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Pitfalls and potential of high-throughput plant phenotyping platforms
Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infras...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481964/ https://www.ncbi.nlm.nih.gov/pubmed/37680357 http://dx.doi.org/10.3389/fpls.2023.1233794 |
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author | Poorter, Hendrik Hummel, Grégoire M. Nagel, Kerstin A. Fiorani, Fabio von Gillhaussen, Philipp Virnich, Olivia Schurr, Ulrich Postma, Johannes A. van de Zedde, Rick Wiese-Klinkenberg, Anika |
author_facet | Poorter, Hendrik Hummel, Grégoire M. Nagel, Kerstin A. Fiorani, Fabio von Gillhaussen, Philipp Virnich, Olivia Schurr, Ulrich Postma, Johannes A. van de Zedde, Rick Wiese-Klinkenberg, Anika |
author_sort | Poorter, Hendrik |
collection | PubMed |
description | Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infrastructure, or are considering doing so. To make optimal use of limited resources, it is important to plan and use these facilities prudently and to interpret the results carefully. Here we present a number of points that users should consider before purchasing, building or utilizing such equipment. They relate to (1) the financial and time investment for acquisition, operation, and maintenance, (2) the constraints associated with such machines in terms of flexibility and growth conditions, (3) the pros and cons of frequent non-destructive measurements, (4) the level of information provided by proxy traits, and (5) the utilization of calibration curves. Using data from an Arabidopsis experiment, we demonstrate how diurnal changes in leaf angle can impact plant size estimates from top-view cameras, causing deviations of more than 20% over the day. Growth analysis data from another rosette species showed that there was a curvilinear relationship between total and projected leaf area. Neglecting this curvilinearity resulted in linear calibration curves that, although having a high r(2) (> 0.92), also exhibited large relative errors. Another important consideration we discussed is the frequency at which calibration curves need to be generated and whether different treatments, seasons, or genotypes require distinct calibration curves. In conclusion, HTPP systems have become a valuable addition to the toolbox of plant biologists, provided that these systems are tailored to the research questions of interest, and users are aware of both the possible pitfalls and potential involved. |
format | Online Article Text |
id | pubmed-10481964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104819642023-09-07 Pitfalls and potential of high-throughput plant phenotyping platforms Poorter, Hendrik Hummel, Grégoire M. Nagel, Kerstin A. Fiorani, Fabio von Gillhaussen, Philipp Virnich, Olivia Schurr, Ulrich Postma, Johannes A. van de Zedde, Rick Wiese-Klinkenberg, Anika Front Plant Sci Plant Science Automated high-throughput plant phenotyping (HTPP) enables non-invasive, fast and standardized evaluations of a large number of plants for size, development, and certain physiological variables. Many research groups recognize the potential of HTPP and have made significant investments in HTPP infrastructure, or are considering doing so. To make optimal use of limited resources, it is important to plan and use these facilities prudently and to interpret the results carefully. Here we present a number of points that users should consider before purchasing, building or utilizing such equipment. They relate to (1) the financial and time investment for acquisition, operation, and maintenance, (2) the constraints associated with such machines in terms of flexibility and growth conditions, (3) the pros and cons of frequent non-destructive measurements, (4) the level of information provided by proxy traits, and (5) the utilization of calibration curves. Using data from an Arabidopsis experiment, we demonstrate how diurnal changes in leaf angle can impact plant size estimates from top-view cameras, causing deviations of more than 20% over the day. Growth analysis data from another rosette species showed that there was a curvilinear relationship between total and projected leaf area. Neglecting this curvilinearity resulted in linear calibration curves that, although having a high r(2) (> 0.92), also exhibited large relative errors. Another important consideration we discussed is the frequency at which calibration curves need to be generated and whether different treatments, seasons, or genotypes require distinct calibration curves. In conclusion, HTPP systems have become a valuable addition to the toolbox of plant biologists, provided that these systems are tailored to the research questions of interest, and users are aware of both the possible pitfalls and potential involved. Frontiers Media S.A. 2023-08-23 /pmc/articles/PMC10481964/ /pubmed/37680357 http://dx.doi.org/10.3389/fpls.2023.1233794 Text en Copyright © 2023 Poorter, Hummel, Nagel, Fiorani, von Gillhaussen, Virnich, Schurr, Postma, van de Zedde and Wiese-Klinkenberg https://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) and the copyright owner(s) 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 Poorter, Hendrik Hummel, Grégoire M. Nagel, Kerstin A. Fiorani, Fabio von Gillhaussen, Philipp Virnich, Olivia Schurr, Ulrich Postma, Johannes A. van de Zedde, Rick Wiese-Klinkenberg, Anika Pitfalls and potential of high-throughput plant phenotyping platforms |
title | Pitfalls and potential of high-throughput plant phenotyping platforms |
title_full | Pitfalls and potential of high-throughput plant phenotyping platforms |
title_fullStr | Pitfalls and potential of high-throughput plant phenotyping platforms |
title_full_unstemmed | Pitfalls and potential of high-throughput plant phenotyping platforms |
title_short | Pitfalls and potential of high-throughput plant phenotyping platforms |
title_sort | pitfalls and potential of high-throughput plant phenotyping platforms |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481964/ https://www.ncbi.nlm.nih.gov/pubmed/37680357 http://dx.doi.org/10.3389/fpls.2023.1233794 |
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