Abstract
The objective of this research was to detect plant stress caused by disease infestation and to discriminate this type of stress from nutrient deficiency stress in field conditions using spectral reflectance information. Yellow Rust infected winter wheat plants were compared to nutrient stressed and healthy plants. In-field hyperspectral reflectance images were taken with an imaging spectrograph. A normalisation method based on reflectance and light intensity adjustments was applied. For achieving high performance stress identification, Self-Organising Maps (SOMs) and Quadratic Discriminant Analysis (QDA) were introduced. Winter wheat infected with Yellow Rust was successfully recognised from nutrient stressed and healthy plants. Overall performance using five wavebands was more than 99%.
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Acknowledgements
This work was performed as part of the OPTIDIS project (QLK5-CT1999-01280), which was funded by the EU under the Quality of Life Programme—Framework V.
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Moshou, D., Bravo, C., Wahlen, S. et al. Simultaneous identification of plant stresses and diseases in arable crops using proximal optical sensing and self-organising maps. Precision Agric 7, 149–164 (2006). https://doi.org/10.1007/s11119-006-9002-0
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DOI: https://doi.org/10.1007/s11119-006-9002-0