precision agriculture an overview. precision agriculture? human need environment –hypoxia...

Precision AgriculturePrecision Agriculturean Overviewan Overview

Precision Agriculture?Precision Agriculture?

• Human need• Environment

– Hypoxia – $750,000,000 (excess N flowing down the

Mississippi river/yr)

• Developed vs Developing Countries• High vs Low yielding environments

Many research & development practices are not Many research & development practices are not designed to foster site-specific managementdesigned to foster site-specific management

• Continued success in wheat germplasm and technology dissemination worldwide depends on the free and uninhibited flow of genetic materials and information. Restrictions imposed on such movement due to intellectual property protection could have serious consequences on the ability of developing countries to sustain wheat productivity growth.

• …. further gains would have to come from specifically targeting breeding efforts to the unique characteristics of marginal environments

What is Precision Agriculture?What is Precision Agriculture?

• Treating small areas of a field as separate management units for the purpose of optimizing crop production based on in-field variability

Site Specific ManagementSite Specific Management

• The application of an input to a specific area based on the evaluation of variability of the need for that input. Richardson, 1996.

• Recognition of site-specific differences within fields and tailoring management accordingly, instead of managing an entire field based on some hypothetical average. Emmert, 1995.

Definitions of Precision Definitions of Precision AgricultureAgriculture

• Using information to better manage farms at the field level or finer resolution.

• Optimizing inputs to produce the largest net income.

• Combine yield monitors, GPS, Grid Soil Sampling.

What is Precision Farming?What is Precision Farming?

• Management by the Field• Management by the foot• Global Positioning Systems• Yield Monitors• Sensor Based Weed Control• Grid Sampling• Variable Rate Fertilizer Application

Oklahoma State University’s Oklahoma State University’s Definition of Precision AgricultureDefinition of Precision Agriculture

• Variable rate application of fertilizers, pesticides or other materials based on the sensed needs of the crop within the following constraints:– Available Technology– Agronomic – Economic

Large Scale Large Scale (Macro) Variability (Macro) Variability

Within a FieldWithin a Field

Intermediate Scale Variability Within a FieldIntermediate Scale Variability Within a Field

IKONI Imagery 4 m Resolution

Small Scale (Micro) Variability Small Scale (Micro) Variability Within a FieldWithin a Field

Variability in Weed PopulationsVariability in Weed Populations

Variability in Grain YieldVariability in Grain Yield

97 Yield Poly 98 Yield Poly

Klinsick; 98 (186.0 ac.)

Date: Sep 25, 1999Field Name: Klinsick; 98Location: Texas Co., Oklahoma, United StatesFarm Name: KlinsickClient Name: Long Bros.Total Acres: 186.0Field Boundary Start Location: Latitude: 36.80187915 Longitude: -101.41159014

500 0 500 Feet

97 Yield Poly18.261 - 27.8627.86 - 38.2338.23 - 47.4947.49 - 53.4653.46 - 65.425

98 Yield Poly22.99 - 41.152 (1.0 ac.)41.152 - 59.314 (14.5 ac.)59.314 - 77.476 (100.9 ac.)77.476 - 95.638 (62.9 ac.)95.638 - 113.8 (6.8 ac.)

Map BasedMap Based - Precision Farming - Precision Farming

ManagementComputer Yield MapYield Map

GIS - Precision FarmingSoftware

GPS Referenced Soil SamplesGPS Referenced Soil Samples

Fertilizer PrescriptionFertilizer Prescription

GPS ConstellationsGPS ConstellationsAerial and Aerial and Satellite Satellite ImagesImages

Soils Maps, Elevation Maps, Soils Maps, Elevation Maps, etc.etc.

On-the- Go Sensing of Plant Needs and On-the- Go Sensing of Plant Needs and Variable Rate TreatmentVariable Rate Treatment

Variable RateVariable RateSpray NozzleSpray NozzleVariable RateVariable RateSpray NozzleSpray Nozzle

DirectionDirectionof Travelof TravelDirectionDirectionof Travelof Travel

Computer andComputer andSensorSensor

AssemblyAssembly

Computer andComputer andSensorSensor

AssemblyAssembly

Decision MakingDecision MakingAnd Agronomic StrategyAnd Agronomic StrategyDecision MakingDecision MakingAnd Agronomic StrategyAnd Agronomic Strategy

PlantPlantPlantPlant

Map Based vs. Real TimeMap Based vs. Real Time

Map Based:

1. Treat next season’s crop

2. Historic information

2. Slowly changing variables e.g. pH

3. Coarse resolution

4. Can directly measure variables e.g. pH

Transition: Aerial/Satellite Imagery

1. Sense and treat current crop

2. Near real-time

3. Variables that change rapidly, e.g. N

4. Resolution limited by ability to accurately and precisely locate position

Real-Time:

1. Sense and treat current crop

2. Real-Time, sense and treat on-the-go

3. Variables that change rapidly, e.g. N

4. High resolution, 1 m

5. Indirect measurement

History Oklahoma State University Optical History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer ApplicationSensor Based Nitrogen Fertilizer Application

19911991


1993199319921992First discussion between the Departments of Plant and Soil Sciences and Biosystems and Agricultural Engineering concerning the possibility of sensing biomass in wheat and bermudagrass. Biomass was to be used as an indicator of nutrient need (based on removal).


Distance, mDistance, m

Rep 2, Miller-2Rep 2, Miller-2

00

1010

2020

3030

4040

5050

6060

00 1010 2020 3030 4040 5050 6060 7070

Gra

in N

up

tak

e,

kg

/ha

G

rain

N u

pta

ke

, k

g/h

a

Check 28.9 ± 6.4Check 28.9 ± 6.4

Variable Rate 48.5 ± 4.2Variable Rate 48.5 ± 4.2

Fixed Rate 44.1 ± 8.2 Fixed Rate 44.1 ± 8.2

19941994


19951995Mean surface soil test P and fertilizer P recommendations, bemudagrass pasture, Burneyville, OK Mean surface soil test P and fertilizer P recommendations, bemudagrass pasture, Burneyville, OK

00

1010

2020

3030

4040

5050

6060

7070

00 22 44 66 88 1010 1212 1414 1616 1818 2020 2222DISTANCE, mDISTANCE, m

ME

HL

ICH

III

P,

mg

/kg

ME

HL

ICH

III

P,

mg

/kg

00

55

1010

1515

2020

2525

3030

P F

ER

TIL

IZE

R,

kg/h

aP

FE

RT

ILIZ

ER

, kg

/ha

Mehlich IIIMehlich III

P FertilizerP Fertilizer


19961996


19981998

00

10001000

20002000

30003000

40004000

50005000

60006000

0.010.01 0.020.02 0.030.03 0.040.04 0.050.05 0.060.06 0.070.07

NDVI F4+NDVI F5/days from F4 to F5NDVI F4+NDVI F5/days from F4 to F5

Gra

in Y

ield

Gra

in Y

ield

Perkins, N*PPerkins, N*P

Perkins, S*NPerkins, S*N

Tipton, S*NTipton, S*N

y = 1E+06x2 - 12974x + 951.24R2 = 0.89y = 1E+06x2 - 12974x + 951.24R2 = 0.89

00

10001000

20002000

30003000

40004000

50005000

60006000

0.010.01 0.020.02 0.030.03 0.040.04 0.050.05 0.060.06 0.070.07

NDVI F4+NDVI F5/days from F4 to F5NDVI F4+NDVI F5/days from F4 to F5

Gra

in Y

ield

Gra

in Y

ield

Perkins, N*PPerkins, N*P

Perkins, S*NPerkins, S*N

Tipton, S*NTipton, S*N

y = 1E+06x2 - 12974x + 951.24R2 = 0.89y = 1E+06x2 - 12974x + 951.24R2 = 0.89

www.dasnr.okstate.edu/nitrogen_use

19971997


y = 0.8278x + 0.4981

R2 = 0.70

0

0.5

1

1.5

2

2.5

3

3.5

4

0.5 1 1.5 2 2.5 3 3.5 4

RI NDVI

RI H

arve

st

Fertilized N required to maximize yield (Lahoma, OK).

y = 0.65x + 27 (CV = 62)

0

10

20

30

40

50

60

70

80

90

19

71

19

74

19

76

19

78

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

Year

Fe

rtili

zer-

N (

lb/a

cre

)

20002000

Covington, 1999Wheat Grain Yield

Covington, 1999Wheat Grain Yield

N Rate Method Yield Yieldlb/ac kg/ha bu/ac__________________________________________0 - 1122 16.740 Fixed 1269 18.980 Fixed 1846 27.568 YP-INSEY 2396 35.7SED 230 3.4

__________________________________________CV, % 19

N Rate Method Yield Yieldlb/ac kg/ha bu/ac__________________________________________0 - 1122 16.740 Fixed 1269 18.980 Fixed 1846 27.568 YP-INSEY 2396 35.7SED 230 3.4

__________________________________________CV, % 19

19991999TEAM-VRT entered into

discussions with John Mayfield, Patchen, Inc., concerning the potential commercialization of a sensor-based N fertilizer applicator for cereal crops.

0

1

2

3

4

5

6

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

INSEY (NDVI Feekes 4-6/days from planting to Feekes 4-6)

Gra

in Y

ield

, Mg

ha

-1

N*P Perkins, 1998

S*N Perkins, 1998

S*N Tipton, 1998

N*P Perkins, 1999

Experiment 222, 1999


Efaw AA, 1999



N*P Perkins, 2000



Efaw AA, 2000



Hennessey, AA, 2000

VIRGINIA (7 Loc's)

20012001


2002

Treatment Pre-Trt. N, lb/ac

Trt. N, lb/ac

Total N,

lb/ac

Yield, lb/ac

Net Rtn, $/ac

N-Rich Strip

94 0 94 44.6 110

Var. Rate 56 23 79 39.8 100

Fixed Rate A

56 35 91 37.3 91

Fixed Rate B

58 24 82 35.4 85

Field Rate 73 20 92 34.6 82

SED 3.1 9.5

Treated March 20 to April 10, 2002Net Revenue = grain yield * $3.00 / bu – N Fertilizer * $0.25 / lb

SED = Standard Error of the Difference


2003

INSEYMax eYP 4.324359.0

039.2

YPYPR N

FldRate

NRichYP YP

YPRI

FldRate

NRichNDVI NDVI

NDVIRI

RIYPYPN 0

maxYPYPN 101219.00 CVRIRI CVCV

precision agriculture an overview. precision agriculture? human need environment –hypoxia...

Documents

precision farming

evaluation of variability

field level

entire field

tailoring management

crop production

historic information

variable rate treatmentmap