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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

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soil 4213 bioen 4213 history of using indirect measures for detecting nutrient status

SOIL 4213BIOEN 4213History of Using Indirect Measures for detecting Nutrient Status

Oklahoma State University

field element size
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
slide3
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
slide4

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
slide5

Absorption of Visible Light

by Photopigments

SPAD 501, 502

(430, 750)

Sunlight reaching

earth

Phycoerythrin

Chlorophyll b

Phycocyanin

Absorption

B-Carotene

Chlorophyll a

300 400 500 600 700 800

Wavelength, nm

Lehninger, Nelson and Cox

slide6

Short wavelength

High frequency

High energy

Long wavelength

Low frequency

Low energy

Yellow-green Yellow Violet Blue Green-blue Blue-green

VISIBLE Color Transmitted

Microwaves and short radio

Violet Blue Green Yellow Orange Red

Radio, FM, TV

Gamma Rays

Ultraviolet

VISIBLE Color Absorbed

Infrared

X-Rays

0.01 10 380 450 495 570 590 620 750 1x106 1x1011

wavelength, nm

Electronic Vibrational Rotational

transitions transitions transitions

slide7

Short wavelength

High energy

Long wavelength

Low energy

Phycoerythrin

Chlorophyll b

Phycocyanin

B-Carotene

Chlorophyll a

Ultraviolet

Infrared

X-Rays

0.01 10 380 450 495 570 590 620 750

wavelength, nm

near infrared absorption major amino and methyl analytical bands and peak positions

CH3

CH3

CH3

CH3

CH3

CH3

RNH2

RNH2

RNH2

RNH2

| | | | | | | | | | | | | | | |

700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200

Wavelength, nm

Near-Infrared AbsorptionMajor Amino and Methyl Analytical Bands and Peak Positions
slide9

White Light

Interference Filter

Photodiode

Phycocyanin

Chlorophyll b

B-Carotene

Phycoerythrin

Chlorophyll a

380 450 495 570 590 620 750

wavelength, nm

slide10

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.

slide11

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.

cimmyt
CIMMYT

Date

Location

Personnel

Objectives

Feb, 1997

Ciudad Obregon

TEAM-VRT

Discuss potential

collaborative work

Jan, 1999

Obregon & Texcoco

Steve Phillips, Joanne LaRuffa,

IRSP 98, refine INSEY, 2-

Wade Thomason, Sherry Britton,

wheel tractor and wheat

Joe Vadder, Gordon Johnson,

bed planter design

John Solie, Dick Whitney

Sep, 1999

Texcoco

Erna Lukina

IRSP 98, use of EY as a

selection tool

Aug, 2000

Texcoco

Marvin Stone, Kyle Freeman,

IRSP 99, applications of

Roger Teal, Robert Mullen,

INSEY, sensor design

Kathie Wynn, Carly Washmon,

for plant breeding

Dwayne Needham

Jan-Mar 2001

Ciudad Obregon

Kyle Freeman

Joint collaboration on

200-03530 NRI Grant

Apr 2001

Ciudad Obregon

Kyle Freeman

Wheat harvest

July 2001

El Batan

Jagadeesh Mosali, Shambel MogesMicah Humphreys, Paul Hodgen,Carly Washmon

Wheat harvest

Apr 2002

Ciudad Obregon

Paul Hodgen

NASA Grant

June 2002

El Batan

Robert Mullen, Kyle Freeman

Corn Sensing

Oct 2002

El Batan

Keri Brixey, Jason Lawles, Kyle Freeman

Corn Harvest

TOTAL

8

33

http://www.dasnr.okstate.edu/nitrogen_use/cimmyt_visit_2001.htm

slide16

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
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
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
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/agfs0394.htm
  • http://www.store.ripplecreek.com/category-greenformulas.html
slide20

Short wavelength

High energy

Long wavelength

Low energy

Phycoerythrin

Chlorophyll b

Phycocyanin

B-Carotene

Chlorophyll a

Ultraviolet

Infrared

X-Rays

0.01 10 380 450 495 570 590 620 750

wavelength, nm

on the go chemical analyses
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
slide25

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
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
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
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.
slide29

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

slide30

Sensor Design (1991-96)

Micro-Processor, A/D Conversion, and Signal Processing

Photo-Detector

Optical Filters

Ultra-Sonic

Collimation

March 1996

Sensor

Plant and Soil target