Methods for IPM: advances in the methodological workpackage of PURE

Aubertot Jean-Noël, Holst N., Messéan Antoine, Hennen W., Langrel S., Angevin Frédérique, Bockstaller Christian, Bout Alexandre, Buurman Peter, Daehmlow D., Ernst D., Fortino G., Golla B., Grechi Isabelle, Grognard Frédéric, Gutsche V., Heijne B., Horney P., Lefebvre M., Lo-Pelzer E., Mahmoud Ould Sidi, Mailleret Ludovic, Peyrard Nathalie, Sabbadin Régis, Strassemeyer J., Teixeira Alves Mickaël, Thiard J., Trepos Ronan, Zerourou Arezki, Lescourret Françoise. 2013. Methods for IPM: advances in the methodological workpackage of PURE. In : Book of abstracts of Future IPM in Europe, Riva del Garda, Italy, 19-21 March 2013. Fondazione Edmund Mach ; Centro di sperimentazione agraria e forestale di Laimburg ; European project "Pesticide Use-and-risk Reduction in European farming system (PURE). s.l. : s.n., Résumé Conference Future IPM in Europe, Riva del Garda, Italie, 19 March 2013/21 March 2013.

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Abstract : The overall objective of PURE is to provide practical IPM solutions to reduce dependence on pesticides in selected major farming systems in Europe. This paper summarises methodological advances with regards to the design and assessment of IPM solutions. The presented case studies include major crops (cropping systems based on wheat or maize), field vegetables, orchards, vineyard and Controlled Environment Agriculture systems. - Ecological modelling. A software package (Universal Simulator) for collaborative ecological modelling is now available: - Modelling for ex-ante and ex post assessment of IPM solutions. A multi-criteria model (DEXIPM) for sustainability assessment of innovative crop protection strategies has been developed along with SYNOPS, a web-based model for scaling up ex-post pesticide risk assessments at the individual crop level to the farm and regional levels. In addition, a model for ex-ante evaluation of IPM solutions is currently under development specifically for orchards (PREMISE). - Multiple pest modelling. An interactive generic modelling platform to help design models that simulate yield losses caused by an injury profile in a given production situation (X-PEST) is currently under development. Moreover, theoretical mathematical modelling approaches are conducted to represent the interactions between generalist biological control agents and multiple pests. - Optimisation techniques. Reinforcement learning methods have been adapted and applied to IPM. Multiobjective optimisation algorithms for model-based design of IPM solutions are being developed. The Graph based Markov Decision Process framework is being used for the optimisation of sequential decisions under uncertainty in a spatial context. - Cost-benefit analysis and consumers' willingness to pay. Cost-benefit analyses are conducted for IPM solutions tested in the PURE project. An experimental approach is planned to characterise consumers' willingness to pay for agricultural goods produced under IPM solutions as a function of their level of information on the mode of production. It is important to state that the methodological breakthroughs produced in this work package will not only benefit to the PURE project, but also aim at contributing to the design of practical IPM solutions to reduce dependence on pesticides for a wider range of farming systems. This is made possible by ensuring as much as possible genericity in the developed approaches. (Texte intégral)

Classification Agris : H10 - Pests of plants
F08 - Cropping patterns and systems
U10 - Mathematical and statistical methods

Auteurs et affiliations

  • Aubertot Jean-Noël, INRA (FRA)
  • Holst N., Aarhus University (DNK)
  • Messéan Antoine, INRA (FRA)
  • Hennen W., Wageningen University (NLD)
  • Langrel S., European Commission (ESP)
  • Angevin Frédérique, INRA (FRA)
  • Bockstaller Christian, INRA (FRA)
  • Bout Alexandre, INRA (FRA)
  • Buurman Peter, Wageningen Agricultural University (NLD)
  • Daehmlow D., JKI (DEU)
  • Ernst D., JKI (DEU)
  • Fortino G., INRA (FRA)
  • Golla B., JKI (DEU)
  • Grechi Isabelle, CIRAD-PERSYST-UPR HortSys (FRA) ORCID: 0000-0002-3399-6102
  • Grognard Frédéric, INRIA (FRA)
  • Gutsche V., JKI (DEU)
  • Heijne B., Wageningen University (NLD)
  • Horney P., JKI (DEU)
  • Lefebvre M., European Commission (ESP)
  • Lo-Pelzer E., INRA (FRA)
  • Mahmoud Ould Sidi, INRA (FRA)
  • Mailleret Ludovic, INRA (FRA)
  • Peyrard Nathalie, INRA (FRA)
  • Sabbadin Régis, INRA (FRA)
  • Strassemeyer J., JKI (DEU)
  • Teixeira Alves Mickaël, INRA (FRA)
  • Thiard J., INRA (FRA)
  • Trepos Ronan, INRA (FRA)
  • Zerourou Arezki, INRA (FRA)
  • Lescourret Françoise, INRA (FRA)

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