ARS  Vol.2 No.1 , March 2013
Remote Monitoring of Wheat Streak Mosaic Progression Using Sub-Pixel Classification of Landsat 5 TM Imagery for Site Specific Disease Management in Winter Wheat
Abstract: Wheat streak mosaic (WSM), caused by Wheat streak mosaic virus is a viral disease that affects wheat (Triticum aestivum L.), other grains, and numerous grasses over large geographical areas around the world. To improve disease management and crop production, it is essential to have adequate methods for monitoring disease epidemics at various scales and multiple times. Remote sensing has become an essential tool for monitoring and quantifying crop stress due to biotic and abiotic factors. The objective of our study was to explore the utility of Landsat 5 TM imagery for detecting, quantifying, and mapping the occurrence of WSM in irrigated commercial wheat fields. The infection and progression of WSM was biweekly assessed in the Texas Panhandle during the 2007-2008 crop years. Diseased-wheat was separated from uninfected wheat on the images using a sub-pixel classifier. The overall classification accuracies were >91% with kappa coefficient between 0.80 and 0.94 for disease detection were achieved. Omission errors varied between 2% and 14%, while commission errors ranged from 1% to 21%. These results indicate that the TM image can be used to accurately detect and quantify disease for site-specific WSM management. Remote detection of WSM using geospatial imagery may substantially improve monitoring, planning, and management practices by overcoming some of the shortcomings of the ground-based surveys such as observer bias and inaccessibility. Remote sensing techniques for accurate disease mapping offer a unique set of advantages including repeatability, large area coverage, and cost-effectiveness over the ground-based methods. Hence, remote detection is particularly and practically critical for repeated disease mo- nitoring and mapping over time and space during the course of a growing season.
Cite this paper: M. Mirik, R. Ansley, J. Price, F. Workneh and C. Rush, "Remote Monitoring of Wheat Streak Mosaic Progression Using Sub-Pixel Classification of Landsat 5 TM Imagery for Site Specific Disease Management in Winter Wheat," Advances in Remote Sensing, Vol. 2 No. 1, 2013, pp. 16-28. doi: 10.4236/ars.2013.21003.

[1]   M. Carew, M. Schiffer, P. Umina, A. Weeks and A. Hoffmann, “Molecular Markers Indicate That the Wheat Curl Mite, Aceria tosichella Keifer, May Represent a Species Complex in Australia,” Bulletin of Entomological Research, Vol. 99, No. 5, 2009, pp. 479-486. doi:10.1017/S0007485308006512

[2]   B. A. Coutts, G. R. Strickland, M. A. Kehoe, D. L. Severtson and R. A. C. Jones, “The Epidemiology of Wheat Streak Mosaic Virus in Australia: Case Histories, Gradients, Mite Vectors, and Alternative Hosts,” Australian Journal of Agricultural Research, Vol. 59, No. 9, 2008, pp. 844-853. doi:10.1071/AR07475

[3]   M. Fahim, A. Mechanicos, L. Ayala-Navarrete, S. Haber and P. J. Larkin, “Resistance to Wheat Streak Mosaic Virus-A Survey of Resources and Development of Molecular Markers,” Plant Pathology, Vol. 61, No. 3, 2012, pp. 425-440.

[4]   R. French and D. C. Stenger, “Evolution of Wheat Streak Mosaic Virus: Dynamics of Population Growth within Plants May Explain Limited Variation,” Annual Review of Phytopathology, Vol. 41, No. 1, 2003, pp. 199-214. doi:10.1146/annurev.phyto.41.052002.095559

[5]   E. S. Jiménez-Martínez and N. A. Bosque-Pérez, “Life History of the Bird Cherry-Oat Aphid, Rhopalosiphum padi, on Transgenic and Non-Transformed Wheat Challenged with Wheat Streak Mosaic Virus,” Entomologia Experimentalis et Applicata, Vol. 133, No. 1, 2009, pp. 19-26. doi:10.1111/j.1570-7458.2009.00905.x

[6]   M. Murugan, P. S. Cardona, P. Duraimurugan, A. E. Whitfield, D. Schneweis, S. Starkey and C. M. Smith, “Wheat Curl Mite Resistance: Interactions of Mite Feeding with Wheat Streak Mosaic Virus Infection,” Journal of Economic Entomology, Vol. 104, No. 4, 2011, pp. 1406-1414. doi:10.1603/EC11112

[7]   M. Schiffer, P. Umina, M. Carew, A. Hoffmann, B. Rodoni and A. Miller, “The Distribution of Wheat Curl Mite (Aceria tosichella) Lineages in Australia and Their Potential to Transmit Wheat Streak Mosaic Virus,” Annals of Applied Biology, Vol. 155, No. 3, 2009, pp. 371-379. doi:10.1111/j.1744-7348.2009.00349.x

[8]   D. C. Stenger and R. French, “Wheat Streak Mosaic Virus Genotypes Introduced to Argentina Are Closely Related to Isolates from the American Pacific Northwest and Australia,” Archives of Virology, Vol. 154, No. 2, 2009, pp. 331-336. doi:10.1007/s00705-008-0297-1

[9]   T. L. Harvey, D. L. Seifers and T. J. Martin, “Host Range Differences between Two Strains of Wheat Curl Mites (Acari: Eriophyidae),” Journal of Agricultural and Urban Entomology, Vol. 18, No. 1, 2001, pp. 35-41.

[10]   J. A. Price, F. Workneh, S. R. Evett, D. C. Jones, J. Arthur and C. M. Rush, “Effects of Wheat Streak Mosaic Virus on Root Development and Water-Use Efficiency of Hard Red Winter Wheat,” Plant Disease, Vol. 94, No. 6, 2010, pp. 766-770. doi:10.1094/PDIS-94-6-0766

[11]   H. Sánchez-Sánchez, M. Henry, E. Cárdenas-Soriano and H. F. Alvizo-Villasana, “Identification of Wheat Streak Mosaic Virus and Its Vector Aceria tosichella in Mexico,” Plant Disease, Vol. 85, No. 1, 2001, pp. 13-17. doi:10.1094/PDIS.2001.85.1.13

[12]   M. Velandia, R. M. Rejesus, D. C. Jones, J. A. Price, F. Workneh and C. M. Rush, “Economic Impact of Wheat Streak Mosaic Virus in the Texas High Plains,” Crop Protection, Vol. 29, No. 7, 2010, pp. 699-703. doi:10.1016/j.cropro.2010.02.005

[13]   F. Workneh, J. A. Price, D. C. Jones and C. M. Rush, “Wheat Streak Mosaic: A Classic Case of Plant Disease Impact on Soil Water Content and Crop Water-Use Efficiency,” Plant Disease, Vol. 94, No. 6, 2010, pp. 771-774. doi:10.1094/PDIS-94-6-0771

[14]   L. A. Divis, R. A. Graybosch, C. J. Peterson, P. S. Baenziger, G. L. Hein, B. B. Beecher and T. J. Martin, “Agronomic and Quality Effects in Winter Wheat of a Gene Conditioning Resistance to Wheat Streak Mosaic Virus,” Euphytica, Vol. 152, No. 1, 2006, pp. 41-49. doi:10.1007/s10681-006-9174-8

[15]   G. I. Dwyer, M. J. Gibbs, A. J. Gibbs and R. A. C. Jones, “Wheat Streak Mosaic Virus in Australia: Relationship to Isolates from the Pacific Northwest of the USA and Its Dispersion via Seed Transmission,” Plant Disease, Vol. 91, No. 2, 2007, pp. 164-170. doi:10.1094/PDIS-91-2-0164

[16]   M. Fahim, H. Dove, W. M. Kelman, L. Ayala-Navarrete and P. J. Larkin, “Does Grazing of Infected Wheat by Sheep Result in Salivary Transmission of Wheat Streak Mosaic Virus?” Crop and Pasture Science, Vol. 61, No. 3, 2010, pp. 247-254. doi:10.1071/CP09301

[17]   R. M. Hunger, J. L. Sherwood, C. K. Evans and J. R. Montana, “Effects of Planting Date and Inoculation Date on Severity of Wheat Streak Mosaic in Hard Red Winter Wheat Cultivars,” Plant Disease, Vol. 76, No. 10, 1992, pp. 1056-1060. doi:10.1094/PD-76-1056

[18]   H. Li, R. L. Conner, Q. Chen, R. J. Graf, A. Lorache, F. Ahmad and A. D. Kuzyk, “Promising Genetic Resources for Resistance to Wheat Streak Mosaic Virus and the Wheat Curl Mite in Wheat—Thinopyrum Partial Amphiploids and Their Derivatives,” Genetic Resources and Crop Evolution, Vol. 51, No. 8, 2004, pp. 827-835.

[19]   E. Sivamani, C. W. Brey, L. E. Talbert, M. A. Young, W. E. Dyer, W. K. Kaniewski and R. Qu, “Resistance to Wheat Streak Mosaic Virus in Transgenic Wheat Engineered with the Viral Coat Protein Gene,” Transgenic Research, Vol. 11, No. 1, 2002, pp. 31-41.

[20]   B. Chen, S. Li, K. Wang, G. Zhou and J. Bai, “Evaluating the Severity Level of Cotton Verticillium Using Spectral Signature Analysis,” International Journal of Remote Sensing, Vol. 33, No. 9, 2012, pp. 2706-2724. doi:10.1080/01431161.2011.619586

[21]   I. Herrmann, M. Berenstein, A. Sade, A. Karnieli, D. J. Bonfil and P. G. Weintraub, “Spectral Monitoring of Two-Spotted Spider Mite Damage to Pepper Leaves,” Remote Sensing Letters, Vol. 3, No. 4, 2012, pp. 277-283. doi:10.1080/01431161.2011.576709

[22]   S. A. O’Shaughnessy, S. R. Evett, P. D. Colaizzi and T. A. Howell, “Using Radiation Thermography and Thermome-try to Evaluate Crop Water Stress in Soybean and Cotton,” Agricultural Water Management, Vol. 98, No. 10, 2011, pp. 1523-1535. doi:10.1016/j.agwat.2011.05.005

[23]   R. O. Pacumbaba Jr. and C. A. Beyl, “Changes in Hyper-spectral Reflectance Signatures of Lettuce Leaves in Response to Macronutrient Deficiencies,” Advances in Space Research, Vol. 48, No. 1, 2011, pp. 32-42. doi:10.1016/j.asr.2011.02.020

[24]   S. S. Ray, N. Jain, R. K. Arora, S. Chavan and S. Panigrahy, “Utility of Hyperspectral Data for Potato Late Blight Disease Detection,” Journal of the Indian Society of Remote Sensing, Vol. 39, No. 2, 2011, pp. 161-169. doi:10.1007/s12524-011-0094-2

[25]   B. B. M. Sridhar, R. K. Vincent, S. J. Roberts and K. Czajkowski, “Remote Sensing of Soybean Stress as an Indicator of Chemical Concentration of Biosolid Amended Surface Soils,” International Journal of Applied Earth Observation and Geoinformation, Vol. 13, No. 4, 2011, pp. 676-681. doi:10.1016/j.jag.2011.04.005

[26]   N. Subash, H. S. R. Mohan and K. Banukumar, “Comparing Water-Vegetative Indices for Rice (Oryza sativa L.)—Wheat (Triticum aestivum L.) Drought Assessment,” Computers and Electronics in Agriculture, Vol. 77, No. 2, 2011, pp. 175-187. doi:10.1016/j.compag.2011.05.001

[27]   P. Chávez, C. Yarlequé, H. Loayza, V. Mares, P. Hancco, S. Priou, M. P. Márquez, A. Posadas, P. Zorogastúa, J. Flexas and R. Quiroz, “Detection of Bacterial Wilt Infection Caused by Ralstonia solanacearum in Potato (Solanum tuberosum L.) through Multifractal Analysis Applied to Remotely Sensed Data,” Precision Agriculture, Vol. 13, No. 2, 2012, pp. 236-255. doi:10.1007/s11119-011-9242-5

[28]   P. Chávez, C. Yarlequé, O. Piro, A. Posadas, V. Mares, H. Loayza, C. Chuquillanqui, P. Zorogastúa, J. Flexas and R. Quiroz, “Applying Multifractal Analysis to Remotely Sensed Data for Assessing PYVV Infection in Potato (Solanum tuberosum L.) Crops,” Remote Sensing, Vol. 2, No. 5, 2010, pp. 1197-1216. doi:10.3390/rs2051197

[29]   U. R. Rosyara, S. Subedi, E. Duveiller and R. C. Sharma, “Photochemical Efficiency and SPAD Value as Indirect Selection Criteria for Combined Selection of Spot Blotch and Terminal Heat Stress in Wheat,” Journal of Phytopathology, Vol. 158, No. 11-12, 2010, pp. 813-821. doi:10.1111/j.1439-0434.2010.01703.x

[30]   H. Santoso, T. Gunawan, R. H. Jatmiko, W. Darmosarkoro and B. Minasny, “Mapping and Identifying Basal Stem Rot Disease in Oil Palms in North Sumatra with QuickBird Imagery,” Precision Agriculture, Vol. 12, No. 2, 2011, pp. 233-248.

[31]   H. Z. M. Shafri, M. I. Anuar, I. A. Seman and N. M. Noor, “Spectral Discrimination of Healthy and Ganoderma-Infected Oil Palms from Hyperspectral Data,” International Journal of Remote Sensing, Vol. 32, No. 22, 2011, pp. 7111-7129. doi:10.1007/s11119-010-9172-7

[32]   C. Yang, S. M. Greenberg, J. H. Everitt and C. J. Fernandez, “Assessing Cotton Defoliation, Regrowth Control and Root Rot Infection Using Remote Sensing Technology,” International Journal of Agricultural and Biological Engineering, Vol. 4, No. 4, 2011, pp. 1-11.

[33]   D. Y. Zhang, J. C. Zhang, D. Z. Zhu, J. H. Wang, J. H. Luo, J. L. Zhao and W. J. Huang, “Investigation of the Hyperspectral Image Characteristics of Wheat Leaves under Different Stress,” Guang Pu Xue Yu Guang Pu Fen Xi/ Spectroscopy and Spectral Analysis, Vol. 31, No. 4, 2011, pp. 1101-1105.

[34]   M. Mirik, G. J. Michels, S. K. Mirik, N. C. Elliott and V. Catana, “Spectral Sensing of Aphid (Hemiptera: Aphididae) Density Using Field Spectrometry and Radiometry,” Turkish Journal of Agriculture and Forestry, Vol. 30, No. 5, 2006, pp. 421-428.

[35]   W. Huang, X. Song, D. W. Lamb, Z. Wang, Z. Niu, L. Liu and J. Wang, “Estimation of Winter Wheat Grain Crude Protein Content from in Situ Reflectance and Advanced Spaceborne Thermal Emission and Reflection Radiometer Image,” Journal of Applied Remote Sensing, Vol. 2, No. 1, Article ID: 023530. doi:10.1117/1.2968954

[36]   S. V. Ollinger, “Sources of Variability in Canopy Reflectance and the Convergent Properties of Plants,” New Phytologist, Vol. 189, No. 2, 2011, pp. 375-394. doi:10.1111/j.1469-8137.2010.03536.x

[37]   G. Samseemoung, H. P. W. Jayasuriya and P. Soni, “Oil Palm Pest Infestation Monitoring and Evaluation by Helicopter-Mounted, Low Altitude Remote Sensing Platform,” Journal of Applied Remote Sensing, Vol. 5, No. 1, 2011, Article ID: 053540. doi:10.1117/1.3609843

[38]   C. V. M. Barton, “Advances in Remote Sensing of Plant Stress,” Plant and Soil, Vol. 354, No. 1-2, 2012, p. 41.

[39]   M. Mirik, R. J. Ansley, G. J. J. Michels and C. N. Elliot, “Spectral Vegetation Indices Selected for Quantifying Russian Wheat Aphid (Diuraphis noxia) Feeding Damage in Wheat (Triticum aestivum L.),” Precision Agriculture, Vol. 13, No. 4, 2012, pp. 501-516. doi:10.1007/s11119-012-9264-7

[40]   D. Moshou, C. Bravo, R. Oberti, J. S. West, H. Ramon, S. Vougioukas and D. Bochtis, “Intelligent Multi-Sensor System for the Detection and Treatment of Fungal Diseases in Arable Crops,” Biosystems Engineering, Vol. 108, No. 4, 2011, pp. 311-321. doi:10.1016/j.biosystemseng.2011.01.003

[41]   M. Mirik, D. C. Jones, J. A. Price, F. Workneh, R. J. Ansley and C. M. Rush, “Satellite Remote Sensing of Wheat Infected by Wheat streak mosaic virus,” Plant Disease, Vol. 95, No. 1, 2011, pp. 4-12. doi:10.1094/PDIS-04-10-0256

[42]   G. F. Backoulou, N. C. Elliott, K. L. Giles, M. Phoofolo, V. Catana, M. Mirik and J. Michelsd, “Spatially Discriminating Russian Wheat Aphid Induced Plant Stress from Other Wheat Stressing Factors,” Computers and Electronics in Agriculture, Vol. 78, No. 2, 2011, pp. 123-129.

[43]   K. H. Dammer, B. M?ller, B. Rodemann and D. Heppner, “Detection of Head Blight (Fusarium ssp.) in Winter Wheat by Color and Multi-Spectral Image Analyses,” Crop Protection, Vol. 30, No. 4, 2011, pp. 420-428. doi:10.1016/j.cropro.2010.12.015

[44]   A. M. H. Elmetwalli, A. N. Tyler, P. D. Hunter and C. A. Salt, “Detecting and Distinguishing Moisture-and Salinity-Induced Stress in Wheat and Maize through in Situ Spectroradiometry Measurements,” Remote Sensing Letters, Vol. 3, No. 4, 2012, pp. 363-372. doi:10.1080/01431161.2011.599346

[45]   Z. Y. Liu, H. F. Wu and J. F. Huang, “Application of Neural Networks to Discriminate Fungal Infection Levels in Rice Panicles Using Hyperspectral Reflectance and Principal Components Analysis,” Computers and Electronics in Agriculture, Vol. 72, No. 2, 2010, pp. 99-106. doi:10.1016/j.compag.2010.03.003

[46]   T. Mewes, J. Franke and G. Menz, “Spectral Requirements on Airborne Hyperspectral Remote Sensing Data for Wheat Disease Detection,” Precision Agriculture, Vol. 12, No. 6, 2011, pp. 795-812. doi:10.1007/s11119-011-9222-9

[47]   J. Zhao, D. Zhang, J. Luo, D. Wang and W. Huang, “Identifying Leaf-Scale Wheat Aphids Using the Near-Ground Hyperspectral Pushbroom Imaging Spectrometer,” Springer, New York, 2012.

[48]   H. E. Nilsson, “Hand-Held Radiometry and IR Thermography of Plant Diseases in Field Plot Experiments,” International Journal of Remote Sensing, Vol. 12, No. 3, 1991, pp. 545-557.

[49]   H. Nilsson and L. Johnsson, “Hand-held Radiometry of Barley Infected by Barley Stripe Disease in a Field Experiment,” Journal of Plant Disease and Protection, Vol. 103, No. 5, 1996, pp. 517-526.

[50]   C. C. D. Lelong, P. C. Pinet and H. Poilvé, “Hyperspectral Imaging and Stress Mapping in Agriculture: A Case Study on Wheat in Beauce (France),” Remote Sensing of Environment, Vol. 66, No. 2, 1998, pp. 179-191. doi:10.1016/S0034-4257(98)00049-2

[51]   W. Huang, D. W. Lamb, Z. Niu, Y. Zhang, L. Liu and J. Wang, “Identification of Yellow Rust in Wheat Using in-Situ Spectral Reflectance Measurements and Airborne Hyperspectral Imaging,” Precision Agriculture, Vol. 8, No. 4-5, 2007, pp. 187-197. doi:10.1007/s11119-007-9038-9

[52]   J. Franke and G. Menz, “Multi-Temporal Wheat Disease Detection by Multi-Spectral Remote Sensing,” Precision Agriculture, Vol. 8, No. 3, 2007, pp. 161-172. doi:10.1007/s11119-007-9036-y

[53]   K. Steddom, G. Heidel, D. Jones and C. M. Rush, “Remote Detection of Rhizomania in Sugar Beets,” Phytopathology, Vol. 93, No. 6, 2003, pp. 720-726. doi:10.1094/PHYTO.2003.93.6.720

[54]   E. Bauriegel, A. Giebel, M. Geyer, U. Schmidt and W. B. Herppich, “Early Detection of Fusarium Infection in Wheat Using Hyper-Spectral Imaging,” Computers and Electronics in Agriculture, Vol. 75, No. 2, 2011, pp. 304-312. doi:10.1016/j.compag.2010.12.006

[55]   D. Cammarano, G. Fitzgerald, B. Basso, G. O’Leary, D. Chen, P. Grace and C. Fiorentino, “Use of the Canopy Chlorophyl Content Index (CCCI) for Remote Estimation of Wheat Nitrogen Content in Rainfed Environments,” Agronomy Journal, Vol. 103, No. 6, 2011, pp. 1597-1603. doi:10.2134/agronj2011.0124

[56]   Q. Cheng and X. Wu, “Mapping Paddy Rice Yield in Zhejiang Province Using MODIS Spectral Index,” Turkish Journal of Agriculture and Forestry, Vol. 35, No. 6, 2011, pp. 579-589.

[57]   S. Elsayed, B. Mistele and U. Schmidhalter, “Can Changes in Leaf Water Potential Be Assessed Spectrally?” Functional Plant Biology, Vol. 38, No. 6, 2011, pp. 523-533.

[58]   J. I. N. L. Zhao, D. Y. A. N. Zhang, J. Luo, H. Yang, L. I. N. S. Huang and W. E. N. J. Huang, “A Comparative Study on Monitoring Leaf-Scale Wheat Aphids Using Pushbroom Imaging and Non-Imaging ASD Field Spectrometers,” International Journal of Agriculture & Biology, Vol. 14, No. 1, 2012, pp. 136-140.

[59]   B. M. A. de Coninck, O. Amand, S. L. Delauré, S. Lucas, N. Hias, G. Weyens, J. Mathys, E. de Bruyne and B. P. A. Cammue, “The Use of Digital Image Analysis and Real-Time PCR Fine-Tunes Bioassays for Quantification of Cercospora Leaf Spot Disease in Sugar Beet Breeding,” Plant Pathology, Vol. 61, No. 1, 2012, pp. 76-84. doi:10.1111/j.1365-3059.2011.02497.x

[60]   Y. Kim, D. M. Glenn, J. Park, H. K. Ngugi and B. L. Lehman, “Hyperspectral Image Analysis for Water Stress Detection of Apple Trees,” Computers and Electronics in Agriculture, Vol. 77, No. 2, 2011, pp. 155-160. doi:10.1016/j.compag.2011.04.008

[61]   E. M. Abdel-Rahman, F. B. Ahmed, M. van den Berg and M. J. Way, “Potential of Spectroscopic Data Sets for Sugarcane Thrips (Fulmekiola serrata Kobus) Damage Detection,” International Journal of Remote Sensing, Vol. 31, No. 15, 2010, pp. 4199-4216. doi:10.1080/01431160903241981

[62]   M. W. Carroll, J. A. Glaser, R. L. Hellmich, T. E. Hunt, T. W. Sappington, D. Calvin, K. Copenhaver and J. Fridgen, “Use of Spectral Vegetation Indices Derived from Airborne Hyperspectral Imagery for Detection of European Corn Borer Infestation in Iowa Corn Plots,” Journal of Economic Entomology, Vol. 101, No. 5, 2008, pp. 1614-1623. doi:10.1603/0022-0493(2008)101[1614:UOSVID]2.0.CO;2

[63]   B. Chen, S. k. Li, K. R. Wang, J. Wang, F. Y. Wang, C. H. Xiao, J. C. Lai and N. Wang, “Spectrum Characterissics of Cotton Canopy Infected with Verticillium Wilt and Applications,” Agricultural Sciences in China, Vol. 7, No. 5, 2008, pp. 561-569. doi:10.1016/S1671-2927(08)60053-X

[64]   R. J. Hill, B. A. Wilson, J. E. Rookes and D. M. Cahill, “Use of High Resolution Digital Multi-Spectral Imagery to Assess the Distribution of Disease Caused by Phytophthora cinnamomi on Heathland at Anglesea, Victoria,” Australasian Plant Pathology, Vol. 38, No. 2, 2009, pp. 110-119. doi:10.1071/AP08092

[65]   C. Hillnhütter, A. K. Mahlein, R. A. Sikora and E. C. Oerke, “Remote Sensing to Detect Plant Stress Induced by Heterodera schachtii and Rhizoctonia solani in Sugar Beet Fields,” Field Crops Research, Vol. 122, No. 1, 2011, pp. 70-77. doi:10.1016/j.fcr.2011.02.007

[66]   Z. Y. Liu, J. J. Shi, L. W. Zhang and J. F. Huang, “Discrimination of Rice Panicles by Hyperspectral Reflectance Data Based on Principal Component Analysis and Support Vector Classification,” Journal of Zhejiang University: Science B, Vol. 11, No. 1, 2010, pp. 71-78. doi:10.1631/jzus.B0900193

[67]   M. Prabhakar, Y. Prasad and M. N. Rao, “Remote Sensing of Biotic Stress in Crop Plants and Its Applications for Pest Management,” Springer, New York, 2012.

[68]   D. D. Reisig and L. D. Godfrey, “Remotely Sensing Arthropod and Nutrient Stressed Plants: A Case Study with Nitrogen and Cotton Aphid (Hemiptera: Aphididae),” Environmental Entomology, Vol. 39, No. 4, 2010, pp. 1255-1263. doi:10.1603/EN09218

[69]   J. A. Price, J. Smith, A. Simmons, J. Fellers and C. M. Rush, “Multiplex Real-Time RT-PCR for Detection of Wheat Streak Mosaic Virus and Tritcum Mosaic Virus,” Journal of Virological Methods, Vol. 165, No. 2, 2010, pp. 198-201. doi:10.1016/j.jviromet.2010.01.019

[70]   J. J. Michell and E. F. Glenn, “Subpixel Abundance Estimates in Mixture-Tuned Matched Filtering Classifications of Leafy Spurge (Euphorbia esula L.),” International Journal of Remote Sensing, Vol. 30, No. 23, 2009, pp. 6099-6119. doi:10.1080/01431160902810620

[71]   A. P. Williams and E. R. Hunt Jr., “Estimation of Leafy Spurge Cover from Hyperspectral Imagery Using Mixture Tuned Matched Filtering,” Remote Sensing of Environment, Vol. 82, No. 2-3, 2002, pp. 446-456. doi:10.1016/S0034-4257(02)00061-5

[72]   M. Mirik, K. Steddom and G. J. Michels Jr., “Estimating Biophysical Characteristics of Musk Thistle (Carduus nutans) with Three Remote Sensing Instruments,” Rangeland Ecology and Management, Vol. 59, No. 1, 2006, pp. 44-54. doi:10.2111/05-106R2.1

[73]   J. Zhang, W. Huang, J. Li, G. Yang, J. Luo, X. Gu and J. Wang, “Development, Evaluation and Application of a Spectral Knowledge Base to Detect Yellow Rust in Winter Wheat,” Precision Agriculture, Vol. 12, No. 5, 2011, pp. 716-731. doi:10.1007/s11119-010-9214-1

[74]   C. Bravo, D. Moshou, J. West, A. McCartney and H. Ramon, “Early Disease Detection in Wheat Fields Using Spectral Reflectance,” Biosystems Engineering, Vol. 84, No. 2, 2003, pp. 137-145. doi:10.1016/S1537-5110(02)00269-6

[75]   A. Apan, A. Held, S. Phinn and J. Markley, “Detecting Sugarcane ‘Orange Rust’ Disease Using EO-1 Hyperion Hyperspectral Imagery,” International Journal of Remote Sensing, Vol. 25, No. 2, 2004, pp. 489-498. doi:10.1080/01431160310001618031

[76]   F. W. Nutter Jr., G. L. Tylka, J. Guan, A. J. D. Moreira, C. C. Marett, T. R. Rosburg, J. P. Basart and C. S. Chong, “Use of Remote Sensing to Detect Soybean Cyst Nematode-Induced Plant Stress,” Journal of Nematology, Vol. 34, No. 3, 2002, pp. 222-231.

[77]   J. Guan and F. W. Nutter Jr., “Relationships between Defoliation, Leaf Area Index, Canopy Reflectance, and Forage Yield in the Alfalfa-Leaf Spot Pathosystem,” Computers and Electronics in Agriculture, Vol. 37, No. 1-3, 2002, pp. 97-112. doi:10.1016/S0168-1699(02)00113-8

[78]   J. Guan and F. W. Nutter Jr., “Relationships between Percentage Defoliation, Dry Weight, Percentage Reflectance, Leaf-to-Stem Ratio, and Green Leaf Area Index in the Alfalfa Leaf Spot Pathosystem,” Crop Science, Vol. 42, No. 4, 2002, pp. 1264-1273. doi:10.2135/cropsci2002.1264

[79]   F. W. Nutter Jr., J. Guan, A. R. Gotlieb, L. H. Rhodes, C. R. Grau and R. M. Sulc, “Quantifying Alfalfa Yield Losses Caused by Foliar Diseases in Iowa, Ohio, Wisconsin, and Vermont,” Plant Disease, Vol. 86, No. 3, 2002, pp. 269-277. doi:10.1094/PDIS.2002.86.3.269

[80]   M. Zhang, Z. Qin and X. Liu, “Remote Sensed Spectral Imagery to Detect Late Blight in Field Tomatoes,” Precission Agriculture, Vol. 6, No. 6, 2005, pp. 489-508. doi:10.1007/s11119-005-5640-x

[81]   K. Bürling, M. Hunsche and G. Noga, “Use of Blue-Green and Chlorophyll Fluorescence Measurements for Differentiation between Nitrogen Deficiency and Pathogen Infection in Winter Wheat,” Journal of Plant Physiology, Vol. 168, No. 14, 2011, pp. 1641-1648. doi:10.1016/j.jplph.2011.03.016

[82]   G. J. Reynolds, C. E. Windels, I. V. MacRae and S. Laguette, “Remote Sensing for Assessing Rhizoctonia Crown and Root Rot Severity in Sugar Beet,” Plant Disease, Vol. 96, No. 4, 2012, pp. 497-505. doi:10.1094/PDIS-11-10-0831

[83]   B. L. Yusuf and Y. He, “Application of Hyperspectral Imaging Sensor to Differentiate between the Moisture and Reflectance of Healthy and Infected Tobacco Leaves,” African Journal of Agricultural Research, Vol. 6, No. 29, 2011, pp. 6267-6280.