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Application of the Maryblyt Model for the Infection of Fire Blight on Apple Trees at Chungju, Jecheon, and Eumsung during 2015-2020

  • Received : 2021.07.26
  • Accepted : 2021.09.30
  • Published : 2021.12.01

Abstract

To preventively control fire blight in apple trees and determine policies regarding field monitoring, the Maryblyt ver. 7.1 model (MARYBLYT) was evaluated in the cities of Chungju, Jecheon, and Eumseong in Korea from 2015 to 2020. The number of blossom infection alerts was the highest in 2020 and the lowest in 2017 and 2018. And the common feature of MARYBLYT blossom infection risks during the flowering period was that the time of BIR-High or BIR-Infection alerts was the same regardless of location. The flowering periods of the trees required to operate the model varied according to the year and geographic location. The model predicts the risk of "Infection" during the flowering periods, and recommends the appropriate times to control blossom infection. In 2020, when flower blight was severe, the difference between the expected date of blossom blight symptoms presented by MARYBLYT and the date of actual symptom detection was only 1-3 days, implying that MARYBLYT is highly accurate. As the model was originally developed based on data obtained from the eastern region of the United States, which has a climate similar to that of Korea, this model can be used in Korea. To improve field utilization, however, the entire flowering period of multiple apple varieties needs to be considered when the model is applied. MARYBLYT is believed to be a useful tool for determining when to control and monitor apple cultivation areas that suffer from serious fire blight problems.

Keywords

Acknowledgement

This work was supported by the Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ01530204) of the Rural Development Administration of the Republic of Korea.

References

  1. Agrios, G. N. 2005. Plant pathology. 5th ed. Academic Press, San Diego, CA, USA. 952 pp.
  2. Beer, S. V. and Norelli, J. L. 1977. Fire blight epidemiology: factors affecting release of Erwinia amylovora by cankers. Phytopathology 67:1119-1125. https://doi.org/10.1094/Phyto-67-1119
  3. Billing, E. 1980. Fireblight Erwinia amylovora and weather: a comparison of warning systems. Ann. Appl. Biol. 95:365-377. https://doi.org/10.1111/j.1744-7348.1980.tb04756.x
  4. Billing, E. 2007. Challenges in adaptation of plant disease warning systems to new locations: re-appraisal of Billing's integrated system for predicting fire blight in a warm dry environment. Phytopathology 97:1036-1039. https://doi.org/10.1094/PHYTO-97-9-1036
  5. Campbell, C. L. and Madden, L. V. 1990. Introduction to plant disease epidemiology. Wiley, New York, USA. 532 pp.
  6. Cesaraccio, C., Spano, D., Snyder, R. L. and Duce, P. 2004. Chilling and forcing model to predict bud-burst of crop and forest species. Agric. For. Meteorol. 126:1-13. https://doi.org/10.1016/j.agrformet.2004.03.002
  7. Choi, D.-W., Kim, D.-C. and Lim, C.-R. 2018. Analysis of factors influencing cultivation area of apple cultivars. J. Korean Soc. Rural Plan. 24:25-31 (in Korean). https://doi.org/10.7851/ksrp.2018.24.3.025
  8. Gent, D. H., Mahaffee, W. F., McRoberts, N. and Pfender, W. F. 2013. The use and role of predictive systems in disease management. Annu. Rev. Phytopathol. 51:267-289. https://doi.org/10.1146/annurev-phyto-082712-102356
  9. Ham, H., Lee, K. J., Hong, S. J., Kong, H. G., Lee, M.-H., Kim, H.-R. and Lee, Y. H. 2020. Outbreak of fire blight of apple and pear and its characteristics in Korea in 2019. Res. Plant Dis. 26:239-249 (in Korean). https://doi.org/10.5423/RPD.2020.26.4.239
  10. Hattingh, M. J., Beer, S. V. and Lawson, E. W. 1986. Scanning electron microscopy of apple blossoms colonized by Erwinia amylovora and E. herbicola. Phytopathology 76:900-904. https://doi.org/10.1094/Phyto-76-900
  11. Kim, M.-S. and Yun, S.-C. 2018. MARYBLYT study for potential spread and prediction of future infection risk of fire blight on blossom of Singo pear in Korea. Res. Plant Dis. 24:182-192 (in Korean). https://doi.org/10.5423/RPD.2018.24.3.182
  12. Kim, S.-O., Chung, U., Kim, S.-H., Choi, I.-M. and Yun, J. I. 2009. The suitable region and site for 'Fuji' apple under the projected climate in South Korea. Korean J. Agric. For. Meteorol. 11:162-173 (in Korean). https://doi.org/10.5532/KJAFM.2009.11.4.162
  13. Kim, Y. E., Kim, J. Y., Noh, H. J., Lee, D. H., Kim, S. S. and Kim, S. H. 2019. Investigating survival of Ewrinia amylovora from fire blight-diseased apple and pear trees buried in soil as control measure. Korean J. Environ. Agric. 38:269-272 (in Korean). https://doi.org/10.5338/KJEA.2019.38.4.36
  14. Lightner, G. W. and Steiner, P. W. 1993. An update on version 4.1 of MARYBLYT computer program for predicting fire blight. Acta Hortic. 338:131-136. https://doi.org/10.17660/actahortic.1993.338.18
  15. Park, D. H., Lee, Y.-G., Kim, J.-S., Cha, J.-S. and Oh, C.-S. 2017. Current status of fire blight caused by Erwinia amylovora and action for its management in Korea. J. Plant Pathol. 99:59-63. https://doi.org/10.4454/jpp.v99i0.3918
  16. Park, D. H., Yu, J.-G., Oh, E.-J., Han, K.-S., Yea, M. C., Lee, S. J., Myung, I.-S., Shim, H. S. and Oh, C.-S. 2016. First report of fire blight disease on Asian pear caused by Erwinia amylovora in Korea. Plant Dis. 100:1946.
  17. Schroth, M. N., Thomson, S. V., Hildebrand, D. C. and Moller, W. J. 1974. Epidemiology and control of fire blight. Annu. Rev. Phytopathol. 12:389-412. https://doi.org/10.1146/annurev.py.12.090174.002133
  18. Steiner, P. W. 1990a. Predicting apple blossom infections by Erwinia amylovora using the Maryblyt model. Acta Hortic. 273:139-148. https://doi.org/10.17660/actahortic.1990.273.18
  19. Steiner, P. W. 1990b. Predicting canker, shoot and trauma blight phases of apple fire blight epidemics using the Maryblyt model. Acta Hortic. 273:149-158. https://doi.org/10.17660/actahortic.1990.273.19
  20. Steiner, P. W. and Lightner, G. 1996. Maryblyt, version 4.3, a predictive program for forecasting fire blight disease in apples and pears. Office of Technology Liaison, University of Maryland, College Park, MD, USA.
  21. The R Foundation. 2021. The R project for statistical computing. URL http://www.r-project.org/index.html [31 July 2021].
  22. Thomson, S. V., Schroth, M. N., Moller, W. J. and Reil, W. O. 1982. A forecasting model for fire blight of pear. Plant Dis. 66:576-579. https://doi.org/10.1094/PD-66-576
  23. Thomson, S. V. 1986. The role of the stigma in fire blight infections. Phytopathology 76:476-482. https://doi.org/10.1094/Phyto-76-476
  24. Thomson, S. V. 2000. Epidemiology of fire blight. In: Fire blight: the disease and its causative agent, Erwinia amylovora, ed. by J. L. Vanneste, pp. 9-36. CABI Publishing, Wallingford, UK.
  25. Turechek, W. W. and Biggs, A. R. 2015. Maryblyt v. 7.1 for Windows: an improved fire blight forecasting program for apples and pears. Plant Health Prog. 16:16-22. https://doi.org/10.1094/php-rs-14-0046
  26. van der Zwet, T. and Beer, S. V. 1999. Fire blight--its nature, prevention, and control: a practical guide to integrated disease management. U. S. Department of Agriculture, Washington, DC, USA. 83 pp.