Effectively Using GPS in Management

Terry Griffin & Jess Lowenberg-DeBoer

Site Specific Management Center

Purdue University

• Objective of on-farm trials is different from Objective of on-farm trials is different from research trialsresearch trials

• Farmers want to make the best economic Farmers want to make the best economic decisions for their operationdecisions for their operation

• Most farmers do not care about underlying Most farmers do not care about underlying mechanisms or whether results are generalizablemechanisms or whether results are generalizable

• For on-farm trials we need to shift focus away For on-farm trials we need to shift focus away from research to farm management decision from research to farm management decision makingmaking

MotivationMotivation

Photo: Farmphotos.com

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Issues in Yield Data Analysis

• Why spatial analysis is important

• Quality yield monitor data – Cleaning data

• On-farm comparisons– Good experimental design– Good research question

• Who offers quality spatial analysis?

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Spatial Analysis: A Definition

• Spatial statistics assume that data is spatially correlated and explicitly includes that in the analysis. This is in contrast to the usual assumption of independent observations.

• Most yield monitor and other site-specific data is spatially correlated. If that correlation is not accounted for in the analysis, results will be biased and misleading.

• Yield monitor data with appropriate spatial analysis can lead to more reliable decision making with limited replications.

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“Eyeballing” vs Spatial Analysis • The most common analysis for yield monitor

data is “eyeballing” the maps to identify patterns.

• The human brain is good at finding visual patterns. – It finds them whether they are there or not.

• Spatial analysis reduces the subjectivity in analysis of yield monitor and other precision agriculture data

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Spatial Effects in Point Patternsby location not necessarily by value

RandomClustered Uniform/regular

Quiz!

Clustered!

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Data Quality• Under certain conditions, harvester unable

to make accurate measurements

• Remove erroneous data with protocol– www.purdue.edu/ssmc

• Yield Editor software (USDA-ARS)

http://www.fse.missouri.edu/ars/YE/YE_Reg.ASP

Flow Delay = 8 secondsStart Pass Delay = 8 secondsMax Velocity = 6 mphMin Velocity = 3.5 mph“Smooth” Velocity = 20%Maximum Yield = 330 buMinimum Yield = 50 buSTD Filter = plus/minus 3

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On-Farm Comparison Examples Using Spatial Analysis

• Soybean seeding rate in Montgomery County

• Nitrogen timing in Fayette County

Example On-Farm TrialExample On-Farm Trial

• Central Indiana soybean seeding rate trialCentral Indiana soybean seeding rate trial– 80, 100, 120, 140, and 160K seeds per acre80, 100, 120, 140, and 160K seeds per acre– 4 replications in 1700 foot strips4 replications in 1700 foot strips– 30 inch rows30 inch rows

• Planter tractor has RTK-GPS auto-guidancePlanter tractor has RTK-GPS auto-guidance• End result is more reliable informationEnd result is more reliable information

– A production recommendationA production recommendation– Not a mapNot a map

Photo: Griffin – Twilight Farms

Raw yield monitor data • As-is from the combine• No cleaning or filtering

Yield data in GIS after removing erroneous observations

Study area

Yield data in GIS after removing erroneous observations

Yield monitor data used in analysis

Rate trial: 80K to 160K seeds per acre

Major soilSecondary soil

Minor eroded soil

2004 Soybean Seeding Rate Study

50

55

60

65

70

60 80 100 120 140 160 180

Seeding rate (000 seed ac-1)

Yie

ld (b

u ac

-1)

Major soil Secondary soil Minor soil

Major soil: 130K yield maxMajor soil :

100K profit max

Secondary soil: 150K yield maxSecondary soil:

120K profit max

Can reduce input costs by lowering seeding population from 130K to about 100K on most of the field, increasing planting timeliness

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On-farm Nitrogen Timing Study

• N-Timing study example– Treatment A: “Preplant” 100% of N at planting– Treatment B: “Sidedress” 100% of N at sidedress– Treatment C: “Split” 50:50 planting and sidedress

Raw yieldmonitor data

Cleaned and filtered yieldmonitor data

With Yield Editor from USDA-ARS

Corn following corn

Corn followingsoybean

{

{Sp

lit N

Side

dres

s NPr

epla

nt NSp

lit N

Split

N

Prep

lant

N

Proposed N timing experimental design

Corn following corn

Corn followingsoybean

{

{

N timing experimental design and field layout

Split N

Sidedress N

Split N

Preplant N

Soil A

Soil B

150

160

170

180

190

200

210

220

Other Soils Soil A

Cor

n Y

ield

(bu/

ac)

.

Planter Split Sidedress

Corn Response to N Timing

Economic Results of N Timing using custom application rates

380

400

420

440

460

480

500

520

540

Other Soils Soil A

Rev

enue

min

ues

appl

icat

ion

cost

s

.

Planter Split Sidedress

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On-Farm Experimentation Summary

• Spatial analysis converts farm-level data to farm management decision making– Verify regional recommendations – Fine-tune farm-level response

• More confidence in results and decisions

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Suggestions for On-Farm Trials

• Experimental designs include each treatment on each “zone”

• Electronically record as much as possible

• Must have planned comparison – testable question– data mining techniques not yet developed

Extension’s RoleExtension’s Role• Support on-farm & field-scale research

– Suggest appropriate experimental design

– Guide selection of treatments

• Facilitate spatial analysis

• Teach interpretation of analysis results

• Assist farm management decision making

• Make regional recommendations that often serve as a

starting point for on-farm testing

Photo: Griffin – Twilight Farms

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Purdue Offers Spatial Analysis at the Top Farmer Crop Workshop

• Participants bring on-farm trial data• Spatial Analysis team analyzes data• Farmers taught to interpret results• The 39th Annual Top Farmer Crop

Workshop planned for July 16-19, 2006 • Winter Yield Monitor Data Workshop

– November 14, 2005

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Summary

• Most farmers do on-farm comparisons. – need reliable information for decision-making

• Spatial analysis converts data to information• Extension can coordinate these relationships• Winter Top Farmer Yield Monitor Workshop

– November 14, 2005

• Research supported by NCR USDA-SARE graduate student research grant

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Jess Lowenberg-DeBoer765.494.4230lowenbej@purdue.edu

Terry Griffintwgriffi@purdue.edu765.494.4257

Site-Specific Management Centerwww.purdue.edu/ssmc

Top Farmer Crop Workshopwww.agecon.purdue.edu/topfarmer

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Software tools

• ESRI ArcGIS

• Yield Editor (USDA-ARS)

• GeoDa

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Free Software

• Yield Editor – USDA-ARS (Drummond, 2005)– http://www.fse.missouri.edu/ars/YE/YE_Reg.ASP

• GeoDa University of Illinois (Anselin, 2005)– https://www.geoda.uiuc.edu/

• ArcGIS or ArcView GIS – ESRI (Redlands, CA)– http://www.esri.com

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Free ArcView 3.X Extensions

• XTools – http://arcscripts.esri.com/details.asp?dbid=11526

• Minnesota DNR– http://www.dnr.state.mn.us/mis/gis/tools/arcview/

• Jenness Enterprises– http://www.jennessent.com/arcview/arcview_extensions.htm

• SpaceStat ArcView Extension – TerraSeer (Anselin)– http://www.terraseer.com/products/spacestat.html