1. Case Study Evidence of New Opportunities for Farm Management Specialists in Spatial Analysis of On- farm Trial Data Terry Griffin 1, Craig Dobbins 2, Jess Lowenberg-DeBoer 2 1 University of Arkansas – Cooperative Extension Service 2 Department of Agricultural Economics, Purdue University National Farm Management Conference

2. Motivation On-farm trials often violate statistical assumptions Farmers continue to conduct on-farm trials –PA and GPS lead to resurgence of on-farm trials –Harvested with yield monitors w/out interference Reduced public research funding –More weight on local on-farm experiments Farmers’ objective: make best decision

3. Goal of Case Study Research Better understand the motivations of farmers for conducting field-scale experiments and document their perceptions of spatial analysis Propose plan to Extension and industry for spatial analysis service

4. Research Methods Case studies evaluated perceptions of conducting on-farm research and spatial analysis Qualitative research methods Lack of general information to conduct quantitative survey

5. Multiple Case Study Data Reference and comparison group farmers –IL, IN, KY, Ontario Direct 3 year observation of reference group –During farm-visits, frequent communication –Farmers conducting field-scale on-farm trials –Spatial analysis reports provided to farmers One-on-one interviews of both groups Two yield monitor data analysis workshops

6. Spatial Analysis: A Definition Spatial statistics assume that data is spatially correlated and explicitly included in analysis; in contrast to independent observations assumption. Yield monitor and 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.

7. Spatial Analysis Reports Description of on-farm trial –Design, treatment, data available Data handling procedures –Yield data filtering, data assimilation Spatial statistical analysis and diagnostics Economic analysis Production recommendation

8. 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 End result is more reliable informationEnd result is more reliable information –A production recommendation –Not a map Photo: Griffin – Twilight Farms

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

10. Yield data in GIS after removing erroneous observations

11. Study area Yield data in GIS after removing erroneous observations

12. Yield monitor data used in analysis

13. Rate trial: 80K to 160K seeds per acre Four replications of five population rates { { { { 1 2 3 4

15. Major soil Secondary soil All five rates on each soil “zone” { Minor eroded soil

16. Spatial Error Estimation Variable Spatial error Coefficientt-Statistic CONSTANT64.141***17.38 POP0.176***3.50 POP_SQ-0.001***-2.81 Soil 3 -246.321-1.01 Soil 2 -356.830***-3.92 POP*Soil 3 0.117***5.44 POP_Soil 2 0.023***2.59 ELV*Soil 3 0.2710.94 ELV*Soil 2 0.417***3.86 POP*ELV-0.002-1.49 ELV-0.500***-3.21 LAMBDA0.78163.11

17. 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

18. Yield Data Analysis Workshops November 2005 and March 2007 Farmers, consultants, university personnel

19. Who should conduct spatial analysis? Farmers –some farmers perform own spatial analysis University Extension –Technical skill, but can only work directly with a few farmers Private industry –farmers, co-op, dedicated analysts, consultants

20. Role of Extension Assist with designing experiments Network of research collaborators –Regional research projects Continued education/training for analysts Troubleshooting and problem solving Teaching interpretation of analysis Assist with decision making

21. Comparative Advantage for Farm Management Analysts Already dealing with vast amounts of data Familiar with assisting interpretation of results Assist with whole-farm decision making

22. Farmers’ Willingness to Pay Will farmers be willing to pay a fee that entices qualified analysts to offer service? FarmerDFWPT What would you expect to pay for full-service spatial analysis? $3 per acre $5 per acre or $500 per trial. Percent of predicted value. Up to several hundred dollars. $2 per acre. Up to $500 per trial. $5 to $10 per acre or 40 to 50% of payback.

23. Third-party Spatial Analysts Questions What software to assemble the data? What software to statistically analyze the data? –R, GeoDa, Stata, SpaceStat, MATLAB, SAS What type of spatial analysis conducted? –How characteristics of neighboring data used? Where received spatial analysis training? How confident are you in the results? Does client receive copy of original or raw data? Is focus on providing maps or recommendations?

24. Conclusions More confidence in data and decisions when using spatial analysis –Farmers made more decisions more quickly Unclear who will be primary analysis provider Role for Extension and private sector industry –Depends upon farmers’ willingness to pay –Will any tax money be put into this? –Are any public goods generated? Farm management specialists may be among the first to demonstrate benefits of the yield monitor

25. Wish to thank USDA-SARE for providing funding to evaluate alternative on-farm designs and develop spatial analysis methods

26. Terry Griffin tgriffin@uaex.edu 501.249.6360(O) Craig Dobbins cdobbins@purdue.edu Jess Lowenberg-DeBoer lowenbej@purdue.edu