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The effects of sampling and instrument orientation on LiDAR data from crop plots

Wheat is one of the most widely consumed grains in the world and improving its yield, especially under severe climate conditions, is of great importance to world food security. Phenotyping methods can evaluate plants according to their different traits, such as yield and growth characteristics. Asse...

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Autores principales: Khorsandi, Azar, Tanino, Karen, Noble, Scott D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043300/
https://www.ncbi.nlm.nih.gov/pubmed/36998694
http://dx.doi.org/10.3389/fpls.2023.1087239
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author Khorsandi, Azar
Tanino, Karen
Noble, Scott D.
author_facet Khorsandi, Azar
Tanino, Karen
Noble, Scott D.
author_sort Khorsandi, Azar
collection PubMed
description Wheat is one of the most widely consumed grains in the world and improving its yield, especially under severe climate conditions, is of great importance to world food security. Phenotyping methods can evaluate plants according to their different traits, such as yield and growth characteristics. Assessing the vertical stand structure of plants can provide valuable information about plant productivity and processes, mainly if this trait can be tracked throughout the plant’s growth. Light Detection And Ranging (LiDAR) is a method capable of gathering three-dimensional data from wheat field trials and is potentially suitable for providing non-destructive, high-throughput estimations of the vertical stand structure of plants. The current study considers LiDAR and focuses on investigating the effects of sub-sampling plot data and data collection parameters on the canopy vertical profile (CVP). The CVP is a normalized, ground-referenced histogram of LiDAR point cloud data representing a plot or other spatial domain. The effects of sub-sampling of plot data, the angular field of view (FOV) of the LiDAR and LiDAR scan line orientation on the CVP were investigated. Analysis of spatial sub-sampling effects on CVP showed that at least 144000 random points (600 scan lines) or an area equivalent to three plants along the row were adequate to characterize the overall CVP of the aggregate plot. A comparison of CVPs obtained from LiDAR data for different FOV showed that CVPs varied with the angular range of the LiDAR data, with narrow ranges having a larger proportion of returns in the upper canopy and a lower proportion of returns in the lower part of the canopy. These findings will be necessary to establish minimum plot and sample sizes and compare data from studies where scan direction or field of view differ. These advancements will aid in making comparisons and inform best practices for using close-range LiDAR in phenotypic studies in crop breeding and physiology research.
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spelling pubmed-100433002023-03-29 The effects of sampling and instrument orientation on LiDAR data from crop plots Khorsandi, Azar Tanino, Karen Noble, Scott D. Front Plant Sci Plant Science Wheat is one of the most widely consumed grains in the world and improving its yield, especially under severe climate conditions, is of great importance to world food security. Phenotyping methods can evaluate plants according to their different traits, such as yield and growth characteristics. Assessing the vertical stand structure of plants can provide valuable information about plant productivity and processes, mainly if this trait can be tracked throughout the plant’s growth. Light Detection And Ranging (LiDAR) is a method capable of gathering three-dimensional data from wheat field trials and is potentially suitable for providing non-destructive, high-throughput estimations of the vertical stand structure of plants. The current study considers LiDAR and focuses on investigating the effects of sub-sampling plot data and data collection parameters on the canopy vertical profile (CVP). The CVP is a normalized, ground-referenced histogram of LiDAR point cloud data representing a plot or other spatial domain. The effects of sub-sampling of plot data, the angular field of view (FOV) of the LiDAR and LiDAR scan line orientation on the CVP were investigated. Analysis of spatial sub-sampling effects on CVP showed that at least 144000 random points (600 scan lines) or an area equivalent to three plants along the row were adequate to characterize the overall CVP of the aggregate plot. A comparison of CVPs obtained from LiDAR data for different FOV showed that CVPs varied with the angular range of the LiDAR data, with narrow ranges having a larger proportion of returns in the upper canopy and a lower proportion of returns in the lower part of the canopy. These findings will be necessary to establish minimum plot and sample sizes and compare data from studies where scan direction or field of view differ. These advancements will aid in making comparisons and inform best practices for using close-range LiDAR in phenotypic studies in crop breeding and physiology research. Frontiers Media S.A. 2023-03-14 /pmc/articles/PMC10043300/ /pubmed/36998694 http://dx.doi.org/10.3389/fpls.2023.1087239 Text en Copyright © 2023 Khorsandi, Tanino and Noble 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
Khorsandi, Azar
Tanino, Karen
Noble, Scott D.
The effects of sampling and instrument orientation on LiDAR data from crop plots
title The effects of sampling and instrument orientation on LiDAR data from crop plots
title_full The effects of sampling and instrument orientation on LiDAR data from crop plots
title_fullStr The effects of sampling and instrument orientation on LiDAR data from crop plots
title_full_unstemmed The effects of sampling and instrument orientation on LiDAR data from crop plots
title_short The effects of sampling and instrument orientation on LiDAR data from crop plots
title_sort effects of sampling and instrument orientation on lidar data from crop plots
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043300/
https://www.ncbi.nlm.nih.gov/pubmed/36998694
http://dx.doi.org/10.3389/fpls.2023.1087239
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