REMOTE SENSING OF IPM:Reflectance Measurements

of Aphid Infestation and Density Estimation in

Wheat Growing under Field Conditions.

Mustafa Mirik, Gerald J. Michels Jr., Norman C. Elliott, Sabina Kassymzhanova, Roxanne Bowling, Bob Villarreal, Vasile Catana, Timothy D. Johnson

As a part of the participation with AWPM for Wheat, the Entomology As a part of the participation with AWPM for Wheat, the Entomology Program in Amarillo is using an airborne hyperspectral spectrometer Program in Amarillo is using an airborne hyperspectral spectrometer for detecting aphid infestations. for detecting aphid infestations.

The work is conducted as a part of the Precision Agriculture Initiative The work is conducted as a part of the Precision Agriculture Initiative at Texas A & M in cooperation with Oklahoma State University and at Texas A & M in cooperation with Oklahoma State University and the USDA-ARS.the USDA-ARS.

How this fits with How this fits with AWPM for WheatAWPM for Wheat

Remote sensing helps detect greenbug Remote sensing helps detect greenbug infestations in wheat fields and helps infestations in wheat fields and helps demonstrate alternatives to costly spraying.demonstrate alternatives to costly spraying.

We hope to detect infestations before wheat We hope to detect infestations before wheat fields would require insecticide application to fields would require insecticide application to protect crops from economic losses.protect crops from economic losses.

It can be used to generate spatial, up-to-date It can be used to generate spatial, up-to-date information over time and space in combination information over time and space in combination with statistical tools such as GISwith statistical tools such as GIS

Remote sensing is the Remote sensing is the art & science of art & science of collecting information collecting information about the earth’s about the earth’s surface using some surface using some portions of the portions of the electromagnetic electromagnetic spectrum from ground, spectrum from ground, air and space platforms air and space platforms without physical contact without physical contact with the objects under with the objects under surveillancesurveillanceTo the right is the equipment that they use. Above right: Cessna 172; Right: airborne aerial spectometer.

MethodologyMethodologyCollected aphid density and spectral Collected aphid density and spectral reflectance data from Texas, Oklahoma and reflectance data from Texas, Oklahoma and ColoradoColorado

oAphid density included greenbug, bird-cherry oat, Aphid density included greenbug, bird-cherry oat, & Russian wheat aphids& Russian wheat aphidsoData collected in & over stressed and non-Data collected in & over stressed and non-stressed 0.25mstressed 0.25m22 wheat plots wheat plotsoReflectance data gathered by hyperspectral Reflectance data gathered by hyperspectral ground spectrometer over aphid infested wheat ground spectrometer over aphid infested wheat and non-infested wheat nearbyand non-infested wheat nearby

oSubsequently, at least 30 tillers were cut at Subsequently, at least 30 tillers were cut at ground level and transported to laboratory to ground level and transported to laboratory to count the number of aphids per 0.25mcount the number of aphids per 0.25m22 sample sample plotplotoRemaining tillers in each plot were tallied in Remaining tillers in each plot were tallied in the fields to estimate aphid density for each the fields to estimate aphid density for each sample plotsample plotoSometimes, aphid density was determined in Sometimes, aphid density was determined in the fields by counting all aphids within plots the fields by counting all aphids within plots during the early growing season or clipping all during the early growing season or clipping all plants and counting aphids in the laboratory plants and counting aphids in the laboratory during the late growing season as time permitsduring the late growing season as time permits

MethodologyMethodology

MethodologyMethodologyoAll in all, aphid density was All in all, aphid density was determined at 0.25mdetermined at 0.25m2 2 level for each level for each samplesample

oThe methodology was applied The methodology was applied to all sites and information given to all sites and information given during the following slidesduring the following slides

Distractive Distractive sampling to count sampling to count

aphids in the lab aphids in the lab when wheat was at when wheat was at

mid- and late mid- and late growth stages.growth stages.

TAMU employees at TAMU employees at work counting Russian work counting Russian

wheat aphids in the labwheat aphids in the lab

Russian wheat aphid Russian wheat aphid population in a population in a

0.25m0.25m22 wheat plot wheat plot

Survey team from the USDA-ARS, Survey team from the USDA-ARS, Stillwater, and TAMU collecting Stillwater, and TAMU collecting

aphid and remote sensing data in aphid and remote sensing data in the fieldthe field

400 500 600 700 800 900

Wavelength (nm)

0

10

20

30

40

50

No-StressAboitic & Aphid StressAphid Stress

The plot at the top represents the greenbug (GB) and The plot at the top represents the greenbug (GB) and bird-cherry oat aphid (BCOA) (mainly GB), combination of bird-cherry oat aphid (BCOA) (mainly GB), combination of aphid and abiotic stress, and no-stress on volunteer aphid and abiotic stress, and no-stress on volunteer wheat. The data were collected over infested wheat near wheat. The data were collected over infested wheat near Dumas, Texas in late fall 2003.Dumas, Texas in late fall 2003.

400 500 600 700 800 900

Wavelength (nm)

0

10

20

30

40

RWA StressAbiotic StressNo-StressSoil

Percen

t R

eflectan

ce

The plot above is the Russian wheat aphid (RWA) and The plot above is the Russian wheat aphid (RWA) and abiotic stress, no-stress on winter wheat, and exposed soil abiotic stress, no-stress on winter wheat, and exposed soil collected in a field near Amarillo, Texas in mid-April 2004. collected in a field near Amarillo, Texas in mid-April 2004.

Spectral reflectance of GB and RWA data were Spectral reflectance of GB and RWA data were plotted across the Visible and Near Infrared plotted across the Visible and Near Infrared (NIR) wavelengths.(NIR) wavelengths.

These plots clearly indicates that hot spots of GB These plots clearly indicates that hot spots of GB and RWA can be accurately detected and and RWA can be accurately detected and discriminated from the soil, abiotic stress and discriminated from the soil, abiotic stress and non-stressed wheat in fields with air- and space-non-stressed wheat in fields with air- and space-borne remote sensing platforms at an appropriate borne remote sensing platforms at an appropriate scalescale

The graph and table below depicts sampling done on The graph and table below depicts sampling done on wheat under 3 levels of stress: healthy plants, plants wheat under 3 levels of stress: healthy plants, plants stressed by greenbug alone, and plants stressed by a stressed by greenbug alone, and plants stressed by a combination of greenbug and abiotic factors (bar plot on combination of greenbug and abiotic factors (bar plot on the left) and RWA stress (table on the right).the left) and RWA stress (table on the right).

We found there were statistically significant We found there were statistically significant differences in the reflectance from each of these differences in the reflectance from each of these wheat conditions.wheat conditions.

A similar comparison of wheat stressed by Russian A similar comparison of wheat stressed by Russian wheat aphid versus healthy plants also showed wheat aphid versus healthy plants also showed significant differences in reflected lightsignificant differences in reflected light

These data substantiates the trend seen in the two These data substantiates the trend seen in the two previous graphs; it suggests we can use air- and space-previous graphs; it suggests we can use air- and space-borne imageries to detect aphid stress.borne imageries to detect aphid stress.

Healthy wheatHealthy wheat

Abiotic and Aphid Abiotic and Aphid Stressed WheatStressed Wheat

Aphid Stressed Aphid Stressed WheatWheat

These are the sample pictures of aphid stress, combination of aphid These are the sample pictures of aphid stress, combination of aphid and abiotic stress, and no-stress on volunteer wheat taken in the and abiotic stress, and no-stress on volunteer wheat taken in the same field near Dumas, Texas.same field near Dumas, Texas.

Aphid and combination of aphid and abiotic stresses are visually Aphid and combination of aphid and abiotic stresses are visually assessable in these pictures. We found eight spots heavily damaged assessable in these pictures. We found eight spots heavily damaged by aphid, both GB and BCOA; we also found 22 spots stressed by by aphid, both GB and BCOA; we also found 22 spots stressed by abiotic and biotic factors.abiotic and biotic factors.

These eight pictures were analyzed using ASSESS, Image Analysis These eight pictures were analyzed using ASSESS, Image Analysis Software for Plant Disease Quantification, to determine percent Software for Plant Disease Quantification, to determine percent damage caused by aphid feeding on wheat, (see next slide).damage caused by aphid feeding on wheat, (see next slide).

Then total aphid (GB + BCOA), GB, and BCOA densities were Then total aphid (GB + BCOA), GB, and BCOA densities were regressed against percent aphid damage to estimate aphid density. regressed against percent aphid damage to estimate aphid density. See slides 20, 21, & 22 for these results.See slides 20, 21, & 22 for these results.

This picture shows how the percent aphid damage was This picture shows how the percent aphid damage was assessed by masking either healthy or unhealthy parts of assessed by masking either healthy or unhealthy parts of the canopy. the canopy.

Aphid damage was outlined, and percent damage was Aphid damage was outlined, and percent damage was estimated on wheat leaves.estimated on wheat leaves.

We found strong correlations between percent We found strong correlations between percent aphid damage and density of total aphid, GB, and aphid damage and density of total aphid, GB, and BCOA (RBCOA (R22 = 0.85 for total aphid, GB, and BCOA = 0.85 for total aphid, GB, and BCOA Densities). The next three slides present slides Densities). The next three slides present slides that illustrate this.that illustrate this.

This graph shows This graph shows strong correlation strong correlation found between found between percent aphid percent aphid damage and total damage and total aphid density, aphid density, greenbug and greenbug and bird-cherry oat bird-cherry oat aphid. Raphid. R22 = 0.85 = 0.85

100 200 300 400 500

Aphid Density (0.25 m2)

30

40

50

60

70

Pe

rce

nt

Da

ma

ge

R2 = 0.85

N = 8

50 100 150 200 250 300

Greenbug Density (0.25 m2)

30

40

50

60

70

Perc

en

t D

am

ag

e

R2 = 0.85

N = 8This graph shows This graph shows percent damage percent damage and the and the correlation with correlation with greenbug density greenbug density (R(R22 = 0.85) = 0.85)

0 50 100 150 200

Bird-cherry Oat Aphid Density (0.25 m2)

30

40

50

60

70

Pe

rce

nt

Da

ma

ge

R2 = 0.85

N = 8This graph shows This graph shows percent damage percent damage and its and its correlation with correlation with bird-cherry oat bird-cherry oat aphid density (Raphid density (R22 = 0.85)= 0.85)

Reflectance data were analyzed by calculating 25 Reflectance data were analyzed by calculating 25 existing spectral vegetation indices and regressing existing spectral vegetation indices and regressing them against density of total aphid, GB, and BCOA them against density of total aphid, GB, and BCOA for 30 samples situated near Dumas. Of which, the for 30 samples situated near Dumas. Of which, the Carotenoid Reflectance Index (CRI) was best Carotenoid Reflectance Index (CRI) was best correlated with density of aphids.correlated with density of aphids.

0 500 1000 1500 2000 2500

Aphid Number (AN)

-100

-50

0

50

100

150

CR

I =

1/(

R 50

4-R

51

4)-1

/(R 5

40-

R56

4)

R2 = 0.74

N = 30

This graph shows This graph shows the correlation the correlation between CRI and between CRI and total aphid (GB & total aphid (GB & BCOA) number.BCOA) number.

This graph shows This graph shows the correlation the correlation between CRI and between CRI and greenbug density.greenbug density.

0 400 800 1200

Greenbug Density (0.25 M2)

-100

-50

0

50

100

150

CR

I =

1/(

R 504-

R514)

-1/(

R 540-

R564)

R2 = 0.67

N = 30

0 200 400 600 800 1000 1200

Bird-cherry Oat Aphid

-100

-50

0

50

100

150

CR

I =

1/(

R 504-R

514)-1

/(R 5

40-R

564)

R2 = 0.73

N = 30

This graph This graph shows the shows the correlation correlation between CRI between CRI and bird-and bird-cherry oat cherry oat aphid density.aphid density.

0 1000 2000 3000 4000 5000 6000 7000

Aphid Density (AD)/0.25 M2

0

10

20

30

ND

VI =

(R 84

0-R

87

5-R

66

0-R

68

0)/(

(R84

0-R

87

5)+

(R66

0-R

68

0))

R2 = 0.75

N = 24

Spectral Spectral reflectance data reflectance data gathered in gathered in Oklahoma winter Oklahoma winter wheat fields wheat fields exhibited similar exhibited similar trends to the trends to the data collected data collected near Dumas for near Dumas for aphid density aphid density estimation. estimation.

This graph shows the relationship This graph shows the relationship between NDVI (Normalized Difference between NDVI (Normalized Difference Reflectance Index) and total aphid (GB & Reflectance Index) and total aphid (GB & BCOA) density.BCOA) density.

0 1000 2000 3000 4000

GB/0.25 M2

0

10

20

30

ND

VI =

(R

84

0-R

87

5-R

66

0-R

68

0)/(

(R84

0-R

87

5)+

(R60

0-R

68

0))

R2 = 0.73

N = 24

The graph shows The graph shows the relationship the relationship between NDVI between NDVI and greenbug and greenbug density.density.

0 500 1000 1500 2000 2500 3000

BCOA/0.25 M2

2.2

2.7

3.2

3.7

4.2

4.7

gN

DV

I =

(R 7

52-

R8

96-

R5

40-

R5

68)

/((R

75

2-R

89

6)+

(R5

40-

R5

68)

)

R2 = 0.75

N = 24

The graph shows The graph shows the relationship the relationship between green between green NDVI and bird-NDVI and bird-cherry oat aphid cherry oat aphid density.density.

Strong linear relationship were found between RWA Strong linear relationship were found between RWA density and spectral vegetation indices for both density and spectral vegetation indices for both Texas (slide 31) and Colorado (slide 32) winter Texas (slide 31) and Colorado (slide 32) winter wheat fields. Correlations were 97% for Texas and wheat fields. Correlations were 97% for Texas and 77% for the Colorado wheat fields.77% for the Colorado wheat fields.

TexasTexasThis slide shows This slide shows the correlation the correlation between CR between CR (Chlorophyll (Chlorophyll Ratio) and RWA Ratio) and RWA densitydensity

0 10000 20000 30000 40000

RWA/0.25 m2)

020

000

4000

060

000

CR

= (

R75

7- R

890)

/(R

554-

R56

1)2

R2 = 0.97

N = 20

ColoradoColorado

ColoradoColoradoThis slide shows This slide shows the correlation the correlation between NDVI between NDVI and RWA densityand RWA density

500 3000 5500 8000 10500 13000 15500

RWA Density (0.25 m2)

0.1

0.2

0.3

0.4

0.5

0.6

ND

VI

= (

R 760

- R

708)

/(R

760

+ R

708)

R2 = 0.77

N = 25

We have also worked on estimating and We have also worked on estimating and comparing wet and dry biomass of stressed by comparing wet and dry biomass of stressed by RWA and non-stressed wheat near Amarillo. The RWA and non-stressed wheat near Amarillo. The next slide shows that there were significant next slide shows that there were significant differences between wet and dry biomass of differences between wet and dry biomass of stressed and non-stressed wheat. The next slide stressed and non-stressed wheat. The next slide gives a slide illustrating this.gives a slide illustrating this.

0

200

400

600

800W

ET

AN

D D

RY

BIO

MA

SS

(G

R/0

.25 M

2 )WET BIOMASS OF NO STRESS PLOTS

N = 21

WET BIOMASS OF

RWA STRESS PLOTS

N = 21

DRY BIOMASS OF

NO STRESS PLOTS

N = 21

DRY BIOMASS OF

RWA STRESS PLOTS

N = 21

a

b

a b

10000 20000 30000 40000

Dry Biomass2 (gr/m2) in RWA Infested Plots

0.0

02

00.0

02

50.0

03

00.0

03

50.0

04

00.0

04

50.0

05

0

mN

DV

I =

(R

77

8 - R 7

43)/

(R77

8+ R

74

3)2R2 = 0.80

N = 21

This slide shows dry biomass estimation for RWA infested and This slide shows dry biomass estimation for RWA infested and non-infested wheat. High Rnon-infested wheat. High R22 values (0.80 and 0.69 for infested values (0.80 and 0.69 for infested and non-infested wheat, respectively) indicate the usefulness of and non-infested wheat, respectively) indicate the usefulness of remote sensing technology and techniques to predict wheat remote sensing technology and techniques to predict wheat biomass regardless of aphid infestation.biomass regardless of aphid infestation.

Last year, we collected baseline data to correlate Last year, we collected baseline data to correlate observed aphid density and damage in wheat to observed aphid density and damage in wheat to ground-based remote sensing data. ground-based remote sensing data.

These preliminary results showing established These preliminary results showing established correlations strongly force us to move to forward. correlations strongly force us to move to forward.

In addition to these, remote sensing technologies and In addition to these, remote sensing technologies and techniques are highly promising to detect aphid techniques are highly promising to detect aphid stress in other field crops.stress in other field crops.

In the next year, we plan to move from the ground-In the next year, we plan to move from the ground-based remote sensing to air-borne hyperspectral based remote sensing to air-borne hyperspectral and/or satellite multispectral remote sensing.and/or satellite multispectral remote sensing.

We expect to use hyperspectral or multispectral We expect to use hyperspectral or multispectral imageries to detect aphid-induced stress in wheat imageries to detect aphid-induced stress in wheat and sorghum, and possibly other crops at larger and sorghum, and possibly other crops at larger scales if the conditions permit.scales if the conditions permit.

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