Molecular Breeding

, 36:95 | Cite as

Mapping of spot blotch disease resistance using NDVI as a substitute to visual observation in wheat (Triticum aestivum L.)

  • Suneel Kumar
  • Marion S. Röder
  • Ravi P. Singh
  • Sundeep Kumar
  • Ramesh Chand
  • Arun K. Joshi
  • Uttam Kumar


Evaluation of wheat for spot blotch disease resistance relies on various visual observation methods. The person evaluating the lines needs to be experienced in scoring disease severity. To facilitate high-throughput phenotyping, a hand-held green seeker NDVI sensor was used to map spot blotch disease resistance QTLs. A total of 108 germplasm lines along with 335 SSD-derived lines (F4 and F5 generations) originating from the cross ‘YS116 × Sonalika’ were used. The population was evaluated at BISA, Pusa Bihar, a hot spot for spot blotch, for 2 consecutive years. Data were recorded using the NDVI as well as by visual observation as % disease severity. The correlation coefficient was calculated between two scoring methods (NDVI and % DS) recorded at different growth stages. High negative correlation was observed between the NDVI and % DS at GS69 and GS77 on Zadoks' scale. With both methods, the QTL was mapped in the same chromosomal region on 5BL. Using the NDVI value, the detected QTL explained up to 54.9 % of phenotypic variation while up to 56.1 % using the % DS. The Sb2 gene was mapped between the markers Xgwm639 and Xgwm1043 with an interval of 0.62 cM. The markers linked to the Tsn1 gene (Xfcp1 and Xfcp623) were mapped 1.1 cM apart from the sb2 gene. It is concluded that the NDVI the can be used as an alternative to visual scoring of spot blotch disease in wheat and create a new avenue for high-throughput phenotyping.


NDVI Wheat Bipolaris sorokiniana Spot blotch QTL mapping 



All authors acknowledge the financial support from the Department of Biotechnology, Government of India (project ref. no. BT/IN/Indo-German/10/UK2010) and the BMBF, Germany (Project 01DQ12016). SK was the beneficiary of a Department of Biotechnology JRF/SRF fellowship granted under the Biotechnology Eligibility Test programme.

Authors’ contributions

SK: performed most of the experimental work and drafted the manuscript. MSR: provided the facility for genotyping of the mapping population in IPK. RPS: provided scientific inputs for the initial conduct of the trial. SK: screened the mapping population with Tsn1 linked markers and performed statistical analysis. RC: artificial inoculation and evaluation of lines for disease resistance in the field. AKJ: scientific contribution for conducting the experiment and manuscript preparation. UK: overall experiment conducting and planning, analysis, result interpretation and helping in manuscript writing.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

11032_2016_515_MOESM1_ESM.docx (422 kb)
Supplementary material 1 (DOCX 422 kb)


  1. Alam A, Xue F, Ali M, Wang C, Ji W (2013) Identification and molecular mapping of powdery mildew resistance gene PmG25 in common wheat originated from wild emmer (Triticum Turgidum Var. Dicoccoides). Pak J Bot 45:203–208Google Scholar
  2. Apan A, Held A, Phinn S, Markley J (2004) Detecting sugarcane “orange rust” disease using EO-1 Hyperion hyperspectral imagery. Int J Remote Sens 25(2):489–498CrossRefGoogle Scholar
  3. Aparicio N, Villegas D, Casadesus J, Araus JL, Royo C (2000) Spectral vegetation indices as nondestructive tools for determining durum wheat yield. Agron J 92:83–91CrossRefGoogle Scholar
  4. Babar MA, Reynolds MP, Van Ginkel M, Klatt AR, Raun WR, Stone ML (2006) Spectral reflectance indices as a potential indirect selection criteria for wheat yield under irrigation. Crop Sci 46:578–588CrossRefGoogle Scholar
  5. Bravo C, Moshou D, West J, McCartney A, Ramon H (2003) Early disease detection in wheat fields using spectral reflectance. Biosyst Eng 84:137–145CrossRefGoogle Scholar
  6. Carter GA, Knapp AK (2001) Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. Am J Bot 88:677–684CrossRefPubMedGoogle Scholar
  7. Chaurasia S, Chand R, Joshi AK (2000) Relative dominance of Alternaria triticina Pras. et Prab. and Bipolaris sorokiniana (Sacc.) Shoemaker in different growth stages of wheat (Triticum aestivum L.). Z Pflanzenkrankh Pflanzenschutz 107:176–181Google Scholar
  8. Chen B, Li SK, Wang KR, Zhou GQ (2012) Evaluating the severity level of cotton Verticillium using spectral signature analysis. Int J Remote Sens 33:2706–2724CrossRefGoogle Scholar
  9. Deering DW, Rouse JW, Haas RH, Schell JA (1975) Measuring “forage production” of grazing units from Landsat MSS data. Proceedings of the Tenth International Symposium on Remote Sensing of Environment. ERIM, Ann Arbor, pp 1169–1178Google Scholar
  10. Devadas R, Lamb DW, Simpfendorfer S, Backhouse D (2009) Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves. Precis Agric 10:459–470CrossRefGoogle Scholar
  11. Faris JD, Anderson JA, Francl LJ, Jordahl JG (1996) Chromosomal location of a gene conditioning insensitivity in wheat to a necrosis-inducing culture filtrate from Pyrenophora tritici-repentis. Phytopathology 86:459–463CrossRefGoogle Scholar
  12. Franke J, Menz G (2007) Multi-temporal wheat disease detection by multi-spectral remote sensing. Precis Agric 8:161–172CrossRefGoogle Scholar
  13. Gurung S, Sharma RC, Duveiller E, Shrestha SM (2012) Comparative analysis of spot blotch and tan spot under optimum and late sowing period in South Asia. Eur J Plant Pathol 2:257–266CrossRefGoogle Scholar
  14. Jacobi J, Kühbauch W (2005) Site-specific identification of fungal infection and nitrogen deficiency in wheat crop using remote sensing. In: Proceedings of the European conference on precision agriculture, pp 73–80Google Scholar
  15. Joshi AK, Kumar S, Chand R, Ortiz-Ferrara G (2004) Inheritance of resistance to spot blotch caused by Bipolaris sorokiniana in spring wheat. Plant Breed 123:213–219CrossRefGoogle Scholar
  16. Joshi AK, Mishra B, Chatrath R, Ortiz Ferrara G, Singh RP (2007) Wheat improvement in India: present status, emerging challenges and future prospects. Euphytica 157:431–446CrossRefGoogle Scholar
  17. Kumar R, Silva L (1973) Light ray tracing through a leaf cross-section. Appl Opt 12:2950–2954CrossRefPubMedGoogle Scholar
  18. Kumar U, Kumar S, Tyagi K, Chand R, Joshi AK (2005) Microsatellite markers for resistance to spot blotch in spring wheat. Commun Agric Appl Biol Sci 70(3):59–60PubMedGoogle Scholar
  19. Kumar U, Joshi AK, Kumar S, Chand R, Röder MS (2009) Mapping of resistance to spot blotch disease caused by Bipolaris sorokiniana in spring wheat. Theor Appl Genet 118:783–792CrossRefPubMedGoogle Scholar
  20. Kumar U, Joshi AK, Kumar S, Chand R, Röder MS (2010) Quantitative trait loci for resistance to spot blotch caused by Bipolaris sorokiniana in wheat (T. aestivum L.) lines “Ning 8201” and “Chirya 3”. Mol Breed 26(3):477–491CrossRefGoogle Scholar
  21. Kumar S, Tripathi SB, Kumar U (2015a) Dissection of wheat spot blotch disease resistance QTLs into single Mendelian genes. Indian J Genet 75(4):434–439Google Scholar
  22. Kumar S, Röder MS, Tripathi SB, Kumar S, Chand R, Joshi AK, Kumar U (2015b) Mendelization and fine mapping of a bread wheat spot blotch disease resistance QTL. Mol Breed 35:1–10CrossRefGoogle Scholar
  23. Lander ES, Botstein D (1989) Mapping Mendelian factors underlying quantitative traits using RFPP linkage maps. Genetics 121:185–199PubMedPubMedCentralGoogle Scholar
  24. Lillemo M, Joshi AK, Prasad R, Chand R, Singh RP (2013) QTL for spot blotch resistance in bread wheat line Saar co-locate to the biotrophic disease resistance loci Lr34 and Lr46. Theor Appl Genet 126:711–719CrossRefPubMedGoogle Scholar
  25. Mehta YR (1994) Manejo Integrado de Enfermedadas de Trigo-Santa Cruz. CIAT/IAPAR, Bolivia, p 314Google Scholar
  26. Moshou D, Bravo C, West J, Wahlen S, McCartney A, Ramon H (2004) Automatic detection of “yellow rust” in wheat using reflectance measurements and neural networks. Comput Electron Agric 44:173–188CrossRefGoogle Scholar
  27. Nyquist WE (1991) Estimation of heritability and prediction of selection response in plant populations. Crit Rev Plant Sci 10:235–322CrossRefGoogle Scholar
  28. Penuelas 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 48:135–146CrossRefGoogle Scholar
  29. Rees RG, Platz GJ (1983) Effects of yellow spot on wheat: comparison of epidemics at different stages of crop development. Austr J Agric Res 34:39–46CrossRefGoogle Scholar
  30. Röder MS, Korzun V, Wendehake K, Plaschke J, Tixier M-H, Leroy P, Ganal MW (1998) A microsatellite 559 map of wheat. Genetics 149(4):2007–2023PubMedPubMedCentralGoogle Scholar
  31. Röder MS, Huang X-Q, Börner A (2008) Fine mapping of the region on wheat chromosome 7D 557 controlling grain weight. Funct Integr Genomics 8(1):79–86CrossRefPubMedGoogle Scholar
  32. Saari EE (1998) Leaf blight disease and associated soil borne fungal pathogens of wheat in South and South East Asia. In: Duveiller E, Dubin HJ, Reeves J, McNab A (eds) Helminthosporium blights of wheat: spot blotch and tan spot. CIMMYT, Mexico, pp 37–51Google Scholar
  33. Sankaran S, Mishra A, Ehsani R, Davis C (2010) A review of advanced techniques for detecting plant diseases. Comput Electron Agric 72(1):1–13CrossRefGoogle Scholar
  34. Santin-Janin H, Garel M, Chapuis JL, Pontier D (2009) Assessing the performance of NDVI as a proxy for plant biomass using non-linear models: a case study on the kerguelen archipelago. Polar Biol 32:861–871CrossRefGoogle Scholar
  35. Shanahan JF, Schepers JS, Francis DD, Varvel GE, Wilhelm WW, Tringe JM, Major DJ (2001) Use of remote-sensing imagery to estimate corn grain yield. Agron J 93:583–589CrossRefGoogle Scholar
  36. Sharma RC, Duveiller E, Jacquemin JM (2007) Microsatellite markers associated with spot blotch resistance in spring wheat. J Phytopathol 155:316–319CrossRefGoogle Scholar
  37. Sharp EL, Perry CR, Scharen AL, Boatwright GO, Sands DC, Lautenschlager LF, Yahyaoui CM, Ravet FW (1985) Monitoring cereal rust development with a spectral radiometer. Phytopathol 75:936–939CrossRefGoogle Scholar
  38. Solari F, Shanahan J, Ferguson R, Schepers J, Gitelson A (2008) Active sensor reflectance measurements of corn nitrogen status and yield potential. Agron J 100:571–579CrossRefGoogle Scholar
  39. Turvey CG, Mclaurin MK (2012) Applicability of the normalized difference vegetation index (NDVI) in index-based crop insurance design. Weather Clim Soc 4(4):271–284CrossRefGoogle Scholar
  40. Van Der Meer F, Bakker W, Scholte K, Skidmore A, De Jong S, Clevers J, Epema G (2001) Spatial scale variations in vegetation indices and above-ground biomass estimates: implications for MERIS. Int J Remote Sens 22(17):3381–3396CrossRefGoogle Scholar
  41. Wang J, Li H, Zhang L, Meng L (2012) User’s manual of QTL Icimapping version 3.2. Chinese Academy of Agricultural Science (CAAS), Beijing, p 208Google Scholar
  42. West JS, Bravo C, Oberti R, Lemaire D, Moshou D, McCartney HA (2003) The potential of optical canopy measurement for targeted control of field crop diseases. Annu Rev Phytopathol 41:593–614CrossRefPubMedGoogle Scholar
  43. Young A, Britton G (1990) Carotenoids and stress. In: Alscher RG, Cumming JR (eds) Stress responses in plants: adaptation and acclimation mechanisms. Wiley-Liss Inc, New York, pp 87–112Google Scholar
  44. Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421CrossRefGoogle Scholar
  45. Zhang J, Huang W, Li J, Yang G, Luo J, Gu X, Wang J (2010) Development, evaluation and application of a spectral knowledge base to detect yellow rust in winter wheat. Precis Agric 12:716–731CrossRefGoogle Scholar
  46. Zhu Z, Bonnett D, Ellis M, Singh RP, Heslot N, Dreisigaker S, Gao D, Kazi AM (2014) Mapping resistance to spot blotch in a CIMMYT synthetic-derived bread wheat. Mol Breed 34:1215–1228CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Suneel Kumar
    • 1
  • Marion S. Röder
    • 2
  • Ravi P. Singh
    • 3
  • Sundeep Kumar
    • 4
  • Ramesh Chand
    • 5
  • Arun K. Joshi
    • 5
    • 6
  • Uttam Kumar
    • 3
    • 7
  1. 1.TERI UniversityNew DelhiIndia
  2. 2.Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)GaterslebenGermany
  3. 3.International Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico
  4. 4.National Bureau of Plant Genetics Resources (NBPGR)New DelhiIndia
  5. 5.Institute of Agricultural SciencesBanaras Hindu UniversityVaranasiIndia
  6. 6.International Maize and Wheat Improvement Center (CIMMYT)New DelhiIndia
  7. 7.Borlaug Institute for South Asia (BISA)LudhianaIndia

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