Missouri algorithm:Missouri algorithm:Design & objectivesDesign & objectives

Peter ScharfPeter Scharf

University of MissouriUniversity of Missouri

Peter ScharfNewell Kitchen, Ken Sudduth, Glenn Davis, John Lory, Vicky Hubbard, Kent Shannon, Harlan Palm

On the way here,On the way here,I saw a lot of I saw a lot of

money laying on money laying on the ground!!the ground!!

Missouri Algorithm: Objectives

1. Don’t leave money laying on the ground

– Supply enough N to the crop to support full yield

– Don’t apply N that the crop doesn’t need

2. Don’t let N escape from fields to water

Crop N need is variableCrop N need is variable

• Twenty on-farm N rate experiments in Missouri, corn after soybean, no manure

• Most profitable N rates were 109, 114, 175, 0, 90, 190, 244, 63, 119, 300, 0, 146, 146, 180, 52, 175, 112, 149, 136, 114 lb N/acre

Crop N need is variable: Crop N need is variable: MissouriMissouri

Optim al N rates, kg/ha

0 to 80

80 to 120

120 to 160

160 to 200

200 to 280

Oran00 Rep3 Block26

0

4

8

12

16

0 100 200 300

N rate (kg ha-1)

Yie

ld (

Mg

ha-1

)

Nopt

Oran00 Rep3 Block26

0

4

8

12

16

0 100 200 300100 200 300

N rate (kg ha-1)

Yie

ld (

Mg

ha-1

)

Nopt

lb/ac

Crop N need is variable: Crop N need is variable: MinnesotaMinnesota

Overapplication = leftover N in soil

N underapplied N overapplied

Wasted $Environmental

risk

Mouth of Mississippi RiverHuge algal

bloom

Spatially intensive Spatially intensive diagnosis is neededdiagnosis is needed

How?How?

Diagnosing where to put more NDiagnosing where to put more N

PredictorPredictor % of variability in N % of variability in N need explainedneed explained

Yield 2 to 20

Soil nitrate 17 to 25

Soil N quick tests 0 to 18

Soil conductivity 8

Corn color 53 to 77

Missouri algorithm design:Missouri algorithm design:Just an empirical relationshipJust an empirical relationship

• John Lory and I: initial calibration with Cropscan

• Newell Kitchen et al: more recent field-scale calibration of Greenseeker and Crop Circle

• Multi-state (country) data from this group

0

50

100

150

200

250

0.9 1.1 1.3 1.5 1.7

Green/near infrared relative to high-N plots

Op

tim

um

sid

ed

ress

N ra

te

Missouri Algorithm: Objectives, Set 2

1. Deal with spatial variability in N need

2. Support producer, retailers, consultants in planned sidedress operations from V6 to V16

3. Support producer, retailers, consultants in rescue N applications when previously applied N has been lost

Supporting producers in planned sidedress operations using sensors

• 26 demo fields in 2007 ( )

• 61 demo fields 2004-2007

Nearly 30 demo fields 2008, including first cotton field

Color sensors can be used Color sensors can be used for sidedressing anhydrous…for sidedressing anhydrous…

sensorssensors

Computer in cab reads sensors, calculates N rate, directs controller

Controller runs ball valve to change fertilizer rate

…or sidedressing solution

…or with a high-clearance spinner

…with a big sprayer

…or a big injector

On-farm sensor demos 2004-2007On-farm sensor demos 2004-2007

N rate system

Average yield

Average N rate

Producer rate

157

Sensor-controlled

$ to sensor

On-farm sensor demos 2004-2007On-farm sensor demos 2004-2007

N rate system

Average yield

Average N rate

Producer rate

157

Sensor-controlled

156

$ to sensor

On-farm sensor demos 2004-2007On-farm sensor demos 2004-2007

N rate system

Average yield

Average N rate

Producer rate

157

Sensor-controlled

156

$ to sensor -$3

On-farm sensor demos 2004-2007On-farm sensor demos 2004-2007

N rate system

Average yield

Average N rate

Producer rate

157 145

Sensor-controlled

156

$ to sensor -$3

On-farm sensor demos 2004-2007On-farm sensor demos 2004-2007

N rate system

Average yield

Average N rate

Producer rate

157 145

Sensor-controlled

156 123

$ to sensor -$2

On-farm sensor demos 2004-2007On-farm sensor demos 2004-2007

N rate system

Average yield

Average N rate

Producer rate

157 145

Sensor-controlled

156 123

$ to sensor -$2 +$15

Overall:+$13/ac tosensors

Sensor Benefits:Sensor Benefits:

• Make sure enough N is appliedMake sure enough N is applied

• Avoid unneeded N applicationAvoid unneeded N application

N application to head-high corn

N rate map

June 20, 2007

129 bu/ac149 bu/ac

High-N reference area

115

175

175

Sensor Benefits:Sensor Benefits:

• Make sure enough N is appliedMake sure enough N is applied

• Avoid unneeded N applicationAvoid unneeded N application

August 1 Aerial Photo after the June 13 UAN Application

215.4 212.1 204.2 212.4 215.5 204.9 206.6

214.1 208.0 208.5 206.6 206.6 211.6 205.4

Variable

Fixed

Avg Bu/A

208.6

210.2

2008: Our first cotton demo