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Decision-Making and Decision Support System for a Successful Weed Management

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Information and Communication Technologies for Agriculture—Theme III: Decision

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 184))

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Abstract

The introduction of Decision Support Systems (DSSs) in weed management poses an attractive option for creating improved and more environmentally friendly control strategies. The aim of the current study was to present key factors affecting decision-making process that need to be taken into account before developing a DSS in terms of weed management. First, attention should be paid to the effects of environmental factors and agronomic practices on weed emergence and the composition of the weed flora in an agricultural field. If weed emergence and timing of weed emergence could be predicted, then a DSS could make accurate suggestions for weed control. Secondly, to develop any weed management program, it is essential to have a deep understanding of weed biology and ecology. The biological traits of weeds, weed growth, the impact of weed competition during crucial growth stages for the crop should be estimated in order to optimize decision-making process. Moreover, a better understanding of seed production and weed seedbank dynamics into the soil would help experts develop DSSs able to provide management strategies also in the long-term period. However, these objectives are quite complex and need to be addressed in the near future. Furthermore, carrying out field surveys, hosting workshops, and group meetings in order to communicate with farmers and help them familiarize with the adoption of DSS methodologies. This is a vital step for persuading farmers to trust the use DSSs for the management of weeds in their fields. Further research and extended experimentation are needed in order to develop effective DSSs in terms of weed management under different soil and climatic conditions, always according to the special needs of each farmer.

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Authors and Affiliations

  1. Department of Crop Science, University of Patras, Mesolonghi, Greece

    P. Kanatas

  2. Department of Crop Science, Agricultural University of Athens, Athens, Greece

    I. Travlos, A. Tataridas & I. Gazoulis

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  1. P. Kanatas
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  2. I. Travlos
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  3. A. Tataridas
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  4. I. Gazoulis
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Editors and Affiliations

  1. Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece

    Dionysis D. Bochtis

  2. Department of Electrical and Computer Engineering, University of Aarhus, Aarhus N, Denmark

    Claus Grøn Sørensen

  3. Department of Resources Management and Agricultural Engineering, Agricultural University of Athens, Athens, Greece

    Spyros Fountas

  4. Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece

    Vasileios Moysiadis

  5. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

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Kanatas, P., Travlos, I., Tataridas, A., Gazoulis, I. (2022). Decision-Making and Decision Support System for a Successful Weed Management. In: Bochtis, D.D., Sørensen, C.G., Fountas, S., Moysiadis, V., Pardalos, P.M. (eds) Information and Communication Technologies for Agriculture—Theme III: Decision. Springer Optimization and Its Applications, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-030-84152-2_8

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