pp 1–10 | Cite as

Characterization of Sclerotinia sclerotiorum airborne inoculum, the widespread agent of white mould disease

  • Christel LeyronasEmail author
  • Marc Benigni
  • Stéphane Leignez
  • Magali Duffaud
  • François Villeneuve
  • Philippe C. Nicot
Original Paper


A means to rationalize the use of fungicides for crop protection and to make agriculture friendlier to environment and human health is to develop disease-risk forecasting systems based on the assessment of airborne inoculum abundance. Sclerotinia sclerotiorum, the pandemic agent of white mould disease, is disseminated via the atmosphere in the form of ascospores. These airborne spores are the primary sources of inoculum initiating the majority of epidemics. However, for witloof chicory (Cichorium intybus var. foliosum L.), there is no data about airborne inoculum of S. sclerotiorum, which makes it difficult to develop a forecasting model. In the present study, we characterized the temporal evolution of the abundance and of the genetic characteristics of S. sclerotiorum inoculum on a witloof chicory field located in Northern France over a 3-year period. To our knowledge, this study provides the first quantification of viable airborne populations of this fungus in witloof chicory crops. Moreover, it provides the first genetic characterization of S. sclerotiorum airborne inoculum. The results show that viable ascospores were present through 80% of the sampling dates. A significant correlation between abundance of airborne ascospores and local relative humidity suggests a local origin of inoculum. However, the existence of a slight genetic differentiation between isolates carried by air masses coming from the West and from the North-West is compatible with the hypothesis of a distant origin of S. sclerotiorum inoculum. We discuss the additional studies that are envisioned to clarify the origin of S. sclerotiorum airborne inoculum in witloof chicory fields.


Air mass trajectory Ascospores Quantification Microsatellite markers Witloof chicory 



This study was supported in part by a CASDAR grant of the French Ministry of Agriculture (SCLEROLEG Project) and by the Groupement d’Intérêt Scientifique pour la Production Intégrée des Cultures légumières (GIS PIClég).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Abawi, G. S., & Grogan, R. G. (1979). Epidemiology of diseases caused by Sclerotinia species. Phytopathology, 69(8), 899–904.CrossRefGoogle Scholar
  2. Arnaud-Haond, S., & Belkhir, K. (2007). Genclone: A computer program to analyse genotypic data, test for clonality and describe spatial clonal organization. Molecular Ecology Notes, 7(1), 15–17.CrossRefGoogle Scholar
  3. Arnaud-Haond, S., Duarte, C. M., Alberto, F., & Serrao, E. A. (2007). Standardizing methods to address clonality in population studies. Molecular Ecology, 16(24), 5115–5139.CrossRefGoogle Scholar
  4. Benigni, M., & Bompeix, G. (2010). Chemical and biological control of Sclerotinia sclerotiorum in witloof chicory culture. Pest Management Science, 66(12), 1332–1336.CrossRefGoogle Scholar
  5. Ben-Yephet, Y., & Bitton, S. (1985). Use of a selective medium to study the dispersal of ascospores of Sclerotinia sclerotiorum. Phytoparasitica, 13(1), 33–40.CrossRefGoogle Scholar
  6. Boland, G. J., & Hall, R. (1994). Index of plant hosts of Sclerotinia sclerotiorum. Canadian Journal of Plant Pathology, 16(2), 93–108.CrossRefGoogle Scholar
  7. Brown, J. K. M., & Hovmøller, M. S. (2002). Aerial dispersal of pathogens on the global and continental scales and its impact on plant disease. Science, 297(5581), 537–541.CrossRefGoogle Scholar
  8. Clarkson, J. P., Phelps, K., Whipps, J. M., Young, C. S., Smith, J. A., & Watling, M. (2007). Forecasting sclerotinia disease on lettuce: A predictive model for carpogenic germination of Sclerotinia sclerotiorum sclerotia. Phytopathology, 97(5), 621–631.CrossRefGoogle Scholar
  9. Clarkson, J. P., Warmington, R., Walley, P. G., Denton-Giles, M., Barbetti, M. J., Brodal, G., et al. (2017). Population structure of Sclerotinia subarctica and Sclerotinia sclerotiorum in England. Scotland and Norway: Frontiers in Microbiology. Scholar
  10. Draxler, R. R., & Rolph, G. D. (2011). HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY. NOAA Air Resources Laboratory, Silver Spring, MD. Accessed 10 Jan 2018.
  11. Earl, D. A., & vonHoldt, B. M. (2012). STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources, 4(2), 359–361.CrossRefGoogle Scholar
  12. Elbert, W., Taylor, P. E., Andreae, M. O., & Pöschl, U. (2007). Contribution of fungi to primary biogenic aerosols in the atmosphere: Wet and dry discharged spores, carbohydrates, and inorganic ions. Atmospheric Chemistry and Physics, 7, 4569–4588.CrossRefGoogle Scholar
  13. Excoffier, L., Laval, G., & Schneider, S. (2005). Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online, 1, 47–50.Google Scholar
  14. Falush, D., Stephens, M., & Pritchard, J. K. (2003). Inference of population structure using multilocus genotype data: Linked loci and correlated allele frequencies. Genetics, 164(4), 1567–1587.Google Scholar
  15. Foster, A. J., Kora, C., McDonald, M. R., & Boland, G. J. (2011). Devlopment and validation of a disease forecast model for Sclerotinia rot of carrot. Canadian Journal of Plant Pathology, 33(2), 187–201.CrossRefGoogle Scholar
  16. Hammond, C. N., Cummings, T. F., & Johnson, D. A. (2008). Deposition of ascospores of Sclerotinia sclerotiorum in and near potato fields and the potential to impact efficacy of a biocontrol agent in the Columbia basin. American Journal of Potato Research, 85(5), 353–360.CrossRefGoogle Scholar
  17. Lehner, M. S., Trazilbo, J. P., & Mizubuti, E. S. G. (2016). Does hyphal-tip ensure the same allelic composition at SSR loci as monosporic isolates of Sclerotinia sclerotiorum? Journal of Phytopathology, 164(6), 417–420.CrossRefGoogle Scholar
  18. Leroy, T., Caffier, V., Celton, J. M., Anger, N., Durel, C. E., Lemaire, C., et al. (2016). When virulence originates from nonagricultural hosts: evolutionary and epidemiological consequences of introgressions following secondary contacts in Venturia inaequalis. New Phytologist, 210(4), 1443–1452.CrossRefGoogle Scholar
  19. Lewartowska, E., Jedryczka, M., & Frencel, I. (1996). Pathogenicity of Sclerotinia sclerotiorum (Lib.) de Bary isolates from different localities of rapeseed in Poland. In: Proceedings scientific symposium on plant diseases and the environment, Poznan, Poland. 27–28 June 1996.Google Scholar
  20. Leyronas, C., Halkett, F., & Nicot, P. C. (2015). Relationship between the genetic characteristics of Botrytis sp. airborne inoculum and meteorological parameters, seasons and the origin of air masses. Aerobiologia, 31(3), 367–380.CrossRefGoogle Scholar
  21. Leyronas, C., & Nicot, P. C. (2013). Monitoring viable airborne inoculum of Botrytis cinerea in the South-East of France over 3 years: Relation with climatic parameters and the origin of air masses. Aerobiologia, 29(2), 291–299.CrossRefGoogle Scholar
  22. Leyronas, C., Troulet, C., Duffaud, M., Villeneuve, F., Benigni, M., Leignez, S., et al. (2018). First report of Sclerotinia subarctica in France detected with a rapid PCR-based test. Canadian Journal of Plant Pathology. Scholar
  23. Meier, F. C., Stevenson, J. A., & Charles, V. K. (1933). Spores in the upper air. Phytopathology, 23, 23.Google Scholar
  24. Meredith, D. S. (1973). Significance of spore release and dispersal mechanisms in plant disease epidemiology. Annual Review of Phytopathology, 11, 313–342.CrossRefGoogle Scholar
  25. Mila, A. L., & Yang, X. B. (2008). Effects of fluctuating soil temperature and water potential on sclerotia germination and apothecial production of Sclerotinia sclerotiorum. Plant Disease, 92(1), 78–82.CrossRefGoogle Scholar
  26. Monteil, C. L., Cai, R., Liu, H., Llontop, M. E., Leman, S., Studholme, D. J., et al. (2013). Nonagricultural reservoirs contribute to emergence and evolution of Pseudomonas syringae crop pathogens. New Phytologist, 199(3), 800–811.CrossRefGoogle Scholar
  27. Pan, Z., Yang, X. B., Pivonia, S., Xue, L., Pasken, R., & Roads, J. (2006). Long-term prediction of soybean rust entry into the continental United States. Plant Disease, 90(7), 840–846.CrossRefGoogle Scholar
  28. Pascual, A., Campa, A., Perez-Vega, E., Giraldez, R., Miklas, P. N., & Ferreira, J. J. (2010). Screening common bean for resistance to four Sclerotinia sclerotiorum isolates collected in Northern Spain. Plant Disease, 94(7), 885–890.CrossRefGoogle Scholar
  29. Petrofeza, S., & Nasser, L. C. B. (2012). Case study: Sclerotinia sclerotiorum—genetic diversity and disease control. In M. Caliskan (Ed.), The molecular basis of plant genetic diversity. Delhi: InTech.Google Scholar
  30. Prospero, J. M., Blades, E., Mathison, G., & Naidu, R. (2005). Interhemispheric transport of viable fungi and bacteria from Africa to the Caribbean with soil dust. Aerobiologia, 21(1), 1–19.CrossRefGoogle Scholar
  31. Purdy, L. H. (1979). Sclerotinia sclerotiorum: History, diseases and symptomatology, host range, geographic distribution, and impact. Phytopathology, 69(8), 875–880.CrossRefGoogle Scholar
  32. Purdy, L. J., Krupa, S. V., & Dean, J. L. (1985). Introduction of sugarcane rust into the Americas and its spread to Florida. Plant Disease, 69(8), 689–693.CrossRefGoogle Scholar
  33. Qandah, I. S., & Del Rio Mendoza, L. E. (2011). Temporal dispersal patterns of Sclerotinia sclerotiorum ascospores during canola flowering. Canadian Journal of Plant Pathology, 33(2), 159–167.CrossRefGoogle Scholar
  34. Qandah, I. S., & Del Rio Mendoza, L. E. (2012). Modelling inoculum dispersal and Sclerotinia stem rot gradients in canola fields. Canadian Journal of Plant Pathology, 34(3), 390–400.CrossRefGoogle Scholar
  35. Rolph, G. D. (2011) Real-time environmental applications and display system (READY). NOAA Air Resources Laboratory, Silver Spring, MD. Accessed 10 Jan 2018.
  36. Roper, M., Seminara, A., Bandi, M. M., Ann Cobb, A., Dillard, H. R., & Pringle, A. (2010). Dispersal of fungal spores on a cooperatively generated wind. PNAS, 107(41), 17474–17479.CrossRefGoogle Scholar
  37. Savage, D., Barbetti, M. J., MacLeod, W. J., Salam, M. U., & Renton, M. (2012). Seasonal and diurnal patterns of spore release can significantly affect the proportion of spores expected to undergo long-distance dispersal. Microbial Ecology, 63(3), 578–585.CrossRefGoogle Scholar
  38. Shaw, M. W., Emmanuel, C. J., Emilda, D., Terhem, R. B., Shafia, A., Tsamaidi, D., et al. (2016). Analysis of cryptic, systemic Botrytis infections in symptomless hosts. Frontiers in Plant Science. Scholar
  39. Sirjusingh, C., & Kohn, L. M. (2001). Characterization of microsatellites in the fungal plant pathogen, Sclerotinia sclerotiorum. Molecular Ecology Notes, 1(4), 267–269.CrossRefGoogle Scholar
  40. Sowley, E. N. K., Dewey, F. M., & Shaw, M. W. (2010). Persistent, symptomless, systemic, and seedborne infection of lettuce by Botrytis cinerea. European Journal of Plant Pathology, 126(1), 61–71.CrossRefGoogle Scholar
  41. Steadman, J. R., Marcinkowska, J., & Rutledge, S. (1994). A semi-selective medium for isolation of Sclerotinia sclerotiorum. Canadian Journal of Plant Pathology, 16(1), 68–70.CrossRefGoogle Scholar
  42. Tao, Z., Malvick, D., Claybrooke, R., Floyd, C., Bernacchi, C. J., Spoden, G., et al. (2009). Predicting the risk of soybean rust in Minnesota based on an integrated atmospheric model. International Journal of Biometeorology, 53(6), 509–521.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Christel Leyronas
    • 1
    Email author
  • Marc Benigni
    • 2
  • Stéphane Leignez
    • 2
  • Magali Duffaud
    • 1
  • François Villeneuve
    • 3
  • Philippe C. Nicot
    • 1
  1. 1.Pathologie VégétaleINRAMontfavetFrance
  2. 2.APEFArrasFrance
  3. 3.Ctifl, Centre de LanxadePrigonrieuxFrance

Personalised recommendations