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Development and evaluation of a decision prediction tool for the reduction of fungicide applications for the control of strawberry powdery mildew epidemics. / Liu, Bo; Hall, Avice; Wileman, H J ; Dodgson, Jolyon; Mutasa-Gottgens, Euphemia.

In: PLoS ONE, 16.07.2021.

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@article{d81b7f5281c04f6f8adcd0227ad327eb,
title = "Development and evaluation of a decision prediction tool for the reduction of fungicide applications for the control of strawberry powdery mildew epidemics",
abstract = "Strawberry powdery mildew (Podosphaera aphanis) causes serious losses in UK crops, potentially reducing yields by as much as 70%. Consequently, conventional fungicide application programmes tend to recommend a prophylactic approach using insurance sprays, risking the development of fungicide insensitivity and requiring careful management relative to harvest periods to avoid residual fungicides on harvested fruit. This paper describes the development of a prediction system to guide the control of P. aphanis by the application of fungicides only when pathogen infection and disease progression are likely. The system was developed over a 15-year period on commercial farms starting with its establishment, validation and then deployment to strawberry growers. This involved three stages: 1. Identification and validation of parameters for inclusion in the prediction system (2004-2008). 2. Development of the prediction system in compact disc format (2009-2015). 3. Development and validation of the prediction system in a web-based format and cost-benefit analysis (2016-2020). The prediction system was based on the temporal accumulation of conditions (temperature and relative humidity) conducive to the development of P. aphanis, which sporulates at 144 accumulated disease-conducive hours. Sensitivity analysis was performed to refine the prediction system parameters. Field validation of the results demonstrated that to effectively control disease, the application of fungicides was best done between 125 and 144 accumulated hours of disease-conducive conditions. A cost-benefit analysis indicated that, by comparison with the number and timing of fungicide applications in conventional insurance disease control programmes, the prediction system enabled good disease control with significantly fewer fungicide applications (between one and four sprays less) (df=7, t=7.6, p=0.001) and reduced costs (savings between £35-£493/hectare) (df=7, t=4.0, p=0.01) for the growers. ",
keywords = "Rule-based prediction system ∙ decision support system DSS ∙ field based ∙ real-time, web-based ∙ optimise fungicide sprays ∙ cost-benefit analysis ∙ Podosphaera aphanis",
author = "Bo Liu and Avice Hall and Wileman, {H J} and Jolyon Dodgson and Euphemia Mutasa-Gottgens",
year = "2021",
month = jul,
day = "16",
language = "English",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",

}

RIS

TY - JOUR

T1 - Development and evaluation of a decision prediction tool for the reduction of fungicide applications for the control of strawberry powdery mildew epidemics

AU - Liu, Bo

AU - Hall, Avice

AU - Wileman, H J

AU - Dodgson, Jolyon

AU - Mutasa-Gottgens, Euphemia

PY - 2021/7/16

Y1 - 2021/7/16

N2 - Strawberry powdery mildew (Podosphaera aphanis) causes serious losses in UK crops, potentially reducing yields by as much as 70%. Consequently, conventional fungicide application programmes tend to recommend a prophylactic approach using insurance sprays, risking the development of fungicide insensitivity and requiring careful management relative to harvest periods to avoid residual fungicides on harvested fruit. This paper describes the development of a prediction system to guide the control of P. aphanis by the application of fungicides only when pathogen infection and disease progression are likely. The system was developed over a 15-year period on commercial farms starting with its establishment, validation and then deployment to strawberry growers. This involved three stages: 1. Identification and validation of parameters for inclusion in the prediction system (2004-2008). 2. Development of the prediction system in compact disc format (2009-2015). 3. Development and validation of the prediction system in a web-based format and cost-benefit analysis (2016-2020). The prediction system was based on the temporal accumulation of conditions (temperature and relative humidity) conducive to the development of P. aphanis, which sporulates at 144 accumulated disease-conducive hours. Sensitivity analysis was performed to refine the prediction system parameters. Field validation of the results demonstrated that to effectively control disease, the application of fungicides was best done between 125 and 144 accumulated hours of disease-conducive conditions. A cost-benefit analysis indicated that, by comparison with the number and timing of fungicide applications in conventional insurance disease control programmes, the prediction system enabled good disease control with significantly fewer fungicide applications (between one and four sprays less) (df=7, t=7.6, p=0.001) and reduced costs (savings between £35-£493/hectare) (df=7, t=4.0, p=0.01) for the growers.

AB - Strawberry powdery mildew (Podosphaera aphanis) causes serious losses in UK crops, potentially reducing yields by as much as 70%. Consequently, conventional fungicide application programmes tend to recommend a prophylactic approach using insurance sprays, risking the development of fungicide insensitivity and requiring careful management relative to harvest periods to avoid residual fungicides on harvested fruit. This paper describes the development of a prediction system to guide the control of P. aphanis by the application of fungicides only when pathogen infection and disease progression are likely. The system was developed over a 15-year period on commercial farms starting with its establishment, validation and then deployment to strawberry growers. This involved three stages: 1. Identification and validation of parameters for inclusion in the prediction system (2004-2008). 2. Development of the prediction system in compact disc format (2009-2015). 3. Development and validation of the prediction system in a web-based format and cost-benefit analysis (2016-2020). The prediction system was based on the temporal accumulation of conditions (temperature and relative humidity) conducive to the development of P. aphanis, which sporulates at 144 accumulated disease-conducive hours. Sensitivity analysis was performed to refine the prediction system parameters. Field validation of the results demonstrated that to effectively control disease, the application of fungicides was best done between 125 and 144 accumulated hours of disease-conducive conditions. A cost-benefit analysis indicated that, by comparison with the number and timing of fungicide applications in conventional insurance disease control programmes, the prediction system enabled good disease control with significantly fewer fungicide applications (between one and four sprays less) (df=7, t=7.6, p=0.001) and reduced costs (savings between £35-£493/hectare) (df=7, t=4.0, p=0.01) for the growers.

KW - Rule-based prediction system ∙ decision support system DSS ∙ field based ∙ real-time, web-based ∙ optimise fungicide sprays ∙ cost-benefit analysis ∙ Podosphaera aphanis

M3 - Article

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

ER -