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MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea

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 m...

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Autores principales: Kim, Hyo-suk, Jo, Jung-hee, Kang, Wee Soo, Do, Yun Su, Lee, Dong Hyuk, Ahn, Mun-Il, Park, Joo Hyeon, Park, Eun Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Plant Pathology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901243/
https://www.ncbi.nlm.nih.gov/pubmed/31832039
http://dx.doi.org/10.5423/PPJ.OA.09.2019.0236
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author Kim, Hyo-suk
Jo, Jung-hee
Kang, Wee Soo
Do, Yun Su
Lee, Dong Hyuk
Ahn, Mun-Il
Park, Joo Hyeon
Park, Eun Woo
author_facet Kim, Hyo-suk
Jo, Jung-hee
Kang, Wee Soo
Do, Yun Su
Lee, Dong Hyuk
Ahn, Mun-Il
Park, Joo Hyeon
Park, Eun Woo
author_sort Kim, Hyo-suk
collection PubMed
description 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 (L(day)), maximum hourly rainfall (P(max)) and average daily maximum wind speed (W(avg)) during a rain event were most appropriate in describing variations in air-borne spore catches during SLP (S(i)) in 2013. The ASM, Ŝ(i) = 30.280+5.860×L(day)×P(max)–2.123×L(day)×P(max)×W(avg) 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(i)) and the daily infection rate (R(i)). The IRM, R̂(i) = 0.039+0.041×Ŝ(i), 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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spelling pubmed-69012432019-12-12 MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea Kim, Hyo-suk Jo, Jung-hee Kang, Wee Soo Do, Yun Su Lee, Dong Hyuk Ahn, Mun-Il Park, Joo Hyeon Park, Eun Woo Plant Pathol J Research Article 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 (L(day)), maximum hourly rainfall (P(max)) and average daily maximum wind speed (W(avg)) during a rain event were most appropriate in describing variations in air-borne spore catches during SLP (S(i)) in 2013. The ASM, Ŝ(i) = 30.280+5.860×L(day)×P(max)–2.123×L(day)×P(max)×W(avg) 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(i)) and the daily infection rate (R(i)). The IRM, R̂(i) = 0.039+0.041×Ŝ(i), 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. Korean Society of Plant Pathology 2019-12 2019-12-12 /pmc/articles/PMC6901243/ /pubmed/31832039 http://dx.doi.org/10.5423/PPJ.OA.09.2019.0236 Text en © The Korean Society of Plant Pathology This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Kim, Hyo-suk
Jo, Jung-hee
Kang, Wee Soo
Do, Yun Su
Lee, Dong Hyuk
Ahn, Mun-Il
Park, Joo Hyeon
Park, Eun Woo
MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
title MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
title_full MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
title_fullStr MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
title_full_unstemmed MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
title_short MBCAST: A Forecast Model for Marssonina Blotch of Apple in Korea
title_sort mbcast: a forecast model for marssonina blotch of apple in korea
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901243/
https://www.ncbi.nlm.nih.gov/pubmed/31832039
http://dx.doi.org/10.5423/PPJ.OA.09.2019.0236
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