Show simple item record

dc.contributor.author
Liebisch, Frank
dc.contributor.author
Kirchgessner, Norbert
dc.contributor.author
Schneider, David
dc.contributor.author
Walter, Achim
dc.contributor.author
Hund, Andreas
dc.date.accessioned
2019-04-17T08:14:53Z
dc.date.available
2017-06-11T17:12:30Z
dc.date.available
2019-04-17T08:14:53Z
dc.date.issued
2015-02-25
dc.identifier.issn
1746-4811
dc.identifier.other
10.1186/s13007-015-0048-8
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/100461
dc.identifier.doi
10.3929/ethz-b-000100461
dc.description.abstract
Background Field-based high throughput phenotyping is a bottleneck for crop breeding research. We present a novel method for repeated remote phenotyping of maize genotypes using the Zeppelin NT aircraft as an experimental sensor platform. The system has the advantage of a low altitude and cruising speed compared to many drones or airplanes, thus enhancing image resolution while reducing blurring effects. Additionally there was no restriction in sensor weight. Using the platform, red, green and blue colour space (RGB), normalized difference vegetation index (NDVI) and thermal images were acquired throughout the growing season and compared with traits measured on the ground. Ground control points were used to co-register the images and to overlay them with a plot map. Results NDVI images were better suited than RGB images to segment plants from soil background leading to two separate traits: the canopy cover (CC) and its NDVI value (NDVIPlant). Remotely sensed CC correlated well with plant density, early vigour, leaf size, and radiation interception. NDVIPlant was less well related to ground truth data. However, it related well to the vigour rating, leaf area index (LAI) and leaf biomass around flowering and to very late senescence rating. Unexpectedly, NDVIPlant correlated negatively with chlorophyll meter measurements. This could be explained, at least partially, by methodical differences between the used devices and effects imposed by the population structure. Thermal images revealed information about the combination of radiation interception, early vigour, biomass, plant height and LAI. Based on repeatability values, we consider two row plots as best choice to balance between precision and available field space. However, for thermography, more than two rows improve the precision. Conclusions We made important steps towards automated processing of remotely sensed data, and demonstrated the value of several procedural steps, facilitating the application in plant genetics and breeding. Important developments are: the ability to monitor throughout the season, robust image segmentation and the identification of individual plots in images from different sensor types at different dates. Remaining bottlenecks are: sufficient ground resolution, particularly for thermal imaging, as well as a deeper understanding of the relatedness of remotely sensed data and basic crop characteristics.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Remote sensing
en_US
dc.subject
Aerial phenotyping
en_US
dc.subject
Near infrared imaging
en_US
dc.subject
Image analysis
en_US
dc.subject
NDVI
en_US
dc.subject
Thermal imaging
en_US
dc.subject
Zea mays
en_US
dc.title
Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Plant Methods
ethz.journal.volume
11
en_US
ethz.journal.issue
1
en_US
ethz.journal.abbreviated
Plant methods
ethz.pages.start
9
en_US
ethz.size
19 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.scopus
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03894 - Walter, Achim / Walter, Achim
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03894 - Walter, Achim / Walter, Achim
ethz.date.deposited
2017-06-11T17:12:50Z
ethz.source
ECIT
ethz.identifier.importid
imp59365322b07a659950
ethz.ecitpid
pub:157665
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-15T08:35:06Z
ethz.rosetta.lastUpdated
2019-04-17T08:15:17Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Remote,%20aerial%20phenotyping%20of%20maize%20traits%20with%20a%20mobile%20multi-sensor%20approach&rft.jtitle=Plant%20Methods&rft.date=2015-02-25&rft.volume=11&rft.issue=1&rft.spage=9&rft.issn=1746-4811&rft.au=Liebisch,%20Frank&Kirchgessner,%20Norbert&Schneider,%20David&Walter,%20Achim&Hund,%20Andreas&rft.genre=article&
 Search via SFX

Files in this item

Thumbnail

Publication type

Show simple item record