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UAS

UAV-based high-throughput phenotyping to discriminate barley vigour with visible and near-infrared vegetation indices

ORCID Icon, , , , , , , & show all
Pages 5330-5344 | Received 16 Mar 2017, Accepted 13 Oct 2017, Published online: 22 Nov 2017
 

ABSTRACT

In the context of plant breeding, high-throughput phenotyping is an assessment of plant phenotypes on a scale and with a level of speed and precision not achievable with traditional methods, through the application of emerging technologies such as automation and robotics, new sensors, and imaging technologies (hardware and software). In the present work, high-resolution digital images have been acquired with an unmanned aerial vehicle (UAV) prototype platform on an experimental phenotyping barley field. Six vegetation indices generated from the red–green–blue and near-infrared-based images were calculated for 912 experimental barley plots and provided high correlation with the indices determined from hyperspectral data taken at the ground (gt); the indices performance in discriminating the vigour of genotypes was finally assessed.

Acknowledgements

The authors are grateful to Silvia Baronti, Carolina Vagnoli (IBIMET—CNR), Luigi Cattivelli, Renzo Alberici, Ivana Tagliaferri (CREA) for their support in the field experiment. Special thanks to Whealbi Project (Whealbi Citation2014) that funds the phenotyping experiment through the European Union’s Seventh Framework Programme (grant agreement n°FP7-613556).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Seventh Framework Programme [FP7-613556].

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