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A Review of Imaging Techniques for Plant Phenotyping
Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279472/ https://www.ncbi.nlm.nih.gov/pubmed/25347588 http://dx.doi.org/10.3390/s141120078 |
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author | Li, Lei Zhang, Qin Huang, Danfeng |
author_facet | Li, Lei Zhang, Qin Huang, Danfeng |
author_sort | Li, Lei |
collection | PubMed |
description | Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review. |
format | Online Article Text |
id | pubmed-4279472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-42794722015-01-15 A Review of Imaging Techniques for Plant Phenotyping Li, Lei Zhang, Qin Huang, Danfeng Sensors (Basel) Review Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review. MDPI 2014-10-24 /pmc/articles/PMC4279472/ /pubmed/25347588 http://dx.doi.org/10.3390/s141120078 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Li, Lei Zhang, Qin Huang, Danfeng A Review of Imaging Techniques for Plant Phenotyping |
title | A Review of Imaging Techniques for Plant Phenotyping |
title_full | A Review of Imaging Techniques for Plant Phenotyping |
title_fullStr | A Review of Imaging Techniques for Plant Phenotyping |
title_full_unstemmed | A Review of Imaging Techniques for Plant Phenotyping |
title_short | A Review of Imaging Techniques for Plant Phenotyping |
title_sort | review of imaging techniques for plant phenotyping |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279472/ https://www.ncbi.nlm.nih.gov/pubmed/25347588 http://dx.doi.org/10.3390/s141120078 |
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