Transcript Slide 1

Decision Making Tools for N
Management in Corn and
Wheat: a U.S. Perspective
C.S. Snyder, PhD, CCA
Nitrogen Program Director
Acknowledgements
• IPNI
• Paul Fixen
• U. of Nebraska
– Richard Ferguson
•
•
•
Tom Bruulsema
Scott Murrell
Steve Phillips
• Oklahoma State U.
– Bill Raun
• Iowa State U.
– John Sawyer
• Virginia Tech. U.
– Steve Phillips (IPNI),
Mark Alley
Public Perception ….. Ag is Bad Actor
A Need for Industry to be More Proactive?
Nitrogen Use Efficiency
• “…… estimated NUE for cereal
production ranges from 30 to 35%.”
Corn grain produced in the U.S. per unit
of fertilizer N used, 1964 to 2005.
1.4
1.15
bu per lb of N
1.3
1.2
*
1.1
1.0
0.9
0.76
0.8
0.7
0.6
*Application rate for 2004 estimated as avg of 2003 & 2005.
0.5
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Since 1975:
51% increase in N efficiency
12% increase in N fertilizer use
Data sources: USDA Ag Chem Use Survey & Annual Crop Production.
Effects of Crop Harvest N Removal on
Net Anthropic Nitrogen Input (NANI)
Figure 1. Net anthropogenic N input (NANI) in major sub-basins of
the Mississippi River Basin estimated from state level statistics.
Source: McIsaac, 2006.
Increased Farmer Interest in
Better N Management
• Increased N costs
• Better crop prices
• Calibration and
verification of
newer technologies
• Improved farmer
skills and availability
of professional
guidance
by crop advisers
“The Market” Nov.1, 2007
USGS Spatial Modeling
of Stream Nutrient Flux
SPAtially Referenced Regression on Watershed Attributes
(Smith et al., Water Resour. Res., 1997)
Source: Personal comm. – R. Alexander. USGS
Kg/ha
.01
.01- 0.1
0.1 to 1
1 to 5
5 to 10
>10
N Loss Consequences Requiring
Management Attention
• Decreased crop production and profitability
– Inefficient land use, reduced performance of other
crop inputs, reduced water use efficiency
• Water resource contamination
– eutrophication: lakes, streams, rivers, estuaries
– groundwater contamination
– coastal water contamination - urea and harmful algal
blooms (neurotoxin poisoning)
• Air pollution
– Ammonia and particulates, nitrous oxide and NOx
(global warming, stratospheric ozone depletion, acid
rain)
U.S. Consumption of N Sources
30,000,000
Short tons of fertilizer
25,000,000
Other
20,000,000
Am. thiosulfate
Am. sulfate
15,000,000
N Soln.
Am. nitrate
10,000,000
Urea
Aqua ammonia
5,000,000
A. ammonia
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
-
A. ammonia, urea, and UAN solution
consumption in IL, IN, IA, MN, NE, and OH
Anhydrous ammonia
Urea + UAN Sol.
Anhydrous ammonia + urea + UAN
4,000,000
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000
500,000
0
2,500,000
Metric tons of N
Metric tons of N
Year ending June 30
1965
1970
1975
1980
1985
1990
Year
1995
2000
2005
2010
2,000,000
AA
urea
UAN Sol.
1,500,000
1,000,000
500,000
0
1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Year
Decision Support Systems
• “Computer programs or recommendation
guides used by field practitioners in
consultation with farmers/land managers in
a facilitated decision making process.”
– May or may not include
• On-the-go sensing
• Remote sensing
• Manual sampling and analysis
– Soil (30 cm or greater): pre-season, pre-sidedress
(corn)
– Plant tissue
Soft Red Winter Wheat
Spring N Recommendations
Estimate
tiller density
at GS 25
Tiller density
< 100 tillers ft-2?
NO
YES
Willing
to split spring
N applications?
NO
Obtain
tissue test
at GS 30
Measure soil
NO3-N to 1 m
at GS 25
Apply N as
recommended
at GS 30
Apply N as
recommended
at GS 25
YES
Apply N as
recommended
at GS 25
GS 25 N recommendation, lb/acre
GS 25 N APPLICATION
Also, have GS 30 N interpretation
60
40
20
0
40
50
60
70
80
90
GS 25 tillers/ft2
100 110 120
N Sensing and Spatial
Management in DSS
USDA NSTL
Okla. State U.
U. of MO, P. Scharf
Miss. State U., J . Varco
USDA ARS, Nebraska
USDA-ARS, Missouri
InfoAg 2007 Springfield, IL
N Management Talks
http://www.infoag.org/ConferenceBuilder/cb_SpeakerPictures.asp?ConfID=7
• A Comparison of Approaches to N Management –
J. Meisinger
• GreenSeeker Experiences – R. Mullen
• Developing Optical Sensor-Based N Rate
Algorithms – S. Phillips
• Crop Circle Experiences – J. Schepers
• European Perspective on N Management –H.
Matthieu
• AgriQuest – D. Lepoutre
InfoAg 2007 Springfield, IL
N Management Talks
http://www.infoag.org/ConferenceBuilder/cb_SpeakerPictures.asp?ConfID=7
• Changing from Yield-based to Yield ResponseBased N Management – P. Fixen
• Fertilizer Recommendation Software for Irrigated
Corn –R. Ferguson
• Precision Agriculture, Apple Pie, Motherhood and
Other Good "Stuff“ – D. Fairchild
• Slow-Release Nitrogen Products for Nitrogen
Conservation – A. Blaylock
Agronomic DSS -Examples
Variable-Rate N Fertilization
of Wheat and Corn
in Virginia
Steve Phillips, Paul Davis,
and Ursula Deitch
Eastern Shore Agricultural Research and Extension Center
Small Plot Results – Virginia Tech.
l
l
l
Used in-field high N reference strips
Developed N rate algorithms: wheat
and corn
Virginia wheat studies:
l
l
l
8% increase in grain yield (7 bu/A or 470 kg/ha)
10% reduction in N (11 kg N/A)
Virginia corn studies:
l
5% increase in grain yield (11 bu/A or 690 kg/ha)
l
21% reduction in N (24 kg N/ha)
http://nue.okstate.edu/
http://www.soiltesting.okstate.
edu/SBNRC/SBNRC.php
N- Rich Strip Approach: Wheat
• Jan.- Mar. NDVI readings (value output from
the sensors) from N- Rich Strip compared to
“Farmer Practice”, and known planting date
• Used to estimate biomass, and to predict the
obtainable wheat grain yield.
• Calibrated algorithms, are used to estimate
both the yield and the need for additional N.
• Benefits of this approach were valued at about
$25/ha
Source: Raun et al. Oklahoma State University
Mosaic InSite VRN
http://www.mosaicco.com/
• “The InSite VRN® (Variable Rate Nutrient)
system can be utilized by working closely with
your local agronomist to develop a detailed
plan for each field using:
–
–
–
–
–
–
Variable yield goals across the field
Preplant fertility levels
Organic-N mineralization
Manure N availability
Legume N availability
Nitrates in irrigation water”
Environmentally-Driven or
Motivated DSS
http://www.soil.ncsu.edu/nmp/ncnm
wg/ncanat/about.htm
• Nitrogen Loss Estimation Worksheet (NLEW)
• Phosphorus Loss Assessment Tool (PLAT)
• Neuse River and Tar-Pamlico River Basins –
animal waste and other nutrient loss, public
policy, “environmentally driven” tools
• Development supported by EPA 319(h) funds,
with little to no state government financing
Fertilizer Recommendation
Software for Irrigated Corn
• Richard B. Ferguson
• Dept. of Agronomy & Horticulture
• University of Nebraska
University of Nebraska Nitrogen
Recommendation Algorithm for Corn
N Rate (lb/acre) = 35 + (1.2 x EY) – (8 x NO3-N) –
(0.14 x EY x OM).
= Expected yield (bu/acre)
AreEYrecommendations
NO -N = Root zone residual nitrate-N (ppm)
developed
OM = Soil organicfrom
matter (%)research 20 –
Additional credits for legumes, manure and irrigation water
30 years
ago
still valid today?
subtracted from
basic algorithm.
3
Developed from 81 site/years of research conducted
between 1976 and 1982; 51 irrigated, 30 dryland.
Implemented in 1990.
Nebraska N
Rate Calculator
for Corn
soilfertility.unl.edu
Work is underway, with coordination led
by IPNI, to include N fertilization logic
•
•
•
•
Corn Belt Regional N Rate
Recommendation
Iowa
Illinois
Wisconsin
Minnesota
Hong, N., P.C. Scharf, J. G. Davis, N.R.
Kitchen, and K.A. Sudduth. 2007
Economically Optimal Nitrogen Rate Reduces Soil
Residual Nitrate
J. Environ. Qual. 36:354–362
• EONR should be evaluated at both wholeand sub-field scales
• Both environmental impacts of N fertilizer
and economic needs, to avoid overapplication of N, can be addressed by
applying the EONR
• Techniques might be based on crop
reflectance sensors, aerial imagery, soil
tests, and/or soil/landscape attributes.
SUMMARY
• Corn decision support software
 Regional N rate calculator approach
• considers previous crop, crop and fertilizer
N price ratio
 extension.agron.iastate.edu/soilfertility/nrate.aspx

Great Plains states approach


Considers rainfed and irrigated production and
wider climatic variety, generally include yield goal,
soil organic matter and residual nitrate in addition
to previous crop and economic factors.
soilfertility.unl.edu
• Wheat decision support software
 Ramped calibration strips,
in-season sensing.
• http://nue.okstate.edu/
Nutrient Use Efficiency
Fertilizer N BMPs
Nutrient Use Efficiency and Effectiveness:
Indices of Agronomic and Environmental Benefit
Nitrogen DSS Essentials
• Practical, user-friendly
• Field-calibrated and verified
• Sensitive to site-specific considerations:
–
–
–
–
agronomic response (yield and yield gain)
weather (rainfall, temperature)
soil characteristics (physical, chemical, biological)
environmental loss (to minimize (optimize?) water
and air discharge/emission)
• Risks of loss
• Magnitude of loss
– short-term and long-term economics
– personal grower choice (owned or rented land)
– measures of Nutrient Use Efficiency
IPNI Member Companies
and Affiliates
Questions?