Variable Rate Nitrogen Application The Ultimate Nitrogen Management Practice

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Variable Rate Nitrogen Application The Ultimate
Nitrogen Management Practice

• Randy Taylor
• Extension Engineer
• Biosystems and Ag Engineering

NRCS Precision Agriculture Workshop October 31,
2006
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VRN - The Holy Grail?
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Variable Rate Application

• Production inputs are applied on an optimum basis
  for the local conditions.
• VRA requires
• Knowledge of economic optimum rates at chosen
  management scale
• Ability to apply desired rate at desired scale

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Implementing VRA

• Map-Based VRA
• Sensor-Based VRA
• The primary element of either approach is a rate
  controller

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Map-Based VRA

• Uses a georeferenced map as a guideline for
  adjusting application rate
• Need a means for determining machine location
• Need to Look Ahead
• Rate is based on a user-defined and monitored
  algorithm

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Sensor-Based VRA

• Application rate is determined from sensors
• Rate is based on an algorithm that ties the
  sensor reading to a prescription
• Machine location is not that important (unless
  collecting data)

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Feedback Loop Rate Controllers

• Adjust rate to a desired value
• Measure actual rate
• Readjust rate
• When desired rate changes, they must be able to
  quickly adjust to the new rate

Select Rate
Measure Flow
Set Flow
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Rate Controllers

• Why do we need rate controllers?
• Rate controllers were developed to account for
  variation in application speed
• What is the application goal?
• Whats the difference between a controller and
  monitor?

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Rate Controllers

• Nebraska looked at application rate errors of 61
  NH3 applicators
• Traditional Regulator Systems
• 17 of had acceptable error
• 32 over applied
• 41 under applied
• Electronic or Ground Drive Controllers
• 59 of had acceptable error
• 41 over applied

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Back To Basics

• Application Rate is a function of speed, width,
  and flow rate
• Does width change?
• To keep application rate constant, flow rate must
  change when speed changes

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Maintaining Application Rate
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Controller Components

• Speed Sensor
• Radar, Sonar, Proximity, GPS
• Flow Sensor
• Turbines (small impeller)
• Pressure Sensor
• Used to predict flow based on orifice size
• Control Valve
• Ball or butterfly flow control
• Microprocessor
• Brains of the outfit

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Electronic Monitor System for NH3
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What is the Goal?

• Apply the desired amount of product
• Account for changes in speed
• Wheel slip
• Turns
• Account for desired rate changes

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Raven 440 NH3 Controller
1.5 s of response time. About 9 ft at 4 mph
3 mph
5 mph
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Response Times

• PAMI Evaluation Report 723 NH3 Controllers
• About 2 seconds to adjust to speed or rate
  changes
• At 5 mph, 2 s 15 ft
• So we can typically change rates with more
  resolution than applicator width

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Raven 440 NH3 Flow Limitations
35 ft width 5 mph
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Flow Control

• Advantages
• Consistent application rate regardless of speed
• Wider speed range of operation
• Easier calibration
• Chemical savings greater than controller cost

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Orifice Metering
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What PWM Does

• Allows control of both nozzle pressure and flow
  independently
• Increases the effective operating range by a
  factor of 4 (81 versus 21)
• Increased control of spray particle droplet size
• Even coverage using blended pulse technology

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What is the Duty Cycle?

• Pulse Width Modulation
• Nozzles on time and off time per second
• The Aim Command System changes the amount of on
  time each second to control nozzle flow
  (application rate)

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Duty Cycle and Flow Control
LONG ON TIME HIGH FLOW RATE
SHORT ON TIME LOW FLOW RATE
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Blended Pulse Coverage

• Nozzles pulse 10 times per second
• Even and odd nozzles are alternately fired for
  blended coverage

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Variable Rate N Management

• What measurements will be used to identify
  within-field variation in N supply or
  availability?
• What N recommendation or base N rate will be
  used?
• What management scale will be used?

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Map-Based

• Determine management scale
• Apply diagnostic tools to develop N prescription
• Develop N rate prescription map for the field
• e.g. grid sampling, soil nitrate tests, field map
  showing variable N rate to apply

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Map-Based Decision Inputs

• Soil nitrate testing
• Remote sensing of crop and soil properties
• Site-specific data from yield monitors
• Soil electrical conductivity maps
• Other information?

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Traditional Approach

• N recommendation yield goal x 1.2 N credits

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Spatial Yield Goals
Start with multiple yield maps on the same
field. Do they need to be the same crop?
Normalize each year and average the maps. Does
yield stability matter?
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In-Field Response
The results presented here indicated that there
was, in most cases, significant variability in
grain yield response to increasing N rates among
in-field locations. The minimum N rate
corresponding to maximum corn yield was as low as
52 kg N / ha and as high as 182 kg N / ha,
considering all locations across three fields in
this study. However, variability in yield
responses to N was not consistently related to
soil OM content.
Schmidt, J.P., A.J. DeJoia, R.B. Ferguson, R.K.
Taylor, R.K. Young, and J.L. Havlin. 2003. Corn
Yield Response to Nitrogen at Multiple In-Field
Locations. Agron. J. 94798806.
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Traditional Method Smaller Scale
Over 13 site-years, no consistent benefit
(either increased yield or reduced soil residual
NO3-N) was observed with variable rate N
application. There was no disadvantage to using
variable rate N application in terms of N applied
or grain yield, but no advantage that would
justify the cost and effort of variable rate
application with procedures used in this study.
Ferguson, R.B., G.W. Hergert, J.S. Schepers, C.A.
Gotway, J.E. Cahoon, and T.A. Peterson. 2002.
Site-Specific Nitrogen Management of Irrigated
Maize Yield and Soil Residual Nitrate Effects.
Soil Sci. Soc. Am. J. 66544553.
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Management Zones
Grain yield response to N was also shown to be
significantly different across management zones.
This study showed that spatially variable crop
parameters could potentially be managed using
SSMZs.
Inman, D., R. Khosla, D. G. Westfall, and R.
Reich. 2005. Nitrogen Uptake across Site
Specific Management Zones in Irrigated Corn
Production Systems. Agron. J. 97169176 (2005).
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Sensor-Based

• Monitor crop N status in the field
• Apply N at variable rates to meet crop needs

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Sensor-Based Decision Inputs

• Plant or canopy reflectance
• Chlorophyll measurements
• On-the-go or remotely sensed crop canopy imagery
• Pre-selected N prescription
• In-field reference strip may be needed

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Sensor Based Nitrogen Management
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2005 Field Scale Tests

• Evaluation of nitrogen topdressing methods for
  winter wheat
• RT500
• RT200
• Three uniform rates (farmer practice, check,
  average rate from RT500)
• Four fields in NC Oklahoma
• Harvested in 2005

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Yield and Applied N
Treatments that received the most nitrogen at two
fields (2 and 4) also had the greatest yield.
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Challenges

• Measuring differences at larger scales
• Non uniform plots
• Matching application and harvest equipment
• Harvesting plots
• Managing data with potential errors

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Integrating Crop Sensors and Yield Monitor Data

• We know that the response to N varies spatially
  across the field.
• We also know that response to N varies each year.
• Can we incorporate other information (yield
  monitor data) that we have to aid nitrogen
  decisions?
• Use yield monitor data to determine yield
  potential zones and crop sensors to determine
  seasonal N needs.

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Wheat Transect
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High yielding zone where the NDVI is greater in
the N-Rich strip and nitrogen was recommended.
Low yielding area where NDVI between the N-Rich
strip and farmer practice are similar. No extra
nitrogen was recommended.
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Obstacles/Challenges for variable rate N
management

• Reliable method to identify within-field
  variation in crop N supply
• Absence of yield, profitability, or environmental
  benefits in comparisons
• Small differential between potential profit
  increases and costs of variable rate management

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Management Scale
Sub Meter
Sub Field
Field
Farm