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Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images

In this paper we report on an automated procedure to capture and characterize the detailed structure of a crop canopy by means of stereo imaging. We focus attention specifically on the detailed characteristic of canopy height distribution—canopy shoot area as a function of height—which can provide a...

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Detalles Bibliográficos
Autores principales: Cai, Jinhai, Kumar, Pankaj, Chopin, Joshua, Miklavcic, Stanley J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5967702/
https://www.ncbi.nlm.nih.gov/pubmed/29795568
http://dx.doi.org/10.1371/journal.pone.0196671
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author Cai, Jinhai
Kumar, Pankaj
Chopin, Joshua
Miklavcic, Stanley J.
author_facet Cai, Jinhai
Kumar, Pankaj
Chopin, Joshua
Miklavcic, Stanley J.
author_sort Cai, Jinhai
collection PubMed
description In this paper we report on an automated procedure to capture and characterize the detailed structure of a crop canopy by means of stereo imaging. We focus attention specifically on the detailed characteristic of canopy height distribution—canopy shoot area as a function of height—which can provide an elaborate picture of canopy growth and health under a given set of conditions. We apply the method to a wheat field trial involving ten Australian wheat varieties that were subjected to two different fertilizer treatments. A novel camera self-calibration approach is proposed which allows the determination of quantitative plant canopy height data (as well as other valuable phenotypic information) by stereo matching. Utilizing the canopy height distribution to provide a measure of canopy height, the results compare favourably with manual measurements of canopy height (resulting in an R(2) value of 0.92), and are indeed shown to be more consistent. By comparing canopy height distributions of different varieties and different treatments, the methodology shows that different varieties subjected to the same treatment, and the same variety subjected to different treatments can respond in much more distinctive and quantifiable ways within their respective canopies than can be captured by a simple trait measure such as overall canopy height.
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spelling pubmed-59677022018-06-08 Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images Cai, Jinhai Kumar, Pankaj Chopin, Joshua Miklavcic, Stanley J. PLoS One Research Article In this paper we report on an automated procedure to capture and characterize the detailed structure of a crop canopy by means of stereo imaging. We focus attention specifically on the detailed characteristic of canopy height distribution—canopy shoot area as a function of height—which can provide an elaborate picture of canopy growth and health under a given set of conditions. We apply the method to a wheat field trial involving ten Australian wheat varieties that were subjected to two different fertilizer treatments. A novel camera self-calibration approach is proposed which allows the determination of quantitative plant canopy height data (as well as other valuable phenotypic information) by stereo matching. Utilizing the canopy height distribution to provide a measure of canopy height, the results compare favourably with manual measurements of canopy height (resulting in an R(2) value of 0.92), and are indeed shown to be more consistent. By comparing canopy height distributions of different varieties and different treatments, the methodology shows that different varieties subjected to the same treatment, and the same variety subjected to different treatments can respond in much more distinctive and quantifiable ways within their respective canopies than can be captured by a simple trait measure such as overall canopy height. Public Library of Science 2018-05-24 /pmc/articles/PMC5967702/ /pubmed/29795568 http://dx.doi.org/10.1371/journal.pone.0196671 Text en © 2018 Cai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cai, Jinhai
Kumar, Pankaj
Chopin, Joshua
Miklavcic, Stanley J.
Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images
title Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images
title_full Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images
title_fullStr Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images
title_full_unstemmed Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images
title_short Land-based crop phenotyping by image analysis: Accurate estimation of canopy height distributions using stereo images
title_sort land-based crop phenotyping by image analysis: accurate estimation of canopy height distributions using stereo images
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5967702/
https://www.ncbi.nlm.nih.gov/pubmed/29795568
http://dx.doi.org/10.1371/journal.pone.0196671
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