Abstract

Nitrogen (N) fertilisation in crops can be made more efficient by moving from uniform application to meeting variable crop requirements within fields. Within field variable rate N fertilisation of winter wheat (Triticum aestivum L.) is practically feasible using information from web-based decision support systems (DSS). Data from different source platforms, such as satellite, unmanned aerial vehicle (UAV) or weather stations can be used for fertilisation planning. System output offers information that can be used  to instruct variable rate fertilizer spreaders to increase or decrease fertilizer application rate on-the-go. In Sweden, satellite-based variable rate N fertilisation was available for winter wheat via a DSS, however, the existing module could be improved in different ways. In this thesis work, a new N-uptake model was estimated and opportunities using UAV-based modelling of grain quality were tested. Transferability of UAV-based models to a satellite data scale improved understanding of the complexity of data transfer from UAV-scale to a satellite scale for use in a DSS. Furthermore, it was possible to model crop phenology from historical data, which can improve accuracy of current implemented models, by taking timing of field operations in to account.

Keywords

phenology; precision agriculture; remote sensing; Sentinel-2; unmanned aerial vehicle

Published in

Acta Universitatis Agriculturae Sueciae
2022, number: 2022:59
ISBN: 978-91-7760-993-3, eISBN: 978-91-7760-994-0
Publisher: Swedish University of Agricultural Sciences

SLU Authors

• Wolters, Sandra

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Agricultural Science
Remote Sensing


Permanent link to this page (URI)

https://res.slu.se/id/publ/119069