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USING GIS CROP INFORMATION TO DETERMINE SITE-SPECIFIC MANURE MANAGEMENT RECOMMENDATIONS

USING GIS CROP INFORMATION TO DETERMINE SITE-SPECIFIC MANURE MANAGEMENT RECOMMENDATIONS. Dayton Lambert a , Gary Malzer b , and Jess Lowenberg-DeBoer a. a Department of Agricultural Economics, Purdue University West Lafayette, Indiana

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USING GIS CROP INFORMATION TO DETERMINE SITE-SPECIFIC MANURE MANAGEMENT RECOMMENDATIONS

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  1. USING GIS CROP INFORMATION TO DETERMINE SITE-SPECIFIC MANURE MANAGEMENT RECOMMENDATIONS Dayton Lambert a, Gary Malzer b, and Jess Lowenberg-DeBoer a a Department of Agricultural Economics, Purdue University West Lafayette, Indiana b Department of Soil, Water, and Climate, University of Minnesota SOURCE: The Whitecap foundation

  2. Organization • Motivation and Background • Using GIS information to make on-farm manure management decisions: an example using Variable Rate Manure (VRM) • Regression analysis of on-farm trial • Economic Results for VRM Trial • Site-specific Manure (SSM) and Whole-field (WF) Profitability Comparison • Comparison of economically optimal rates (EOR) • Using GIS to establish buffers for water-shed management • Conclusions

  3. Motivation • 1982-1997, Heartland showed greatest percentage increase in excess on-farm manure nutrients • 2% of the large class farms (> 1000 AU) produce 50% of the excess manure nitrogen (N) and phosphorous (P) • About 75% of US counties have one farm that needs to transport manure to avoid excess nutrient loading • 5% of US counties have farms that produce enough manure to meet 50% of the N needs for the entire county • 10% of US counties have farms that produce enough manure to meet 50% of the P needs for the entire county SOURCE: Gollehon et al., 2001. SOURCE: The Whitecap foundation

  4. Assimilative capacity of land and watersheds is challenged with recent boom in livestock/poultry sector SOURCE: Ribauldo, 2003.

  5. Motivation • In 2000, EPA proposed new regulations to compel large poultry and livestock operations to manage manure with a nutrient management plan • Regulations were implemented in 2003 as the “Unified National Strategy for Animal Feeding Operations” • Goal: Minimize water quality impacts from improperly managed animal manure • Focus on large operators (more than 1000 Animal Units, AU) SOURCE: Ribauldo, 2003.

  6. Motivation • Can Precision Agriculture (PA) and related technologies help producers better manage animal manure? • How can GIS information be used? • Can manure disposal plans include SSM of animal manure? • When is SSM of manure profitable? SOURCE: The Whitecap foundation

  7. CEC K Zn pH OM Ca + + + + + Yield P Mg Fe Mn S B + + + + + = + Inputs + Skill + ??? Challenge of PA technologies: Translation of GIS crop layers into information for farm management decisions requires many steps... Which relationships are useful? Do these maps establish causality? Data source: Fairholme Farms, Lewiston County, IN

  8. To address these questions, a Variable Rate Manure (VRM) on-farm trial was conducted in Sleepy Eye, Minnesota * Geo-referenced weigh wagon data* Spatially detailed soil test information* 1999 (corn), 2000 (soybean) strip trial*0, 2000, 4000, 6000, 8000 gal/acre

  9. Experiment Hogs Wetland area Source: Dr. Gary Malzer

  10. Bringing Data into GIS Software

  11. Bringing Data into GIS Software

  12. Identifying Soil Types

  13. Identifying Soil Types

  14. Identifying Soil Types

  15. Identifying Soil Types

  16. Identifying Spatial Structure of Soil Attributes: pH

  17. Identifying Spatial Structure of Soil Attributes: P

  18. Identifying Spatial Structure of Soil Attributes : %OM

  19. Identifying Spatial Structure of Soil Attributes : Zn

  20. Identifying Spatial Structure of Soil Attributes : K

  21. Identifying Spatial Structure: Corn Yield Map

  22. Identifying Spatial Structure: Soybean Yield Map

  23. Yield clusters vary significantly across field

  24. Soil tests correlate strongly with other soil test variables in some locations, and less so in others Conditional scatterplots: P vs Zn Relation between variables is site-specific

  25. Management Zones Are Defined using Soil Test Information In this study, P-Bray soil test levels were Used as a proxy for management zones Since this variable correlated strongly with K, pH, and Zn

  26. Spatial Regression Model to Identify Site-specific yield response to manure • Yield = f(manure, soil characteristics, management zones) • Spatial regression analysis used to estimate yield response to manure in management zones (Anselin, 1988) • Yield response estimates used to evaluate profitability and optimal manure rates

  27. 7 Management Strategies Compared • Variable Rate Manure (VRM) • Whole-field Manure (WFM) based on extension recommendations (3500 gal/acre) • VRM-Whole field P, K, and lime (WFF, based on extension recommendations) • VRM-variable rate P, K, lime (VRM-VRA) • WFM-VRA • WFM-WFF • WFM*-VRA (evaluated at whole field EOR)

  28. Results: Yield response to manure varies significantly across the site *All yield response zones for corn were different from the whole-field (WF) average at the 5% level, except Zone 3. *All yield response zones for soybean were different from the WF average at the 5% level.

  29. Results: Site-specific manure application is different, depending on the Management Strategy

  30. If an upper limit on application is in place, less manure can be applied without compromising profit

  31. Sensitive areas can be documented… SOURCE: Terry Griffin

  32. …and buffers can be established SOURCE: Terry Griffin

  33. Conclusions • GIS can be used to help producers make decisions about managing fertility with manure • Compared to extension recommendations, less manure per acre can be applied using VRM combined with a variable rate P, K, and lime program • Because of product homogeneity problems, a WFM-VRA strategy may be more profitable if EOR manure rates are used at the whole field level SOURCE: Wood-Land-Lakes RC&D, DeKalb, Elkhart, LaGrange, Noble, Steuben & Whitley counties, Indiana

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