Development of Algorithm for Determining N Fertiliser Requirements of Winter Wheat Based on N Status Using APSIM Modelling

Iris Vogeler Cronin*, Uttam Kumar, Leif Knudsen, Elly Møller Hansen, Val Snow, Ingrid Kaag Thomsen

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review


The determination of optimum nitrogen (N) fertilisation rates, which maximise yields and
minimise N losses, remains problematic due to unknown upcoming crop requirements and nearfuture
supply by the soil. Remote sensing can be used for determining the crop N status and to
assess the spatial variability within a field or between fields. This can be used to improve N fertilisation,
provided that the optimal fertilisation rate at the time of fertiliser application for an expected
yield is known. Using the APSIM-wheat model, we developed an algorithm that relates the N status
of the plants at early development stages to the yield response to N. Simulations were performed
for winter wheat under growth conditions in Denmark. To obtain a range of different N status in
the biomass at early growth stages, the soil N in autumn was varied from 20 to 180 kg N ha−1, and
at BBCH23, fertiliser was applied at a rate of 50 kg N ha−1. In a full factorial setup, additional N
fertiliser was applied ranging from 0 to 150 kg N ha−1 during three different development stages
(BBCH30, 32, and 37). The algorithm was evaluated by comparing model outputs with a standard
N application of 50 kg N ha−1 at BBCH23 and 150 kg N ha−1 at BBCH30. The evaluation showed that,
depending on the N status of the soil, the algorithm either provided higher or lower optimal N
fertilisation rates when targeting 95% of the maximum yield, and these affected the grain yield and
the grain N, as well as the amount of N leaching. Split application of fertiliser into three applications
was generally beneficial, with decreased product-related N leaching of up to nearly 30%. Further
testing of the model under different environmental conditions is needed before such an algorithm
can be used to guide N fertilisation.
Original languageEnglish
Pages (from-to)134-144
Publication statusPublished - Apr 2024


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