Crop Canopy Sensors for High Throughput Phenomic SystemsDr. Mike Schlemmer, Agronomist/Wheat Trial Manager

Bayer Field Phenomics Program

Scope • Exploit the potential of phenomics to provide

novel insights in plant response to genetic and environmental variation.

Intent• Integrate phenomics with genomic marker

assisted selection to create a more efficient marker based selection process.

High Throughput Phenomic Sensor Suite Testing: Initial Phase

Genotype x Nitrogen x Plant Density

Data Collection

6 May

14 May

3 Jun

16 Jul

26 Apr

Yield Results

• Yield Response plateaus, 40-60 lbs N ac-1.

• Yield Response plateaus, 0.8-1.2 M plants ac-1.

Rapid Field Phenomic Sensor Suite

Optical Sensor

Companion Sensor

Upwelling PAR IRT

2 Chan Voltage Input/Pulse Counter Downwelling PAR

Humidity/Temp

Crop Circle DAS43X

Rapid Field Phenomic Sensor SuiteMeasured Variables

• Reflectance from 3 bands, 10nm FWHM (Red, Red Edge(RE), NIR)

• Select Optical Indices - Canopy Chlorophyll Index(RE), NDVI.

• Canopy Chl Content.

• Green Leaf LAI.

• Canopy Height (via optical methods and ultra-sonic).

• Downwelling PAR, Upwelling PAR = Fractional PAR (fPAR).

• Relative Humidity.

• Ambient Temperature, Canopy Temperature = Temperature Departure (DT).

3-second Running Average

0

1

2

3

4

5

6

1 459 917 1375 1833 2291 2749 3207 3665 4123 4581 5039 5497 5955 6413

Number of Readings

CI re

d-ed

ge

y = 773.74x - 198.3r2 = 0.8702

0

500

1000

1500

2000

2500

3000

0 0.5 1 1.5 2 2.5 3 3.5 4

Chl Index Red Edge (CIRE)

Can

opy

Chl

Con

tent

, mg

m-2

Data Collection Rate: 5Hz

yRed = -0.0041x + 13.134R2 = 0.2472

yBlue = -0.0035x + 12.985R2 = 0.2827

yGRN = -0.0233x + 30.76R2 = 0.7473

yRE = -0.0267x + 42.563R2 = 0.7628

yNIR = 0.0019x + 52.433R2 = 0.0149

0

10

20

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40

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100 200 300 400 500 600 700

Leaf Chl Content, mg m-2

Ref

lect

ance

, %

BlueGreenRedRed EdgeNIR

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

400 450 500 550 600 650 700 750 800 850 900

Wavelength, nm

Coe

ffici

ent o

f Det

erm

inat

ion,

r2

Coefficient of determination for the relationship between reflectance and chl content for each wavelength. • The peaks at 555 nm and 715 nm

indicate these regions to be maximally sensitive to chl content.

• Those peaks show a strong linear relationship to chl content where the blue and red absorbance regions do not.

Blue/Red - Absorb.

Upper and Lower Epidermis

Spongy mesophyll

Green-Refl.Near IR-Refl.

Air space

Stoma

Palisade Cells Chlorophyll

What spectral regions are most sensitive to Chlorophyll Content. Green and Red Edge

Canopy Chl Content as a function of the Red Edge Chl Index.

• Canopy Chl at the time of flowering may reach a response plateau near 100 lbs N ac-1.

• Yield Response plateaus near 40-60 lbs N ac-1.

• N Partitioning / Translocation? Grain Protein Content?

Fractionally Absorbed PAR (fAPAR).

• fAPAR was derived by calculating the ratio of upwelling to downwelling PAR, both measured at the height of the sensor.

• Provides an indication as to the efficiency of Photosynthesis and Net Primary Production.

Leaf Area Index as a function of NDVI

• Relationship between the NDVI function and leaf area index is not linear but reaches it’s limit more gradually at higher LAI’s.

• Green LAI is an exponential function of NDVI linearly related to measured LAI.

Canopy Height

• Plant height was determined by subtracting calculated sensor to target distance from measured sensor height.

• Sensor to target distance was calculated using square root of inverse NIR irradiance.

Holland et al., IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. (JSTARS) , V5, N6, 2012

Canopy Temperature Departure

• Delta Temperature was calculated by subtracting IRT measured canopy temperature from measured ambient temperature.

• Aerial IR cameras were used to acquire late season imagery. Stay green and late season varieties are clearly identifiable.

• Develop Phenomic markers to compliment Genomic markers that assist with efficient breeder selections.

• Utilize Greenhouse Lemnatec system to incorporate phenomic data into decision support system. Move this concept to the field scale.

• Future advances in high speed data capture, transfer, and analysis should enable on-the-go image based phenomic systems, providing more morphological information.

• UAV’s should be exploited to deliver both image and spectral sensor based systems to the field.

Opportunities with Phenomic Sensor Systems in Precision Agriculture and Plant Breeding:

Variety Plant Density N Average Yld chl fPAR LAI Height Delta TBL110002 800 40 - 0 0 - 0 0NE06545 1200 60 + - - - + -Overland 800 40 0 0 + + - 0Robidoux 1000 40 - 0 + - - 0

Wesley 1200 40 - + 0 + + +

•Image Recognition Approach (Field and Greenhouse).

•Lemnatec Greenhouse Activities.

Parallel Phenomic Research within Bayer

Additional Information

Sampling Date GDD:26 Apr 12 – 835.76 May 12 – 944.3

14 May 12 – 1068.73 Jun 12 – 1441.9