2/19/2003SOIL/BAE of 50 Sensing technologies for precision Farming Application of optical sensors

2/19/2003SOIL/BAE of 50 Optical sensing in Precision Farming (Techniques) Aerial remote sensing Film (visible/NIR/IR) and digitization Direct Digital recording Field machine based remote sensing Direct Digital recording Manual crop survey methods Direct Digital (manual recording /logging) Aerial remote sensing Film (visible/NIR/IR) and digitization Direct Digital recording Field machine based remote sensing Direct Digital recording Manual crop survey methods Direct Digital (manual recording /logging)

2/19/2003SOIL/BAE of 50 Purpose for use of optical sensing in Precision Farming Used to characterize plant or soil status Requirement: Calibration of spectral parameters to status Used to characterize boundaries –Physical –Morphological Requirement: Accurate spatial calibration (1m actual = 1 pixel) Lat/Lon = f(pixel position) Used to characterize plant or soil status Requirement: Calibration of spectral parameters to status Used to characterize boundaries –Physical –Morphological Requirement: Accurate spatial calibration (1m actual = 1 pixel) Lat/Lon = f(pixel position)

2/19/2003SOIL/BAE of 50 Issues in conducting remote sensing –Variability in light source –Filtering of light along path –Measuring units/calibration of sensing system –Geometry –Spatial and temporal frequency of measurements –Variability in light source –Filtering of light along path –Measuring units/calibration of sensing system –Geometry –Spatial and temporal frequency of measurements

2/19/2003SOIL/BAE of 50 Typical Multi-Spectral Sensor Construction Analog to Digital Converter Computer One Spectral Channel Photo-Diode detector / Amplifier Optical Filter Collimator Target Illumination CPU Radiometer

2/19/2003SOIL/BAE of 50 Fiber-Optic Spectrometer Optical Glass Fiber Photo Diode Array Optical Grating Analog to Digital Converter Computer CPU Element selection One Spectral Channel at a time

2/19/2003SOIL/BAE of 50 Fundamentals of Light Light = Energy (radiant energy) –Readily converted to heat Light shining on a surface heats the surface Heat = energy Light = Electro-magnetic phenomena –Has the characteristics of electromagnetic waves (eg. radio waves) –Also behaves like particles (e.g.. photons) Light = Energy (radiant energy) –Readily converted to heat Light shining on a surface heats the surface Heat = energy Light = Electro-magnetic phenomena –Has the characteristics of electromagnetic waves (eg. radio waves) –Also behaves like particles (e.g.. photons)

2/19/2003SOIL/BAE of 50 Relationship between frequency and wavelength Plus Minus Plus

2/19/2003SOIL/BAE of 50 Relationship between frequency and wavelength Wavelength = speed of light divided by frequency (miles between bumps = miles per hour / bumps per hour)

2/19/2003SOIL/BAE of 50 Relationship between frequency and wavelength Plus Minus Plus Antenna +- KOSU = 3 x 10 8 / 97.1 x 10 6 KOSU = 3 m red = 6.40 x m = 640 nm Bohr’s Hydrogen = 5 x m

2/19/2003SOIL/BAE of 50 Light emission / absorption governed by quantum effects Planck  E is light energy flux n is an integer (quantum) h is Planck’s constant is frequency Einstein One “photon”

2/19/2003SOIL/BAE of 50 Changes in energy states of matter are quantitized Bohr Where E k, E j are energy states (electron shell states etc.) and frequency, , is proportional to a change of state and hence color of light. Bohr explained the emission spectrum of hydrogen. Where E k, E j are energy states (electron shell states etc.) and frequency, , is proportional to a change of state and hence color of light. Bohr explained the emission spectrum of hydrogen. Hydrogen Emission Spectra (partial representation) Wavelength

2/19/2003SOIL/BAE of 50 Photo-ChemistryPhoto-Chemistry Light may be absorbed and participate (drive) a chemical reaction. Example: Photosynthesis in plants The wavelength must be correct to be absorbed by some participant(s) in the reaction Some structure must be present to allow the reaction to occur Chlorophyll Plant physical and chemical structure The wavelength must be correct to be absorbed by some participant(s) in the reaction Some structure must be present to allow the reaction to occur Chlorophyll Plant physical and chemical structure

2/19/2003SOIL/BAE of 50 Visual reception of color Receptors in our eyes are tuned to particular photon energies (h ) Discrimination of color depends on a mix of different receptors Visual sensitivity is typically from wavelengths of ~350nm (violet) to ~760nm (red) Receptors in our eyes are tuned to particular photon energies (h ) Discrimination of color depends on a mix of different receptors Visual sensitivity is typically from wavelengths of ~350nm (violet) to ~760nm (red) Wavelength 400 nm 700 nm 500 nm

2/19/2003SOIL/BAE of 50 Silicon Responsivity

2/19/2003SOIL/BAE of 50 Primary and secondary absorbers in plants Primary –Chlorophyll-a –Chlorophyll-b Secondary –Carotenoids –Phycobilins –Anthocyanins Primary –Chlorophyll-a –Chlorophyll-b Secondary –Carotenoids –Phycobilins –Anthocyanins

2/19/2003SOIL/BAE of 50 Nature of absorption by the atmosphere Incident Reflected Transmitted Absorbed Radiant energy balance must be computed for each component of the atmosphere and for each wavelength to estimate the radiation incident on the earth's surface Radiant energy balance must be computed for each component of the atmosphere and for each wavelength to estimate the radiation incident on the earth's surface Earth's surface Atmosphere

2/19/2003SOIL/BAE of 50 Radiation Energy Balance Incoming radiation interacts with an object and may follow three exit paths: Reflection Absorption Transmission  +  +  = 1.0 , , and  are the fractions taking each path Known as absorbance,transmittance, reflectance respectively Incoming radiation interacts with an object and may follow three exit paths: Reflection Absorption Transmission  +  +  = 1.0 , , and  are the fractions taking each path Known as absorbance,transmittance, reflectance respectively I 0  I 0  I 0  I 0

2/19/2003SOIL/BAE of 50 ReflectanceReflectance –Ratio of incoming to reflected irradiance –Incoming can be measured using a “white” reflectance target –Reflectance is not a function of incoming irradiance level or spectral content, but of target characteristics –Ratio of incoming to reflected irradiance –Incoming can be measured using a “white” reflectance target –Reflectance is not a function of incoming irradiance level or spectral content, but of target characteristics

2/19/2003SOIL/BAE of 50 Solar Irradiance NIR UV

Sunlight Chlorophyll b B-Carotene Phycocyanin Chlorophyll a Wavelength, nm Absorption Lehninger, Nelson and Cox Absorption of Visible Light by Photopigments Absorption of Visible Light by Photopigments

Wavelength (nm) Reflectance (%) Visible Near Infrared Plant Reflectance

2/19/2003SOIL/BAE of 50 Spectral response to Nitrogen

2/19/2003SOIL/BAE of 50 Soil and crop reflectance

2/19/2003SOIL/BAE of 50 Interfering Inputs: Soil Reflectances - Oklahoma

2/19/2003SOIL/BAE of 50 Soil Reflectances - Oklahoma

2/19/2003SOIL/BAE of 50 Thermal or Infrared imaging Nature of the Emission of Radiation –Black-body radiation Matter is made up of inter-related particles which may be considered to vibrate or change energy state A distribution of energy states exists within a blackbody Matter emits radiation in proportion to the energy state changes –Warm matter emits radiation You can feel the radiated energy from a hot poker Colder bodies also emit, just at a lower level Nature of the Emission of Radiation –Black-body radiation Matter is made up of inter-related particles which may be considered to vibrate or change energy state A distribution of energy states exists within a blackbody Matter emits radiation in proportion to the energy state changes –Warm matter emits radiation You can feel the radiated energy from a hot poker Colder bodies also emit, just at a lower level

2/19/2003SOIL/BAE of 50 Sun vs. Plant / Soil radiation 6000K 300K SUN Terrestrial Thermal radiation

2/19/2003SOIL/BAE of 50 Infrared Image example GER Corporation

2/19/2003SOIL/BAE of 50 Sensor-Based Nitrogen Management Variable Rate Nozzle system Direction of Travel Computer and Sensor Assembly Decision Making And Agronomic Strategy Plant

2/19/2003SOIL/BAE of 50 NDVI - Normalized Difference Vegetative Index Developed as an irradiance Index for remote sensing Varies from -1 to 1 Soil NDVI = to.05 Plant NDVI = 0.6 to 0.9 Typical plants with soil background NDVI= NDVI from different sources vary –Bandwidths for Red, NIR vary –Irradiance vs. reflectance based Properties Difference increases with greater red absorption Increase or decrease in total irradiance does not effect NDVI Typically computed with irradiances, use of reflectance eliminates spectral shift sensitivity Developed as an irradiance Index for remote sensing Varies from -1 to 1 Soil NDVI = to.05 Plant NDVI = 0.6 to 0.9 Typical plants with soil background NDVI= NDVI from different sources vary –Bandwidths for Red, NIR vary –Irradiance vs. reflectance based Properties Difference increases with greater red absorption Increase or decrease in total irradiance does not effect NDVI Typically computed with irradiances, use of reflectance eliminates spectral shift sensitivity

2/19/2003SOIL/BAE of 50 Irradiance Indices Spectral shift in illumination prevents use of simple irradiance sensing Based on ratios of reflected Red and NIR intensity Example Index: R red / R nir

2/19/2003SOIL/BAE of 50 OSU Irradiance ratio sensor

2/19/2003SOIL/BAE of 50 Reflectance Indices Based on ratios of Red and NIR Reflectance Red Reflectance:  red = R red / I red Reflectance is primarily a function of target NIR Reflectance:  nir = R red / I red Index:

2/19/2003SOIL/BAE of 50 OSU Reflectance Sensor

2/19/2003SOIL/BAE of 50 OSU Reflectance Sensor Natural Illumination Battery powered Wide dynamic range Low noise 0.75 x 0.25 m field of view Natural Illumination Battery powered Wide dynamic range Low noise 0.75 x 0.25 m field of view

2/19/2003SOIL/BAE of 50 Self contained illumination (NTech)

2/19/2003SOIL/BAE of 50 Sensor Function

2/19/2003SOIL/BAE of 50 Sensor-Based Variable Rate Top-Dress Fertilizer Concept: (OSU wheat) Plant spectral reflectance in red and NIR bands are used to measure nitrogen uptake and estimate crop yield Plant is an indicator of availability of nutrients, germination levels, previous environment, insect damage, etc. Application rate determined based on estimated yield and response index Plant spectral reflectance in red and NIR bands are used to measure nitrogen uptake and estimate crop yield Plant is an indicator of availability of nutrients, germination levels, previous environment, insect damage, etc. Application rate determined based on estimated yield and response index

2/19/2003SOIL/BAE of 50 Farmer PracticeNon-N Limiting In-Season Response Index (RI NDVI )

2/19/2003SOIL/BAE of 50 GreenSeeker TM N-Fertilizer Handheld Optical Sensor The same active lighting optical sensor used on the variable rate fertilizer applicator Optically measures plant biomass, total nitrogen in the crop, and plant stress Can sample scan a wheat field (or other crop) Data can use to calculated response index for added nitrogen fertilizer The same active lighting optical sensor used on the variable rate fertilizer applicator Optically measures plant biomass, total nitrogen in the crop, and plant stress Can sample scan a wheat field (or other crop) Data can use to calculated response index for added nitrogen fertilizer

2/19/2003SOIL/BAE of 50 TilleringTillering Stem Extension HeadingHeading RipeningStage Yield Estimation: (modeling growth in wheat)

2/19/2003SOIL/BAE of 50 Yield Estimation INSEY vs Grain Yield (24 locations, )

2/19/2003SOIL/BAE of 50 Role of RI in Yield Estimation y = 1.06x R 2 = 0.56 RI Harvest RI NDVI Estimates yield with added N

2/19/2003SOIL/BAE of 50 Yield Estimation with Fertilizer (OSU wheat) YP 0 YP N (RI=1.5) Farmer Selected YP MAX YP N (RI=2.0)

2/19/2003SOIL/BAE of 50 N Fertilization Rate Algorithm (OSU wheat)

2/19/2003SOIL/BAE of 50 Implementation of Sensor-Based Variable Rate Nitrogen Application

2/19/2003SOIL/BAE of 50 G REEN S EEKER TM Applicator G REEN S EEKER TM Applicator Sense and treat each 2 ft by 2 ft area Applies one of seven fertilizer rates based on the crops yield potential Up to 15 mph machine speed Day or night operation Provide the capability to detect and treat other plant problems Record and georeference sensor data for GIS analysis Sense and spot spray weeds (current Patchen technology) Sense and treat each 2 ft by 2 ft area Applies one of seven fertilizer rates based on the crops yield potential Up to 15 mph machine speed Day or night operation Provide the capability to detect and treat other plant problems Record and georeference sensor data for GIS analysis Sense and spot spray weeds (current Patchen technology)

2/19/2003SOIL/BAE of 50 Tri-valve Set for Varying Rate 8 Stepped rates –OFF to 7x Treats 24”x 24” area applying the target rate on 85% of that area 8 Stepped rates –OFF to 7x Treats 24”x 24” area applying the target rate on 85% of that area ValveRate 1x2x4xTotal x 2x 4x

2/19/2003SOIL/BAE of 50 Summary of Results - 10 Field Trials GreenSeeker TM Field Sprayer (OSU Wheat) TreatmentPre-Trt. N, lb/ac Trt. N, lb/ac Total N, lb/ac Yield, lb/ac Net Rtn, $/ac N-Rich Strip Var. Rate Fixed Rate A Fixed Rate B Field Rate SED Treated March 20 to April 10, 2002 Net Revenue = grain yield * $3.00 / bu – N Fertilizer * $0.25 / lb SED = Standard Error of the Difference