POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits

A weather-based simulation model, called Powdery Mildew of Cucurbits Simulation (POMICS), was constructed to predict fungicide application scheduling to manage powdery mildew of cucurbits. The model was developed on the principle that conditions favorable for Podosphaera xanthii, a causal pathogen o...

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Published in:Phytopathology
Main Author: Sapak Z.; Salam M.U.; Minchinton E.J.; MacManus G.P.V.; Joyce D.C.; Galea V.J.
Format: Article
Language:English
Published: American Phytopathological Society 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027576222&doi=10.1094%2fPHYTO-11-16-0413-R&partnerID=40&md5=f9b84c84f83542811dd4614ca6f9051d
id 2-s2.0-85027576222
spelling 2-s2.0-85027576222
Sapak Z.; Salam M.U.; Minchinton E.J.; MacManus G.P.V.; Joyce D.C.; Galea V.J.
POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
2017
Phytopathology
107
9
10.1094/PHYTO-11-16-0413-R
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027576222&doi=10.1094%2fPHYTO-11-16-0413-R&partnerID=40&md5=f9b84c84f83542811dd4614ca6f9051d
A weather-based simulation model, called Powdery Mildew of Cucurbits Simulation (POMICS), was constructed to predict fungicide application scheduling to manage powdery mildew of cucurbits. The model was developed on the principle that conditions favorable for Podosphaera xanthii, a causal pathogen of this crop disease, generate a number of infection cycles in a single growing season. The model consists of two components that (i) simulate the disease progression of P. xanthii in secondary infection cycles under natural conditions and (ii) predict the disease severity with application of fungicides at any recurrent disease cycles. The underlying environmental factors associated with P. xanthii infection were quantified from laboratory and field studies, and also gathered from literature. The performance of the POMICS model when validated with two datasets of uncontrolled natural infection was good (the mean difference between simulated and observed disease severity on a scale of 0 to 5 was 0.02 and 0.05). In simulations, POMICS was able to predict high- and low-risk disease alerts. Furthermore, the predicted disease severity was responsive to the number of fungicide applications. Such responsiveness indicates that the model has the potential to be used as a tool to guide the scheduling of judicious fungicide applications. © 2017 The American Phytopathological Society.
American Phytopathological Society
0031949X
English
Article
All Open Access; Hybrid Gold Open Access
author Sapak Z.; Salam M.U.; Minchinton E.J.; MacManus G.P.V.; Joyce D.C.; Galea V.J.
spellingShingle Sapak Z.; Salam M.U.; Minchinton E.J.; MacManus G.P.V.; Joyce D.C.; Galea V.J.
POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
author_facet Sapak Z.; Salam M.U.; Minchinton E.J.; MacManus G.P.V.; Joyce D.C.; Galea V.J.
author_sort Sapak Z.; Salam M.U.; Minchinton E.J.; MacManus G.P.V.; Joyce D.C.; Galea V.J.
title POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
title_short POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
title_full POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
title_fullStr POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
title_full_unstemmed POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
title_sort POMICS: A simulation disease model for timing fungicide applications in management of Powdery Mildew of Cucurbits
publishDate 2017
container_title Phytopathology
container_volume 107
container_issue 9
doi_str_mv 10.1094/PHYTO-11-16-0413-R
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027576222&doi=10.1094%2fPHYTO-11-16-0413-R&partnerID=40&md5=f9b84c84f83542811dd4614ca6f9051d
description A weather-based simulation model, called Powdery Mildew of Cucurbits Simulation (POMICS), was constructed to predict fungicide application scheduling to manage powdery mildew of cucurbits. The model was developed on the principle that conditions favorable for Podosphaera xanthii, a causal pathogen of this crop disease, generate a number of infection cycles in a single growing season. The model consists of two components that (i) simulate the disease progression of P. xanthii in secondary infection cycles under natural conditions and (ii) predict the disease severity with application of fungicides at any recurrent disease cycles. The underlying environmental factors associated with P. xanthii infection were quantified from laboratory and field studies, and also gathered from literature. The performance of the POMICS model when validated with two datasets of uncontrolled natural infection was good (the mean difference between simulated and observed disease severity on a scale of 0 to 5 was 0.02 and 0.05). In simulations, POMICS was able to predict high- and low-risk disease alerts. Furthermore, the predicted disease severity was responsive to the number of fungicide applications. Such responsiveness indicates that the model has the potential to be used as a tool to guide the scheduling of judicious fungicide applications. © 2017 The American Phytopathological Society.
publisher American Phytopathological Society
issn 0031949X
language English
format Article
accesstype All Open Access; Hybrid Gold Open Access
record_format scopus
collection Scopus
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