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TRACY ROWLANDSON UNIVERSITY OF GUELPH Model vs. Measurement: Evaluation of IPM strategies Discussion Topic.

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Presentation on theme: "TRACY ROWLANDSON UNIVERSITY OF GUELPH Model vs. Measurement: Evaluation of IPM strategies Discussion Topic."— Presentation transcript:

1 TRACY ROWLANDSON UNIVERSITY OF GUELPH Model vs. Measurement: Evaluation of IPM strategies Discussion Topic

2 Need for re-evaluation Many IPM strategies have been based on leaf wetness duration (LWD) No standard has been set by the community regarding LWD What are the options going forward?

3 Measurement (Sensors) DecagonEnvirondataSpectrumNetsens OnSet Campbell Sci. RainwiseGlobal Water

4 Measurement (Sensors) Pros:  Several commercially available products  Provide site specific information  Visible  Capable of providing accurate LWD estimates

5 Measurement (Sensors) Cons:  Several commercially available products  Require calibration and maintenance  Placement requires consideration  Treatment is not standard; placement is not standard

6 Models Pros:  Both physically and empirically based models have been developed (both with success)  Require the input of standardized information  Representative for regions larger than sensors can provide; non- invasive  Data can be accessible  Entirely transferable (physical) with some adjustment (empirical)

7 Models Cons:  Some models require many, many inputs – particularly physically based  Data quality may be uncertain  Empirical models require calibration  No accepted standard

8 What we have proposed Adoption of a relative humidity based empirical model RH> threshold Why?  Requires a single variable (standard input)  A standard practice  Suggested method for threshold determination

9 RH > Threshold Ames, IA 83%; Elora, ON 85%; Florence, Italy 92%; Piracicaba, Brazil 90%

10 Discussion How can we provide RH data at a necessary resolution? IPM strategies have been developed based on LWD – should they be re-evaluated based on hours of RH> threshold? Concern has been expressed over quality of meteorological data – do we have a say in improvement?


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