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

Crops Pub Date : 2024-04-03 DOI:10.3390/crops4020010
I. Vogeler, Uttam Kumar, Leif Knudsen, E. Hansen, Val Snow, I. Thomsen
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Abstract

The determination of optimum nitrogen (N) fertilisation rates, which maximise yields and minimise N losses, remains problematic due to unknown upcoming crop requirements and near-future 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.
利用 APSIM 模型开发基于氮状况确定冬小麦氮肥需求量的算法
由于未知作物的未来需求和土壤的近期供应量,如何确定最佳氮肥施用量,从而最大限度地提高产量并减少氮肥损失,仍然是一个难题。遥感技术可用于确定作物的氮状况,并评估田地内部或田地之间的空间变化。如果知道施肥时预期产量的最佳施肥量,就可以利用遥感技术改进氮肥施用。利用 APSIM 小麦模型,我们开发了一种算法,将植物早期发育阶段的氮状况与产量对氮的反应联系起来。为了获得生长初期生物量中不同的氮状况,秋季的土壤氮在 20 至 180 千克/公顷之间变化,在 BBCH23 期,施肥量为 50 千克/公顷。在全因子设置中,三个不同生长阶段(BBCH30、32 和 37)的额外氮肥施用量为 0 至 150 千克氮/公顷。通过比较 BBCH23 和 BBCH30 的标准氮肥施用量(分别为每公顷 50 千克氮肥和每公顷 150 千克氮肥),对该算法进行了评估。评估结果表明,根据土壤的氮状况,该算法在以最高产量的 95% 为目标时,提供了较高或较低的最佳氮肥施用量,这对谷物产量、谷物氮以及氮的沥滤量都有影响。将肥料分成三次施用通常是有益的,与产品相关的氮浸出减少了近 30%。在使用这种算法指导氮肥施用之前,还需要在不同环境条件下对模型进行进一步测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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