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Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases

Author

Listed:
  • Nyi-Nyi Htun

    (Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, Belgium)

  • Diego Rojo

    (Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, Belgium)

  • Jeroen Ooge

    (Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, Belgium)

  • Robin De Croon

    (Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, Belgium)

  • Aikaterini Kasimati

    (Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece)

  • Katrien Verbert

    (Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, Belgium)

Abstract

Decision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limits their flexibility and portability. They also rarely provide interactivity, visualise uncertainty and are evaluated with end-users. To address these gaps, we developed six web-based visual-assisted DSSs for various agricultural use cases, including biological efficacy correlation analysis, water stress and irrigation requirement analysis, product price prediction, etc. We then evaluated our DSSs with domain experts, focusing on usability, workload, acceptance and trust. Results showed that our systems were easy to use and understand, and participants perceived them as highly performant, even though they required a slightly high mental demand, temporal demand and effort. We also published the source code of our proposed systems so that they can be re-used or adapted by the agricultural community.

Suggested Citation

  • Nyi-Nyi Htun & Diego Rojo & Jeroen Ooge & Robin De Croon & Aikaterini Kasimati & Katrien Verbert, 2022. "Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases," Agriculture, MDPI, vol. 12(7), pages 1-30, July.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:7:p:1027-:d:863060
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    References listed on IDEAS

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    1. Hahsler, Michael & Hornik, Kurt & Buchta, Christian, 2008. "Getting Things in Order: An Introduction to the R Package seriation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i03).
    2. Lundström, Christina & Lindblom, Jessica, 2018. "Considering farmers' situated knowledge of using agricultural decision support systems (AgriDSS) to Foster farming practices: The case of CropSAT," Agricultural Systems, Elsevier, vol. 159(C), pages 9-20.
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    Cited by:

    1. Xiaohan Li & Yuwei Zhang & Ali Sorourkhah & S. A. Edalatpanah, 2024. "Introducing Antifragility Analysis Algorithm for Assessing Digitalization Strategies of the Agricultural Economy in the Small Farming Section," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 12191-12215, September.

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