1. Precision Agriculture

2. 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

3. Many research & development practices are not designed 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

4. What is Precision Agriculture?
The concept of precision farming entails the use of some high-tech equipment, assessing field conditions and applying chemicals and fertilizers. …. Managing small areas within a field to reduce chemical use and improve productivity is the goal of precision farming methods. Ess and Morgan

5. 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

6. Site 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.

7. Definitions of Precision Agriculture
Using information to better manage farms at the field level or finer resolution.
Optimizing inputs to produce the largest net income.
Optimizing inputs to produce the highest long term yields.
Combine yield monitors, GPS, Grid Soil Sampling.

8. 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
Managing to Maximize Net Return –
Agronomic
Economic

9. Oklahoma State University’s Definition of Precision Agriculture
Variable rate application of fertilizers, pesticides or other inputs based on the sensed needs of the crop within the following constraints:
Available Technology
Agronomic
Economic
Environmental

10. Large Scale (Macro) Variability Within a Field

11. Intermediate Scale Variability Within a Field
IKONI Imagery 4 m Resolution

12. Small Scale (Micro) Variability Within a Field

13. Variability in Weed Populations

14. Variability in Grain Yield

15. Map Based - Precision Farming
Management
Computer
Yield Map
GIS - Precision
Farming
Software
GPS Referenced Soil Samples
Fertilizer Prescription
GPS Constellations
Aerial and Satellite Images
Soils Maps, Elevation Maps, etc.

16. On-the- Go Sensing of Plant Needs and Variable Rate Treatment
Spray Nozzle
Direction
of Travel
Computer and
Sensor
Assembly
Decision Making
And Agronomic Strategy
Plant

17. Map Based vs. Real Time Transition: Aerial/Satellite Imagery
Sense and treat current crop
Near real-time
Variables that change rapidly, e.g. N
Resolution limited by ability to accurately and precisely locate position
Indirect Measurements
Real-Time:
Sense and treat current crop
Real-Time, sense and treat on-the-go
Variables that change rapidly, e.g. N
High resolution, m
Indirect measurement (with existing sensors)
Map Based:
Treat next season’s crop
Historic information
3. Slowly changing variables e.g. pH
4. Coarse resolution
5. Can directly measure variables e.g. pH

18. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
1991

19. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
1993
1992
First 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).

20. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
1994

21. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
1995

22. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
1996

23. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
1998
1997

24. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
2001
1999
TEAM-VRT entered into discussions with John Mayfield, Patchen, Inc., concerning the potential commercialization of a sensor-based N fertilizer applicator for cereal crops.
2000

25. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
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
44.6
110
Var. Rate 56 23 79
39.8
100
Fixed Rate A 35 91
37.3
Fixed Rate B 58 24 82
35.4 85
Field Rate 73 20 92
34.6
SED
3.1
9.5
Treated March 20 to April 10, 2002 Net Revenue = grain yield * $3.00 / bu – N Fertilizer * $0.25 / lb
SED = Standard Error of the Difference

26. History Oklahoma State University Optical Sensor Based Nitrogen Fertilizer Application
2003-Present

27. Today