A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding
Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological trai...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-08-01
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| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpls.2016.01131/full |
| _version_ | 1818328186790871040 |
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| author | Maria Tattaris Matthew P Reynolds Scott C Chapman |
| author_facet | Maria Tattaris Matthew P Reynolds Scott C Chapman |
| author_sort | Maria Tattaris |
| collection | DOAJ |
| description | Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30-100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5-1m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 x 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency. |
| first_indexed | 2024-12-13T12:28:10Z |
| format | Article |
| id | doaj.art-828eb40e9da74731addd9444b1d604d5 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-12-13T12:28:10Z |
| publishDate | 2016-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-828eb40e9da74731addd9444b1d604d52022-12-21T23:46:10ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2016-08-01710.3389/fpls.2016.01131206105A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breedingMaria Tattaris0Matthew P Reynolds1Scott C Chapman2CIMMYTCIMMYTCSIRO AgricultureRemote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30-100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5-1m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 x 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.http://journal.frontiersin.org/Journal/10.3389/fpls.2016.01131/fullthermal imagingUAVhigh-throughput phenotypingMultispectral imagingairborne imagery |
| spellingShingle | Maria Tattaris Matthew P Reynolds Scott C Chapman A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding Frontiers in Plant Science thermal imaging UAV high-throughput phenotyping Multispectral imaging airborne imagery |
| title | A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding |
| title_full | A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding |
| title_fullStr | A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding |
| title_full_unstemmed | A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding |
| title_short | A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding |
| title_sort | direct comparison of remote sensing approaches for high throughput phenotyping in plant breeding |
| topic | thermal imaging UAV high-throughput phenotyping Multispectral imaging airborne imagery |
| url | http://journal.frontiersin.org/Journal/10.3389/fpls.2016.01131/full |
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