Spectral light-reflection data dimensionality reduction for timely detection of yellow rust
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences
Link
https://link.springer.com/content/pdf/10.1007/s11119-020-09742-2.pdf
Reference70 articles.
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3. Ashourloo, D., Mobasheri, M., & Huete, A. (2014a). Developing two spectral disease indices for detection of wheat leaf rust (Pucciniatriticina). Remote Sensing, 6(6), 4723–4740. https://doi.org/10.3390/rs6064723.
4. Ashourloo, D., Mobasheri, M., & Huete, A. (2014b). Evaluating the effect of different wheat rust disease symptoms on vegetation indices using hyperspectral measurements. Remote Sensing, 6(6), 5107–5123. https://doi.org/10.3390/rs6065107.
5. Baresel, J. P., Rischbeck, P., Hu, Y., Kipp, S., Hu, Y., Barmeier, G., et al. (2017). Use of a digital camera as alternative method for non-destructive detection of the leaf chlorophyll content and the nitrogen nutrition status in wheat. Computers and Electronics in Agriculture, 140, 25–33. https://doi.org/10.1016/j.compag.2017.05.032.
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