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. 2020 Aug 20;9(8):giaa090. doi: 10.1093/gigascience/giaa090

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© The Author(s) 2020. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 4: — A general trait visualization. Plant traits are parameters that describe the hyperspectral properties of the plant tissue. Nevertheless, these traits can be grouped according to the effort that is needed for their extraction. First-level traits (TL 1) describe the spectrum of the whole canopy. By using a classification based on a ML algorithm it is possible to identify spectra of single organs (TL 2). By taking measurements over time the development of these spectra can be visualized (TL 3), and by using further sensors it is possible to reduce geometrical effects based on a particular sensor by means of fusion of sensor data (TL 4).