IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-031-49740-7_3.html
   My bibliography  Save this book chapter

Implementing a Decision Support System for Plant Variety Testing in the Czech Republic

In: Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry

Author

Listed:
  • David Hampel

    (Mendel University in Brno)

  • Martin Tláskal

    (Mendel University in Brno)

  • Jitka Janová

    (Mendel University in Brno)

Abstract

In our contribution, we address advanced problems of plant variety experiments, which are organised at the official level of the Czech Republic by the Central Institute for Supervising and Testing in Agriculture (CISTA), a specialised authority established by the Ministry of Agriculture of the Czech Republic. Experiments carried out by CISTA are typically conducted with a low number of replications, and it is often necessary to take into account the limited experimental area when planning an experiment. These are mostly organised according to Alpha-design which represents a specific optimisation issue. In official plant variety testing, various restrictions appear (shape of the area, height of plant varieties, appearance of the replicated neighbourhood of the plant variety) which are not included in the original optimisation, and ex post design modifications must be made. The aim of this chapter is to describe the process of the development and validation of a decision support system (DSS) that accommodates an optimal Alpha-design for these restrictions and provide detailed information on the implementation of the DSS in practice. The DSS was developed in 2012–2013 and implemented through 2014–2015, but the development of the DSS is still ongoing. Currently, it is in routine usage and works effectively.

Suggested Citation

  • David Hampel & Martin Tláskal & Jitka Janová, 2024. "Implementing a Decision Support System for Plant Variety Testing in the Czech Republic," Springer Books, in: Víctor M. Albornoz & Alejandro Mac Cawley & Lluis M. Plà-Aragonés (ed.), Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry, pages 35-61, Springer.
  • Handle: RePEc:spr:sprchp:978-3-031-49740-7_3
    DOI: 10.1007/978-3-031-49740-7_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-031-49740-7_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.