SOIL 4213
BIOEN 4213
History of Using Indirect
Measures for detecting
Nutrient Status
Oklahoma State University
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
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
Review
Science: 283:310-316
• 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” CIMMYT
• Supercharging Photosynthesis:
Reproduce the C4 cycle in rice
• Role of Biotechnology in Precision
Agriculture
Absorption of Visible Light
by Photopigments
Absorption
Sunlight reaching
earth
SPAD 501, 502
(430, 750)
Phycoerythrin
Chlorophyll b
Phycocyanin
B-Carotene
Chlorophyll a
300
400
500
600
700
Wavelength, nm
800
Lehninger, Nelson and Cox
Yellow-green
Yellow
Violet
Blue
Green-blue
Blue-green
0.01
10
Violet
Blue
Green
Yellow Orange
VISIBLE Color Absorbed
380
450
495
570 590 620
wavelength, nm
Electronic
transitions
Red
Infrared
Ultraviolet
X-Rays
Gamma Rays
VISIBLE Color Transmitted
750
Radio, FM, TV
Long wavelength
Low frequency
Low energy
Microwaves and short radio
Short wavelength
High frequency
High energy
1x106 1x101
Vibrational Rotational
transitions transitions
Short wavelength
High energy
Long wavelength
Low energy
Phycoerythrin
Chlorophyll b
Phycocyanin
B-Carotene
0.01
10
Infrared
Ultraviolet
X-Rays
Chlorophyll a
380
450
495
570 590 620
wavelength, nm
750
Near-Infrared Absorption
Major Amino and Methyl Analytical Bands
and Peak Positions
CH3
CH3
RNH2
CH3
CH3
CH3
CH3
RNH2
RNH2
|
|
|
|
|
|
|
|
700
800
900
1000
1100
1200
1300
1400
|
RNH2
|
1500 1600
Wavelength, nm
|
|
|
|
|
|
1700
1800
1900
2000
2100
2200
White Light
Interference Filter
Photodiode
Phycocyanin
Chlorophyll b
B-Carotene
Phycoerythrin
Chlorophyll a
380
450
495
570
590 620
wavelength, nm
750
1993
Dr. Marvin Stone adjusts the fiber
optics in a portable spectrometer
used in early bermudagrass N rate
studies with the Noble Foundation,
1994.
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.
1995
Extensive field experiments looking at changes in
sensor readings with changing, growth stage,
variety, row spacing, and N rates were conducted.
New ‘reflectance’ sensor developed.
Collaborative Project with CIMMYT
Variety Selection/Yield Potential
Spring Wheat 1996
CIMMYT
Date
Location
Personnel
Objectives
Feb, 1997
Ciudad Obregon
TEAM-VRT
Discuss potential
Steve Phillips, Joanne LaRuffa,
collaborative work
IRSP 98, refine INSEY, 2-
Wade Thomason, Sherry Britton,
wheel tractor and wheat
Joe Vadder, Gordon Johnson,
bed planter design
Jan, 1999
Obregon & Texcoco
John Solie, Dick Whitney
Sep, 1999
Aug, 2000
Jan-Mar 2001
Texcoco
Texcoco
Ciudad Obregon
Erna Lukina
IRSP 98, use of EY as a
Marvin Stone, Kyle Freeman,
selection tool
IRSP 99, applications of
Roger Teal, Robert Mullen,
INSEY, sensor design
Kathie Wynn, Carly Washmon,
for plant breeding
Dwayne Needham
Kyle Freeman
Joint collaboration on
200-03530 NRI Grant
Wheat harvest
Wheat harvest
Apr 2001
July 2001
Ciudad Obregon
El Batan
Apr 2002
June 2002
Oct 2002
Ciudad Obregon
El Batan
El Batan
Kyle Freeman
Jagadeesh Mosali, Shambel Moges
Micah Humphreys, Paul Hodgen,
Carly Washmon
Paul Hodgen
NASA Grant
Robert Mullen, Kyle Freeman
Corn Sensing
Keri Brixey, Jason Lawles, Kyle Freeman Corn Harvest
TOTAL
8
33
http://www.dasnr.okstate.edu/nitrogen_use/cimmyt_visit_2001.htm
OSU Reflectance Sensor
(1996-2002)
Sensor/Amplifier
Integrated Circuit
Photo-Detector
Optical Filters
Collimation
Glass
Cover
Fiber Optic
Light Guides
Turf target
Crop Target
Light signal
Light
detection
Light
generation
Valve settings




Calculate NDVI
Lookup valve setting
Apply valve setting
Send data to UI
“Sensor”
OSU Active Sensor
(2001-present)
Valves
and
Nozzles
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
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
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 NO3-N
Chlorophyll Meters (cont.)
http://www.specmeters.com/Plant_Chlorophyll_
Meters/
How SPAD meters work IRRI (READ)
Go to Factors affecting SPAD values
Go to CRITCAL SPAD VALUES for varietal work
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://www.store.ripplecreek.com/categorygreenformulas.html
Short wavelength
High energy
Long wavelength
Low energy
Phycoerythrin
Chlorophyll b
Phycocyanin
B-Carotene
0.01
10
Infrared
Ultraviolet
X-Rays
Chlorophyll a
380
450
495
570 590 620
wavelength, nm
750
Response Index vs. Sufficiency
Measurement/Action
Non-N limiting
Farmer Check
NDVI
0.85
0.65
OSU-Precision Sensing
Varvel, Schepers, and Francis (1997)
NFOA
Sufficiency
Response Index = 0.85/0.65
= 0.65/0.85 * 100
= 1.31
= 76%
Planting date
1.days where GDD >0
2.days from planting to sensing
= 60
Predict Yield Potential
= 0.65/ days where GDD>0
YP0 = 2334.9 exp(NDVI*2.6493)
= 13071 kg/ha
Grain N uptake YP 0
= 13071 * 1.25%N
163
Grain N uptake YP N
= 13071 * 1.31 * 1.25%N
214
N Recommendation
= (214-163)/0.70
73
+ N if <95%
Rate = 30 lb N/ac
checked every 7 days
applied N all the way to R3
At max uptake (5 lb N/ac/day)
Sufficiency <90%, Max yields not achieved with in-season N, as yield potential had already been reduced.
corn grain = 1.25%N
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
sand deposition
depth to clay pan
electrical conductivity
Use of EM as a data
layer to better predict
yield potential
On-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)
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
K vs yield
P vs yield
N vs yield
pH vs yield
FES and SPAD
Chlorophyll Meters and Field Element Size
What is the connection?
Indirect Measures?
Is this a process of elimination like soil
testing?
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.
Normalized Difference Vegetation Index
(NDVI)
= NIR ref – red ref / NIR ref + red ref
Units:
Early-season plant N uptake, kg ha
-1
(up – down)
excellent predictor of plant N uptake
200
S*N Perkins, 1998
160
S*N Tipton, 1998
140
transect Stillw ater, 1999
transect Perkins, 1999
120
transect Efaw , 2000, Jan
100
transect Perkins, 2000 Jan
transect Efaw , 2000 Mar
80
transect Perkins, 2000 Mar
60
40
20
0
0
N uptake, kg
y = 1019.5x 3 - 1507.5x 2 + 811.5x - 130.32
R2 = 0.78
N*P Perkins, 1998
180
ha-1
0.1
0.2
0.3
0.4
0.5
0.6
NDVI, Feekes 4-6
0.7
0.8
0.9
1
Sensor Design (1991-96)
Micro-Processor, A/D Conversion, and Signal Processing
Photo-Detector
Optical Filters
Ultra-Sonic
Sensor
Collimation
Plant and Soil target
March 1996