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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4971441/ https://www.ncbi.nlm.nih.gov/pubmed/27536304 http://dx.doi.org/10.3389/fpls.2016.01131 |
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author | Tattaris, Maria Reynolds, Matthew P. Chapman, Scott C. |
author_facet | Tattaris, Maria Reynolds, Matthew P. Chapman, Scott C. |
author_sort | Tattaris, Maria |
collection | PubMed |
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 0.5–1 m 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 × 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. |
format | Online Article Text |
id | pubmed-4971441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-49714412016-08-17 A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding Tattaris, Maria Reynolds, Matthew P. Chapman, Scott C. Front Plant Sci Plant Science 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 0.5–1 m 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 × 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. Frontiers Media S.A. 2016-08-03 /pmc/articles/PMC4971441/ /pubmed/27536304 http://dx.doi.org/10.3389/fpls.2016.01131 Text en Copyright © 2016 Tattaris, Reynolds and Chapman. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Tattaris, Maria Reynolds, Matthew P. Chapman, Scott C. A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding |
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 | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4971441/ https://www.ncbi.nlm.nih.gov/pubmed/27536304 http://dx.doi.org/10.3389/fpls.2016.01131 |
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