Remote Sensing, Climate Change and Insect Pest: Can Biotic Interactions Be Explored?

  • N. R. Prasannakumar
  • H. R. Gopalkrishna
  • A. N. D. T. Kumara
  • P. N. Guru


Remote sensing is a powerful technology that obtains data about an object without being in contact with it. Many of the responses of plants to herbivore attack are difficult to quantify or assess visually. Remote sensing techniques catch the altering reflectance spectrum of plants as a result of pest or disease attack. Spectral signatures from healthy plant canopies are compared with infested plant canopies to determine the extent and severity of pest/disease attack. The hyperspectral images from the fields can be used for pest scouting and differential pesticide applications. Based on spectral index, entomologists/pathologists have developed regression models. Airborne multispectral imaging system has great potential in area-wide pest management. Climate change impacts the reflectance spectrum received from plants in a multitude of ways causing significant changes in the physiology, biochemistry and molecular response of plants to pest and disease attack.


Remote sensing Spectra Pests Climate change 



The authors are thankful to the authorities of ICAR-Indian Institute of Horticultural Research, Bangalore for their support and encouragement.


  1. Adams ML, Norvell WA, Philpot WD, Peverly JH (2000) Spectral detection of micronutrient deficiency in ‘Bragg’s soybean. Agron J 92(2):261–268Google Scholar
  2. Aggarwal PK, Kalra N, Chander S, Pathak H (2006) InfoCrop: a dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. I Model description. Agric Syst 89(1):1–25CrossRefGoogle Scholar
  3. Ahmed FE, Hall AE, Madore MA (1993) Interactive effects of high temperature and elevated carbon dioxide concentration on cowpea [Vigna unguiculata (L) Walp.]. Plant Cell Environ 16(7):835–842CrossRefGoogle Scholar
  4. Al-Kindi KM, Kwan P, Andrew NR, Welch M (2017) Remote sensing and spatial statistical techniques for modelling Ommatissus lybicus (Hemiptera: Tropiduchidae) habitat and population densities. Peer J 5:e3752. Scholar
  5. Andrew NR, Hughes L (2005) Diversity and assemblage structure of phytophagous Hemiptera along a latitudinal gradient: predicting the potential impacts of climate change. Glob Ecol Biogeogr 14(3):249–262CrossRefGoogle Scholar
  6. Apan A, Datt B, Kelly R (2005) Detection of pests and diseases in vegetable crops using hyperspectral sensing: a comparison of reflectance data for different sets of symptoms. In Proceedings of the 2005 Spatial Sciences Institute biennial conference 2005: spatial intelligence, innovation and praxis (SSC2005). Spatial Sciences Institute. ISBN 0-9581366-2-9, pp 10–18Google Scholar
  7. Asner GP (1998) Biophysical and biological sources of variability in canopy reflectance. Remote Sens Environ 64:234–253CrossRefGoogle Scholar
  8. Awmack CS, Harrington R, Leather SR, Lawton JH (1996) The impacts of elevated CO2 on aphid-plant interactions. Aspects Appl Biol 45:317–322Google Scholar
  9. Awmack CS, Harrington R, Leather SR (1997) Host plant effects on the performance of the aphid Aulacorthum solani (Kalt.) (Homoptera: Aphididae) at ambient and elevated CO2. Glob Chang Biol 3:545–549CrossRefGoogle Scholar
  10. Baker RHA, Sansford CE, Jarvis CH, Cannon RJC, MacLeod A, Walters KFA (2000) The role of climatic mapping in predicting the potential geographical distribution of non-indigenous pests under current and future climates. Agric Ecosyst Environ 82(1–3):57–71CrossRefGoogle Scholar
  11. Bale JS, Masters GJ, Hodkinson ID, Awmack C, Bezemer TM, Brown VK et al (2002) Herbivory in global climate change research: direct effects of rising temperature on insect herbivores. Glob Chang Biol 8(1):1–16CrossRefGoogle Scholar
  12. Baret F, Guyot G (1991) Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens Environ 35(2–3):161–173CrossRefGoogle Scholar
  13. Bezemer TM, Jones TH (1998) Plant-insect herbivore interactions in elevated atmospheric CO2: quantitative analyses and guild effects. Oikos 82:212–222CrossRefGoogle Scholar
  14. Boote KJ, Jones JW, Mishoe JW, Berger RD (1983) Coupling pests to crop growth simulators to predict yield reductions [mathematical models]. Phytopathology (USA) 73:1581–1587CrossRefGoogle Scholar
  15. Butler GD Jr, Henneberry TJ, Clayton TE (1983) Bemisia tabaci (Homoptera: Aleyrodidae): development, oviposition, and longevity in relation to temperature. Ann Entomol Soc Am 76(2):310–313CrossRefGoogle Scholar
  16. Byrne DN, Bellows TS Jr (1991) Whitefly biology. Annu Rev Entomol 36:431–457CrossRefGoogle Scholar
  17. Cannon RJ (1998) The implications of predicted climate change for insect pests in the UK, with emphasis on non-indigenous species. Glob Chang Biol 4(7):785–796CrossRefGoogle Scholar
  18. Carroll MW, Glaser JA, Hellmich RL, Hunt TE, Sappington TW, Calvin D, Fridgen J (2008) Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of European corn borer infestation in Iowa corn plots. J Econ Entomol 101(5):1614–1623CrossRefGoogle Scholar
  19. Chander S, Phadke KG (1994) Incidence of mustard aphid, Lipaphis erysimi and potato aphid, Myzus persicae on rapeseed crop. Annu Agric Res 15(3):385–387Google Scholar
  20. Charles JG, Kean JM, Chhagan A (2006) Developmental parameters and voltinism of the painted apple moth, Teia anartoides Walker (Lepidoptera: Lymantriidae) in New Zealand. N Z Entomol 29(1):27–36CrossRefGoogle Scholar
  21. Coll M, Hughes L (2008) Effects of elevated CO2 on an insect omnivore: a test for nutritional effects mediated by host plants and prey. Agric Ecosyst Environ 123(4):271–279CrossRefGoogle Scholar
  22. Cotrufo MF, Briones MJI, Ineson P (1998) Elevated CO2 affects field decomposition rate and palatability of tree leaf litter: importance of changes in substrate quality. Soil Biol Biochem 30(12):1565–1571CrossRefGoogle Scholar
  23. Coley PD, Markham A (1998) Possible effects of climate change on plant/herbivore interactions in moist tropical forests. Clim Change 39:455–472CrossRefGoogle Scholar
  24. Coviella CE, Trumble JT (1999) Effects of elevated atmospheric carbon dioxide on insect-plant interactions. Conserv Biol 13(4):700–712CrossRefGoogle Scholar
  25. Das DK, Behera KS, Dhandapani A, Trivedi TP, Chona N, Bhandari P (2008) Development of forewarning systems of rice pests for their management. Rice Pest Manag:187–200Google Scholar
  26. Delalieux S, Auwerkerken A, Verstraeten WW, Somers B, Valcke R, Lhermitte S, Coppin P (2009) Hyperspectral reflectance and fluorescence imaging to detect scab induced stress in apple leaves. Remote Sens 1(4):858–874CrossRefGoogle Scholar
  27. Diku A, Mucak L (2010) Identification and implementation of adaptation response measures to Drini–Mati River Deltas Report on expected climate change impacts on agriculture & livestock and their influence in the other economic sectors in the DMRD. UNDP Climate Change Program, p 34Google Scholar
  28. Dugal A, Yelle S, Gosselin A (1990) Influence of CO2 enrichment and its method of distribution on the evolution of gas exchanges in greenhouse tomatoes. Can J Plant Sci 70(1):345–356CrossRefGoogle Scholar
  29. El Kohen A, Pontailler JY, Mousse-au M (1991) Effect of doubling of atmospheric CO2 concentration on dark respiration in aerial parts of young chestnut trees (Castanea sativa Mill.). C R Acad Sci Ser 3(312):47Google Scholar
  30. Evans H, Straw N, Watt A, Broadmeadow M (2002) Climate change: implications for insect pests. For Comm Bull 125:99–118Google Scholar
  31. Gamon J, Serrano L, Surfus JS (1997) The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels. Oecologia 112(4):492–501CrossRefGoogle Scholar
  32. Gao F, Zhu SR, Sun YC, Du L, Parajulee M, Kang L, Ge F (2008) Interactive effects of elevated CO2 and cotton cultivar on tri-trophic interaction of Gossypium hirsutum, Aphis gossypii, and Propylaea japonica. Environ Entomol 37(1):29–37CrossRefGoogle Scholar
  33. Gates DM (1970) Physical and physiological properties of plants, remote sensing with special reference to agriculture and forestry. The National Academy of Sciences, Washington, DC, pp 224–252Google Scholar
  34. Gilbert GS, Reynolds DR, Bethancourt A (2007) The patchiness of epi foliar fungi in tropical forests: host range, host abundance, and environment. Ecology 88(3):575–581CrossRefGoogle Scholar
  35. Gitelson AA, Merzlyak MN, Chivkunova OB (2001) Optical properties and nondestructive estimation of anthocyanin content in plant leaves. Photochem Photobiol 74(1):38–45CrossRefGoogle Scholar
  36. Gitelson AA, Zur Y, Chivkunova OB, Merzlyak MN (2002) Assessing carotenoid content in plant leaves with reßectance spectroscopy. J Photochem Photobiol 75:272–281CrossRefGoogle Scholar
  37. Gore A (2006) An inconvenient truth: the planetary emergency of global warming and what we can do about it. Rodale, EmmausGoogle Scholar
  38. Govender M, Chetty K, Bulcock H (2007) A review of hyperspectral remote sensing and its application in vegetation and water resource studies. Water SA 33(2):33Google Scholar
  39. Gregory PJ, Johnson SN, Newton AC, Ingram JS (2009) Integrating pests and pathogens into the climate change/food security debate. J Exp Bot 60(10):2827–2838CrossRefGoogle Scholar
  40. Groninger JW, Seiler JR, Zedaker SM, Berrang PC (1996) Photosynthetic response of loblolly pine and sweetgum seedling stands to elevated carbon dioxide, water stress, and nitrogen level. Can J For Res 26(1):95–102CrossRefGoogle Scholar
  41. Hall AE, Allen LH (1993) Designing cultivars for the climatic conditions of the next century. Int Crop Sci I(internationalcr):291–297Google Scholar
  42. Harrington R, Fleming RA, Woiwod IP (2001) Climate change impacts on insect management and conservation in temperate regions: can they be predicted? Agric For Entomol 3(4):233–240CrossRefGoogle Scholar
  43. Hart WG, Myers VI (1968) Infrared aerial color photography for detection of populations of brown soft scale in citrus groves. J Econ Entomol 61(3):617–624CrossRefGoogle Scholar
  44. Heagle AS (2003) Influence of elevated carbon dioxide on interactions between Frankliniella occidentalis and Trifolium repens. Environ Entomol 32(3):421–424CrossRefGoogle Scholar
  45. Hamilton J, Orla D, Mihai A, Arthur Z, Alistair R, May B, Evan D (2005) Anthropogenic changes in tropospheric composition increase susceptibility of soybean to insect herbivory. Environ Entomol 34:479–485. Scholar
  46. Himanen SJ, Nissinen A, Dong WX, Nerg AM, Stewart CN Jr, Poppy GM, Holopainen JK (2008) Interactions of elevated carbon dioxide and temperature with aphid feeding on transgenic oilseed rape: are Bacillus thuringiensis (Bt) plants more susceptible to nontarget herbivores in future climate? Glob Chang Biol 14(6):1437–1454CrossRefGoogle Scholar
  47. Huang C, Song K, Kim S, Townshend JR, Davis P, Masek JG, Goward SN (2008) Use of a dark object concept and support vector machines to automate forest cover change analysis. Remote Sens Environ 112(3):970–985CrossRefGoogle Scholar
  48. Huang J, Liao H, Zhu Y, Sun J, Sun Q, Liu X (2012) Hyperspectral detection of rice damaged by rice leaf folder (Cnaphalocrocis medinalis). Comput Electron Agric 82:100–107CrossRefGoogle Scholar
  49. Huete AR (1988) Soil influences in remotely sensed vegetation-canopy spectra. In: Asrar G (ed) Theory and applications of optical remote sensing. Wiley, New York, pp 107–141Google Scholar
  50. Hughes L, Bazzaz FA (2001) Effects of elevated CO2 on five plant-aphid interactions. Entomol Exp Appl 99(1):87–96CrossRefGoogle Scholar
  51. Hullé M, Bonhomme J, Maurice D, Simon JC (2008) Is the life cycle of high arctic aphids adapted to climate change? Polar Biol 31(9):1037–1042CrossRefGoogle Scholar
  52. Hunter MD (2001) Effects of elevated atmospheric carbon dioxide on insect–plant interactions. Agric For Entomol 3(3):153–159CrossRefGoogle Scholar
  53. IPCC (2001) Climate change 2001: the scientific basis, report from Working Group I. Intergovernmental Panel on Climate Change, GenevaGoogle Scholar
  54. IPCC (2007) Summary for policymakers. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averty KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the IV assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 1–18Google Scholar
  55. Jordan CF (1969) Derivation of leaf-area index from quality of light on the forest floor. Ecology 50(4):663–666CrossRefGoogle Scholar
  56. Kiritani K (2006) Predicting impacts of global warming on population dynamics and distribution of arthropods in Japan. Popul Ecol 48(1):5–12CrossRefGoogle Scholar
  57. Kroschel J, Sporleder M, Simon R, Juarez H, Gonzales J, Carhuapoma P, Tonnang H (2010) Predicting the effects of global warming on insect pests. Technical innovation brief. No. 5, September 2010Google Scholar
  58. Kruse FA (1998) Advances in hyperspectral remote sensing for geologic mapping and exploration. In: Proceedings 9th Australasian remote sensing conference, p 19Google Scholar
  59. Kudo G, Hirao AS (2006) Habitat-specific responses in the flowering phenology and seed set of alpine plants to climate variation: implications for global-change impacts. Popul Ecol 48(1):49–58CrossRefGoogle Scholar
  60. Kumar J, Vashisth A, Sehgal VK, Gupta VK (2010) Identification of aphid infestation in mustard by hyperspectral remote sensing. J Agric Phys 10:53–60Google Scholar
  61. Kumar J, Vashisth A, Sehgal VK, Gupta VK (2012) Assessment of aphid infestation in mustard by hyperspectral remote sensing. J Indian Soc Remote Sens 41(1):83–90CrossRefGoogle Scholar
  62. Kustas WP, Daughtry CS, Van Oevelen PJ (1993) Analytical treatment of the relationships between soil heat flux/net radiation ratio and vegetation indices. Remote Sens Environ 46(3):319–330CrossRefGoogle Scholar
  63. LaMarche VC, Graybill DA, Fritts HC, Rose MR (1984) Increasing atmospheric carbon dioxide: tree ring evidence for growth enhancement in natural vegetation. Science 225(4666):1019–1021CrossRefGoogle Scholar
  64. Lawton JH (1995) The response of insects to environmental change. In: Harrington R, Stork NE (eds) Insects in a changing environment. Academic, London, pp 3–26Google Scholar
  65. Lewis T (1997) Thrips as crop pests. CAB International, Cambridge University Press, Wallingford/Cambridge, p 740Google Scholar
  66. Lelong CCD, Pinet PC, Poilvé H (1998) Hyperspectral imaging and stress mapping in agriculture: a case study on wheat in Beauce (France). Remote Sens Environ 66:179–191CrossRefGoogle Scholar
  67. Lilies TM, Kiefer RW, Chipman JW (2004) Remote sensing and image interpretation. Wiley, Chichester, p 763Google Scholar
  68. Lincoln DE, Couvet D, Sionit N (1986) Response of an insect herbivore to host plants grown in carbon dioxide enriched atmospheres. Oecologia 69(4):556–560CrossRefGoogle Scholar
  69. Magor JI, Pender J (1997) Desert locust forecasters’ GIS: a researchers’ view. In: New strategies in locust control. Birkhäuser, Basel, pp 21–26CrossRefGoogle Scholar
  70. Mahal MS, Agarwal N (2010) Impact of global climate change on arthropod fauna. In: Souvenir: national symposium on perspectives and challenges of integrated pest management for sustainable agriculture. Dr. Y.S Parmer University of Agriculture and Forestry, Nauni, Solan, India, pp 50–56Google Scholar
  71. Mattson WJ Jr (1990) Herbivory in relation to plant nitrogen content. Annu Rev Ecol Syst 11:119–161CrossRefGoogle Scholar
  72. Merton RN (1998) Monitoring community hysteresis using spectral shift analysis and the red-edge vegetation stress index. In: Proceedings of the 7th annual JPL airborne earth science workshop. NASA, Jet Propulsion Laboratory, Pasadena, 12–16 Jan 1998Google Scholar
  73. Milford JR, Dugdale G (1990) Estimation of rainfall using geostationary satellite data. In: Clark JA, Steven MJ (eds) Applications of remote sensing in agriculture. Butterworth, LondonGoogle Scholar
  74. Milton EJ, Schaepman ME, Anderson K, Kneubühler M, Fox N (2009) Progress in field spectroscopy. Remote Sens Environ 113:S92–S109CrossRefGoogle Scholar
  75. Mirik M, Michels GJ Jr, Kasimdzhanov-Mirik S, Elliott NC, Bowling R (2006) Hyperspectral spectrometry as a means to differentiate uninfested and infested winter wheat by greenbug (Hemiptera: Aphididae). J Econ Entomol 99(5):1682–1690CrossRefGoogle Scholar
  76. Mirik, M., Michels, G.J., Kassymzhanova-Mirik, S Jr, . and Elliott, N.C. (2007). “Reflectance characteristics of russian wheat aphid (Hemiptera: Aphididae) stress and abundance in winter wheat,” Comput Electron Agric 57(2):123–134CrossRefGoogle Scholar
  77. Mirik M, Ansley RJ, Michels GJ Jr, Elliott NC (2012) Spectral vegetation indices selected for quantifying Russian wheat aphid (Diuraphis noxia) feeding damage in wheat (Triticum aestivum L). Precis Agric 13(4):501–516Google Scholar
  78. Mitchell RAC, Mitchell VJ, Driscoll SP, Franklin J, Lawlor DW (1993) Effects of increased CO2 concentration and temperature on growth and yield of winter wheat at two levels of nitrogen application. Plant Cell Environ 16(5):521–529CrossRefGoogle Scholar
  79. Miyagi KM, Kinugasa T, Hikosaka K, Hirose T (2007) Elevated CO2 concentration, nitrogen use, and seed production in annual plants. Glob Chang Biol 13(10):2161–2170CrossRefGoogle Scholar
  80. Moran MS, Inoue Y, Barnes EM (1997) Opportunities and limitations for image-based remote sensing in precision crop management. Remote Sens Environ 61(3):319–346CrossRefGoogle Scholar
  81. Muharam FM, Ruslan SA, Zulkafli SL, Mazlan N, Adam NA, Husin NA (2017) Remote sensing derivation of land surface temperature for insect Pest monitoring. Asian J Plant Sci 16:160–171CrossRefGoogle Scholar
  82. Netherer S, Schopf A (2010) Potential effects of climate change on insect herbivores in European forests—general aspects and the pine processionary moth as specific example. For Ecol Manag 259(4):831–838CrossRefGoogle Scholar
  83. Neumeister L (2010) Climate change and crop protection-anything can happen. Doctoral dissertation, p 41Google Scholar
  84. Newton AC, Begg GS, Swanston JS (2009) Deployment of diversity for enhanced crop function. Ann Appl Biol 154(3):309–322CrossRefGoogle Scholar
  85. Nilsson HE (1980) Application of remote sensing methods and image analysis at macroscopic and microscopic levels. University of Minnesota Miscellaneous Publication 7. Agricultural Experiment Station, University of Minnesota, St. PaulGoogle Scholar
  86. Nilson T (1991) Approximate analytical methods for calculating the reflection functions of leaf canopies in remote sensing applications. In: Photon-vegetation interactions. Springer, Berlin, Heidelberg, pp 161–190CrossRefGoogle Scholar
  87. Nilsson H (1995) Remote sensing and image analysis in plant pathology. Annu Rev Phytopathol 33(1):489–528CrossRefGoogle Scholar
  88. Nilsson H, Johnsson L (1996) Hand-held radiometry of barley infected by barley stripe disease in a field experiment/Hand-getragene Radiometrie in Gerste, infiziert unter Feldbedingungen mit Streifenkrankheit. Zeitschrift für Pflanzenkrankheiten und Pflanzenschutz. J Plant Dis Protect 103:517–526Google Scholar
  89. Niño E (2002) The use of a multispectral radiometer to detect greenbug, Schizaphis Graminum (Rodani) damage in winter wheat, Triticum Aestivum L. Doctoral dissertation, A & M University, West TexasGoogle Scholar
  90. Norby RJ, Cotrufo MF (1998) Global change: a question of litter quality. Nature 396(6706):17CrossRefGoogle Scholar
  91. Nutter FW Jr, Littrell RH, Brenneman TB (1990) Utilization of a multispectral radiometer to evaluate fungicide efficacy to control late leaf spot in peanut. Phytopathology 80(1):102–108CrossRefGoogle Scholar
  92. Osbrink WL, Trumble JT, Wagner RE (1987) Host suitability of Phaseolus lunatus for Trichoplusia ni (Lepidoptera: Noctuidae) in controlled carbon dioxide atmospheres. Environ Entomol 16(3):639–644CrossRefGoogle Scholar
  93. Pelini SL, Prior KM, Parker DJ, Dzurisin JD, Lindroth RL, Hellmann JJ (2009) Climate change and temporal and spatial mismatches in insect communities. In: Climate change. Elsevier, Amsterdam, pp 215–231CrossRefGoogle Scholar
  94. Peñuelas J, Gamon JA, Fredeen AL, Merino J, Field CB (1994) Reflectance indices associated with physiological changes in nitrogen-and water-limited sunflower leaves. Remote Sens Environ 48(2):135–146CrossRefGoogle Scholar
  95. Petzoldt C, Seaman A (2007) Climate change effects on insects and pathogens. Climate change and agriculture: promoting practical and profitable responses.
  96. Piikki K, Vorne V, Ojanperä K, Pleijel H (2007) Impact of elevated O3 and CO2 exposure on potato (Solanum tuberosum L. cv. Bintje) tuber macronutrients (N, P, K, Mg, Ca). Agric Ecosyst Environ 118(1–4):55–64CrossRefGoogle Scholar
  97. Pinter PJ Jr, Kimball BA, Mauncy JR, Hendrey GR, Lewin KF, Nagy J (1994) Effects of free-air carbon dioxide enrichment on PAR absorption and conversion efficiency by cotton. Agric For Meteorol 70(1–4):209–230CrossRefGoogle Scholar
  98. Pinter PJ Jr, Hatfield JL, Schepers JS, Barnes EM, Moran MS, Daughtry CS, Upchurch DR (2003) Remote sensing for crop management. Photogramm Eng Remote Sens 69(6):647–664CrossRefGoogle Scholar
  99. Pollard E, Yates TJ (1993) Monitoring butterflies for ecology and conservation. Chapman and Hall, London. Google ScholarGoogle Scholar
  100. Poorter H, Pot S, Lambers H (1988) The effect of elevated atmospheric CO2 concentration on growth, photosynthesis and respiration of Plantago major. Physiol Plant 73(4):553–559CrossRefGoogle Scholar
  101. Porter JH, Parry ML, Carter TR (1991) The potential effects of climatic change on agricultural insect pests. Agric For Meteorol 57(1–3):221–240CrossRefGoogle Scholar
  102. Pöyry J, Böttcher K, Fronzek S, Gobron N, Leinonen R, Metsämäki S, Virkkala R (2018) Predictive power of remote sensing versus temperature-derived variables in modelling phenology of herbivorous insects. Remote Sens Ecol Conserv 4(2):113–126CrossRefGoogle Scholar
  103. Prabhakar M, Prasad YG, Thirupathi M, Sreedevi G, Andhra Jyothi B, Venkateswarlu B (2011) Use of ground based hyperspectral remote sensing for detection of stress in cotton caused by leafhopper (Hemiptera: Cicadellidae). Comput Electron Agric 79(2):189–198CrossRefGoogle Scholar
  104. Prasannakumar NR, Chander S, Sahoo RN (2014) Characterization of brown planthopper damage on rice crops through hyperspectral remote sensing under field conditions. Phytoparasitica 42(3):387–395CrossRefGoogle Scholar
  105. Qi J, Chehbouni A, Huete AR, Kerr YH, Sorooshian S (1994) A modified soil adjusted vegetation index. Remote Sens Environ 48(2):119–126CrossRefGoogle Scholar
  106. Rao MS, Khan MM, Srinivas K, Vanaja M, Rao GGSN, Ramakrishna YS (2006) Effects of elevated carbon dioxide and temperature on insect-plant interactions-a review. Agric Rev 27(3):200Google Scholar
  107. Rao M, Srinivasa K, Srinivas M, Vanaja GGSN, Venkateswarlu Rao B, Ramakrishna YS (2009) Host plant (Ricinus communis Linn.) mediated effects of elevated CO2 on growth performance of two insect folivores. Curr Sci 97:1047–1054Google Scholar
  108. Reddy AR, Rasineni GK, Raghavendra AS (2010) The impact of global elevated CO2 concentration on photosynthesis and plant productivity. Curr Sci 99(10):46–57Google Scholar
  109. Reekie EG, Bazzaz FA (1991) Phenology and growth in four annual species grown in ambient and elevated CO2. Can J Bot 69(11):2475–2481CrossRefGoogle Scholar
  110. Riedell WE, Blackmer TM (1999) Leaf reflectance spectra of cereal aphid-damaged wheat. Crop Sci 39:1835–1840CrossRefGoogle Scholar
  111. Riley JR (1989) Remote sensing in entomology. Annu Rev Entomol 34:247–271CrossRefGoogle Scholar
  112. Rondeaux G, Steven M, Baret F (1996) Optimization of soil-adjusted vegetation indices. Remote Sens Environ 55:95–107CrossRefGoogle Scholar
  113. Root TL, Schneider SH (1993) Can large-scale climatic models be linked with multi scale ecological studies? Conserv Biol 7:256–270CrossRefGoogle Scholar
  114. Rose DJW, Page WW, Dewhurst CF (2000) The African armyworm handbook: the status, biology, ecology, epidemiology and management of Spodoptera exempta (Lepidoptera: Noctuidae). Natural Resources Institute, ChathamGoogle Scholar
  115. Rouse JW, Haas RH, Schell JA, Deering DW (1973) Monitoring vegetation systems in the great plains with ERTS. Paper presented at the Third ERTS-1 symposium, December 10–14, Washington, DC, NASA SP-351, vol 1, pp 309–317Google Scholar
  116. Sanders NJ, Belote RT, Weltzin JF (2004) Multitrophic effects of elevated atmospheric CO2 on understory plant and arthropod communities. Environ Entomol 33(6):1609–1616CrossRefGoogle Scholar
  117. Schädler M, Roeder M, Brandl R, Matthies D (2007) Interacting effects of elevated CO2, nutrient availability and plant species on a generalist invertebrate herbivores. Glob Chang Biol 13(5):1005–1015CrossRefGoogle Scholar
  118. Sharma HC (2010) Global warming and climate change: impact on arthropod biodiversity, pest management, and food security, (pp 3–14). In: Souvenier: national symposium on perspectives and challenges of integrated pest management for sustainable agriculture. Dr. Y.S Parmer university of agriculture and forestry, Nauni, Solan, India, November, 19–21, 2010Google Scholar
  119. Sharma HC, Srivastava CP, Durairaj C, Gowda CLL (2010) Pest management in grain legumes and climate change. In: Climate change and management of cool season grain legume crops. Springer, Dordrecht, pp 115–139CrossRefGoogle Scholar
  120. Smith H (1996) The effects of elevated CO2 on aphids. Antenna 20:109–111Google Scholar
  121. Sindhuja S, Mishra A, Reza E, Davis C (2010) A review of advanced techniques for detecting plant diseases. Comput Electron Agric 72:1–13CrossRefGoogle Scholar
  122. Stiling P, Cornelissen T (2007) How does elevated carbon dioxide (CO2) affect plant-herbivore interactions? A field experiment and meta-analysis of CO2-mediated changes on plant chemistry and herbivore performance. Glob Chang Biol 13:1823–1842CrossRefGoogle Scholar
  123. Stone C, Chisholm L, Coops N (2001) Spectral reflectance characteristics of eucalypt foliage damaged by insects. Aust J Bot 49:687–698CrossRefGoogle Scholar
  124. Sudha Rani D, Venkatesh MN, Satya NS, Anand KK (2018) Remote sensing as pest forecasting model in agriculture. Int J Curr Microbiol App Sci 7(3):2680–2689CrossRefGoogle Scholar
  125. Thomson LJ, Macfadyen S, Hoffmann AA (2010) Predicting the effects of climate change on natural enemies of agricultural pests. Biol Control 52:296–306CrossRefGoogle Scholar
  126. Trumble JT, Kolodny HDM, Ting IP (1993) Plant compensation for arthropod herbivory. Annu Rev Entomol 38:93–119CrossRefGoogle Scholar
  127. Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150CrossRefGoogle Scholar
  128. Voigt W, Perner J, Davis AJ, Eggers T, Schumacher J, Bahram R, Fabian B, Heinrich W, Kohler G, Lichter D, Marstaller R, Sander FW (2003) Impact of climate change on crop-pest and pest-natural enemy interactions. Ecology 84:2444–2453CrossRefGoogle Scholar
  129. Wang KH, Tsai JH (1996) Temperature effect on development and reproduction of silver leaf whitefly (Homoptera: Aleyrodidae). Ann Entomol Soc Am 89:375–384CrossRefGoogle Scholar
  130. Warren MS, Hill JK, Thomas JA, Asher J, Fox R, Huntley B, Roy DB, Telfer MG, Jeffcoate S, Harding P, Jeffcoate G, Willis SG, Davies GJN, Moss D, Thomas CD (2001) Impact of global warming on butterflies distributions. Nature 41:65–69CrossRefGoogle Scholar
  131. Yamamura K, Kiritani K (1998) A simple method to estimate the potential increase in the number of generations under global warming in temperate zones. Appl Entomol Zool 33:289–298CrossRefGoogle Scholar
  132. Yang CM (2010) Assessment of the severity of bacterial leaf blight in rice using canopy hyperspectral reflectance. Precis Agric 11:61–81CrossRefGoogle Scholar
  133. Yang CM, Cheng CH (2001) Spectral characteristics of rice plants infested by brown planthoppers. Proc Natl Sci Counc 25(3):180–186Google Scholar
  134. Yang L, Stehman SV, Smith JH, Wickham JD (2001) Thematic accuracy of MRLC land cover for the eastern United States. Remote Sens Environ 76:418–422CrossRefGoogle Scholar
  135. Yang Z, Rao MN, Elliott NC, Kindler SD, Popham TW (2005) Using ground based multispectral radiometry to detect stress in wheat caused by greenbug (Homoptera: Aphididae) infestation. Comput Electron Agric 47:121–135CrossRefGoogle Scholar
  136. Yang CM, Cheng CH, Chen RK (2007) Changes in spectral characteristics of rice canopy infested with brown plant hopper and leaf folder. Crop Sci 47:329–335CrossRefGoogle Scholar
  137. Yuan L, Bao Z, Zhang H, Zhang Y, Liang X (2017) Habitat monitoring to evaluate crop disease and pest distributions based on multi-source satellite remote sensing imagery. Optik 145:66–73CrossRefGoogle Scholar
  138. Zhou Z, Zang Y, Zhao Z, Luo X, Zhou X (2010) Canopy hyper spectral reflectance features of rice caused by rice brown planthopper (Nilaparvata lugens) infestation. American Society of Agricultural and Biological Engineers, Pittsburgh, pp 20–23Google Scholar
  139. Ziska LH, Runion GB (2007) Future weed, pest and disease problems for plants. In: Agroecosystem in a changing climate. CRC Press, Boca Raton, pp 261–287Google Scholar
  140. Ziska LH, Teramura AH (1992) CO2 enhancement of growth and photosynthesis in Rice (Oryza sativa): modification by increased ultraviolet-B radiation. Plant Physiol 99:473–481CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • N. R. Prasannakumar
    • 1
  • H. R. Gopalkrishna
    • 2
  • A. N. D. T. Kumara
    • 3
  • P. N. Guru
    • 4
  1. 1.ICAR-Indian Institute of Horticultural ResearchBengaluruIndia
  2. 2.Division of Floriculture and Medicinal CropsICAR-Indian Institute of Horticultural ResearchBangaloreIndia
  3. 3.Crop Protection Division, Coconut Research InstituteLunuwilaSri Lanka
  4. 4.ICAR-Central Institute of Post Harvest Engineering and Technology, PAU CampusLudhianaIndia

Personalised recommendations