Effectively Using GPS in Management Terry Griffin & Jess Lowenberg-DeBoer Site Specific Management Center Purdue University

Objective of on-farm trials is different from research trialsObjective of on-farm trials is different from research trials Farmers want to make the best economic decisions for their operationFarmers want to make the best economic decisions for their operation Most farmers do not care about underlying mechanisms or whether results are generalizableMost farmers do not care about underlying mechanisms or whether results are generalizable For on-farm trials we need to shift focus away from research to farm management decision makingFor on-farm trials we need to shift focus away from research to farm management decision making Motivation Photo: Farmphotos.com

3 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?

4 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.

5 “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

7 Spatial Effects in Point Patterns by location not necessarily by value RandomClusteredUniform/regular Quiz! Clustered!

8 Data Quality Under certain conditions, harvester unable to make accurate measurements Remove erroneous data with protocol – Yield Editor software (USDA-ARS)

Flow Delay = 8 seconds Start Pass Delay = 8 seconds Max Velocity = 6 mph Min Velocity = 3.5 mph “Smooth” Velocity = 20% Maximum Yield = 330 bu Minimum Yield = 50 bu STD Filter = plus/minus 3

11 On-Farm Comparison Examples Using Spatial Analysis Soybean seeding rate in Montgomery County Nitrogen timing in Fayette County

Example On-Farm Trial Central Indiana soybean seeding rate trialCentral Indiana soybean seeding rate trial –80, 100, 120, 140, and 160K seeds per acre –4 replications in 1700 foot strips –30 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 recommendation –Not 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 soil Secondary soil Minor eroded soil

2004 Soybean Seeding Rate Study Major soil: 130K yield max Major soil : 100K profit max Secondary soil: 150K yield max Secondary 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

21 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 yield monitor data

Cleaned and filtered yield monitor data With Yield Editor from USDA-ARS

Corn following corn Corn following soybean { { Split N Sidedress N Preplant N Split N Preplant N Proposed N timing experimental design

Corn following corn Corn following soybean { { N timing experimental design and field layout Split N Sidedress N Split N Preplant N

Soil A

Soil B

Corn Response to N Timing

Economic Results of N Timing using custom application rates

33 On-Farm Research Results Split application highest yield AND profit On-farm tests provide reliable information

34 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

35 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 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

37 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 39 th Annual Top Farmer Crop Workshop planned for July 16-19, 2006 Winter Yield Monitor Data Workshop –November 14, 2005

38 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

39 Jess Lowenberg-DeBoer Terry Griffin Site-Specific Management Center Top Farmer Crop Workshop

40 Software tools ESRI ArcGIS Yield Editor (USDA-ARS) GeoDa

41 Free Software Yield Editor – USDA-ARS (Drummond, 2005) – GeoDaUniversity of Illinois (Anselin, 2005) – ArcGIS or ArcView GIS – ESRI (Redlands, CA) –

42 Free ArcView 3.X Extensions XTools – Minnesota DNR – Jenness Enterprises – SpaceStat ArcView Extension – TerraSeer (Anselin) –