The Plant Pathology Journal

The Korean Society of Plant Pathology (한국식물병리학회)
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MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea

  • Kim, Hyo-suk (Department of Agricultural Biotechnology, Seoul National University) ;
  • Jo, Jung-hee (Department of Agricultural Biotechnology, Seoul National University) ;
  • Kang, Wee Soo (Department of Agro-food Safety and Crop Protection, National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Do, Yun Su (Research Policy Bureau, Rural Development Administration) ;
  • Lee, Dong Hyuk (Apple Research Institute, National Institute of Horticultural & Herbal Science) ;
  • Ahn, Mun-Il (EPINET Corporation) ;
  • Park, Joo Hyeon (EPINET Corporation) ;
  • Park, Eun Woo (Department of Agricultural Biotechnology, Seoul National University)
  • Received : 2019.09.05
  • Accepted : 2019.09.19
  • Published : 2019.12.01
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Abstract

A disease forecast model for Marssonina blotch of apple was developed based on field observations on airborne spore catches, weather conditions, and disease incidence in 2013 and 2015. The model consisted of the airborne spore model (ASM) and the daily infection rate model (IRM). It was found that more than 80% of airborne spore catches for the experiment period was made during the spore liberation period (SLP), which is the period of days of a rain event plus the following 2 days. Of 13 rain-related weather variables, number of rainy days with rainfall ≥ 0.5 mm per day (Lday), maximum hourly rainfall (Pmax) and average daily maximum wind speed (Wavg) during a rain event were most appropriate in describing variations in airborne spore catches during SLP (Si) in 2013. The ASM, Ŝi = 30.280+5.860×Lday×Pmax-2.123×Lday×Pmax×Wavg was statistically significant and capable of predicting the amount of airborne spore catches during SLP in 2015. Assuming that airborne conidia liberated during SLP cause leaf infections resulting in symptom appearance after 21 days of incubation period, there was highly significant correlation between the estimated amount of airborne spore catches (Ŝi) and the daily infection rate (Ri). The IRM, ${\hat{R}}_i$ = 0.039+0.041×Ŝi, was statistically significant but was not able to predict the daily infection rate in 2015. No weather variables showed statistical significance in explaining variations of the daily infection rate in 2013.

Keywords

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