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논문 기본 정보

자료유형
학술저널
저자정보
Hyo-suk Kim (Seoul National University) Jung-hee Jo (Seoul National University) Wee Soo Kang (Rural Development Administration) Yun Su Do (Rural Development Administration) Dong Hyuk Lee (National Institute of Horticultural & Herbal Science) Mun-Il Ahn (EPINET Corporation) Joo Hyeon Park (EPINET Corporation) Eun Woo Park (Seoul National University)
저널정보
한국식물병리학회 The Plant Pathology Journal The Plant Pathology Journal 제35권 제6호
발행연도
2019.12
수록면
585 - 597 (13page)

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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 days. Of 13 rain-related weather variables, number of rainy days with rainfall ≥ 0.5 mm per day (L<SUB>day</SUB>), maximum hourly rainfall (P<SUB>max</SUB>) and average daily maximum wind speed (W<SUB>avg</SUB>) during a rain event were most appropriate in describing variations in airborne spore catches during SLP (S<SUB>i</SUB>) in 2013. The ASM, Ŝ<SUB>i</SUB> = 30.280+5.860×L<SUB>day</SUB>×P<SUB>max</SUB>-2.123×L<SUB>day</SUB>×P<SUB>max</SUB>×W<SUB>avg</SUB><SUB></SUB> 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 (Ŝ<SUB>i</SUB>) and the daily infection rate (R<SUB>i</SUB>). The IRM, Ȓ<SUB>i</SUB> = 0.039+0.041×Ŝ<SUB>i</SUB>, 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.

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Materials and Methods
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