Field Scanalyzer: An automated robotic field phenotyping platform for detailed crop monitoring

A - Papers appearing in refereed journals

Virlet, N., Sabermanesh, K., Sadeghi-Tehran, P. and Hawkesford, M. J. 2016. Field Scanalyzer: An automated robotic field phenotyping platform for detailed crop monitoring. Functional Plant Biology. 44 (1), pp. 143-153. https://doi.org/10.1071/FP16163

AuthorsVirlet, N., Sabermanesh, K., Sadeghi-Tehran, P. and Hawkesford, M. J.
Abstract

Current approaches to field phenotyping are laborious or permit the use of only a few sensors at a time. In an effort to overcome this, a fully automated robotic field phenotyping platform with a dedicated sensor array that may be accurately positioned in three dimensions and mounted on fixed rails has been established, to facilitate continual and high-throughput monitoring of crop performance. Employed sensors comprise of high-resolution visible, chlorophyll fluorescence and thermal infrared cameras, two hyperspectral imagers and dual 3D laser scanners. The sensor array facilitates specific growth measurements and identification of key growth stages with dense temporal and spectral resolution. Together, this platform produces a detailed description of canopy development across the crops entire lifecycle, with a high-degree of accuracy and reproducibility.

Keywordsdata processing; computer vision; field scanalyzer; nitrogen; phenomics; scanalyzer
Year of Publication2016
JournalFunctional Plant Biology
Journal citation44 (1), pp. 143-153
Digital Object Identifier (DOI)https://doi.org/10.1071/FP16163
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeWheat
[20:20 Wheat] Maximising yield potential of wheat
Publisher's version
Output statusPublished
Publication dates
Online02 Nov 2016
Publication process dates
Accepted02 Sep 2016
Copyright licenseCC BY
PublisherCSIRO Publishing
ISSN1445-4408

Permalink - https://repository.rothamsted.ac.uk/item/8v276/field-scanalyzer-an-automated-robotic-eld-phenotyping-platform-for-detailed-crop-monitoring

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