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Use of pan evaporation and temperature data in Powdery Mildew forecasting

Use of pan evaporation and temperature data in Powdery Mildew forecasting. Michelle M. Moyer Cornell University NYSAES-Geneva. Principles of disease forecasting. Diseases Amenable to Meteopathological Prediction (Bourke 1970) Causes economically significant damage

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Use of pan evaporation and temperature data in Powdery Mildew forecasting

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  1. Use of pan evaporation and temperature data in Powdery Mildew forecasting Michelle M. Moyer Cornell University NYSAES-Geneva

  2. Principles of disease forecasting • Diseases Amenable to Meteopathological Prediction (Bourke 1970) • Causes economically significant damage • Variable seasonal impact (directly/indirectly weather related) • Control measures are available • To adjust spray times • To reduce total number of sprays • To optimize timing of sprays • Protection, eradication • Maximization of chemistries; resistance management

  3. Forecasting the Powdery Mildews • Generally a focus on infection periods and general favorability for severity development • Temperature (Grape, Apple, Beet, Wheat) • Rainfall (Grape, Apple, Beet, Wheat) • Humidity (Grape, Apple, Wheat) • Vapor Pressure Deficit (Apple) • Leaf Wetness (Grape) • Wind (Wheat)

  4. Forecasting Grape Powdery Mildew • Development of a risk assessment model for grapevine powdery mildew in the NE. • Ran existing models for the region • Development of a new model based on a variety of weather inputs. • In NY, powdery mildew severity on clusters is related to temperature the previous fall, and • In-season pan evaporation levels

  5. Estimating Powdery Mildew Risk In Season Weather: How “wet” or “dry” has the weather been (based on pan evaporation). What is the upcoming forecast? Wet to Average (<6.07 mm) Dry (>=6.07 mm) In-season weather is conducive. What was the inoculum potential? In-season weather not conducive. 100% Chance of “Mild Year” Warm previous fall (>=450 DD) Cool previous fall (<450 DD) Moderate to low inoculum load. How conducive is the weather to maximize the impact this load? High inoculum potential with average to highly conducive weather. Potential realized. 100% Chance of “Severe Year” Average (>=5.45 mm) Conducive (<5.45 mm) Low inoculum load, but weather is extremely favorable to maximize potential. 60% Chance of “Severe Year” Low inoculum load with just average weather conditions means a poor start for PM. 80% Chance of “Mild Year”

  6. Advantages of using Epan • Integration of multiple weather parameters • Single measurement • Global pan evaporation networks available • Conceptually easy to explain to growers • “Water Stress” • “Clothesline” Example

  7. Epanvs. Eto Epan Eto • Evaporation from an open surface • Measured parameter • Evaporation from open and vegetative surfaces • Calculated parameter

  8. Requirements in using Eto/Epan • Epanmaintenance crucial for accurate readings • Need daily to weekly Epan averages • Calculation of Eto is only as good as the input values • While Epan and Eto are challenges to forecast, use of historical averages can help

  9. Resulting regression parameters from comparing calculated Eto to actual Epan

  10. Annual Epanvalues decreasing Average Daily Epan Historically (May-Oct,170)= 5.97mm Average Daily Epan2000-2007 (May-Oct,170)= 4.63mm

  11. Trends vs. Events • Epan as a general favorability indicator • Temperature most common and easily accessible weather input • How to temperature trends vs. specific events influence PM development?

  12. Temperature and powdery mildew What we know: What we don’t: • Suboptimal temperature effects on existing colonies • Suboptimal effects on epidemic development • What do cold temperatures do?

  13. Cold-induced resistance * Percent in Class (%) Appressorium Branched hyphae

  14. Cold kills (or at least hurts a little…) Four-day-old colony grown at 25°C:: Line Sketch of colony footprint, and Same colony visualized with a vital stain Four-day-old colony exposed to 2°C for 8h at 3dpi:: Line Sketch of colony footprint, and Same colony visualized with a vital stain

  15. It is true… New York is cold

  16. Similar cold events occur globally

  17. Considerations • Epan, in theory, is a useful environmental parameter to use for disease forecasting • Incorporates multiple weather parameters and their interaction on water stress and availability to the pathogen. • May also help understand plant stress- useful in obligate biotroph systems. • Temperature in PM forecasting may best be used as an indicator of acute unfavorable events for disease or pathogen development

  18. Questions?

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