Resultado final
A curated data set based on deliverables D42 and D44 comprising septoria in wheat downy mildew in grapes aphids in cereals and vegetables and three insects pests in vegetables For any pest crop interaction at least 3 years of data from at least 2 countries will be present The data set will be made available through WP3
DSS evaluated for economic and environmental benefits: weedsWe will evaluate the value of prediction in terms of economics and environment for DSSs related to weeds using data gathered in D46
DSS tested for validity: aphids and vegetable pestsThe phenology of insect pests predicted by DSS models from data on crop cultivar growth stage and weather temperature will be compared to observed insect phenology and the validity of predictions assessed
Data set for DSS evaluation collected: apple scab and potato late blightField data collated for apple scab in apple (>3 years, 3 countries) and potato late blight in potatoes (>3 years, 4 countries), together with concurrent weather data (assisted by WP2).
Project reports in agreement with ECReport: Impact of DDS on pest management and pesticide usage in EU
Section for report summarising the environmental and economic implications of implimentation of DSS in EU agriculture using scenarios of uptake to understand how differing levels of uptake will impact the cost of production as well as wider environmental impacts Analysis will be done using a combination of quantitative and qualativie information
Description of the general outline methods for DSS evaluation of the value of a predictionWe will develop systematic and generic methods to evaluate disease pest and weed DSS tools in terms of the value of prediction These methods focus on economic and environmental value of DSS The general method will be documented
DSS evaluated for economic and environmental benefits: aphids and vegetable pestsWe will evaluate the value of prediction in terms of economics and environment for DSSs related to aphids and vegetable pests using data gathered in D44
DSS evaluated for economic and environmental benefits: apple scab and potato late blightWe will evaluate the 'value of prediction' in terms of economics and environment for DSSs related to apple scab and potato late blight using data gathered in D4.1.
First country list with demonstration activities, number of visitors reachedIPM decisons will disseminate the results of the project through demonstrations of the platform This deliverable will be a report with an overview of these demonstrations per country and the number of visitors reached
Paper: On the methods related to value of predictionWrite papers on the method developed to quantify the value of DSS prediction and its application to case study DSSs
DSS tested for validity: septoria and wine downy mildewDisease epidemics predicted by DSS models from data on crop cultivar growth stage and weather temperature humidity will be compared to observed disease epidemics and the validity of predictions assessed
DSS tested for validity: weedsWe will parameterise and validate IPMwise for winter wheat in Greece Using data on weed abundance of species across seasons along with the relevant management information we will evaluate the WMSS predictions of changes in weed densities using data from across Europe
DSS evaluated for economic and environmental benefits: septoria and wine downy mildewWe will evaluate the value of prediction in terms of economics and environment for DSSs related to septoria and downy mildew using data gathered in D43
Data set for DSS validation collected: aphids and vegetable pestsField data collated for aphids in cereals and vegetables 3 years 5 countries and other insect pests in vegetables 3 pest species 3 years 5 countries together with concurrent weather data assisted by WP2
Data set for DSS validation collected: septoria and wine downy mildewField data collated for septoria in wheat (>3 years, 6 countries) and downy mildew in grapes (3 years, 2 countries), together with concurrent weather data (assisted by WP2).
Catalogue of DSS collated with details on inputs, outputs and functionalityAn updated and extended version of the ENDURE catalogue of DSS: Updated to current DSS and extended with information on which models are incorporated, model inputs and outputs, model logic and mathematics, and the empirical evidence supporting the models.
Scientific paper on interactions between end-users characteristics and structural-performance features of assessed DSSA model using advanced dataanalysis techniques will be developed associating statistically behavioural and environmental traits of the end users with their probability of acceptance or aversion to specific features of the DSS available The output will be written in the form of a scientific article targetting a high impact open access outlet
Data set for DSS validation collected: weedsField data collated for major arable weed species 3 years 5 countries together with available management data for example cultivation type crop rotation and herbicide application
Formats completed
Weather data repository and management API - production version"Data ""completed"". Bugs removed."
DSS validation method available to end-usersThe methods developed for value of prediction will be coded and made available to the end users of the platform
API for interaction with repository of model metadata - final version"Data ""completed"". Bugs removed."
Standard formats for model result outputFormats completed
Stakeholder map (stakeholder list with users) per countryIPM decisions will cooperate with stakeholders from the beginning. D6.1 will have a list of key stakeholders per country, identified by the project partners, by type of DSS and sectors they work for/in
A source code repository will be made available on the project platform This repository will contain all of the source code for all of the components used within the dashboards where it is possible to make the source code available Each set of source code will be accompanied by a text file containing a description of the component and how it works and the functions contained within the source code The repository will publish all of the available source code onto the web platform for the project so that it can be accessed by anoyone wishing to use it
DSS Adaptation Dashboard for farmers, advisors and interest groupsThe source code for webbased integration dashboard for farmers advisors and interest groups will have been written using the specification from D31 The source code for the web services suporting the dashboard will have been written D311 D313 The text for the dashboards and its accompanying help system will have been written The dashboard will have been tested to ensure that it is working correctly before being published on the project web platform for farmers advisors and other interested groups to use
DSS Comparison Dashboard for farmers, advisors and interest groupsThe source code for webbased comparison dashboard for farmers advisors and interest groups will have been written using the specification from D31 The source code for the web services suporting the dashboard will have been written D311 D313 The text for the dashboards and its accompanying help system will have been written The dashboard will have been tested to ensure that it is working correctly before being published on the project web platform for farmers advisors and other interested groups to use
DSS Integration dashboard for researchers and interest groupsThe scientific workflows framework will have been developed for selected datasources and DSS tools D37 D312 A webbased interface that allows the user to access the scientific workflows framework via a Python library D38 will have been developed and the source code for the webbased interface made available via the project web platform repository The interface will have been tested using selected DSS tools and data sources to ensure that the workflows and Python libraries are functioning as expected On succesful completion of the testing phase the webbased interfacee will be made available to researchers and interested groups via the project web platform
DSS Use Dashboard for farmers and advisorsThe source code for webbased dashboard for farmers and advisors will have been written following the specificaiton developed in D31 The source code for the web services suporting the dashboard will have been written D311 D313 The text for the dashboards and its accompanying help system will have been written The dashboard will have been tested to ensure that it is working correctly before being published on the project web platform for farmerS abd advisors to use
Web services providing access to dashboards source code and key information on DSS tools and dataUsing the description of web services required from D31 the source code for the web services that manage access to the dashboards and handle the user requests initiated via the dashboards will have been written The web service code will have been tested using unit testing and via exposure of the dashboards to selected project partners and stakeholders The source code will have been placed in the project repository along with appropriate documentation describing the functions that the code provides and how to use the code
Python-based libraries of tools and data sourcesA set of wrappers for the data sources and DSS tools listed in the web catalogue D312 will be developed in the Python programming language The source code of the wrappers along with accompanying metadata and information about what the wrappers do and how they integrate into the scientific workflows framework will be placed in the source code repository of the project web platform and made freely available to platform users
A web-based portal for the platform with user authenticationA design for the website for the project will be developed in consultation with the project partners and key stakeholders. The source code for the website will be written in a high level programming language and will include user authentication via usernames and passwords to access the website. All of the intial content of the website will have been written, including a description of the project and key information about each workpackage and the anticipated deliverables.
Scientific workflows framework for integration of DSS tools, data manipulation algorithms and data sourcesA decomposition scheme will be developed based on the OpenAlea scheme used for plantpathogen structural models The scheme is a tool to break down the existing DSS tools into macro components that can be combined together to provide novel DSS tools A full description of the decomposition scheme will be produced together with a guide on how to use the scientific workflow framework to build novel DSS
Library of data manipulation algorithms"For the core data manipulations identified from WP2, a set of algorithms will have been identified using a literature search. The algorithms will have been written in a high level programming language (C#) and tested using unit testing. The source code will then be placed into the repository for the project and the algorithms published via the web platform. "
Data management plan agreement will be drawn up in discussion with the PME and other relevant project participants. This will detail how data will be collected, stored, and accessed in line with the GDPR. This will be a live document updated over the course of the project to reflect any changes or additions.
Publicaciones
Autores:
Cyrille Ahmed Midingoyi, Christophe Pradal, Ioannis N Athanasiadis, Marcello Donatelli, Andreas Enders, Davide Fumagalli, Frédérick Garcia, Dean Holzworth, Gerrit Hoogenboom, Cheryl Porter, Hélène Raynal, Peter Thorburn, Pierre Martre
Publicado en:
in silico Plants, Edición 2/1, 2020, ISSN 2517-5025
Editor:
Oxford Academic
DOI:
10.1093/insilicoplants/diaa007
Autores:
Lise Nistrup Jørgensen, Niels Matzen, Andrea Ficke, Björn Andersson, Marja Jalli, Antanas Ronis, Ghita C. Nielsen, Patrik Erlund & Annika Djurle
Publicado en:
Acta Agriculturae Scandinavica, Section B — Soil & Plant Science, Edición 71, 2021, Página(s) 247-260, ISSN 1651-1913
Editor:
Taylor & Francis Online
DOI:
10.1080/09064710.2021.1884742
Autores:
Sébastien Levionnois, Christophe Pradal, Christian Fournier, Jonathan Sanner, and Corinne Robert
Publicado en:
Phytopathology, 2023, ISSN 0031-949X
Editor:
American Phytopathological Society
DOI:
10.1094/phyto-06-22-0197-r
Autores:
Jurij Marinko, Aneta Ivanovska, Martin Marzidovšek, Mark Ramsden & Marko Debeljak
Publicado en:
International Journal of Pest Management, 2023, ISSN 0967-0874
Editor:
Taylor & Francis
DOI:
10.1080/09670874.2023.2244912
Autores:
Lise Nistrup Jørgensen, Niels Matzen, Andrea Ficke, Ghita C. Nielsen, Marja Jalli, Antanas Ronis, Björn Andersson, Annika Djurle
Publicado en:
European Journal of Plant Pathology, Edición 157/3, 2020, Página(s) 599-613, ISSN 0929-1873
Editor:
Kluwer Academic Publishers
DOI:
10.1007/s10658-020-02025-6
Autores:
Björn Andersson, Annika Djurle, Jens Erik Ørum, Marja Jalli, Antanas Ronis, Andrea Ficke & Lise Nistrup Jørgensen
Publicado en:
Agronomy for Sustainable Development, Edición 42, 2022, ISSN 1773-0155
Editor:
Springer
DOI:
10.1007/s13593-022-00767-7
Autores:
Marja Jalli, Janne Kaseva, Björn Andersson, Andrea Ficke, Lise Nistrup-Jørgensen, Antanas Ronis, Timo Kaukoranta, Jens-Erik Ørum & Annika Djurle
Publicado en:
European Journal of Plant Pathology, Edición 158, 2020, Página(s) 315-333, ISSN 1573-8469
Editor:
Springer
DOI:
10.1007/s10658-020-02075-w
Autores:
Daniel Leybourne, Mark Ramsden, Sacha White, Ruhing Wang, He Huang, Chengjun Xie
Publicado en:
Advances in understanding insect pests affecting wheat and other cereals, Edición 2 May 2023, 2023
Editor:
Burleigh Dodds Scientific Publishing
Autores:
Mark Ramsden, Samuel Telling, Daniel J. Leybourne, Natasha Alonso, Sacha White, Nikos Georgantzis
Publicado en:
Advances in monitoring of native and invasive insect pests of crops, Edición 25 April 2023, 2023, ISBN 9781801461078
Editor:
Burleigh Dodds Science Publishing
Autores:
Niels Holst
Publicado en:
Decision Support Systems for Weed Management, 2020, Página(s) 3-23, ISBN 978-3-030-44401-3
Editor:
Springer International Publishing
DOI:
10.1007/978-3-030-44402-0_1
Autores:
Mark Ramsden, Aoife O Driscoll
Publicado en:
In book: Improving integrated pest management in horticulture, 2022, ISBN 9781786767530
Editor:
Burleigh Dodds Science Publishing Limited
DOI:
10.19103/as.2021.0095.07
Autores:
Jørgensen, Lise N.; Heick, Thies M.; Abuley, Isaac K.; Mathiassen, Solvejg K.; Jensen, Peter K.; Kristjansen, Helene S.; Hartvig, Peter
Publicado en:
DCA Report No. 167, Edición 2, 2020
Editor:
AARHUS University - Danish Center for Food and Agriculture
DOI:
10.5281/zenodo.7789025
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