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Advanced phenotyping and phenotype data analysis for the study of plant growth and development
Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global chall...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4530591/ https://www.ncbi.nlm.nih.gov/pubmed/26322060 http://dx.doi.org/10.3389/fpls.2015.00619 |
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author | Rahaman, Md. Matiur Chen, Dijun Gillani, Zeeshan Klukas, Christian Chen, Ming |
author_facet | Rahaman, Md. Matiur Chen, Dijun Gillani, Zeeshan Klukas, Christian Chen, Ming |
author_sort | Rahaman, Md. Matiur |
collection | PubMed |
description | Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis. |
format | Online Article Text |
id | pubmed-4530591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-45305912015-08-28 Advanced phenotyping and phenotype data analysis for the study of plant growth and development Rahaman, Md. Matiur Chen, Dijun Gillani, Zeeshan Klukas, Christian Chen, Ming Front Plant Sci Plant Science Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis. Frontiers Media S.A. 2015-08-10 /pmc/articles/PMC4530591/ /pubmed/26322060 http://dx.doi.org/10.3389/fpls.2015.00619 Text en Copyright © 2015 Rahaman, Chen, Gillani, Klukas and Chen. 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 Rahaman, Md. Matiur Chen, Dijun Gillani, Zeeshan Klukas, Christian Chen, Ming Advanced phenotyping and phenotype data analysis for the study of plant growth and development |
title | Advanced phenotyping and phenotype data analysis for the study of plant growth and development |
title_full | Advanced phenotyping and phenotype data analysis for the study of plant growth and development |
title_fullStr | Advanced phenotyping and phenotype data analysis for the study of plant growth and development |
title_full_unstemmed | Advanced phenotyping and phenotype data analysis for the study of plant growth and development |
title_short | Advanced phenotyping and phenotype data analysis for the study of plant growth and development |
title_sort | advanced phenotyping and phenotype data analysis for the study of plant growth and development |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4530591/ https://www.ncbi.nlm.nih.gov/pubmed/26322060 http://dx.doi.org/10.3389/fpls.2015.00619 |
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