Validation of 'Downcast' in the prediction of sporulation-infection periods of Peronospora destructor in the Lockyer Valley.

1994 ◽  
Vol 34 (4) ◽  
pp. 537 ◽  
Author(s):  
Gerald SM Fitz ◽  
RG O'Brien
Keyword(s):  
Downy Mildew ◽  
Disease Forecasting ◽  
Effective Management ◽  
Field Plot ◽  
Peronospora Destructor ◽  
Disease Progress ◽  
Trap Plants ◽  
Forecasting System ◽  
Unsprayed Plot

The disease forecasting system 'Downcast' was developed in Canada to indicate sporulation-infection periods of Peronospora destructor (Berk.) Caspary in onions. During 1989, observations were made of downy mildew development in trap plants and of disease progress in an unsprayed plot of onions in the Lockyer Valley, Queensland, and related back to predicted sporulation-infection periods using the forecaster. Over 113 days, there were 20 days when sporulation and infection were predicted, and of these 14 occurred during 4 weeks in July and August. Of 16 groups of trap plants exposed in the field, each for 7 days, 7 were subjected to predicted sporulation-infection periods. Two predicted sporulation-infection periods early in the season did not result in infection of trap plants or of plants in the field plot, probably due to absence of inoculum. Subsequently, groups of trap plants exposed in the field during predicted sporulation-infection periods became infected while those exposed when weather was unsuitable remained healthy. 'Downcast' shows promise as a technique for more effective management of disease caused by Peronospora destructor.

Guides for Estimating Forest Stand Losses to Gypsy Moth

1984 ◽  
Vol 1 (2) ◽  
pp. 21-23 ◽  
Author(s):  
David A. Gansner ◽  
Owen W. Herrick
Keyword(s):  
Species Composition ◽  
Gypsy Moth ◽  
Tree Mortality ◽  
Cost Effective ◽  
Forest Stand ◽  
Measure Data ◽  
Effective Management ◽  
Field Plot ◽  
Crown Condition ◽  
As Species

Abstract People who have to make decisions about cost-effective management for gypsy moth need help in predicting and evaluating its effects. Field plot data collected during recent outbreaks in Pennsylvania are being used to develop guides for predicting forest stand losses to the pest Presented here are some of the more useful products of that effort to date. Easy-to-measure data for forest characteristics such as species composition and crown condition can be collected and applied in models that estimate potential stand and tree mortality and changes in timber value. North. J. Appl. For. 2:21-23, June 1984.

scholarly journals Comparison of Three Fungicide Spray Advisories for Lettuce Downy Mildew

Plant Disease ◽  
2001 ◽  
Vol 85 (8) ◽  
pp. 895-900 ◽  
Author(s):  
B. M. Wu ◽  
K. V. Subbarao ◽  
A. H. C. van Bruggen ◽  
S. T. Koike
Keyword(s):  
Downy Mildew ◽  
Drip Irrigation ◽  
Leaf Wetness ◽  
Lettuce Downy Mildew ◽  
Advisory System ◽  
System 2 ◽  
Forecasting System ◽  
Low Incidence ◽  
System 1 ◽  
First Time

Lettuce growers in coastal California have relied mainly on protective fungicide sprays to control downy mildew. Thus, timing of sprays before infection is critical for optimal results. A leaf-wetness-driven, infection-based advisory system, previously developed, did not always perform satisfactorily. In this study, the advisory system was modified by incorporating a pathogen survival component (system 1) or both survival and sporulation components (system 2). These systems were then evaluated in commercial lettuce fields in coastal California during 1996-1998. Three or four treatments were carried out in each field: (i) no spray; (ii) sprays as scheduled by the growers; (iii) sprays following modified system 1; and (iv) sprays following the original advisory system (1996) or modified system 2 (1998). Downy mildew incidence was evaluated every 2 to 9 days. In fields with drip irrigation, the number of fungicide applications was reduced by one or two regardless of the advisory system used compared to the grower's calendar-based schedule, although one unnecessary spray was recommended in 1996 at Soledad and 1997 at Salinas. Under all three systems, disease levels were low (incidence <25% and about 1 lesion per plant) for fields with drip irrigation, but not for fields with sprinklers (incidence up to 100% and 5 to 10 lesions per plant). For the first time, we established that survival and sporulation components are not needed for a lettuce downy mildew forecasting system. Instead, a threshold with a shorter period of morning leaf wetness and high temperatures were found to have potential for improving forecasting efficiency.

Peronospora destructor. [Descriptions of Fungi and Bacteria].

1975 ◽  
Author(s):  
K. G. Mukerji
Keyword(s):  
South Africa ◽  
New Zealand ◽  
East Asia ◽  
Downy Mildew ◽  
Geographical Distribution ◽  
Wild Species ◽  
Peronospora Destructor ◽  
North East

Abstract A description is provided for Peronospora destructor. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: Affects species of Allium; common on A. cepa, rarer on A. ascalonicum, A. fistulosum, A. porrum, A. sativum, A. schoenoprasum, and a few wild species. DISEASE: Downy mildew (mildiou, falscher Mehitau) of onion. GEOGRAPHICAL DISTRIBUTION: On onion in all parts of Europe and America; north, east and south Africa, west, south and east Asia, Australia, New Zealand; and Tasmania. On other Allium crops in a few countries in Europe and on other continents (CMI Map 76. ed. 3, 1969).

scholarly journals Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić
Keyword(s):  
Downy Mildew ◽  
Fire Blight ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Plasmopara Viticola ◽  
Forecasting System ◽  
Nwp Model ◽  
The Impact

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

scholarly journals Environmental Conditions Associated with Stripe Rust in Kansas Winter Wheat

Plant Disease ◽  
2016 ◽  
Vol 100 (11) ◽  
pp. 2306-2312 ◽  
Author(s):  
B. S. Grabow ◽  
D. A. Shah ◽  
E. D. DeWolf
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Stripe Rust ◽  
Yield Loss ◽  
Initial Step ◽  
Disease Forecasting ◽  
Estimation Equations ◽  
Forecasting System ◽  
Moisture Conditions ◽  
General Estimation

Stripe rust has reemerged as a problematic disease in Kansas wheat. However, there are no stripe rust forecasting models specific to Kansas wheat production. Our objective was to identify environmental variables associated with stripe rust epidemics in Kansas winter wheat as an initial step in the longer-term goal of developing predictive models for stripe rust to be used within the state. Mean yield loss due to stripe rust on susceptible varieties was estimated from 1999 to 2012 for each of the nine Kansas crop reporting districts (CRD). A CRD was classified as having experienced a stripe rust epidemic when yield loss due to the disease equaled or exceeded 1%, and a nonepidemic otherwise. Epidemics were further classified as having been moderate or severe if yield loss was 1 to 14% or greater than 14%, respectively. The binary epidemic categorizations were linked to a matrix of 847 variables representing monthly meteorological and soil moisture conditions. Classification trees were used to select variables associated with stripe rust epidemic occurrence and severity (conditional on an epidemic having occurred). Selected variables were evaluated as predictors of stripe rust epidemics within a general estimation equations framework. The occurrence of epidemics within CRD was linked to soil moisture during the fall and winter months. In the spring, severe epidemics were linked to optimal (7 to 12°C) temperatures. Simple environmentally based stripe rust models at the CRD level may be combined with field-level disease observations and an understanding of varietal reaction to stripe rust as part of an operational disease forecasting system in Kansas.

Temporal Dynamics and Severity of Cucurbit Downy Mildew Epidemics as Affected by Chemical Control and Cucurbit Host Type

Plant Disease ◽  
2021 ◽  
Author(s):  
Isaack Kikway ◽  
Anthony P. Keinath ◽  
Peter S. Ojiambo
Keyword(s):  
Downy Mildew ◽  
Disease Severity ◽  
Temporal Dynamics ◽  
Parameter Estimates ◽  
Spring Season ◽  
Fall Season ◽  
Fungicide Treatment ◽  
Cucurbit Downy Mildew ◽  
Disease Progress ◽  
Host Type

Cucurbit downy mildew caused by the oomycete Pseudoperonospora cubensis is an important disease that affects members of Cucurbitaceae family globally. However, temporal dynamics of the disease have not been characterized at the field scale to understand how control strategies influence disease epidemics. Disease severity was assessed visually on cucumber and summer squash treated with weekly alternation of chlorothalonil with either cymoxanil, fluopicolide or propamocarb, during the 2018 spring season and 2019 and 2020 fall seasons in North Carolina, and the 2018 and 2020 fall seasons in South Carolina. Disease onset was observed around mid-June during the spring season and early September during the fall season, followed by a rapid increase in severity until mid-July in the spring season and late September or mid-October in the fall season, typical of polycyclic epidemics. The Gompertz, logistic and monomolecular growth models were fitted to disease severity using linear regression and parameter estimates used to compare the effects of fungicide treatment and cucurbit host type on disease progress. The Gompertz and logistic models were more appropriate than the monomolecular model in describing temporal dynamics of cucurbit downy mildew, with the Gompertz model providing the best description for 34 of the 44 epidemics examined. Fungicide treatment and host type significantly (P < 0.0001) affected standardized area under disease progress curve (sAUDPC), final disease severity (Final DS) and weighted mean absolute rates of disease progress (ρ), with these variables, in most cases, being significantly (P < 0.05) lower in fungicide treated plots than in untreated control plots. Except in a few cases, sAUDPC, Final DS and ρ were lower in cases where chlorothalonil was alternated with fluopicolide or propamocarb than in cases where chlorothalonil alternated with cymoxanil or when chlorothalonil was applied alone. These results characterized the temporal progress of cucurbit downy mildew and provided an improved understanding of the dynamics of the disease at the field level. Parameters of disease progress obtained from this study could serve as inputs in simulation studies to assess the efficacy of fungicide alternation in managing fungicide resistance in this pathosystem.

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