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Quantifying cereal crop movement through hemispherical video analysis of agricultural plots
BACKGROUND: Violent movement of crop stems can lead to failure under high winds. Known as lodging, this phenomenon is particularly detrimental to cool-season cereals such as oat, barley, and wheat; contributing to yield and economic losses. Phenotyping the movement of cereal crops in real-time could...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533727/ https://www.ncbi.nlm.nih.gov/pubmed/31139244 http://dx.doi.org/10.1186/s13007-019-0437-5 |
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author | Susko, Alexander Q. Marchetto, Peter Jo Heuschele, D. Smith, Kevin P. |
author_facet | Susko, Alexander Q. Marchetto, Peter Jo Heuschele, D. Smith, Kevin P. |
author_sort | Susko, Alexander Q. |
collection | PubMed |
description | BACKGROUND: Violent movement of crop stems can lead to failure under high winds. Known as lodging, this phenomenon is particularly detrimental to cool-season cereals such as oat, barley, and wheat; contributing to yield and economic losses. Phenotyping the movement of cereal crops in real-time could aid in the breeding and selecting of lodging resistant cereals. Since no methods exist to quantify dynamic, real time plant responses in an agricultural setting, we devised a video analysis protocol to quantify mean frequency and amplitude of plant movement for a 360° field of view camera system. RESULTS: We present both the image analysis method for identifying predefined regions of a 2D field design as they appear on 360° field of view video, as well as a signal processing pipeline to quantify movement from time varying color signals from plot canopies within these predefined field regions. We detected significant differences in the natural frequency and amplitude of plant movement from video of 16 cereal cultivars planted in a randomized complete block design on five different windy days. Natural frequencies quantified by this method averaged 1.37 Hz, while over 2.5-fold differences in amplitude within similar frequency ranges were detected across the 16 cereal cultivars. CONCLUSIONS: This method is sensitive enough to systematically differentiate small frequency and amplitude differences in cultivar movement, and shows promise for investigating the physiological basis for differences in cereal movement and lodging resistance. The relative accuracy of the plot demarcation protocol suggests it could be used for other high-throughput phenotyping applications that require both high image resolution and a large field of view. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13007-019-0437-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6533727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65337272019-05-28 Quantifying cereal crop movement through hemispherical video analysis of agricultural plots Susko, Alexander Q. Marchetto, Peter Jo Heuschele, D. Smith, Kevin P. Plant Methods Methodology BACKGROUND: Violent movement of crop stems can lead to failure under high winds. Known as lodging, this phenomenon is particularly detrimental to cool-season cereals such as oat, barley, and wheat; contributing to yield and economic losses. Phenotyping the movement of cereal crops in real-time could aid in the breeding and selecting of lodging resistant cereals. Since no methods exist to quantify dynamic, real time plant responses in an agricultural setting, we devised a video analysis protocol to quantify mean frequency and amplitude of plant movement for a 360° field of view camera system. RESULTS: We present both the image analysis method for identifying predefined regions of a 2D field design as they appear on 360° field of view video, as well as a signal processing pipeline to quantify movement from time varying color signals from plot canopies within these predefined field regions. We detected significant differences in the natural frequency and amplitude of plant movement from video of 16 cereal cultivars planted in a randomized complete block design on five different windy days. Natural frequencies quantified by this method averaged 1.37 Hz, while over 2.5-fold differences in amplitude within similar frequency ranges were detected across the 16 cereal cultivars. CONCLUSIONS: This method is sensitive enough to systematically differentiate small frequency and amplitude differences in cultivar movement, and shows promise for investigating the physiological basis for differences in cereal movement and lodging resistance. The relative accuracy of the plot demarcation protocol suggests it could be used for other high-throughput phenotyping applications that require both high image resolution and a large field of view. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13007-019-0437-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-24 /pmc/articles/PMC6533727/ /pubmed/31139244 http://dx.doi.org/10.1186/s13007-019-0437-5 Text en © The Author(s) 2019 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 Susko, Alexander Q. Marchetto, Peter Jo Heuschele, D. Smith, Kevin P. Quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
title | Quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
title_full | Quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
title_fullStr | Quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
title_full_unstemmed | Quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
title_short | Quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
title_sort | quantifying cereal crop movement through hemispherical video analysis of agricultural plots |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533727/ https://www.ncbi.nlm.nih.gov/pubmed/31139244 http://dx.doi.org/10.1186/s13007-019-0437-5 |
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