PowerPoint Presentationdarr/Files/Pioneer/Darr_EncircaTraining_v5.pdf · Technology Levels: Differential Correction WAAS: Free service provided by the US government within the US

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The DuPont Oval Logo is a registered trademark of DuPont. ®, TM, SM Trademarks and service marks of Pioneer. © 2014 PHII.

INTRODUCTION TO PRECISION AGRICULTURE

Dr. Matt Darr, Iowa State University

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GPS – Where it all starts.






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Technology Levels:

Differential Correction

WAAS: Free service provided by the US government within the

US and Canada.

• Typical accuracy of 8 – 12” pass-to-pass

• Cost range: $1,000 to $2,500

Commercial Subscriptions: Provided by Deere (StarFire SF2)

and Trimble (Omnistar XP and HP).

• Worldwide solution. Popular in countries without WAAS

infrastructure.

• Typical accuracy of 2 – 5” pass-to-pass

• Cost range: $4,000 to $6,500 + annual subscription

(~$800/year)

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Technology Levels:

RTK Differential Correction

RTK: Requires base station within near distance (< 20 miles) of the

vehicle.

• Typical accuracy of 1” pass-to-pass, depended on the distance to

the base station

Traditional RTK: Uses a direct radio communication link to transfer

RTK corrections.

• Rover (ag vehicle) cost range: $12,000 to $15,000

• Base station cost range: Similar to rover or subscription services

are available in a range of $500 to $2,000 per year.

CORS RTK: Uses cellular data connection to link the rover to a

network of base stations. Largest area of growth for RTK systems.

• Cost range: $12,000 to $15,000 + annual subscription

(~$800/year)

• Advantage is the broad coverage network and leverages the

strength of cellular networks.






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GLONASS: Russian Positioning Satellites






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GPS Accuracy

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Applications of WAAS GPS Technology






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Applications of Subscription GPS Technology






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Applications of RTK GPS Technology

FSR_Combine.MPG

FSR_Combine.MPG

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Does Size Matter?






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Autosteering Systems Basics

Guidance products are the most highly adopted

precision ag products because:

• Save on input costs

• Enhance productivity and efficiency

• Allow the operator to better “manage” today’s larger

equipment

• Easily adapt to current equipment






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Adoption of Autosteering Systems

Most tractors built since ~2006 are

Autosteer ready.

• This substantially reduces the

investment cost in Autosteering

technology

Example: Deere 8R Series Tractors

• AutoTrac Ready and includes factory

installed display capable of AutoTrac

• Requires $6,195 upgrade for:

• StarFire 3000 Receiver AutoTrac SF1

Activation

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Adoption of Planter and Sprayer Section Control Products

Section Control products

limit the overlap of inputs

into headland areas and

across waterways using

GPS technology and an

actuation method.

Sprayers use electronic

valves and planters use row

clutches to disengage

specific row units.

These technologies have an

extremely high adoption rate

on self propelled sprayers

and planters 12 rows and

wider.






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Planter Section Control: Before and After






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Planter Clutch Section Control

Individual rows or sections controlled by air or electric clutches.

Reduces excess use of seed and yield drag in headland and field boundary

areas.

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Planter Section Control Products

Guess which plant and ear came from the planter overlap area

of the headlands?






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Section Control Products Sprayers

Buffer Strip

Nozzles OFF

Active Section Control Shines:• Irregular shaped fields

• Self-propelled sprayers (12-18 mph)

Image: Auburn University






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High Speed Planting

00832.MTS

00832.MTS

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High Speed Planting






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Autosteering Systems: Return on Investment

3.3% Planting Overlap Error

•Economic savings of $7.89/ac

7% Tillage Overlap Error







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Grid and Zone Based Soil Sampling

Year 1 pH Map

Year 1 Lime App. Map

Year 3 pH Map

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Variable Rate Fertilizer: Nutrient Removal Based

Nutrient removal VRA is becoming more common particularly in areas of:

• High yield variability, Changes in irrigation, High producing soils

Nutrient removal rates

• Per bushel of corn: 0.375 lbs P2O5, 0.3 lbs K2O

• Per bushel of soybeans: 0.8 lbs P2O5, 1.5 lbs K2O






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Yield Monitoring Basics

User Interface

GPS Receiver

Mass Flow Sensor

Moisture Sensor






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ISU Yield Monitor Test Facility

Field and lab exposure to over 1,000 calibration cycles.

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Yield Monitor Performance Drivers

Impact Plate• Changes in crop conditions like

moisture content or surface

moisture.

• Mechanical tolerances along the

top of the clean grain elevator.

• Consistency of grain flow during

calibration points.

• Diversity and range of calibration

points.

• Accuracy of grain cart scales.

• Slope and terrain of the field.

• Type of calibration curve, Single

point vs. Multi point






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Yield Monitoring: Brands and Differences

Yield Monitor Brand Manufacturer Technology

AGCO AGCO Impact Plate

Ag Leader Ag Leader Impact Plate

Case IH Ag Leader Impact Plate

Deere Ag Leader Impact Plate

Lexion CLAAS Optical

Precision Plant. Prec. Plant. Impact Plate

Raven Loup Elect. Optical

Trimble Trimble Optical

GOPR0041.MP4

GOPR0041.MP4

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Calibration Curve Comparisons

Yield Error b/w 15%MC and

22%MC corn was over 20%

at some flow rates.






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Yield Monitor: When to Calibrate

When changing crop

type (i.e. between

soybeans and corn)

When crop properties

change significantly

• Moisture > 4%

• Test Weight

• Tough crop requires

changes in ground speed

(i.e. downed corn)

Dr. Matt Darr

Agricultural and Biosystems

Engineering






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Poor Yield Monitor Calibration

Calibration Line

Calibration Points

YM Error

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Poor Yield Monitor Calibration

Calibration Line

Calibration Points

YM Error






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Precision Planting Yield Monitoring Solution

Research results show the

precision planting yield monitor

is very consistent within field

but still requires field to field

calibration to maintain optimal

accuracy.






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Adjusting the Time Delay Factor for Yield Data

Linear striping effect is

quite common in yield

maps when the time

delay is not correct for a

specific combine.

The time delay is

typically 10 – 12

seconds but can be up

to 15 seconds for large

headers.

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Adjusting the Time Delay Factor for Yield Data






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Lateral Accuracy of Yield Data



Spatial Placement Accuracy of Yield Data

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Visualizing Combine Delays

381/29/2015






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Yield Monitoring Questions

Question: When should I recalibrate my combine?






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Question: When should I recalibrate my combine?

Answer:

Every year.

Whenever you change crops.

When moisture changes by more than 4%

When test weight changes by more than 4

lb/bu.

When field conditions dramatically change,

i.e. downed corn, lodged beans, ect.

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Question: Do I need to calibrate my yield monitor if I’m

just looking to compare relative differences between fields.






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Question: Do I need to calibrate my yield monitor if I’m

just looking to compare relative differences between fields.

Answer: Yield monitor error over the course of a

season can change ±15% depending on variations

in crop conditions. Without adequate calibration

yield results cannot be compared across fields.






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Question: Can I use a yield monitor to tell the difference

between split planter treatments or split pesticide

treatments in a field?

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Question: Can I use a yield monitor to tell the difference

between split planter treatments or split pesticide

treatments in a field?

Answer: Yes, if crop conditions are similar yield

monitors can work quite well for this. If there are big

differences in moisture, test weight, or crop health

(machine harvest rate) then the margin of error will

increase.






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Question: Which hybrid should I use to calibrate my yield

monitor if I’m harvesting a split planter field?






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Question: Which hybrid should I use to calibrate my yield

monitor if I’m harvesting a split planter field?

Answer: Collect yield monitor calibration loads

from both hybrids. This will reduce the maximum

error potential and improve the likelihood of

measuring a statistical difference.

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Question: Can I use a yield monitor to evaluate

performance differences in variety plots or test plots?






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Question: Can I use a yield monitor to evaluate

performance differences in variety plots or test plots?

Answer: Unless the test plots are quite long yield

monitors generally do not provide adequate

precision for consistently reporting winners and

losers in test plots.






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Yield Monitoring: Setting Expectations

When properly calibrated a yield monitor can provide field

level accuracy of 3%.

As calibrations drift over time and crop conditions change

field level errors in the range of 5 – 10% should be

expected.

Minimum distinguishable yields in single pass test plots

are:

Confidence

Level

150 bu/ac

Average Yield

175 bu/ac

Average Yield

200 bu/ac

Average Yield

50% 5.3 bu/ac 6.2 bu/ac 7.1 bu/ac

68% 7.8 bu/ac 9.1 bu/ac 10.4 bu/ac

90% 12.9 bu/ac 15.1 bu/ac 17.2 bu/ac

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Yield Calibration Procedures: Best Practices

• Ensure grain cart scales are

calibrated.

• Select a uniform and high yielding

area of the field for the calibration.

• Completely empty the combine.

• Start a calibration load and harvest

between 50 – 100 bushels of grain.

• Completely stop the combine and

offload the entire grain tank to a grain

cart or weigh wagon.

• Enter in the true grain weight.

• Repeat this procedure for multiple

flow rates by changing the combine

speed.

Single Point

Multi Point

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Autosteering Systems: Return on Investment

3.3% Planting Overlap Error


7% Tillage Overlap Error


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Benefits of Precision Ag Tools






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Where Do We Find Knowledge?






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Hybrid B

Hybrid A

Hybrid BHybrid A

200

150

100

50

0

Gra

in Y

ield

(b

u/a

c)

131

176

Yield Comparison of Two Hybrids in a Side-by-Side Test






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$168/ac difference


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Agricultural and Biosystems Engineering






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“ABC’s” of Management Zones

A Zone: Highest Productivity. The best of the best.

Growers should be aggressive with inputs on these areas

– better chance of high return on investment.

B Zone: Average Productivity. Consistent and stable

production. Growers should maintain their “average”

management practices in these zones.

C Zone: Below-Average Productivity. Yield-limiting

factors are preventing top production. Growers should be

conservative with inputs – low return on investment.






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How to Define Management Zones?

Multi-year Normalized

Yield

Well Defined Soil

Productivity Regions

Active Crop Data

Topographic Regions

Common Sense

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Multi Year Yield Analysis

Normalized yield data

from multiple years allows

for improved definition of

management zones

across diverse weather

conditions.

Also supports combined

analysis of corn and

soybean data.






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Normalized yield data

from multiple years allows

for improved definition of

management zones

across diverse weather

conditions.

Also supports combined

analysis of corn and

soybean data.







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Wet Season

Dry Season Test Plots






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3D Terrain Analysis – Starting with Raw Data

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3D Terrain Analysis – Smoothing Raw Data






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3D Free Aerial Imagery



3D Yield Overlay on Terrain

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What Makes a Good Management Zone?

Clearly distinguishable

productivity differences.

Large enough area that

changes are testable.

Driver for yield differences

are known or measurable.

Agronomic adjustments

are based on

fundamentals.






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Process for Optimizing Management Zone?

Use data driven

recommendations for

management adjustments.

Use test blocks to validate

crop response to changes.

Use a long term philosophy

to achieve measurable and

incremental improvements

to crop production.

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Is This Field a Good Candidate for Variable Rate Treatment?






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Characteristics of VR Friendly Fields

Identify crop production areas that

have significant differences. Target

general areas that have good

agronomic fundamental.

When using normalized yield a good

starting point is:

• A: Greater than 115%

• B: 115% – 85%

• C: Less than 85%.

Make sure the area is geographically

large enough to support a check block

and that there is sufficient room around

the check block to complete a

comparison analysis.






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To Grid or Not to Grid?

Gridding or contour mapping will often reduce

the visual variability in the yield data.

It can also make bad data look reasonable so

care should be taken to clean data before broad

scale smoothing.

Ask your customers what type of data

visualization format they prefer.






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Characteristics of VR Friendly Fields

Focus on areas where

performance can be

directly measured.

Sell customers on the

value of slow growth in

production practices

rather than single

solutions to achieve

“optimal” results.

Failure to return

improvement is only a

failure if not documented

and used to enhance the

next round of decisions.

High production area greater than 110% of the

field average.

Check block with suitable area around the check

block to confirm results.

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Management Zone Design

Goal: Hands on experience to

determine management zones

based on yield and supporting

data.






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Is Big Data New?

Big Data in 1910s






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What is Big Data?

Geospatial Maps

• Yield

• Imagery

• Fertility

Public Data

• Soils

• Weather

Analytics

• Crop Models

• Data Co-ops

• Markets

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Product Options in Remote Sensing and Aerial Imagery

Satellite Delivered:• 5m Resolution

• Timing can be limiting but more options are becoming available

Contracted Flight:• 1m Resolution

• Typically can schedule images within a +/- 3 day window around target date

Unmanned Aerial Systems (UAS)• ~3 – 10 cm Resolution

• If weather permits scheduling can be within a few hours of target time

Legal and Ethical Questions:• Do I have exclusive rights to the airspace

above my crop?

• Can a competitor purchase yield estimation imagery on fields I rent in order to out bid on land contracts?






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Remote Sensing Basics






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Red-Green-Blue Color (RGB) Imagery

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Near Infrared Imagery






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Normalized Difference Vegetation Index (NDVI)

Based on the fundaments that healthier green vegetation has a higher

infrared reflectance and lower red reflectance.

𝑁𝐷𝑉𝐼 =𝑁𝐼𝑅 − 𝑅𝑒𝑑

𝑁𝐼𝑅 + 𝑅𝑒𝑑






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NDVI Imagery. Green = healthy plants, Red = bare soil

How many decision opportunities can you spot?

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High Resolution Imagery in Agriculture

Planter Induced Compaction




High Resolution Imagery in Agriculture

Planter Induced Compaction






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Crop Health Assessment

Images courtesy

of GeoVantage

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Benchmarking Yield Data Quality

2012 Yield map captured with an S670 combine

with a 12 row head.

2014 25 cm imagery captured at V12






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Comparison to High Resolution Imagery

2014 25 cm imagery captured at V12




Data Analytics: Field Example

Manure Applicator

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Data Analytics: Field ExampleField Cultivator




Data Analytics: Field Example

Hybrid Change

Nitrogen

Misapplication



104

Compaction from previous machine

operations

Variety A

Variety B

10 – 14” Variation Between Compacted and

Uncompacted Plants

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Big Data Field ExampleHighly productive zone

195 bu/ac




Big Data Field ExampleHealthy Plants in Compacted Area

160 bu/ac




Big Data Field ExampleWeak Plants in Compacted Area

145 bu/ac

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Challenges in Management Zone Delineation






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Why Does Imagery Matter?






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Agronomic Zone Management

Data analytics is focused on sub-field precision measurement

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Zone Management Scale

Today: 9 ac

Today Intensive: 2.5 ac

Tomorrow: 1 ac






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Yield Management Scale






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Higher Precision Aerial Systems Can Augment

Traditional Yield Monitoring Technology

Is this real?

Improved zone edge detection

Better spatial placement of yield

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Drones in the News






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UAV Marketplace

Fixed Wing

• Time of Flight: 45 minutes

• Coverage Area: 100 – 200 ac

• Flight Complexity: High

• Intended Use: Spatial map

generation

Quad-copter

• Time of Flight: 15 minutes

• Coverage Area: 20 – 80 ac

• Flight Complexity: Low

• Intended Use: Crop scouting






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Image Mapping Options

Ground Level Georeferenced

Video Example

Crop Inspection with UAV.mp4

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Example: Hail Damage Inspection from First Person Video






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Comparing Image Resolution

Can you rank the image resolution of these three fields?






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Comparing Image Resolution

Can you rank the image resolution of these three fields?

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Eliminate Status Quo Crop Production

Why do rows 7 – 10 appear so much more

healthy than 4 – 6?

Is assessment of individual row crop

performance big data?

12

34

56

78

91

0

111

2

Row Numbers






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Current UAV Legal State

Currently illegal to use UAVs for

commercial applications.

When integrated into the national

airspace their will likely be a

‘licensing’ process which includes:

• Ground station pilots exam

• Medical exam

• Currency requirement of 90 days

• Require combination of pilot and

observer at the flight location

• Limited to low altitude flights and

outside of restricted airspace

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The Digital Transformation of Row Crop Agriculture

Big Data in Agriculture: A very broad term that is used

differently by different people. We are using this confusing term

less than we did previously in favor of more precise terms.

Adapted from “Big Data Project Report”, Iowa AgState Board, The Hale

Group

Big Data is data whose scale, diversity, and complexity

require new architecture, techniques, algorithms,

and analytics to manage it

and extract value and hidden knowledge from it.






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Policy Issues Receiving Major National Attention

Farmer ownership of data

Farmer control of data

Disclosure of data usage

Farmer choice for use of

data

Portability of data

Security from misuse

No vulnerability to FOIA

Compatibility of systems

Protection of GPS

Regulation of UAVs

Use of aggregated data

Consistency of

agreements

Simple language

Transparency and

consistency

Farmers express concern about all of these issues.

Adapted from Big Data ProjectReport. 2014. The Hale Group, Ltd.



Producer Surveys on Big Data

Skeptical of the New Technology – 65%

The biggest concern is misuse of farm data by:

Fear that it favors the large farmers.

Prescriptions will recommend only some products, i.e., are biased.

It doesn’t work. Agriculture is too complex.

Neutral or Nuanced in Attitudes – 19%

It has potential, but must be implemented carefully.

Embracing the New Technology – 16%

The technology is here to stay. Let’s embrace it and make it work for us.

No one that is highly profitable today is doing it with only their own ideas and crop data.

• The ATPs • Activist groups • Grain traders

• The government • Computer hackers

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Key Terms in Digital Agriculture

Data Warehouse

Ag Technology

Provider (ATP)

Data Ownership

and Portability

Aggregate and

AnonymizeFreedom of

Information Act

(FOIA)

Data Compatibility



Grower + ATP Data Partner

Ag Technology Provider (ATP)

• Commercial provider of technology

services in Agriculture

• ATPs work across all branches of ag:

• Data Generation: Machinery industry,

remote sensing

• Recommendations: Crop consultants, ag

retail

• Crop Modeling: Genetics industry

• Most ATP partnerships are driven by

relationships and trust. Formal data

agreements and contracts are becoming

more commonplace in agriculture.



ATP Cut Across Multiple Industries

Definition

Use of new tools that give farmers better operational control.

Examples

• Auto-steer

• Yield monitors

• Variable rate machinery

• Weather stations

Precision Agriculture

DecisionAgriculture

Enterprise Agriculture

Definition

Detailed prescription of agronomic practices to maximize yield or profit per acre using computer algorithms.

Examples

• FieldScripts

• Encirca

• Answer Tech

• Ag retailer scripts

DefinitionIntegrated, computer platform including: planning; agronomy; labor; work orders; purchasing; risk; inventory; logistics; machinery; marketing; profit per acre.

Examples

• Granular

• Conservis

Many

services

in-between

Plus many

other data

components

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American Farm Bureau Big Data Resources

http://www.fb.org/index.php?action=issues.bigdata1. Proprietary data collected from farming and agricultural operations is valuable, should remain the property of the farmer,

and warrants protection.

2. We support:

2.1. Efforts to better educate farmers and ranchers regarding new technology or equipment that may receive, record,

and/or transmit their farming and production data;

2.2. Requiring companies that are collecting, storing, and analyzing proprietary data to provide full disclosure of their

intended use of the data;

2.3. Formation of standardized protocols regarding privacy and terms of conditions to ensure a standard definition of all

components within the contract. We should be an active participant in developing these protocols;

2.4. Compensation to farmers whose proprietary data is shared with third parties that offer products, services or

analyses benefitting from that data;

2.5. Multiple participation options being included in all contracts;

2.6. All proprietary information between the farmer and the company remaining between the two entities. This would not

preclude a farmer from sharing data with whomever he/she chooses (e.g., a consultant);

2.7. Utilizing all safeguards to ensure proprietary data is stored at an entity that is not subject to a Freedom of

Information Act (FOIA) request;

2.8. The farmer’s right to enter into agreement and their rights to sell their proprietary data to another producer (e.g., in a

land sale);

2.9. Private companies entering into agreements which would allow for the compatibility/updating of equipment and

updating of software;

2.10. The right of a farmer to have access to their own data, regardless of when it was shared with a company; and

2.11. The right of the producer who no longer wishes to participate in aggregated data sharing with a private company,

to remove their past aggregated data from the company’s database and revoke that company’s ability to sell or use that

data in the future.

3. We oppose any federal agency or FOIA-eligible entity from serving as a data clearinghouse for all proprietary data or

aggregated data collected by private companies.






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Banking Analogy for Data Warehousing

Crop Consultant

Seed/Fert Supplier

Machinery Supplier

Insurance Agent

Landlord

Internal Mng Team

Data Warehouse






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American Farm Bureau Data Services Questions

Do I own the data?

How will my data be used and what benefits can I expect from allowing a

provider to include my data in a “Big Data” database?

Will I control the management of that data?

What is aggregation of data? How does aggregation protect me?

Is my personal farm data anonymized? How is “anonymize” defined?

Can I stop sharing my data once I have agreed to share?

Who else might have access to my data? Can it be released to the public

or to a third party?

What is the value of my data to ME?

What is the value of my data to the COMPANY?

What type of security protocols are in place to protect against cyber

hacking and data piracy? How will the “bank” avoid a Target incident?

Is the “bank” independent or are they also trying to provide agronomic or

business management services?

http://www.fb.org/index.php?action=issues.bigdata

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Data Ownership and Portability

Most ATPs stress grower data ownership but also reserve a license to use your data for internal purposes.

Portability is currently a major issue in ag. Discuss with your ATP how they will facilitate moving your data to another system in the event you choose to no longer do business with them.

Discuss who owns the results and recommendations that are produced by the ATP. As a producer do you own a copy and can you transfer the recommendations to another system in the future?

Ask specific ownership

and portability questions

to your ATP.

Will you provide copies of

my data to share with our

ATPs?

Can I take results and

recommendations with me

if I terminate services with

you?






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Data Compatibility

Data compatibility between

brands and service providers

remains a major challenge in

agriculture.

Ask ATPs what data formats they

can and can’t work with.

Always keep backups of raw

data in case you need to transfer

to a different ATP in the future.

Getting value out of your

data is a team effort.

Bring together your

equipment dealer,

agronomist, and ag tech

providers to put together a

plan and ensure that all

parties have the right tools

to be successful.






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Freedom of Information Act

Take care not to store data with

entities that must respond to FOIA

requests.

No data is protected against

subpoena or court orders.

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Aggregated and Anonymized Data

Aggregated and Anonymized are two

terms used to describe the de-

personalizing of your production data.

Once your personal information is

removed this data can more safely be

included in benchmarking programs or

large data analytics.

This can be valuable if you are

receiving results from this data

aggregation but you should be

hesitant to participate if you aren’t

receiving value from the use of your

data.

Opt-In: Data sharing

policy in which the grower

has to specifically elect to

be included.

Opt-Out: Data sharing

policy in which the grower

has to specifically elect to

NOT be included.

View drawing guides



guides on screen’

3. Select ’OK’

View drawing guides



guides on screen’

3. Select ’OK’


Will Digital Agriculture Change

Production Ag?

How Will it Impact

Integration of Row

Crop Agriculture?

Will it Create an

Inflection Point in Ag

Production?

Will it Change the

Source of Agronomic

Advice?






Top-PowerPoint menu

Will Digital Agriculture Change Production Ag?

Will Digital Ag Create an Inflection Point in Production Ag?

• The value of Digital Agriculture is still being defined. Most likely there will be

modest returns from Digital Agriculture in the next 4 – 8 years and a true

inflection point in the near future is unlikely.

Will Digital Ag Lead to Major Integration in Agriculture?

• In the next several years we’ll continue to see integration, acquisitions, and

mergers throughout the Digital Agriculture industry as the industry matures.

• If successful, the rapid expansion of services from Digital Agriculture could

drive a trend to larger scale farm integration and consolidation just as other

technologies have had an impact on this trend.

Will Digital Ag Change the Way Agronomic Advice is

Delivered?

• Digital Ag is focused on increasing our ability as growers to make the best

on-farm decisions. It is unlikely that Digital Ag will replace our traditional

sources of agronomic advice although it will certainly provide a new and

potentially very beneficial tool set to help enhance the advice and provide a

broader understand of our farming environment.

29-01-2015

46



Players and Partners:

Common Data Scenario

Farmer + Trusted Data Consultant

Input/Service Supplier + Data Partner

Relationship and Agreement Formed

Source: Shearer & Fulton, 2014






Top-PowerPoint menu

Technology Map

The Technology Map is designed to present companies in the appropriate cells based on their offerings and position in the market.

Precision Ag

Equipment

Data

Warehouse

Ag Retailer

Software

Smart Data

Deterministic

Models

Probabilistic

Models

Farm

Enterprise

System

Data

Generation &

Capture

Cloud &

Computer

Processing

Capacity

Delivery

Systems

Products and Services

Tech

no

log

y D

rive

rs







Top-PowerPoint menu

Precision Ag Equipment

Precision Ag Equipment

Data

Generation

& Capture

John Deere

Trimble/CaseIH

Raven

640 Labs

Ag Leader

Cloud &

Computer

Processing

Capacity

MyJohnDeere.Com

Trimble

Ag Leader

Delivery

Systems

Trimble

BASF


Tech

no

log

y D

rive

rs Includes:

• On Farm Data

• Telematics

• Yield Monitors

• Smart Machines

• Precision Ag Tools


29-01-2015

47






Top-PowerPoint menu

Data Warehouse

Data Warehouse

Data

Generation

& Capture

Geosys-Land O’ Lakes

GeoVantage

Cloud &

Computer

Processing

Capacity

Winfield Data Silo

Mapshots

GeoVantage

Amazon

Delivery

Systems

Answer Tech: R7 + Apps+ Climate

Pro

Mapshots


Tech

no

log

y D

rive

rs Includes:

• Cloud stored data

• Storage of farm

data from many

sources used for

decision-making

and data sharing







Top-PowerPoint menu

Ag Retailer Software

Ag Retailer Software

Data

Generation

& Capture

SST Development

Ag Junction

SMS-Ag Leader

Premier Crop

Raven

Computer

Processing

Capacity

SST Development

Ag Junction

Premier Crop

Raven

Delivery

Systems

Ag Retailer agronomists: SST

Farmer’s crop advisors: Premier Crop


Tech

no

log

y D

rive

rs Specialized software

packages used by ag

retailers & advisors

to serve farmers and

for internal logistics

& work orders







Top-PowerPoint menu

Smart Data Deterministic Models

Smart Data Deterministic Models

Data

Generation

& Capture

Farmer Data to Vendor Cloud

Seed company data

Public Data-Weather & Soils

Market Data

Computer

Processing

Capacity

DuPont Pioneer-Encirca

360 Yield Center

My Farms

Delivery

Systems

Encirca-DuPont Pioneer

My Farms

Beck’s Seed


Tech

no

log

y D

rive

rs

• Smart Data is

good quality,

corrected farm

data

• Key variables

with point

estimates

based on

averages


29-01-2015

48






Top-PowerPoint menu

Probabilistic Models

Probabilistic Models

Data

Generation

& Capture

Farm Link/True Harvest

The Climate Corp

AGSOLVER

Computer

Processing

Capacity

The Climate Corp

Farm Link/True Harvest

IBM

Farmer’s Business Network

Delivery

Systems

Farm Link/True Harvest-Benchmark

Climate Basic

AGSOLVER

Farmer’s Business Network

DuPont Pioneer - Encirca


Tech

no

log

y D

rive

rs

• Outcome is a

probability

distribution.

• Models learn

over time.

• Data science

is a critical

input.







Top-PowerPoint menu

Farm Enterprise Systems

Farm Enterprise System

Data

Generation &

Capture

Farmer current vendors and buyers

Farm accounting system

Machine Data in future

Ag Retailer Data

Computer

Processing

Capacity

Conservis

Granular

Farmlogs

MyAgCentral

Delivery

Systems

Advisors to farmer

Vendor IT customer support


Tech

no

log

y D

rive

rs

Integrated software

applications with a

common process.

Includes:

• planning

• purchasing

• field operations

• inventory

• marketing

• accounting &

financial







Top-PowerPoint menu

Deere’s Industry Position

Data is a strategic focus for JD with about 600-800 staff for this effort and

about $1 Billion investment. Target 20%+ of total revenues.

Have been focused on data capture from the JD machines with a

proprietary system being developed:

• Machine data is for JD internal use only

• Production data is shared with agronomic partners

Open to partnering with whoever wants to partner – conditions of the

agronomic partnerships are not public at this point.

JD is not an agronomic company and does not provide agronomic advice

to its customers. Dealers may have agronomists at the local level.

MyJohnDeere.com and dealers are the connection to farmers.

Future priorities are further development of wireless data collection and

use of sensors for in-season crop management.

In August a new set of Data Privacy policies were announced.

29-01-2015

49






Top-PowerPoint menu

John Deere Privacy Summary Pre Aug 2014






Top-PowerPoint menu






Top-PowerPoint menu

29-01-2015

50






Top-PowerPoint menu






Top-PowerPoint menu

Deere: Backend and Frontend

John Deere

Dealers

MyJohnDeere.

com

Dow Agro

BASF

BCS

Dupont

PioneerGrowMark

Ag Gateway

85+ CosJD Link

Farmers

John Deere & Co

Software

Cos. 100+

IT Staff of

600-800







Top-PowerPoint menu

Monsanto-Climate Industry Position

Major strategic priority for MON with about $1.25 Billion invested

and over 400 staff. The Climate Corporation which is working on

a Silicon Valley playbook is the focus for the business.

Key elements of the approach are (1) Measurement of the

farming world; (2) Proprietary Models; (3) Tools to deliver insights

and recommendations to farmers. Wish to compete on the basis

of tools and apps. Do not benchmark. Want a very open system.

Most of the data used is public or Monsanto proprietary but the

models will work better with actual farmer data.

Route to market is via the ag retailers who sell seed and CPC.

Willing to collaborate with everybody – even competitors.

Data Privacy policies revised in June: no longer a license.

Restrictions on sharing within or outside MON.


29-01-2015

51






Top-PowerPoint menu

Climate Privacy Statement






Top-PowerPoint menu

Climate Privacy Statement






Top-PowerPoint menu

Monsanto-Climate: Backend and Frontend

Climate

Agronomy

Reps Climate.com

Crop

Insurance

Agents

Helena

GrowMark

CPS

WinField

LOL

Precision

Planting

Monsanto

Seed GroupCaseIH

Farmers

Climate Corp.

Climate Corp

2-300 IT staff

OADA

9 Cos


29-01-2015

52






Top-PowerPoint menu

Climate CorporationBasic version is free

• Displays field conditions

• Predicts crop growth stages

• Weather modeling

• Mobile apps to display information to support field scouting

• Predicts future rainfall events to help plan field operations

• Provides Basic Revenue Calculations

Climate Pro

• Pay on a per acre basis

• Provides “advisor” options for harvesting, planting, ……

• Advertises an increase of profit by $100/acre

• Real-time revenue projections based on projected yields.

Ability to track previous weather history (use to look at weather information

for a field before you agree to buy/rent it)

Interfaces with FieldView to share information between the two platforms



1/29/2015

157



1/29/2015

158

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Top-PowerPoint menu

SST Position

SST is technology company focused on providing IT technical

infrastructure and Data Processing to agronomic service

providers at the retail level. Have 75 employees and in business

for 20 years.

Globally touch 100+ million acres with 82 million acres in the U.S.

Fertility models for ag retailers are a key product – can be

customized for each retailer and put under a private label.

Data Privacy: “Whoever puts the data into the system is the

Administrator and thus controls the data.” Would like to see

farmers take data ownership, but that is not likely to happen

soon.

Customers can “opt-in” for data aggregation and a benchmark

system has been developed.

AgX is new system that overcomes the current issues with lack of

standards, incompatibility, and fragmentation of services to

farmers.







Top-PowerPoint menu

SST: Backend and Frontend

Ag Retailer B Helena Ag Retailer CAg Retailer A GrowMark

Data

Warehouse

AgX

Platform

Ag

Gateway

Farmers

SST Development Group

SST Software

75-100 staff

Raven

Slingshot







Top-PowerPoint menu

DuPont-Pioneer Position

New Data based services are a strategic priority for Pioneer with

a target of $500 million in 10 years.

It is estimated that 100-200 staff are devoted to this effort

including Encirca and Mapshots.

The Encirca service business is separate in the U.S. from the

Seed sales system and is brand neutral.

Encirca is focused on the technical and economic aspects of

farming with the positioning being to have an impact on

productivity and profitability.

A substantial amount of the backend has been outsourced to

public and private sector partners. Data collection is via

equipment partners and the Encirca sales agents.

Data Privacy Policies have not changed since 2012. Grants

Pioneer a license to the data.


29-01-2015

54






Top-PowerPoint menu

DuPont-Pioneer: Backend and Frontend

Encirca

Sales AgentsEncirca.com

Pioneer Seed

Agents

DTN USDA AGCO

Farmers

Dupont Pioneer

John Deere

& Co

Land Grant

Universities







Top-PowerPoint menu

DuPont-Pioneer Policy Statement

https://encirca.pioneer.com/privacy/






Top-PowerPoint menu

R7 Tool (WinField)

The R7® Tool is a precision farming

solution that gives variable-rate

prescriptions for seed, crop protection and

crop nutrient applications.

Web based data services interface.

Heavily focused on imagery analysis.

Allows Farmers with limited Data (yield and

soil) to develop variable rate maps based

on past satellite imagery, soil maps and

answer plots.

Focused on promoting customer / dealer

interactions and leveraging “Answer Plots”

from across the US.

29-01-2015

55






Top-PowerPoint menu

True Harvest (farmlink.com)

Micro fields

• Managing field in 150 square foot areas

• Compares your fields to benchmark

fields

• Weather, soil and topography

Yield maps

• Precise yield information from their

benchmark fields

• Free of anomalies and Calibration

Errors

Farmers data is on a secure site that can

be used by owners or partners to make

changes to improve there products






Top-PowerPoint menu

FarmLogs (Farmlogs)

Online solution to keep Records

during the farming operation.

• Tracking Rain Fall per field

• Budget Calculator

• Manage Inventory

• Bushels per bin sight

• Operations being done

Information will be shared with their

third parties that are listed in the

agreement but no information will be

sold to other companies without

written consent.



Examples of Existing Data Services Relationships

One Producer/Farm with a Single Solution

Wireless Cloud-based Platform

Manual Transfer


http://www.google.com/url?sa=i&source=images&cd=&cad=rja&uact=8&docid=eEWX_r6RWOAIyM&tbnid=uWVqxN1lRDlL_M&ved=0CAgQjRw&url=http://www.panurgy.com/solutions/storage/&ei=io_3U7vjE5auyATfvYG4Aw&psig=AFQjCNEIcDHoIs6CwShWVX0XF3tG7P5itw&ust=1408819466409851

http://www.google.com/url?sa=i&source=images&cd=&cad=rja&uact=8&docid=eEWX_r6RWOAIyM&tbnid=uWVqxN1lRDlL_M&ved=0CAgQjRw&url=http://www.panurgy.com/solutions/storage/&ei=io_3U7vjE5auyATfvYG4Aw&psig=AFQjCNEIcDHoIs6CwShWVX0XF3tG7P5itw&ust=1408819466409851

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=hx4wxypLE6KPMM&tbnid=daZggFAmHTFZMM:&ved=0CAUQjRw&url=http://www.bridgetreeresearch.com/&ei=h5D3U_vyK5CcyASks4LIBg&bvm=bv.73612305,d.aWw&psig=AFQjCNEXxrs8aLw21AuhTBtFv-F-IjIMvA&ust=1408819670762704




http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=2hI1A9JiXU9hPM&tbnid=G5Gh8poPMHcRGM:&ved=0CAUQjRw&url=http://www.agleader.com/products/agfiniti/&ei=VDbgU4OJMsWPyASYtIHACA&bvm=bv.72197243,d.aWw&psig=AFQjCNHrgqp9u0UzUawvT0W0BQOBuVhcnQ&ust=1407289297702046


http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=LCeurezEf0IQDM&tbnid=Z3zJwJBn-3bErM:&ved=0CAUQjRw&url=http://www.surefireag.com/product/ag-leader&ei=2zfgU7D_GoGtyATnyIGgAw&bvm=bv.72197243,d.aWw&psig=AFQjCNGZaRxmBzUIHNGppMqU5UpMl3Hc-A&ust=1407289686628018


http://www.google.com/url?sa=i&source=images&cd=&cad=rja&uact=8&docid=qTl8qiMnH7HoBM&tbnid=tpBOCrtCADdC7M&ved=0CAgQjRw&url=http://www.hostirian.com/owncloud/&ei=po_3U6-iII6QyATauIHoAw&psig=AFQjCNEX8HmOY1EDwzcbpoykoWf_YxrjgQ&ust=1408819494617240


29-01-2015

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Today’s Common Scenario

Manual Transfer




Today’s Scenario + Wireless

MyJohnDeere.com




Near Future Scenario w/ Wireless

MyJohnDeere.com

API








http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=OmpqLy-qAxF9_M&tbnid=xTGs0Vq289_BiM:&ved=0CAUQjRw&url=http://www.canstockphoto.com/images-photos/wheelbarrow.html&ei=i5H3U4jLL4-tyATNzILgBg&bvm=bv.73612305,d.aWw&psig=AFQjCNEGg9Ru6qyaTWkm8JchGMLxtR76VA&ust=1408819910837085










http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=OmpqLy-qAxF9_M&tbnid=xTGs0Vq289_BiM:&ved=0CAUQjRw&url=http://www.michigan.gov/mdch/0,1607,7-132-2945_42542_42543_42546_42551-151698--,00.html&ei=epH3U-71KI2PyASQooGgCg&bvm=bv.73612305,d.aWw&psig=AFQjCNEGg9Ru6qyaTWkm8JchGMLxtR76VA&ust=1408819910837085










29-01-2015

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Simplified Future Scenario

MyJohnDeere.com

Primary Data

Partner

Parallel Data

Service




Future Scenario: Data Co-Op

APIAPI

Data Co-Op(Third Party)

Standardization

Cleaning

Certification

Anonymization

Aggregation







Top-PowerPoint menu

Precision Ag Data Management

Grain Harvest

Discuss Harvest

Create Yield Map Discuss Yield Map

Plan Seeding

Planting

Create As-Applied MapDiscuss Planting























http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=qg7waTxknGT7ZM&tbnid=pNMvrEH3-lox0M:&ved=0CAUQjRw&url=http://www.myagcommand.com/&ei=yjTgU9SwC4SuyATggoGIBw&bvm=bv.72197243,d.aWw&psig=AFQjCNEbPCcmBOZqIMjGQ3rC-64nLUO-pA&ust=1407288894997018

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=qg7waTxknGT7ZM&tbnid=pNMvrEH3-lox0M:&ved=0CAUQjRw&url=http://www.myagcommand.com/&ei=yjTgU9SwC4SuyATggoGIBw&bvm=bv.72197243,d.aWw&psig=AFQjCNEbPCcmBOZqIMjGQ3rC-64nLUO-pA&ust=1407288894997018

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=V9r8X71gn-qIDM&tbnid=xgJJLOz0DfxvJM:&ved=0CAUQjRw&url=http://www.chandlersfe.co.uk/precision-farming.htm&ei=5TTgU773CceRyAS7lILQBA&bvm=bv.72197243,d.aWw&psig=AFQjCNEbPCcmBOZqIMjGQ3rC-64nLUO-pA&ust=1407288894997018

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=V9r8X71gn-qIDM&tbnid=xgJJLOz0DfxvJM:&ved=0CAUQjRw&url=http://www.chandlersfe.co.uk/precision-farming.htm&ei=5TTgU773CceRyAS7lILQBA&bvm=bv.72197243,d.aWw&psig=AFQjCNEbPCcmBOZqIMjGQ3rC-64nLUO-pA&ust=1407288894997018

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=1-7jAJWStxMXbM&tbnid=ysBzt4vHAlIx4M:&ved=0CAUQjRw&url=http://precision.agwired.com/2014/06/20/trimble-adds-to-their-connected-farm-solution/&ei=pDXgU5ocy7DIBJuogPAP&bvm=bv.72197243,d.aWw&psig=AFQjCNFt_KXNtMiyRsVkRja-UFFQrHwKuQ&ust=1407288987948674

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=1-7jAJWStxMXbM&tbnid=ysBzt4vHAlIx4M:&ved=0CAUQjRw&url=http://precision.agwired.com/2014/06/20/trimble-adds-to-their-connected-farm-solution/&ei=pDXgU5ocy7DIBJuogPAP&bvm=bv.72197243,d.aWw&psig=AFQjCNFt_KXNtMiyRsVkRja-UFFQrHwKuQ&ust=1407288987948674

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=vm31rJS25iI4VM&tbnid=1O2axe9JRyPnQM:&ved=0CAUQjRw&url=http://www.farmingwithapps.com/2013/01/31/connected-farm/&ei=5DXgU-WvI5a3yAT8xYL4BA&bvm=bv.72197243,d.aWw&psig=AFQjCNFt_KXNtMiyRsVkRja-UFFQrHwKuQ&ust=1407288987948674

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=vm31rJS25iI4VM&tbnid=1O2axe9JRyPnQM:&ved=0CAUQjRw&url=http://www.farmingwithapps.com/2013/01/31/connected-farm/&ei=5DXgU-WvI5a3yAT8xYL4BA&bvm=bv.72197243,d.aWw&psig=AFQjCNFt_KXNtMiyRsVkRja-UFFQrHwKuQ&ust=1407288987948674







29-01-2015

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Top-PowerPoint menu

Managing Your Role with Customer Data and VRS

When to call the machinery dealer:

• Display won’t power on.

• No GPS reception.

• Yield maps don’t show up on the

monitor.

• Planter clutches won’t engage.

• Planter seeding rates fluctuate rapidly.

• Trouble codes come up on the

display.

• Don’t become liable for a

machinery problem!

Producers own their data. Example

Best Practices:

• Keep all yield maps in a binder with a

cover page and never leave the

binders in a public area.

• Immediately download and return data

cards to producers. Don’t leave the

data cards sitting around an office or

open area.

• Have a clear conversation with the

grower about who else should have

access to this data. i.e. independent

crop consultant or fertilizer rep






Top-PowerPoint menu

Hardware Memory Classes

No Internal Memory

• All data is recorded directly to the

memory card.

Internal Hard Drive Memory

• Data is recorded on the display.

• Data is transferred once a

memory card is installed.






Top-PowerPoint menu

Data Management: Introduction

File formats are unique to

each manufacturer and

can also change within a

manufacturer after a

firmware update.

Data storage hardware

can vary significantly

between brands and some

require special handling

equipment.

USB Jump

Drive

Compact

Flash Card

PCMCIA

Card

29-01-2015

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Top-PowerPoint menu

As-Applied Data Management Architecture

Proper data management is critical

to having data to analyze at the end

of the year:

• Grower (i.e. Bob Smith)

• Farm (i.e. Home)

• Field (i.e. East 80)

• Year (i.e. 2012)

• Operation (i.e. Planting)

• Product (i.e. Pioneer 92Y30)






Top-PowerPoint menu

Data Management

A copy of the data is retained on

the display.

Data must be deleted through

the display user interface.

• Deere

• AGCO

Copy & Paste Cut & Paste

Data is deleted from the display after it is

copied to the data card.

• Ag Leader Integra

Care should be taken to prevent loss of

the memory card!






Top-PowerPoint menu

Step 1: Organizing Your Files

180

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Top-PowerPoint menu

Step 2. Generating and Organizing VRS Shapefiles

A “Shapefile” is actually a group of four

individual files (.shp, .shx, .dbf, .prj).

All four files must be in the same directory

for the “Shapefile” to be readable.

“Shapefiles” are a generic file type which is

readable by several displays.






Top-PowerPoint menu

Step 3: Transfer Files to a Grower’s Data Card






Top-PowerPoint menu

Step 3: Transfer Files to a Grower’s Data Card

John Deere Displays (2600 & 2630):

• Create an “Rx” folder on the highest level of the data card, i.e. “E:\Rx”

• Place the shapefiles directly into this folder

Ag Leader Displays (Insight, Edge, Integra, Versa)

• Create an “Rx” folder on the highest level of the data card, i.e. “E:\Rx”

• Place the shapefiles directly into this folder

Precision Planting Displays (20/20)

• Place the shapefiles directly into the top level of the USB drive, i.e.

“E:\”

Case Displays

• Not compatible with shapefiles. FIT can produce prescription setup

files, but care should be taken when merging with producer data.

29-01-2015

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Top-PowerPoint menu

Pioneer Support Documents

Brand new support documents for variable rate implementation are

available through the Pioneer training portal.






Top-PowerPoint menu

Ag Leader Integra “Watch out for this”

Data Formats:

• Integra’s prior to V3 and all Insights, data will be in the .ilf

file format, not .agdata format. DO NOT attempt to

upgrade customers Integra!

Export Data:

• This is a CUT Paste process and this will be the only copy

of the farmers data.

VRS Prescriptions:

• Prescriptions don’t save to the internal memory of the

display the USB will need to stay with the farmer at all

times.

• Shape files for the Integra and Insight displays require

units of Seeds Per Acre. Prescription shapefiles with units

of thousands of seeds per acre or kseeds per acre will not

work correctly.

• Can be Contoured or Surface maps

Split Planter:

• Display needs to be Unlocked for Multiple Product, Please

Contact the Equipment provider for more assistance.

185



Ag Leader Integra “How To”

Press the target rate to

expand the tab.

With the USB in the monitor

press the wrench.

Rate Control Settings: press the

USB under Rx.Highlight the file being used

then press the right arrow.

29-01-2015

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Ag Leader Integra “How To”

Select the variety in your column,

the preview window need to show

seeds per acre, press checkmark.

The Rx icon should show a negative

sign this means the Rx has been

loaded press back to exit.






Top-PowerPoint menu

Case IH Pro 700 “Watch out for this”

Data:

• File format needs to be .cn1

• Can only be one .cn1 on USB: Grower, Farm,

Field and Guidance lines are saved on the display

and USB drive

Exporting Data:

• Make sure Display and tractor are completely shut

off before removing USB.

• The USB is the only copy of the Data

VRS Prescriptions:

• USB Must be in Display at ALL times while Logging

Data

• Grower, Farm, Field need to be spelled and

Capitalized EXACTLY like the monitor for Guidance

lines to be able to work.

• Needs to be Kilo Seeds

• Can only be a Contoured map

188



Case IH Pro 700 “How To”

Press the Performance button

than scroll to Rx Setup.

Select the Grower, Farm and Field

that is to be planted by pressing

on the box under the title.

Press the Prescription down arrow

to choose from the prescription on

the USB.

Make sure there is an out

of zone rate this will be in

kilo seeds per ac.

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Case IH Pro 700 “How To”

Press on the Run

screen and go to

the mapping

screen.

Click on the Layer tab to change the data type to

seed along with data and Rx style’s to color.

Click on Legends, change the legends to

the seeding rates for the prescription.






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John Deere GS3 “Watch out for this”

Data:

• Shapefiles need to be in a Rx folder on the

root drive

Exporting Data:

• GS2 Compact Flash Drive is the only Copy

• GS3 USB can Be copied as Many times as

needed

VRS Prescriptions:

• Can only import 500 Shapefiles into Display.

• The Rx button will not be present if it more

than 500 exist

• Units need to be Seeds per acre


• File name will only display 26 character on

the display

191



John Deere GS3 “How To”

Press on the GS3

button and go to the

Summary tab.

Make sure Client, Farm, Field and task

are correct. Press on the Rx to select

the VRS map.

In the prescription window select

Shapefile under the drop down

menu.

Press on the box next to shapefiles to

select the correct field. Make sure to

change the column to Tgt_Rate_s. The

product type should be seeds by seed

count.

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John Deere GS3 “How To”

Enter in out of field and loss

of GPS rates by selecting

the boxes this is in s/ac.

Press Accept.

Check to make sure everything looks good

on the Shapefile Conversion and

Prescription page press Accept after

checking both pages.

Prescription

should show up






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Precision Planting “Watch out for this”

Data:

• Shapefiles have to be on the root file of

the USB NOT in a folder

• Shapefiles will save on the display

Exporting Data:

• Can Transfer all of the data at once or

select certain fields

• Data remains on the display

VRS Prescriptions:


• Shapefile names can’t exceed 60

characters

194



Precision Planting “How To”

Press setup and than

the field box.

Verify the Client Farm information

than Press the field. On the Field

Setup page press on the

Prescription box.

Press the Boundary file to be the

prescription file press enter to

continue.The seeding prescription attribute will

be target_rat press enter to continue.

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65



Precision Planting “How To”

From the field setup page

press home.

If the tractor is in the field corresponding

to the prescription the RowFlow field

should have a green box indicating it is

planting the variable rate map. Press on

the RowFlow field.

From the RowFlow Setup window you

will be able to see the Current and Next

Rate if everything is working properly.






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Trimble FMX “Watch out for this”

Data:

• Has to be an AG GPS file format

• If you use the FMD file Format

• Map will appear but won’t plant

Exporting Data:

• Data remains on the display

VRS Prescriptions:

• Can only be Contoured maps

• Can only be Kilo Seeds

• The Field-IQ Mater Switch-Box Target Rate

needs to be flipped to Rate 1 before Planting

operation starts this will ensure that the

Seeding rates will be planted accordingly to

the Prescription map.

• Make sure to have shutoffs to A mode or

automatic.

• A prescription can’t be selected until the

operation has been started

• Prescription map will only appear if you’re

within 1.5 miles from the field197



Trimble FMX “How To”

On the

prescription

page highlight

the prescription

Rate Column will be the Variety

being planted.

Press on prescription scale

factor to enter in the scale factor.

Note: This needs to be done the

display assumes everything is in

hectares. Scale factors are

given press ok to move on.

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66



Trimble FMX “How To”

The Field-IQ Mater Switch-Box

Target Rate needs to be flipped to

Rate 1 before Planting operation

starts this will ensure that the

Seeding rates will be planted

accordingly to the Prescription

map. Also make sure to have

shutoffs to A mode or automatic.

The Map Screen will appear with

Prescription map as the background.

The Layers icon allows you to choose if

the Prescription, Variety and etc. maps

are showing up on the mapping screen.

If you press on the drop down arrow you

can select different options.

Layers

View drawing guides



guides on screen’

3. Select ’OK’

View drawing guides



guides on screen’

3. Select ’OK’


WRAP UP AND QUESTIONS







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Yield Monitor: When to Calibrate

When changing crop

type (i.e. between

soybeans and corn)

When crop properties

change significantly

• Moisture > 4%

• Test Weight

• Tough crop requires

changes in ground speed

(i.e. downed corn)

Dr. Matt Darr

Agricultural and Biosystems

Engineering

29-01-2015

67






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Hybrid B

Hybrid A






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NDVI Imagery. Green = healthy plants, Red = bare soil

How many decision opportunities can you spot?

29-01-2015

68






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American Farm Bureau Data Services Questions

Do I own the data?

How will my data be used and what benefits can I expect from allowing a

provider to include my data in a “Big Data” database?

Will I control the management of that data?

What is aggregation of data? How does aggregation protect me?

Is my personal farm data anonymized? How is “anonymize” defined?

Can I stop sharing my data once I have agreed to share?

Who else might have access to my data? Can it be released to the public

or to a third party?

What is the value of my data to ME?

What is the value of my data to the COMPANY?

What type of security protocols are in place to protect against cyber

hacking and data piracy? How will the “bank” avoid a Target incident?

Is the “bank” independent or are they also trying to provide agronomic or

business management services?






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Pioneer Support Documents

Brand new support documents for variable rate implementation are

available through the Pioneer training portal.