improve insights by aggregating on farm trial data

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Sponsored by XSInc Improve Insights by Aggregating On-farm Trial Data Precision Ag Insight Webinar June 27, 2016

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Sponsored by XSInc

Improve Insights by Aggregating On-farm Trial Data

Precision Ag Insight Webinar

June 27, 2016

Sponsored by XSInc

Webcast Format

• You are muted.

• Please ask questions using the “Questions” box.• Click the red arrow to close/open

controls.

• Click the “plus” next to “Questions” if you don’t see the questions box.

• A recording of today’s webcast will be emailed to you.

Minimized Controls

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Speakers

PresenterDr. Chad GodseyOwner, Godsey Precision Ag

HostBen GistBusiness Development Analyst, XS Inc

Sponsored by XSInc

On-farm Research Is Important

• Answer questions important to growers˃ New products

˃ Precision ag practices

• Increase grower profitability

• Compliance, stewardship and sustainability

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Registration Question

• Which best describes how you have considered using aggregate results from on-farm trials?

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Results –Using On-Farm Trials

30%

10%

40%

20%

Have not considered

To account for varying field characteristics that influence site specific recommendations

To discover if a product works overall across the tested acreage

To draw conclusions for other producers/other fields

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3 Keys to Success

• Quality over Quantity

• Keep It Simple

• Reduce Noise

˃ You can never be 100% certain that yield differences in a trial are solely due to the treatments being evaluated.

˃ But you can manage sources of noise with good planning and analysis.

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3 Critical Pieces of a Trial Plan

• The Question

• The Layout

• The Data

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Define the question

• The first step is clearly defining a question that you want to answer with aggregate analysis.

˃ Is Product A better than Product B?

˃ If I increase or decrease the application rate of this

product by 10% in each management zone, how much

will my yield increase or decrease?

• Consider other factors that may influence trial outcome

˃ Management practices

˃ Hybrid or varietal differences

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3 Critical Pieces of a Trial Plan

• The Question

• The Layout

• The Data

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4 Considerations for Layout

1. Objective

2. Background information

3. Equipment and logistics

4. The “Three Rs” of on-farm trials

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An ExampleManagement Zones Elevation Gradient

Trial Boundary

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An Example:

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Using Productivity Zones

• Why?˃ Accounts for temporal variability˃ Provides a baseline to compare treatments against

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3 Critical Pieces of a Trial Plan

• The Question

• The Layout

• The Data

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Data Considerations for Aggregate Analysis• Standardization

• Most important part of on-farm trials. Makes or breaks a study!

• If a data layer appears to be important it needs to be collected on all fields

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The Why and When of Aggregate Analysis

• Why

• Aggregation enables the results of multiple single field on-farm trials where the same product or practice is being tested, to form broader conclusions from the insights of each individual trial.

• CONFIDENCE!!!

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Aggregate Analysis

• Knowing what to aggregate can be even more important

• Product A versus B

• What is the level of aggregation?

• Farm vs. Region

• Are you trying to answer a specific question for a specific farm?

• Seeding Rate Seeding Rate Checks

Compost Trial

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Registration question• Do you see a problem with aggregating data

across multiple producers?

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Results – Include multiple producers?

20%

40%

40%

No Not Sure Yes

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Aggregate Example – Fungicide trials

Fungicide Trial

Soil Types Elevation

- 2 corn fields in Ohio- Analyzing 3 known factors:

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What is AgVeritas?• Web-based yield analysis tool

• Analyzes all the factors that impact yield at the same time Planting choice / rate

Treatment choice / rate

Nutrient levels, soil types, elevation

Or any factor for which you have data

• Uses spatial statistics to detect and account for unidentified factors affecting yield

• Determines which factors impacted yield more and less

• Guides user to profitable adjustments in practices

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Aggregate Analysis Approach

• Start with more precision, end with more precision

• Removes spatial effect areas

• Based on each field’s unique “model”

• Examines the specific conditions under which different responses are seen down to a individual yield point level

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Aggregate Example – Fungicide trials

Fungicide Trial

Soil Types Elevation

- 2 corn fields in Ohio- Analyzing 3 known factors:

Sponsored by XSInc

Sponsored by XSInc

Sponsored by XSInc

Sponsored by XSInc

Sponsored by XSInc

Summary

• When and why of aggregation

• Plan Plan Plan!

• Standardization

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Thank You

Chad Godsey, PhD

Owner, Godsey Precision Ag

Phone: 970-630-7732

Email: [email protected]

Web: godseyag.com

Twitter: @godseyag