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Canopy Sensor Basics and Required Data Inputs

Precision Ag ClinicAugust 2, 2017

Outline

•Active Crop Canopy Sensing

• Sensor-Based Nitrogen Application

•Calculating an EONR

Active Crop Canopy

Sensing

How do we discern crop stress?Color or

patterns on leaves

Leaf or plant shape

Spatial patterns

within a field

Remote SensingCollecting information about an object using a sensing device that is not in contact with the object of interest

Electromagnetic Spectrum

• Visible (0.4-0.7 µm)

• Infrared (0.7-14 µm)• Near-Infrared (0.7-1.3 µm)• Middle Infrared (1.3-3.0 µm)• Thermal Infrared (3.0-14 µm)

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Spectral Signature

Visible NIRPlant pigments (e.g. chlorophyll) Leaf cell structure (biomass)

Chlorophyll and Leaf

Area Affect Reflectance

Chlorophyll Content

0

10

20

30

40

50

60

400 450 500 550 600 650 700 750 800 850

Ref

lect

ance

(%

)

Wavelength (nm)

2% 13% 30% 78% 100%

Leaf Area

Vegetation Indices

𝑵𝑫𝑽𝑰 =𝑁𝐼𝑅 − 𝑅𝑒𝑑

𝑁𝐼𝑅 + 𝑅𝑒𝑑

𝑵𝑫𝑹𝑬 =𝑁𝐼𝑅 − 𝑅𝑒𝑑 𝐸𝑑𝑔𝑒

𝑁𝐼𝑅 + 𝑅𝑒𝑑 𝐸𝑑𝑔𝑒

Active Sensors

• Sensors emit their own light source

• Light is modulated and timed

• No effects of sunlight or clouds

• Point data, not an image

Commercially Available Systems

Trimble GreenSeeker®

Ag Leader OptRxTM

Topcon CropSpecTM

HandheldSensor Demo

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Sensors for Nitrogen Management N Sufficiency

𝑁𝐷𝑅𝐸𝑇𝑎𝑟𝑔𝑒𝑡

𝑁𝐷𝑅𝐸𝑅𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒

Virtual Reference Method• Histogram identifies adequately

fertilized plants

• 95th percentile

Average NDREfor N-Rich Strip (220 lbs/ac)

0.374

95th-percentile NDRE for Base Rate Strip (80 lbs/ac)

0.386

Ag Leader OptRxTM Algorithm

𝑁𝑂𝑃𝑇 − 𝑁𝑃𝑟𝑒 − 𝑁𝐶𝑅𝐷 ∙1 − 𝑆𝐼

∆𝑆𝐼

0

50

100

150

200

250

300

350

0 0.2 0.4 0.6 0.8 1N R

eco

mm

end

atio

n (

lbs/

ac)

Sufficiency Index

Holland-Schepers vs. Ag Leader OptRxTM Algorithm

Holland-Schepers Ag Leader

Advantages• In-season application

• Mitigates N losses• Applied during maximum

N uptake• “Reactive” approach—can

identify and correct early-season stress

Advantages

• Variable rate

• Controls for spatial variability

• Match N supply with crop demand

• Often conserves N

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• On-the-go

• Sensing and fertilizing accomplished

in one pass

• No time delay between assessment

and treatment

Advantages Disadvantages• Non-recoverable N deficiency

• Adverse weather can restrict

field entry and delay application

• High capital investment

What Is My EONR?

Spatial and Temporal Variability

No endorsement or criticism is intended for brand names mentioned or any equivalent products not mentioned.

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UNL Algorithm• Yield goal• Residual soil nitrate• Soil organic matter• Other N sources • Application timing• Corn and fertilizer prices• https://cropwatch.unl.edu/docum

ents/unl_n_calculator_2008.xls

Additional Research Questions• Can management zone-based

recommendations be combined with sensor-based fertilization?

• What is the threshold SI value that determines application?

Additional Research Questions

• How do UAV-mounted passive sensors compare to active sensors for N recommendation?

• Can sensors be used to direct multiple fertigation events?

Extension is a Division of the Institute of Agriculture and Natural Resources at the University of Nebraska–Lincoln cooperating with the

Counties and the United States Department of Agriculture.

crowther.joel@huskers.unl.edu

cropwatch.unl.edu/projectsense

: Nebraska On-Farm Research Network

University of Nebraska–Lincoln Extension educational programs abide with the nondiscrimination policies of the University of Nebraska–

Lincoln and the United States Department of Agriculture.