Soybean iron deficiency chlorosis high throughput phenotyping using an unmanned aircraft system

DOI: 10.1186/s13007-019-0478-9

Keywords: Unmanned aircraft system (UAS), Soybean, Iron deficiency chlorosis, Remote sensing, Random forest, Neural network, Image analysis

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Abstract:

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