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Advances in plant nutrition diagnosis based on remote sensing and computer application

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Abstract

Hyperspectral remote sensing, visible light remote sensing and canopy color analysis have been widely concerned for rapid diagnosis of crop growth and nutrition. They are expected to develop into potential nondestructive diagnostic techniques for crop nitrogen nutrition in the new era on account of the advantages of stable, rapid, convenient and nondestructive results, together with the good correlation between canopy color parameter NRI and plant nitrogen nutrition index and yield satisfying the demand for nondestructive diagnosis of nitrogen nutrition, and their feasibility to monitor plant growth status and nitrogen nutrition level in real time and quickly. At present, with the rapid development of remote sensing satellite, unmanned aerial vehicles remote sensing and Internet of things, remote sensing will be more and more widely used in plant nutrition diagnosis.

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Acknowledgements

This work was supported by the Fund of China Agriculture Research System (CARS-23) and the National Key Research and Development Program of China (2018YFD0201200).

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Authors and Affiliations

  1. College of Resources and Environmental Sciences, Southwest University, Chongqing, 400715, People’s Republic of China

    Deyu Feng, Weihong Xu, Zhangmi He, Wanyi Zhao & Mei Yang

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  1. Deyu Feng
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  2. Weihong Xu
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  3. Zhangmi He
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  5. Mei Yang
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Correspondence to Weihong Xu.

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Feng, D., Xu, W., He, Z. et al. Advances in plant nutrition diagnosis based on remote sensing and computer application. Neural Comput & Applic 32, 16833–16842 (2020). https://doi.org/10.1007/s00521-018-3932-0

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