2. 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

3. 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

4. Motivation
, 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

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

6. 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.

7. 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

8. Which relationships are useful? Do these maps establish causality?
Challenge of PA technologies: Translation of GIS crop layers into information for farm management decisions requires many steps...
Yield + =
CEC K Zn pH OM S P Mg Fe Mn Ca B
Inputs
Skill
???
Relating back to Miller et al., MAPS DO NOT ESTABLISH CAUSALITY
Which relationships are useful?
Do these maps establish causality?
Data source: Fairholme Farms, Lewiston County, IN

9. 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

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

11. Bringing Data into GIS Software

12. Bringing Data into GIS Software

13. Identifying Soil Types

14. Identifying Soil Types

15. Identifying Soil Types

16. Identifying Soil Types

17. Identifying Spatial Structure of Soil Attributes: pH

18. Identifying Spatial Structure of Soil Attributes : P

19. Identifying Spatial Structure of Soil Attributes : %OM

20. Identifying Spatial Structure of Soil Attributes : Zn

21. Identifying Spatial Structure of Soil Attributes : K

22. Identifying Spatial Structure: Corn Yield Map

23. Identifying Spatial Structure: Soybean Yield Map

24. Yield clusters vary significantly across field

25. 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

26. 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

27. 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

28. 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)

29. 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.

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

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

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

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

35. 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