Advances in plant nutrition diagnosis based on remote sensing and computer application
| Autor: | Mei Yang, Zhangmi He, Weihong Xu, Deyu Feng, Wanyi Zhao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Canopy
0209 industrial biotechnology Plant growth Computer science Crop growth Hyperspectral imaging 02 engineering and technology Crop 020901 industrial engineering & automation Artificial Intelligence Remote sensing (archaeology) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Plant nutrition Software Remote sensing |
| Zdroj: | Neural Computing and Applications. 32:16833-16842 |
| ISSN: | 1433-3058 0941-0643 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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