1. SOIL 4213 BIOEN 4213 History of Using Indirect Measures for detecting Nutrient Status Oklahoma State University

2. Field Element Size Area which provides the most precise measure of the available nutrient where the level of that nutrient changes with distance Chlorophyll Meters? What is the connection Area which provides the most precise measure of the available nutrient where the level of that nutrient changes with distance Chlorophyll Meters? What is the connection

3. FES should theoretically identify 1. The smallest resolution where cause and effect relationships can be identified 2. The precise resolution where variances between paired samples of the same size (area) become unrelated and where heterogeneity can be recognized 3. The resolution where misapplication could pose a risk to the environment 4. The treated resolution where net economic return is achieved. 5. The resolution where differences in yield potential may exist

4. ReviewReview Science: 283:310-316 By 2020 global demand for rice, wheat, and maize will increase 40%By 2020 global demand for rice, wheat, and maize will increase 40% People have been predicting yield ceilings for millennia, and they’ve never been right “Matthew Reynolds” CIMMYTPeople have been predicting yield ceilings for millennia, and they’ve never been right “Matthew Reynolds” CIMMYT Supercharging Photosynthesis: Reproduce the C 4 cycle in riceSupercharging Photosynthesis: Reproduce the C 4 cycle in rice Role of Biotechnology in Precision AgricultureRole of Biotechnology in Precision Agriculture Science: 283:310-316 By 2020 global demand for rice, wheat, and maize will increase 40%By 2020 global demand for rice, wheat, and maize will increase 40% People have been predicting yield ceilings for millennia, and they’ve never been right “Matthew Reynolds” CIMMYTPeople have been predicting yield ceilings for millennia, and they’ve never been right “Matthew Reynolds” CIMMYT Supercharging Photosynthesis: Reproduce the C 4 cycle in riceSupercharging Photosynthesis: Reproduce the C 4 cycle in rice Role of Biotechnology in Precision AgricultureRole of Biotechnology in Precision Agriculture

5. Sunlight reaching earth Sunlight reaching earth Chlorophyll b B-Carotene Phycoerythrin Phycocyanin Chlorophyll a 300400500600700800 Wavelength, nm Absorption SPAD 501, 502 (430, 750) SPAD 501, 502 (430, 750) Lehninger, Nelson and Cox Absorption of Visible Light by Photopigments Absorption of Visible Light by Photopigments

6. VISIBLE Color Absorbed VISIBLE Color Transmitted VioletBlueGreenYellowOrange Red Short wavelength High frequency High energy Long wavelength Low frequency Low energy 0.01103804504955705906207501x10 6 1x10 11 wavelength, nm wavelength, nm 0.01103804504955705906207501x10 6 1x10 11 wavelength, nm wavelength, nm Gamma Rays X-RaysX-Rays UltravioletUltravioletInfraredInfrared Microwaves and short radio Radio, FM, TV ElectronicVibrationalRotational transitionstransitionstransitions ElectronicVibrationalRotational transitionstransitionstransitions Yellow-greenYellowVioletBlueGreen-blueBlue-green

7. Short wavelength High energy Long wavelength Low energy 0.0110380450495570590620750 wavelength, nm wavelength, nm 0.0110380450495570590620750 wavelength, nm wavelength, nm X-RaysX-RaysUltravioletUltraviolet InfraredInfrared Chlorophyll b B-Carotene Phycoerythrin Phycocyanin Chlorophyll a

8. Near-Infrared Absorption Major Amino and Methyl Analytical Bands and Peak Positions 7008009001000110012001300140015001600170018001900200021002200 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| Wavelength, nm RNH 2 CH 3

9. 380450495570590620750 wavelength, nm wavelength, nm 380450495570590620750 wavelength, nm wavelength, nm Chlorophyll b B-Carotene Phycoerythrin Phycocyanin Chlorophyll a Photodiode Interference Filter White Light

10. 1993 Sensor readings at ongoing bermudagrass, N rate * N timing experiments with the Noble Foundation in Ardmore, OK. Initial results were promising enough to continue this work in wheat. Dr. Marvin Stone adjusts the fiber optics in a portable spectrometer used in early bermudagrass N rate studies with the Noble Foundation, 1994.

11. 1995 New ‘reflectance’ sensor developed. Extensive field experiments looking at changes in sensor readings with changing, growth stage, variety, row spacing, and N rates were conducted.

12. Collaborative Project with CIMMYT Variety Selection/Yield Potential Spring Wheat 1996

13. Date Location Personnel Objectives Feb, 1997 Ciudad Obregon TEAM-VRT Discuss potential collaborative work Jan, 1999 Obregon & Texcoco Steve Phillips, Joanne LaRuffa, Wade Thomason, Sherry Britton, Joe Vadder, Gordon Johnson, John Solie, Dick Whitney IRSP 98, refine INSEY, 2- wheel tractor and wheat bed planter design Sep, 1999 Texcoco Erna Lukina IRSP 98, use of EY as a selection tool Aug, 2000 Texcoco Marvin Stone, Kyle Freeman, Roger Teal, Robert Mullen, Kathie Wynn, Carly Washmon, Dwayne Needham IRSP 99, applications of INSEY, sensor design for plant breeding Jan-Mar 2001 Ciudad Obregon Kyle Freeman Joint collaboration on 200-03530 NRI Grant Apr 2001 Ciudad Obregon Kyle Freeman Wheat harvest TOTAL 8 8 33 July 2001 El Batan Jagadeesh Mosali, Shambel Moges Micah Humphreys, Paul Hodgen, Carly Washmon Wheat harvest Apr 2002 Ciudad Obregon Paul Hodgen NASA Grant CIMMYTCIMMYT June 2002 El Batan Robert Mullen, Kyle Freeman Corn Sensing Oct 2002 El Batan Keri Brixey, Jason Lawles, Kyle Freeman Corn Harvest http://www.dasnr.okstate.edu/nitrogen_use/cimmyt_visit_2001.htm

14. Crop Target OSU Reflectance Sensor (1996-2002)

15. OSU Active Sensor (2001-present)

16. History of Using Indirect Measures for Detecting Nutrient Status NIRS analyzer which is connected to a computer focuses infrared rays on a prepared sample of dried pulverized plant material. The instrument measures protein, fiber and other plant components because each one reflects infrared rays differently. Samples and standards (previously characterized) and then mathematically compared NIRS analyzer which is connected to a computer focuses infrared rays on a prepared sample of dried pulverized plant material. The instrument measures protein, fiber and other plant components because each one reflects infrared rays differently. Samples and standards (previously characterized) and then mathematically compared

17. History of Using Indirect Measures for Detecting Nutrient Status NIRS (near infrared reflectance spectroscopy) Measuring the vibrations caused by the stretching and bending of hydrogen bonds with carbon oxygen and nitrogen. Each of the major organic components of a forage or other feed has light absorption characteristics. These absorption characteristics cause the reflectance that enables us to identify plant composition

18. Chlorophyll Meters Most WIDELY used “Indirect Measure” Minolta: SPAD (soil plant analysis development unit ) 501 & 502 light absorbance (light attenuation) at 430 (violet) and 750 nm (red/NIR transition) No tissue collection Leaf chlorophyll (SPAD) vs Leaf N concentration and NO 3 -N

19. Chlorophyll Meters (cont.) http://www.specmeters.com/Plant_Chlorophyll_ Meters/ http://www.specmeters.com/Plant_Chlorophyll_ Meters/ How SPAD meters work IRRI (READ) How SPAD meters work IRRI (READ) Go to Factors affecting SPAD values How SPAD meters work IRRI (READ) Go to CRITCAL SPAD VALUES for varietal work University of NEBRASKA, sufficiency approach University of NEBRASKA, sufficiency approach High correlation between leaf chlorophyll and leaf N. Why? Sample area. Problems? http://agronomy.ucdavis.edu/uccerice/afs/agfs03 94.htm http://agronomy.ucdavis.edu/uccerice/afs/agfs03 94.htm http://www.store.ripplecreek.com/category- greenformulas.html http://www.store.ripplecreek.com/category- greenformulas.html

20. Short wavelength High energy Long wavelength Low energy 0.0110380450495570590620750 wavelength, nm wavelength, nm 0.0110380450495570590620750 wavelength, nm wavelength, nm X-RaysX-RaysUltravioletUltraviolet InfraredInfrared Chlorophyll b B-Carotene Phycoerythrin Phycocyanin Chlorophyll a

21. Response Index vs. Sufficiency

22. On-the-go-chemical-analyses ‘SoilDoctor’ selective ion electrode mounted on the shank of an anhydrous ammonia applicator Electromagnetic induction (EMI) http://oldsci.eiu.edu/physics/DDavis/1160/Ch21Ind/Farady.html VERIS measurements (Missouri) predicting grain yield predicting grain yield sand deposition sand deposition depth to clay pan depth to clay pan electrical conductivity electrical conductivity

23. Use of EM as a data layer to better predict yield potential

25. On-the-go-chemical-analysesOn-the-go-chemical-analyses On-the-go sensors for organic matter and ground slope (Yang, Shropshire, Peterson and Whitcraft) Satellite images Aerial images (NIR sensitive film) On-the-go sensors for organic matter and ground slope (Yang, Shropshire, Peterson and Whitcraft) Satellite images Aerial images (NIR sensitive film)

26. Implications Reports of improved correlation between indirect measures and yield (EMI) versus soil test parameters Soil testing (process of elimination) no single parameter is expected to be correlated with yield no single parameter is expected to be correlated with yield K vs yield K vs yield P vs yield P vs yield N vs yield N vs yield pH vs yield pH vs yield

27. FES and SPAD Chlorophyll Meters and Field Element Size What is the connection? Indirect Measures? Is this a process of elimination like soil testing?

28. FYI Spectral Radiance Radiance: the rate of flow of light energy reflected from a surface Measuring the radiance of light (at several wavelengths) that is reflected from the plant canopy Photodiodes detect light intensity (or radiance) of certain wavelengths (interference filters, e.g., red, green, NIR) that are reflected from plants and soil. Radiance: the rate of flow of light energy reflected from a surface Measuring the radiance of light (at several wavelengths) that is reflected from the plant canopy Photodiodes detect light intensity (or radiance) of certain wavelengths (interference filters, e.g., red, green, NIR) that are reflected from plants and soil.

29. Normalized Difference Vegetation Index (NDVI) = NIR ref – red ref / NIR ref + red ref Normalized Difference Vegetation Index (NDVI) = NIR ref – red ref / NIR ref + red ref (up – down) excellent predictor of plant N uptake Units: N uptake, kg ha -1 Units: N uptake, kg ha -1

30. Sensor Design (1991-96) Plant and Soil target Micro-Processor, A/D Conversion, and Signal Processing Ultra-Sonic Sensor Photo-Detector Optical Filters Collimation March 1996