Skip to main navigation menu Skip to main content Skip to site footer

The Septoria leaf blotch of wheat in Central Kazakhstan: prognosis, evaluation and monitoring with remotely sensed data


Fungal diseases represent a widely spread natural phenomenon affecting many wild and domesticated plants. In nature, all plant species form plant communities of a mixed character, and the spatial pattern of dominant species is usually irregular and spotted. Some species are impregnable to a certain infection, which provides a kind of natural barrier to the infection spreading within the natural community. Under the agricultural environment, when a single plant species may occupy a huge area, the species-specific parasite takes a great advantage to develop focal outbreaks and fast spreading of the infection within the area. The concentration of vulnerable plants and the absence of natural barriers within the agricultural areas provoke outbreaks of fungal diseases that may have highly harmful consequences and result in significant yield losses. One of the purposes of the satellite optical data is an operative, cost-effective diagnostic tool and, in combination with climatic datasets and crop rotation information, a prognosis of fungal disease appearance and severity. This paper describes the system of prognostic and monitoring measures to control the fungal diseases of wheat in Central Kazakhstan, with particular attention to Septoria leaf blotch. The prognostic procedure provides a map of the probability of septoria leaf blotch appearance. The prognosis considers the combination of three main variables: the model of ecological niche for Septoria, the presence of wheat residue, and the vegetation condition index counted for the late spring (May) of the current year. The novel spectral-based approach introduced in this paper is the core component of monitoring activity. The SLBS-equation appears to have high sensitivity to Septoria leaf blotch severity in the middle to late (stages 8–11, accordingly, Feekes growth stages) periods of wheat development. Several other spectral indices (RETA, VSDI, and vegetation indices) may help provide information on the spatial unevenness of wheat crops that may indicate the presence of fungal infection.


fungal wheat diseases, remote sensing, monitoring, prognosis



  1. J. A. Verreet, H. Klink, and G. M. Hoffmann, "Regional monitoring for disease prediction and optimization of plant p rotection measures: the IPM Wheat Model," Plant Disease, vol. 84, no. 8, pp. 816-826, 2000 2000.
  2. S. A. Babkenova, A. T. Babkenov, E. V. Pakholkova, and B. K. Kanafin, "Pathogenic complexity of septoria spot disease of wheat in northern Ka zakhstan," Plant Science Today, vol. 7, no. 4, pp. 601-606, 2020 2020, doi: 10.14719/pst.2020.7.4.798.
  3. E. Y. Toropova, O. A. Kazakova, and M. P. Selyuk, "Monitoring of Septoria blight on spring wheat in the forest-steppe of Western Siberia," Dostizheniya nauki i tekhniki APK, vol. 30, no. 12, pp. 33-35, 2016 2016.
  4. G. M. Melkumov and I. A. Brazhnikova, "Taxonomy and ecological peculiarities of Septoria Sacc. species in Vor onezh Region," Proceedings of Volga State University. Series: Chemistry, Biology, Pha rmacy, vol. 2, pp. 185-190, 2018 2018.
  5. R. Karjalainen and S. Karjalainen, "Yield reduction of spring wheat in relation to disease development cau sed by Septoria nodorum," Journal of Agricultural Science in Finland, vol. 62, pp. 255-263, 1990 1990.
  6. Y. Tadesse, A. Chala, and B. Kassa, "Yield loss due to Septoria tritici Blotch (Septoria Tritici) of bread wheat (Triticum aestivum L.) in the Central Highlands of Ethiopia," Journal of Biology, Agriculture and Healthcare, vol. 10, no. 10, pp. 1-7, 2020 2020, doi: 10.7176/JBAH/10-10-01.
  7. V. F. Peresypkin, Ed. Diseases of grain and leguminous crops. Kiev, 1989.
  8. M. Koyshibayev, Diseases of grain crops. Almaty, 2002.
  9. V. F. Peresypkin, Agricultural phytopathology. Kolos, 1969.
  10. D. E. Hess and G. Shaner, "Effect of moisture on Septoria tritici blotch development on wheat in the field," Phytopathology, vol. 77, no. 2, pp. 220-226, 1987 1987.
  11. M. W. Shaw and D. J. Royle, "Factors determining the severity of epidemics of Mycosphaerella gramin icola (Septoria tritici) on winter wheat in the UK," Plant Pathology, vol. 42, pp. 882-899, 1993 1993.
  12. B. M. Cooke, G. D. Jones, and B. Kaye, The epidemiology of plant diseases, 2nd ed. 2006.
  13. D. V. Malakhov, N. Y. Tsychuyeva, and I. S. Vitkovskaya, "Modelling the ecological niche of wheat septoriosis using remote sensi ng data," Current Problems In Remote Sensing Of The Earth From Space, vol. 14, no. 1, pp. 113-124, 2017 2017, doi: 10.21046/2070-7401-2017-14-1-113-124.
  14. M. Kottek, J. Grieser, C. Beck, B. Rudolf, and F. Rubel, "World Map of the Köppen-Geiger climate classification updated," Meteorologische Zeitschrift, vol. 15, no. 3, pp. 259-263, 2006 2006, doi: 10.1127/0941-2948/2006/0130.
  15. H. El Wazziki, B. El Yousfi, and S. Serghat, "Grain yield prediction from brown rust (Puccinia triticina) and leaf b lotch (Septoria tritici) severity on wheat flag leaves," Revue Marocaine de Protection des Plantes, vol. 7, pp. 51-65, 2015 2015.
  16. M. W. Shaw and D. J. Royle, "Estimation and validation of a function describing the rate of yield l oss in winter wheat due to infection by Mycosphaerella graminicola," Annals of Applied Biology, vol. 115, pp. 425-442, 1989 1989.
  17. Y. Wang, S. Zia, S. Owusu-Adu, R. Gerhards, and J. Müller, "Early detection of fungal diseases in winter wheat by multi-optical se nsors," APCBEE Procedia, vol. 8, pp. 199-203, 2014 2014.
  18. J. W. Rouse, Jr., R. H. Haas, J. A. Schell, and D. W. Deering, "Monitoring vegetation systems in the earth with ERTS," Third ERTS Symposium, vol. 1, pp. 309-317, 1973 1973.
  19. R. T. Mzuri, A. A. Omar, and Y. T. Mustafa, "Spatiotemporal analysis of vegetation cover and its response to terrain and climate factors in Duhok Governorate, Kurdistan Region, Iraq," The Iraqi Geological Journal, pp. 110-126, 2021.
  20. A. Huete, K. Didan, T. Miura, E. P. Rodriguez, X. Gao, and L. G. Ferreira, "Overview of the radiometric and biophysical performance of the MODIS v egetation indices," Remote Sensing of Environment, vol. 83, pp. 195-213, 2002 2002.
  21. Y. Mustafa, "Spatiotemporal Analysis of Vegetation Cover in Kurdistan Region-Iraq using MODIS Image Data," Journal of Applied Science and Technology Trends, vol. 1, no. 1, pp. 01-07, 03/10 2020, doi: 10.38094/jastt119.
  22. Z. Yang, P. Willis, and R. Mueller, "Impact of band-ratio enhanced AWIFS image to crop classification accur acy," 2008, 2008.
  23. J. L. Roujean and F. M. Breon, "Estimating PAR absorbed by vegetation from bidirectional reflectance m easurements," Remote Sensing of Environment, vol. 51, pp. 375-384, 1995 1995.
  24. Y. Kaufman and D. Tanre, "Atmospherically resistant vegetation index (ARVI) for EOS-MODIS," IEEE Transactions on Geoscience and Remote Sensing, vol. 2, pp. 261-270, 1992 1992.
  25. F. M. Wang, J. F. Huang, Y. L. Tang, and X. Z. Wang, "New vegetation index and its application in estimating leaf area index of rice," Rice Science, vol. 14, no. 3, pp. 195-203, 2007 2007.
  26. B. Gao, "Normalized difference water index for remote sensing of vegetation liq uid water from space," 1995 1995, 1995, pp. 225-236.
  27. A. A. Gitelson, R. Stark, U. Grits, D. Rundquist, Y. Kaufman, and D. Derry, "Vegetation and soil lines in visible spectral space: a concept and tec hnique for remote estimation of vegetation fraction," International Journal of Remote Sensing, vol. 23, pp. 2537-2562, 2002 2002.
  28. N. Zhang, Y. Hong, Q. Qina, and L. Liu, "VSDI: a visible and shortwave infrared drought index for monitoring so il and vegetation moisture based on optical remote sensing," International Journal of Remote Sensing, vol. 34, no. 13, pp. 4585-4609, 2013 2013.
  29. G. T. Selyaninov, Methodics of agricultural characteristics of climate. Leningrad-Moscow, 1937.
  30. F. N. Kogan, "Operational space technology for global vegetation assessment," Bulletin of the American Meteorological Society, vol. 82, no. 9, pp. 1949-1964, 2001 2001.
  31. J. Peñuelas, J. A. Gamon, A. L. Fredeen, J. Merino, and C. B. Field, "Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves," Remote Sensing of Environment, vol. 48, pp. 135-146, 1994 1994.
  32. T. J. Jackson et al., "Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans," Remote Sensing of Environment, vol. 92, pp. 475-482, 2004 2004.
  33. F. Suffert, N. Galet, and I. Sache, Effect of wheat debris as source of primary inoculum on the early stag es of Septoria leaf blotch epidemics. 2011.
  34. C. S. T. Daughtry, G. Serbin, J. B. Reeves, P. C. Doraiswamy, and E. R. Hunt, "Spectral reflectance of wheat residue during decomposition and remotel y sensed estimates of residue cover," Remote Sensing, vol. 2, pp. 416-431, 2010 2010, doi: 10.3390/rs2020416.
  35. H. McNairn and R. Protz, "Mapping corn residue cover on agricultural fields in Oxford County, On tario, using Thematic Mapper," Canadian Journal of Remote Sensing, vol. 19, pp. 152-159, 1993 1993.
  36. J. Qi et al., "RANGES improves satellite-based information and land cover assessments in Southwest United States," EOS Trans. Am. Geophys. Union, vol. 83, pp. 601-606, 2002 2002.
  37. D. Ashourloo, M. R. Mobasheri, and A. Huete, "Evaluating the effect of different wheat rust disease symptoms on vege tation indices using hyperspectral measurements," Remote Sensing, vol. 6, pp. 5107-5123, 2014 2014, doi: 10.3390/rs6065107.
  38. S. R. Parker, M. W. Shaw, and D. J. Royle, "Measurements of spatial patterns of disease in winter crops and the im plications for sampling," Plant Pathology, vol. 46, pp. 470-480, 1997 1997.
  39. D. Ashourloo, M. R. Mobasheri, and A. Huete, "Developing two spectral disease indices for detection of wheat leaf ru st (Puccinia triticina)," Remote Sensing, vol. 6, pp. 4723-4740, 2014 2014, doi: 10.3390/rs6064723.
  40. T. M. Chaloner, H. N. Fones, V. Varma, D. P. Bebber, and S. J. Gurr, "A new mechanistic model of weather-dependent Septoria tritici blotch d isease risk," Philosophical Transactions of the Royal Society B, vol. 374, 2019 2019, doi: 10.1098/rstb.2018.0266.
  41. D. E. Beest, M. W. Shaw, S. Pietravalle, and F. Bosch, "A predictive model for early-warning of Septoria leaf blotch on winter wheat," European Journal of Plant Pathology, vol. 124, pp. 413-425, 2009 2009, doi: 10.1007/s10658-009-9428-0.
  42. S. Savary, S. Stetkiewicz, F. Brun, and L. Willocquet, "Modelling and mapping potential epidemics of wheat diseases-examples o n leaf rust and Septoria tritici blotch using EPIWHEAT," European Journal of Plant Pathology, 2015 2015, doi: 10.1007/s10658-015-0650-7.
  43. E. Minchinton et al., Validation of a disease forecasting model to manage late blight (Septo ria) in celery. HAL Final report VG06047. State of Victoria, Department of Primary Ind ustries, 2008.


Metrics Loading ...