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Purpose <p>Alignment of crop nitrogen (N) demand with N supply is crucial to improve N use efficiency of organic fertilizers whose N is largely bound organically. This study aimed to evaluate the potential of unmanned aerial vehicle (UAV)-based multispectral imagery to monitor in-season N uptake and to assess how different organic fertilizers affect N dynamics.</p> Methods <p>A field trial in Wallbach, Switzerland, compared untreated cattle slurry, anaerobically digested slurry, solid digestate, a mineral N control, and a zero-N control over two winter cereal seasons. UAV-acquired multispectral data were combined with environmental data (weather, soil and fertilizer) to model dry matter, N concentration, N uptake and the nitrogen nutrition index using random forest regression.</p> Results <p>The random forest models combining UAV-based multispectral imagery with environmental data showed good performance in predicting in-season N uptake of winter wheat (R<sup>2</sup> = 0.85, RMSE = 13.9&#xa0;kg N ha<sup>− 1</sup>) and of winter barley (R² = 0.78, RMSE = 9.3&#xa0;kg N ha<sup>− 1</sup>). Predicted N dynamics revealed transient N uptake maxima in organic treatments before fertilization, likely due to legacy fertilizer effects. Post-fertilization, N uptake increased most under mineral fertilization. N uptake dynamics were affected by fertilizer properties, with low C/N ratio and high NH<sub>4</sub>-N proportion showing stronger effects.</p> Conclusion <p>Highly temporal UAV-based multispectral imagery captures in-season N uptake dynamic and reveals differences in fertilizer N release caused by quality differences of organic fertilizers. These insights support optimized fertilizer application for better synchronization of N mineralization with crop demand.</p>

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Linking organic fertilizer properties to in-season N dynamics using multispectral UAV imagery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月23日

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  • Matthias Diener,
  • L. Agostini,
  • F. Argento,
  • E. K. Bünemann,
  • A. Walter,
  • J. Mayer,
  • F. Liebisch

摘要

Purpose

Alignment of crop nitrogen (N) demand with N supply is crucial to improve N use efficiency of organic fertilizers whose N is largely bound organically. This study aimed to evaluate the potential of unmanned aerial vehicle (UAV)-based multispectral imagery to monitor in-season N uptake and to assess how different organic fertilizers affect N dynamics.

Methods

A field trial in Wallbach, Switzerland, compared untreated cattle slurry, anaerobically digested slurry, solid digestate, a mineral N control, and a zero-N control over two winter cereal seasons. UAV-acquired multispectral data were combined with environmental data (weather, soil and fertilizer) to model dry matter, N concentration, N uptake and the nitrogen nutrition index using random forest regression.

Results

The random forest models combining UAV-based multispectral imagery with environmental data showed good performance in predicting in-season N uptake of winter wheat (R2 = 0.85, RMSE = 13.9 kg N ha− 1) and of winter barley (R² = 0.78, RMSE = 9.3 kg N ha− 1). Predicted N dynamics revealed transient N uptake maxima in organic treatments before fertilization, likely due to legacy fertilizer effects. Post-fertilization, N uptake increased most under mineral fertilization. N uptake dynamics were affected by fertilizer properties, with low C/N ratio and high NH4-N proportion showing stronger effects.

Conclusion

Highly temporal UAV-based multispectral imagery captures in-season N uptake dynamic and reveals differences in fertilizer N release caused by quality differences of organic fertilizers. These insights support optimized fertilizer application for better synchronization of N mineralization with crop demand.