The Plant Pathology Journal

한국식물병리학회 (The Korean Society of Plant Pathology)
권호 표지
DOI QR코드

DOI QR Code

Improvement of Fire Blight Blossom Infection Control Using Maryblyt in Korean Apple Orchards

  • Kyung-Bong Namkung (Department of Phamaceutical Engineering and Biotechnology, Sunmoon University) ;
  • Sung Chul Yun (Department of Phamaceutical Engineering and Biotechnology, Sunmoon University)
  • 투고 : 2023.08.08
  • 심사 : 2023.09.12
  • 발행 : 2023.10.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

After transitioning from periodic to model-based control policy for fire blight blossom infection, it is crucial to provide the timing of field application with easy and accurate information. To assess the risk of blossom infection, Maryblyt was employed in 31 sites across apple-producing regions nationwide, including areas prone to fire blight outbreaks, from 2021 to 2023. In 2021 and 2023, two and seven sites experienced Blossom Infection Risk-Infection warning occurrences among 31 sites, respectively. However, in 2022, most of the sites observed Blossom Infection Risk-Infection from April 25 to 28, highlighting the need for blossom infection control. For the comparison between the two model-based control approaches, we established treatment 1, which involved control measures according to the Blossom Infection Risk-Infection warning and treatment 2, aimed at maintaining the Epiphytic Infection Potential below 100. The analysis of control values between these treatments revealed that treatment 2 was more effective in reducing Blossom Infection Risk-Infection and the number of days with Epiphytic Infection Potential above 100, with respective averages of 95.6% and 93.0% over the three years. Since 2022, the implementation of the K-Maryblyt system and the deployment of Automated Weather Stations capable of measuring orchard weather conditions, with an average of 10 stations per major apple fire blight county nationwide, have taken place. These advancements will enable the provision of more accurate and timely information for farmers based on fire blight models in the future.

키워드

과제정보

This work was supported by the Cooperative Research Program for Agriculture Science & Technology Development (Project No. RS-2020-RD009731) of the Rural Development Administration of the Republic of Korea.

참고문헌

  1. Ahn, M.-I. and Yun, S. C. 2021. Application of the Maryblyt model for the infection of fire blight on apple trees at Chungju, Jecheon, and Eumsung during 2015-2020. Plant Pathol. J. 37:543-554. https://doi.org/10.5423/PPJ.OA.07.2021.0120
  2. Biggs, A. R., Tureckek, W. W. and Gottwald, T. R. 2008. Analysis of fire blight shoot infection epidemics on apple. Plant Dis. 92:1349-1356. https://doi.org/10.1094/PDIS-92-9-1349
  3. Billing, E. 1996. BIS95, an improved approach to fire blight risk assessment. Acta Hortic. 411: 121-126. https://doi.org/10.17660/ActaHortic.1996.411.26
  4. Billing, E. 1999. Fire blight risk assessment: Billing's Integrated System (BIS) and its evaluation. Acta Hortic. 489:399-406. https://doi.org/10.17660/ActaHortic.1999.489.69
  5. Bonn, W. G. and Leuty, T. 1993. An assessment of the MARYBLYT computer program for the prediction of fire blight in Ontario, Canada. Acta Hortic. 338:145-152. https://doi.org/10.17660/ActaHortic.1993.338.20
  6. Giayetto, A. and Rossini, M. 2011. Prediction of symptoms occurrence of fire blight (Erwinia amylovora) by the MARYBLYT program in Rio Negro, Argentina. Acta Hortic. 909:517-520. https://doi.org/10.17660/ActaHortic.2011.909.61
  7. Gouk, S. C., Bedford, R. J., Hutchings, S. O., Cole, L. and Voyle, M. D. 1996. Evaluation of the MARYBLYT model for predicting fire blight blossom infection in New Zealand. Acta Hortic. 411:109-116. https://doi.org/10.17660/ActaHortic.1996.411.24
  8. Gusberti, M., Klemm, U., Meier, M. S., Maurhofer, M. and Hunger-Glaser, I. 2015. Fire blight control: the struggle goes on. A comparison of different fire blight control methods in Switzerland with respect to bio safety, efficacy and duration. Int. J. Envion. Res. Public Health 12:11422-11447. https://doi.org/10.3390/ijerph120911422
  9. Ham, H., Lee, Y.-K., Kong, H. K., Hong, S. J., Lee, K. J., Oh, G.-R., Lee, M.-H. and Lee, Y. H. 2020. Outbreak of fire blight of apple and Asian pear in 2015-2019 in Korea. Res. Plant Dis. 26:222-228 (in Korean). https://doi.org/10.5423/RPD.2020.26.4.222
  10. Johnson, K. B. and Stockwell, V. O. 1998. Management of fire blight: a case study in microbial ecology. Annu. Rev. Phytopathol. 36:227-248. https://doi.org/10.1146/annurev.phyto.36.1.227
  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. H., Ryu, S.-H., Yun, B., Cho, K. H., Cho, S.-Y. and Park, J. G. 2023. Phytotoxicity by continous spraying of fruit fire blight disinfectant during growing season of apple and pear. Korean J. Plant Res. 36:100-106 (in Korean).
  13. 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
  14. Myung, I.-S., Lee, J.-Y., Yun, M.-J., Lee, Y.-H., Lee, Y.-K., Park, D.-H. and Oh, C.-S. 2016. Fire blight of apple, caused by Erwinia amylovora, a new disease in Korea. Plant Dis. 100:1774.
  15. Namkung, K.-B., Ahn, M.-I. and Yun, S.-C. 2022. Validation of K-Maryblyt models for blossom blight control on apple and pear trees. In: The 2022 Fall Conference, p. 168. The Korean Society of Plant Pathology, Seoul, Korea.
  16. Namkung, K.-B. and Yun, S.-C. 2022. A Maryblyt study to apply integrated control of fire blight of pears in Korea. Korean J. Agric. For. Meteorol. 24:305-317.
  17. Palacio-Bielsa, A., Lopez-Quilez, A., Llorente, I., Ruz, L., Lopez, M. M. and Cambra, M. A. 2012. Criteria for efficient prevention of dissemination and successful eradication of Erwinia amylovora (the cause of fire blight) in Aragon, Spain. Phytopathol. Mediterr. 51:505-518.
  18. 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.
  19. Smith, T. J. 1993. A predictive model for forecasting fire blight of pear and apple in Washington State. Acta Hortic. 338:153-160. https://doi.org/10.17660/ActaHortic.1993.338.21
  20. Steiner, P. W. 2000. Integrated orchard and nursery management for the control of fire blight. In: Fire blight: the disease and its causative agent, Erwinia amylovora, ed. by J. L. Vanneste, pp. 339-358. CABI Publishing, Wallingford, UK.
  21. Steiner, P. W. 1990. 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
  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. 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
  24. Van der Zwet, T. and Lightner, G. W. 1993. Efficacy of the MARYBLYT forecasting system to predict blossom blight in West Virginia (1984-1992). Acta Hortic. 338:137-144. https://doi.org/10.17660/ActaHortic.1993.338.19
  25. Yang, H. J., Ahn, M. I., Yun, S. C. Namkung, K. B., Kim, S. K., Park, E. W. and Lee, Y. H. 2022. Development of customized Fireblight prediction model K-MARYBLYT in Korea (Report No. I-23). In: The 2022 KSPP Spring Conference, pp. 88-89. The Korean Society of Plant Pathology, Seoul, Korea.