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Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series

Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment. Terrestrial laser scanning (TLS) is a well-suited tool to study structural rhythm under field conditions. Recent studies have used TLS to describe the structural rhythm of...

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Autores principales: Jin, Shichao, Su, Yanjun, Zhang, Yongguang, Song, Shilin, Li, Qing, Liu, Zhonghua, Ma, Qin, Ge, Yan, Liu, LingLi, Ding, Yanfeng, Baret, Frédéric, Guo, Qinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441379/
https://www.ncbi.nlm.nih.gov/pubmed/34557676
http://dx.doi.org/10.34133/2021/9895241
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author Jin, Shichao
Su, Yanjun
Zhang, Yongguang
Song, Shilin
Li, Qing
Liu, Zhonghua
Ma, Qin
Ge, Yan
Liu, LingLi
Ding, Yanfeng
Baret, Frédéric
Guo, Qinghua
author_facet Jin, Shichao
Su, Yanjun
Zhang, Yongguang
Song, Shilin
Li, Qing
Liu, Zhonghua
Ma, Qin
Ge, Yan
Liu, LingLi
Ding, Yanfeng
Baret, Frédéric
Guo, Qinghua
author_sort Jin, Shichao
collection PubMed
description Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment. Terrestrial laser scanning (TLS) is a well-suited tool to study structural rhythm under field conditions. Recent studies have used TLS to describe the structural rhythm of trees, but no consistent patterns have been drawn. Meanwhile, whether TLS can capture structural rhythm in crops is unclear. Here, we aim to explore the seasonal and circadian rhythms in maize structural traits at both the plant and leaf levels from time-series TLS. The seasonal rhythm was studied using TLS data collected at four key growth periods, including jointing, bell-mouthed, heading, and maturity periods. Circadian rhythms were explored by using TLS data acquired around every 2 hours in a whole day under standard and cold stress conditions. Results showed that TLS can quantify the seasonal and circadian rhythm in structural traits at both plant and leaf levels. (1) Leaf inclination angle decreased significantly between the jointing stage and bell-mouthed stage. Leaf azimuth was stable after the jointing stage. (2) Some individual-level structural rhythms (e.g., azimuth and projected leaf area/PLA) were consistent with leaf-level structural rhythms. (3) The circadian rhythms of some traits (e.g., PLA) were not consistent under standard and cold stress conditions. (4) Environmental factors showed better correlations with leaf traits under cold stress than standard conditions. Temperature was the most important factor that significantly correlated with all leaf traits except leaf azimuth. This study highlights the potential of time-series TLS in studying outdoor agricultural chronobiology.
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spelling pubmed-84413792021-09-22 Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series Jin, Shichao Su, Yanjun Zhang, Yongguang Song, Shilin Li, Qing Liu, Zhonghua Ma, Qin Ge, Yan Liu, LingLi Ding, Yanfeng Baret, Frédéric Guo, Qinghua Plant Phenomics Research Article Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment. Terrestrial laser scanning (TLS) is a well-suited tool to study structural rhythm under field conditions. Recent studies have used TLS to describe the structural rhythm of trees, but no consistent patterns have been drawn. Meanwhile, whether TLS can capture structural rhythm in crops is unclear. Here, we aim to explore the seasonal and circadian rhythms in maize structural traits at both the plant and leaf levels from time-series TLS. The seasonal rhythm was studied using TLS data collected at four key growth periods, including jointing, bell-mouthed, heading, and maturity periods. Circadian rhythms were explored by using TLS data acquired around every 2 hours in a whole day under standard and cold stress conditions. Results showed that TLS can quantify the seasonal and circadian rhythm in structural traits at both plant and leaf levels. (1) Leaf inclination angle decreased significantly between the jointing stage and bell-mouthed stage. Leaf azimuth was stable after the jointing stage. (2) Some individual-level structural rhythms (e.g., azimuth and projected leaf area/PLA) were consistent with leaf-level structural rhythms. (3) The circadian rhythms of some traits (e.g., PLA) were not consistent under standard and cold stress conditions. (4) Environmental factors showed better correlations with leaf traits under cold stress than standard conditions. Temperature was the most important factor that significantly correlated with all leaf traits except leaf azimuth. This study highlights the potential of time-series TLS in studying outdoor agricultural chronobiology. AAAS 2021-09-06 /pmc/articles/PMC8441379/ /pubmed/34557676 http://dx.doi.org/10.34133/2021/9895241 Text en Copyright © 2021 Shichao Jin et al. https://creativecommons.org/licenses/by/4.0/Exclusive Licensee Nanjing Agricultural University. Distributed under a Creative Commons Attribution License (CC BY 4.0).
spellingShingle Research Article
Jin, Shichao
Su, Yanjun
Zhang, Yongguang
Song, Shilin
Li, Qing
Liu, Zhonghua
Ma, Qin
Ge, Yan
Liu, LingLi
Ding, Yanfeng
Baret, Frédéric
Guo, Qinghua
Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
title Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
title_full Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
title_fullStr Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
title_full_unstemmed Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
title_short Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
title_sort exploring seasonal and circadian rhythms in structural traits of field maize from lidar time series
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441379/
https://www.ncbi.nlm.nih.gov/pubmed/34557676
http://dx.doi.org/10.34133/2021/9895241
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