton, 1987;Battilani et al, 1995;De Visser, 1998;Harper, 1998;Friedrich et al, 2003;Gilles et al, 2004 andScott et al, 2008). The computerized model ODM-cast simulates the development of onion downy mildew on the basis of short-term observation of microclimatic factors.…”