Based on pathogen biology and weather data, DSS support decision-making by the farmers and allow to determine the optimal timing of spray interventions, leading to better efficacy of the products

Perazzolli, Michele

Schärer, Hans-Jakob

Treutwein, Jonas

Organic Eprints

   DSS TO OPTIMISE EFFICACY OF COPPER ALTERNATIVES   www.relacs-project.eu  Decision support systems to optimise the efficacy of novel copper alternatives Problem  Fungal diseases can cause significant yield losses. Fungicides used in organic farming generally have a contact mode of action. Such contact fungicides need to be applied shortly before an infection event in order to have the highest effi-cacy. Solution  Decision support systems (DSS) are tools to allow optimal timing of fungicide application. DSS have been developed for various crop-pathogen combinations, e.g., apple scab, grapevine downy mildew, among others. Outcome  Based on pathogen biology and weather data, DSS support decision-making by the farmers and allow to determine the optimal timing of spray interventions, leading to better effi-cacy of the products. Practical recommendations  Different types of DSS are available. Some provide advice on the timing of copper spraying and the quantity of copper needed. Others (i.e., tactical models) are designed to provide farmers with yes/no advice (e.g. treatment is needed or it is not worth the cost), or the model outputs are giving risks of infection (e.g. no risk, low, intermediate, high risk). Some models, e.g. RIMpro (Fig. 1), illustrate the biological processes and visualise the risk of infection. Some DSS are interactive, allowing farmers to enter the basic characteristics of their crops; others work independently, displaying a prediction for the risk of infection (e.g. Agrometeo, Fig. 2). In many countries and regions, advisory systems provide access to appropriate DSS according to the needs of farmers. Local advisory services can be contacted for information and support. Complete solutions for local (private) collection of weather data and integrated disease forecast models are also available (e.g. iMe-tos®, Sencrop).       Figure 1: Graph of the RIMpro output for simulation of downy mildew infec-tions and forecast of infections. Rain and leaf wetness (1, 2), de-velopment of the patho-gen (3, 4, 5), risk of in-fection (6) and develop-ment of the epidemics (8, 9, 10) are displayed. (Sources: https://www.rimpro.eu, https://www.bioaktuell.ch/pflanzenschutz/prognosen/plasmopara.html)  Applicability box  Input used × Copper ☐ Mineral oil ☐ Fertilisers  ☐ Anthelmintics ☐ Antibiotics ☐ Vitamins Geographical coverage  Global Application time During the crop growing season Required time  Regular check of provisions and forecasts by the DSS  Period of impact Current crop   Equipment Smartphone or computer, internet access  Best in Grapevine, apple, potato. DSS is available for an increasing number of crop-disease combinations, as well as for pests    PRACTICE ABSTRACT    RELACS has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 773431.The information contained in this communication only reflects the author’s view.   www.relacs-project.eu   Figure 2: Graph of the Agrometeo output to indicate risk of downy mildew infections. Risk is indicated with numbers based on model calculations and colours (green = no risk, light pink = low risk, dark pink = intermediate risk, dark red = high risk) (Source: https://agro-meteo.ch/de/weinbau/falscher-rebenmehltau) On-farm application   System approach Copper alternatives based on natural substances are often degrade faster or show less rain fastness than chemical products. To achieve the best efficacy of these novel copper alternatives, it is crucial to find the best timing for their application. The forecast information of DSS allow such an optimal timing.  Evaluation  The use of DSS can improve the efficacy of new copper alternatives based on natural substances. DSS may reduce fungicide use by half compared to calendar-based strategies without increasing disease risk.  Further information   Further reading Agrometeo: decision support tool for pest prognosis and risk assessment: https://organic-farmknowledge.org/tool/30592  Weblinks  • Forecast models, weather data and monitoring information for pests and diseases in Switzerland: https://agrome-teo.ch/   • Forecast models, weather data and monitoring for grapevine production https://vitimeteo.de/   • Decision support system for the sustainable management of pests and diseases in fruit and grape production: https://www.rimpro.eu • Information system for integrated plant protection (DE). Disease forecast models and monitoring data for pests and diseases: https://www.isip.de/ Check the Farm Knowledge Platform for more practical recommendations. About this practice abstract and RELACS Publishers:  Research Institute of Organic Agriculture FiBL   Ackerstrasse 113, Postfach 219, CH-5070 Frick Phone: +41 62 865 72 72, info.suisse@fibl.org, www.fibl.org IFOAM Organics Europe Rue du Commerce 124, BE-1000 Brussels Phone: +32 2 280 12 23, info@organicseurope.bio, www.organ-icseurope.bio Fondazione Edmund Mach di San Michele all'Adige Via Edmund Mach, 1, IT-38010 San Michele All'adige Phone: +39 046 161 5111, direzione.generale@fmach.it, www.fmach.it Trifolio-M GmBH Dr.-Hans-Wilhelmi-Weg 1, DE-35633 Lahnau Phone: +49 6441 20 97 70, info@trifolio-m.de, https://www.trifolio-m.de Authors: Hans-Jakob Schärer, Michele Perazolli, Jonas Treutwein Editors: Joelle Herforth-Rahmé, Mathilde Calmels, Lauren Dietemann, Bram Moeskops RELACS: 'Replacement of Contentious Inputs in Organic Farming Systems' (RELACS) builds on results of previous research projects and takes far-ad-vanced solutions forward. As a system approach to sustainable agriculture, organic farming aims to effectively manage ecological processes whilst low-ering dependence on off-farm inputs. The RELACS partners will evaluate solutions to further reduce the use of external inputs and, if needed, develop and adopt cost-efficient and environmentally safe tools and technologies. Project website: www.relacs-project.eu  Social media: Facebook (RELACSeu) & Twitter (@RELACSeu) © 2022  

Decision support systems to optimise the efficacy of novel copper alternatives

https://orgprints.org/id/eprint/45677/1/schaerer-etal-RELACS_PA_20_DSS_final.pdf

Decision support systems to optimise the efficacy of novel copper alternatives

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