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Big data in agriculture: Between opportunity and solution

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  • Osinga, Sjoukje A.
  • Paudel, Dilli
  • Mouzakitis, Spiros A.
  • Athanasiadis, Ioannis N.

Abstract

Big data applications in agriculture evolve fast, as more experience, applications, good practices and computational power become available. Actual solutions to real-life problems are scarce. What characterizes the adoption of big data problems to solutions and to what extent is there a match between them?

Suggested Citation

  • Osinga, Sjoukje A. & Paudel, Dilli & Mouzakitis, Spiros A. & Athanasiadis, Ioannis N., 2022. "Big data in agriculture: Between opportunity and solution," Agricultural Systems, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:agisys:v:195:y:2022:i:c:s0308521x21002511
    DOI: 10.1016/j.agsy.2021.103298
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    References listed on IDEAS

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    Cited by:

    1. Jeroen Ooge & Katrien Verbert, 2022. "Visually Explaining Uncertain Price Predictions in Agrifood: A User-Centred Case-Study," Agriculture, MDPI, vol. 12(7), pages 1-25, July.
    2. Zhang, Chen & Di, Liping & Lin, Li & Li, Hui & Guo, Liying & Yang, Zhengwei & Yu, Eugene G. & Di, Yahui & Yang, Anna, 2022. "Towards automation of in-season crop type mapping using spatiotemporal crop information and remote sensing data," Agricultural Systems, Elsevier, vol. 201(C).
    3. Gniewko Niedbała & Sebastian Kujawa, 2023. "Digital Innovations in Agriculture," Agriculture, MDPI, vol. 13(9), pages 1-10, August.

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