Remote Sensing of Aphid-Induced Stress in Wheat BAE/SOIL Precision Agriculture Oklahoma State University Victor W. Slowik April 20, 2001

Remote Sensing of Aphid-Induced Stress in Wheat  Experimental Hypothesis: Reductions in yield can be associated with insect stress at varied infestation rates.  Experimental Premise –NDVI correlated with biomass and yield –NDVI associated with plant health –Stress adversely impacts plant health –Reductions in NDVI as a result of plant stress can be related to yield reductions.

Remote Sensing of Aphid-Induced Stress in Wheat  Study Objectives –Collect data from infested plots. –Incorporate data from parent study Climatic data from weather station Greenbug and parasite counts Wheat yield data –Determine relationships in data Statistical Analyses Literature Review of similar work –Present Results and Conclusions

Remote Sensing of Aphid-Induced Stress in Wheat  Remotely sense data for infested plots. –Equipment List: Exotech 100BX Radiometer –4 bands filtered to emulate LandSat TM Bands 1 through 4 (Blue to NIR) Laptop for data collection –National Instruments DAQ-500 card for radiometer-computer interaction –ExoCollect – a Visual Basic program to control data collection activities.

Remote Sensing at Perkins Research Station

ExoCollect Data Collection Program

Remote Sensing of Aphid-Induced Stress in Wheat  Data collected for each plot sample: –Plot Identifier from tag* –Date* –Time* –Sensor configuration –Instrument height (sensed area) –Field of View (sensed area) –Gain setting for each of the four channels –Voltage for each of the four channels * required to identify unique sample

Exotech 100BX Radiometer Bandwidths Sensor Band Bandpass (µm) TM 1 Blue 0.45 – 0.52 TM 2 Green 0.52 – 0.60 TM 3 Red 0.63 – 0.69 TM 4 NIR 0.76 – 0.90

Remote Sensing of Aphid-Induced Stress in Wheat  Compute reflectance for plot sample: –For Each of the four bands: Refl = Voltage * Area * (SERE)*10 exp »Refl – Reflectance in Watts »Voltage – Volts »Area – cm 2 »Source Equivalent Radiant Emittance* (W/cm 2 /Volt) »Exp – exponent* * from Radiometer Calibration Table

Remote Sensing of Aphid-Induced Stress in Wheat  Eighty plots are sampled: Two cultivars Four replications for each cultivar –Ten plots per replication –Five infestation rates (0 through 4) »0 = control (no infestation) »one each for Fall and Spring

Remote Sensing at Perkins Research Station

Remote Sensing of Aphid-Induced Stress in Wheat  Study Objectives Incorporate Climatic Data from Parent Study –Temperature –Precipitation –Incident Radiation Incorporate Insect Data –Greenbug counts –Parasite counts (mummies and wasps) Wheat Yield Data –Grain counts (extrapolate to estimate yield)

Weather Station at Perkins Research Station

Remote Sensing of Aphid-Induced Stress in Wheat  Challenges Radiometer Data –Spatial Scale (1m vs. 30m data) –Normalization (Incident Radiation) Climatic Data –Temporal resolution (hourly averages) –Cause / Effect Lag –Non-linear responses Wheat Yield Data –Error introduced by extrapolation

Remote Sensing of Aphid-Induced Stress in Wheat  Summary –The basic challenge is to isolate plant stress caused by greenbugs from other factors that affect NDVI. –I do not expect explicit success due to experimental problems with spatial, radiometric and temporal scales.

Sample Plot of Raw Data

Remote Sensing of Aphid-Induced Stress in Wheat  Conclusion –Eventually, studies of this type could be technically and economically feasible as remote sensing methods becomes more sophisticated. Extent must increase Grain (spatial resolution) must decrease Spectral resolution must improve Radiometric resolution must improve Spatial pattern recognition incorporated (GIS)

Remote Sensing of Aphid-Induced Stress in Wheat References –Model 100BX Hand-Held Radiometer Instruction Manual, Exotech Incorporated. –Lillesand, T.M., Kiefer, R.W. Remote Sensing and Image Interpretation, Third Edition, John Wiley & Sons, Inc., New York, –Riedell, W.E., Blackmer, T. M., Leaf Reflectance Spectra of Cereal Aphid-Damaged Wheat, Crop Science, 39: , –Riedell, W.E. et al., Leaf and Canopy Reflectance Indicators for Remote Sensing of Greenbug Damage, Proceedings of 1999 Entomological Society of America Symposium, Oklahoma State University, 2000.

Remote Sensing of Aphid-Induced Stress in Wheat Acknowledgements –Dr. Norm Elliott, ARS Research Scientist, provided access to an ongoing study in greenbug population dynamics as the basis for this study. –Dr. Stuart Phinn, Professor of Geography at the University of Queensland (Australia), provided compiled code of a data collection program for the 100BX. It facilitated the creation of ExoCollect.