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High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis
BACKGROUND: Genetic studies and breeding of agricultural crops frequently involve phenotypic characterization of large collections of genotypes grown in field conditions. These evaluations are typically based on visual observations and manual (destructive) measurements. Robust image capture and anal...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902915/ https://www.ncbi.nlm.nih.gov/pubmed/27293473 http://dx.doi.org/10.1186/s13007-016-0132-8 |
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author | Lootens, Peter Ruttink, Tom Rohde, Antje Combes, Didier Barre, Philippe Roldán-Ruiz, Isabel |
author_facet | Lootens, Peter Ruttink, Tom Rohde, Antje Combes, Didier Barre, Philippe Roldán-Ruiz, Isabel |
author_sort | Lootens, Peter |
collection | PubMed |
description | BACKGROUND: Genetic studies and breeding of agricultural crops frequently involve phenotypic characterization of large collections of genotypes grown in field conditions. These evaluations are typically based on visual observations and manual (destructive) measurements. Robust image capture and analysis procedures that allow phenotyping large collections of genotypes in time series during developmental phases represent a clear advantage as they allow non-destructive monitoring of plant growth and performance. A L. perenne germplasm panel including wild accessions, breeding material and commercial varieties has been used to develop a low-cost, high-throughput phenotyping tool for determining plant growth based on images of individual plants during two consecutive growing seasons. Further we have determined the correlation between image analysis-based estimates of the plant’s base area and the capacity to regrow after cutting, with manual counts of tiller number and measurements of leaf growth 2 weeks after cutting, respectively. When working with field-grown plants, image acquisition and image segmentation are particularly challenging as outdoor light conditions vary throughout the day and the season, and variable soil colours hamper the delineation of the object of interest in the image. Therefore we have used several segmentation methods including colour-, texture- and edge-based approaches, and factors derived after a fast Fourier transformation. The performance of the procedure developed has been analysed in terms of effectiveness across different environmental conditions and time points in the season. RESULTS: The procedure developed was able to analyse correctly 77.2 % of the 24,048 top view images processed. High correlations were found between plant’s base area (image analysis-based) and tiller number (manual measurement) and between regrowth after cutting (image analysis-based) and leaf growth 2 weeks after cutting (manual measurement), with r values up to 0.792 and 0.824, respectively. Nevertheless, these relations depend on the origin of the plant material (forage breeding lines, current forage varieties, current turf varieties, and wild accessions) and the period in the season. CONCLUSIONS: The image-derived parameters presented here deliver reliable, objective data, complementary to the breeders’ scores, and are useful for genetic studies. Furthermore, large variation was shown among genotypes for the parameters investigated. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-016-0132-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4902915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49029152016-06-12 High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis Lootens, Peter Ruttink, Tom Rohde, Antje Combes, Didier Barre, Philippe Roldán-Ruiz, Isabel Plant Methods Methodology BACKGROUND: Genetic studies and breeding of agricultural crops frequently involve phenotypic characterization of large collections of genotypes grown in field conditions. These evaluations are typically based on visual observations and manual (destructive) measurements. Robust image capture and analysis procedures that allow phenotyping large collections of genotypes in time series during developmental phases represent a clear advantage as they allow non-destructive monitoring of plant growth and performance. A L. perenne germplasm panel including wild accessions, breeding material and commercial varieties has been used to develop a low-cost, high-throughput phenotyping tool for determining plant growth based on images of individual plants during two consecutive growing seasons. Further we have determined the correlation between image analysis-based estimates of the plant’s base area and the capacity to regrow after cutting, with manual counts of tiller number and measurements of leaf growth 2 weeks after cutting, respectively. When working with field-grown plants, image acquisition and image segmentation are particularly challenging as outdoor light conditions vary throughout the day and the season, and variable soil colours hamper the delineation of the object of interest in the image. Therefore we have used several segmentation methods including colour-, texture- and edge-based approaches, and factors derived after a fast Fourier transformation. The performance of the procedure developed has been analysed in terms of effectiveness across different environmental conditions and time points in the season. RESULTS: The procedure developed was able to analyse correctly 77.2 % of the 24,048 top view images processed. High correlations were found between plant’s base area (image analysis-based) and tiller number (manual measurement) and between regrowth after cutting (image analysis-based) and leaf growth 2 weeks after cutting (manual measurement), with r values up to 0.792 and 0.824, respectively. Nevertheless, these relations depend on the origin of the plant material (forage breeding lines, current forage varieties, current turf varieties, and wild accessions) and the period in the season. CONCLUSIONS: The image-derived parameters presented here deliver reliable, objective data, complementary to the breeders’ scores, and are useful for genetic studies. Furthermore, large variation was shown among genotypes for the parameters investigated. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-016-0132-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-10 /pmc/articles/PMC4902915/ /pubmed/27293473 http://dx.doi.org/10.1186/s13007-016-0132-8 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Lootens, Peter Ruttink, Tom Rohde, Antje Combes, Didier Barre, Philippe Roldán-Ruiz, Isabel High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis |
title | High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis |
title_full | High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis |
title_fullStr | High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis |
title_full_unstemmed | High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis |
title_short | High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis |
title_sort | high-throughput phenotyping of lateral expansion and regrowth of spaced lolium perenne plants using on-field image analysis |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4902915/ https://www.ncbi.nlm.nih.gov/pubmed/27293473 http://dx.doi.org/10.1186/s13007-016-0132-8 |
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