Advertisement

Yellow rust does not like cold winters. But how to find out which temperature and time frames could be decisive in vivo?

  • Rufat Aslanov
  • Moussa El Jarroudi
  • Mélanie Gollier
  • Marine Pallez-Barthel
  • Marco BeyerEmail author
Original Article

Abstract

Yellow rust epidemics caused by Puccinia striiformis f. sp. tritici were monitored in winter wheat grown without fungicides at four locations over the years 2010–2016 in the Grand Duchy of Luxembourg (GDL) and were observed at increased frequency since 2014. A total of 29 field case studies were subdivided into epidemic and non-epidemic cases based on the control threshold of the disease defined in the framework of integrated pest management (IPM). Significant air temperature differences were found between the time courses of epidemic and non-epidemic cases during seven periods and seven individual days. The longest periods with significantly higher temperatures for epidemic cases were found between 21 and 28 days after sowing (DAS) and between 132 and 134 DAS, corresponding approximately to the time of winter wheat emergence, when the disease may infect the newly sown crop, and to the coldest period of the year, respectively. Average daily temperatures were 7.33 ± 0.32 °C and 10.79 ± 0.26 °C between 21 and 28 DAS for non-epidemic and epidemic cases, respectively. Between 132 and 134 DAS, average daily temperatures were − 1.62 ± 0.74 °C and 1.58 ± 0.43 °C for non-epidemic and epidemic cases, respectively. Based on the significant temperature differences detected, up to 86.7% of correct classifications were obtained by leave-one out cross-validation, suggesting that some of the temperature differences identified here have considerable prognostic value for forecasting if an economically relevant yellow rust epidemic must be expected or not.

Keywords

Disease forecast Integrated Pest Management (IPM) Pesticide use Puccinia striiformis f. sp. tritici Sustainable agriculture 

Notes

Acknowledgements

We thank Daniel Molitor for critical comments on an early version of the manuscript, Gilles Parisot (Chambre d’Agriculture) for helpful discussion, Jacques Engel for organizational support and the Administration des Services Techniques de l’Agriculture of Luxembourg for financially supporting the project Sentinelle.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Statement of human and animal rights

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

  1. Beer E (2005) Arbeitsergebnisse aus der Projektgruppe „Krankheiten im Getreide“ der Deutschen Phytomedizinischen Gesellschaft e. V. Gesunde Pflanzen 57:59–70.  https://doi.org/10.1007/s10343-004-0064-5
  2. Beyer M, El Jarroudi M, Junk J, Pogoda F, Dubos T, Görgen K, Hoffmann L (2012) Spring air temperature accounts for the bimodal temporal distribution of Septoria tritici epidemics in the winter wheat stands of Luxembourg. Crop Prot 42:250–255.  https://doi.org/10.1016/j.cropro.2012.07.015 CrossRefGoogle Scholar
  3. Chen XM (2005) Epidemiology and control of stripe rust [Puccinia striiformis f. sp. tritici] on wheat. Can J Plant Pathol 27:314–337.  https://doi.org/10.1080/07060660509507230 CrossRefGoogle Scholar
  4. de Vallavieille-Pope C, Bahri B, Leconte M, Zurfluh O, Belaid Y, Maghrebi E, Huard F, Huber L, Launay M, Bancal MO (2018) Thermal generalist behaviour of invasive Puccinia striiformis f.sp. tritici strains under current and future climate conditions. Plant Pathol 67:1307–1320.  https://doi.org/10.1111/ppa.12840
  5. Eickermann M, Junk J, Hoffmann L, Beyer M (2015) Forecasting the breaching of the control threshold for Ceutorhynchus pallidactylus in oilseed rape. Agric For Entomol 17:71–76.  https://doi.org/10.1111/afe.12082 CrossRefGoogle Scholar
  6. El Jarroudi M, Delfosse P, Maraite H, Hoffmann L, Tychon B (2009) Assessing the accuracy of simulation model for Septoria leaf blotch disease progress on winter wheat. Plant Dis 93:983–992.  https://doi.org/10.1094/PDIS-93-10-0983 CrossRefGoogle Scholar
  7. El Jarroudi M, Kouadio L, Bock CH, El Jarroudi M, Junk J, Pasquali M, Maraite H, Delfosse P (2017) A threshold-based weather model for predicting stripe rust infection in winter wheat. Plant Dis 101:693–703.  https://doi.org/10.1094/PDIS-12-16-1766-RE CrossRefGoogle Scholar
  8. Giroux M-E, Bourgeois G, Dion Y, Rioux S, Pageau D, Zoghlami S, Parent C, Vachon E, Vanasse A (2016) Evaluation of forecasting models of wheat under growing conditions of Quebec, Canada. Plant Dis 100:1192–1201.  https://doi.org/10.1094/PDIS-04-15-0404-RE CrossRefGoogle Scholar
  9. Gladders P, Langton SD, Barrie IA, Taylor MC, Paveley ND (2007) The importance of weather and agronomic factors for the overwinter survival of yellow rust (Puccinia striiformis) and subsequent disease risk in commercial wheat crops in England. Ann Appl Biol 150:371–382.  https://doi.org/10.1111/j.1744-7348.2007.00131.x CrossRefGoogle Scholar
  10. Gouache D, Léon MS, Duyme F, Braun P (2015) A novel solution to the variable selection problem in window pane approaches of plant pathogen – climate models: development, evaluation and application of a climatological model for brown rust of wheat. Agric For Meteorol 2015:51–59.  https://doi.org/10.1016/j.agrformet.2015.02.013 CrossRefGoogle Scholar
  11. Hovmøller MS, Walter S, Bayles RA, Hubbard A, Flath K, Sommerfeldt N, Leconte M, Czembor P, Rodriguez-Algaba J, Thach T, Hansen JG, Lassen P, Justesen AF, Ali S, de Vallavieille-Pope C (2016) Replacement of the European wheat yellow rust population by new races from the Centre of diversity in the near-Himalayan region. Plant Pathol 65:402–411.  https://doi.org/10.1111/ppa.12433 CrossRefGoogle Scholar
  12. Jørgensen LN, Hovmøller MS, Grønbæk Hansen J, Lassen P, Clark B, Bayles R, Rodemann B, Flath K, Jahn M, Goral T, Czembor JJ, Cheyron P, Maumene C, De Pope C, Ban R, Cordsen Nielsen G, Berg G (2014) IPM strategies and their dilemmas including an introduction to www.eurowheat.org. J Integr Agric 13:265–281.  https://doi.org/10.1016/S2095-3119(13)60646-2
  13. Junk J, Kouadio L, Delfosse P, El Jarroudi M (2016) Effects of regional climate change on brown rust disease in winter wheat. Clim Chang 135:439–451.  https://doi.org/10.1007/s10584-015-1587-8 CrossRefGoogle Scholar
  14. Lalancette N, Ellis MA, Madden LV (1988) Development of an infection efficiency model for Plasmopara viticola on American grape based on temperature and duration of lead wetness. Phytopathology 78:794–800CrossRefGoogle Scholar
  15. Line RF (2002) Stripe rust of wheat and barley in North America: a retrospective historical review. Annu Rev Phytopathol 40:75–118.  https://doi.org/10.1146/annurev.phyto.40.020102.111645 CrossRefGoogle Scholar
  16. Magarey RD, Sutton TB, Thayer CL (2005) A simple generic infection model for foliar fungal plant pathogens. Phytopathology 95:92–100.  https://doi.org/10.1094/PHYTO-95-0092 CrossRefGoogle Scholar
  17. Molitor D, Augenstein B, Mugnai L, Rinaldi PA, Sofia J, Hed B, Dubuis P-H, Jermini M, Kührer E, Bleyer G, Hoffmann L, Beyer M (2016) Composition and evaluation of a novel web-based decision support system for grape black rot control. Eur J Plant Pathol 144:785–798.  https://doi.org/10.1007/s10658-015-0835-0 CrossRefGoogle Scholar
  18. Walter M, Roy S, Fisher BM, Mackle L, Amponsah NT, Curnow T, Campbell RE, Braun P, Reinecke A, Scheper RWA (2016) How many conidia are required for wound infection of apple plants by Neonectria ditissima? New Zealand Plant Protect 69:238–245Google Scholar
  19. Zadoks JC (1985) On the conceptual basis of crop loss assessment: the threshold theory. Annu Rev Phytopathol 23:455–473.  https://doi.org/10.1146/annurev.py.23.090185.002323 CrossRefGoogle Scholar
  20. Zhao J, Xu C, Xu J, Huang L, Zhang D, Liang D (2017) Forecasting the wheat powdery mildew (Blumeria graminis f. sp. tritici) using a remote sensing-based decision-tree classification at a provincial scale. Autralasian Plant Pathol.  https://doi.org/10.1007/s13313-017-0527-7

Copyright information

© Società Italiana di Patologia Vegetale (S.I.Pa.V.) 2019

Authors and Affiliations

  1. 1.Department “Environmental Research and Innovation”Luxembourg Institute of Science and TechnologyBelvauxLuxembourg
  2. 2.Campus Arlon “Environment”University of LiègeArlonBelgium

Personalised recommendations