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Hyperspectral monitoring of soil urease activity under different water regulation

Abstract

Purpose

The main purpose of this study is to realize the rapid and non-destructive determination of soil urease activity, so as to provide guidance for soil nitrogen transformation in time.

Methods

In this study, five gradient experiments of water regulation were set up under the conditions of multiple cropping of winter wheat and summer soybean. The data of soil urease activity and hyperspectral reflectance were collected. We explored the influence of water regulation on soil urease activity. And based on a variety of spectral transformation algorithms and modeling algorithms, hyperspectral monitoring models of soil urease activity were constructed.

Results

Soil urease activity increased first and then decreased with the aggravation of drought stress. FD, CR, MSC, and SNV transformation can improve the correlation between spectral reflectance and soil urease activity. The accuracy of the models constructed by PLSR and SMLR was high. In the nonlinear algorithm, SPA-ANN based on SNV had the highest accuracy. Among all the models, the PLSR model based on FD had the highest accuracy, with R2v of 0.8564, RMSEv of 0.4013, and RPD of 2.5667. This study can provide technical support for the rapid determination of soil urease activity and provide a theoretical basis for further rational management of farmland.

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References

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Funding

This work was supported by National Natural Science Foundation of China(31871571, 31371572), Basic research program of Shanxi Province(20210302123411, 20210302124236), Outstanding Doctor Funding Award of Shanxi Province(SXYBKY2018040), Scientific and Technological Innovation Fund of Shanxi Agricultural University(2018YJ17), Applied Basic Research Project of Shanxi Province(201801D221299), Science and Technique Innovation Project of Shanxi Agricultural University(2020BQ32), Key Technologies R & D Program of Shanxi Province (201903D211002), and Higher Education Project of Scientific and Technological Innovation in Shanxi (2020L0132).

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Authors and Affiliations

Authors

Contributions

Study concept and design: Meichen Feng and Yongkai Xie. Data analysis and drafting of the manuscript: Chenbo Yang. Experimental participants: Lifang Song, Binghan Jing, Yongkai Xie, Mingxing Qin, Jingjing Sun, and Muhammad Saleem Kubar. Critical revision of the manuscript for important intellectual content: Meichen Feng, Chao Wang, Lujie Xiao, Meijun Zhang, and Xiaoyan Song. Obtained funding: Wude Yang, Meichen Feng, Lujie Xiao, Jingjing Sun, and Chao Wang. Study supervision: Meichen Feng.

Corresponding author

Correspondence to Meichen Feng.

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Conflicts of interest

No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed.

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Cite this article

Yang, C., Feng, M., Song, L. et al. Hyperspectral monitoring of soil urease activity under different water regulation. Plant Soil (2022). https://doi.org/10.1007/s11104-022-05476-4

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  • DOI: https://doi.org/10.1007/s11104-022-05476-4

Keywords

  • Water regulation
  • Winter wheat
  • Soybean
  • Urease activity
  • Hyperspectral
  • Algorithm