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Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.)
Roots are the most important plant organ for absorbing essential elements, such as water and nutrients for living. To develop new climate-resilient soybean cultivars, it is essential to know the variation in root morphological traits (RMT) among diverse soybean for selecting superior root attribute...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8622990/ https://www.ncbi.nlm.nih.gov/pubmed/34834897 http://dx.doi.org/10.3390/plants10112535 |
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author | Tripathi, Pooja Abdullah, Jamila S. Kim, Jaeyoung Chung, Yong-Suk Kim, Seong-Hoon Hamayun, Muhammad Kim, Yoonha |
author_facet | Tripathi, Pooja Abdullah, Jamila S. Kim, Jaeyoung Chung, Yong-Suk Kim, Seong-Hoon Hamayun, Muhammad Kim, Yoonha |
author_sort | Tripathi, Pooja |
collection | PubMed |
description | Roots are the most important plant organ for absorbing essential elements, such as water and nutrients for living. To develop new climate-resilient soybean cultivars, it is essential to know the variation in root morphological traits (RMT) among diverse soybean for selecting superior root attribute genotypes. However, information on root morphological characteristics is poorly understood due to difficulty in root data collection and visualization. Thus, to overcome this problem in root research, we used a 2-dimensional (2D) root image in identifying RMT among diverse soybeans in this research. We assessed RMT in the vegetative growth stage (V2) of 372 soybean cultivars propagated in polyvinyl chloride pipes. The phenotypic investigation revealed significant variability among the 372 soybean cultivars for RMT. In particular, RMT such as the average diameter (AD), surface area (SA), link average length (LAL), and link average diameter (LAD) showed significant variability. On the contrary RMT, as with total length (TL) and link average branching angle (LABA), did not show differences. Furthermore, in the distribution analysis, normal distribution was observed for all RMT; at the same time, difference was observed in the distribution curve depending on individual RMT. Thus, based on overall RMT analysis values, the top 5% and bottom 5% ranked genotypes were selected. Furthermore, genotypes that showed most consistent for overall RMT have ranked accordingly. This ultimately helps to identify four genotypes (IT 16538, IT 199127, IT 165432, IT 165282) ranked in the highest 5%, whereas nine genotypes (IT 23305, IT 208266, IT 165208, IT 156289, IT 165405, IT 165019, IT 165839, IT 203565, IT 181034) ranked in the lowest 5% for RMT. Moreover, principal component analysis clustered cultivar 2, cultivar 160, and cultivar 274 into one group with high RMT values, and cultivar 335, cultivar 40, and cultivar 249 with low RMT values. The RMT correlation results revealed significantly positive TL and AD correlations with SA (r = 0.96) and LAD (r = 0.85), respectively. However, negative correlations (r = −0.43) were observed between TL and AD. Similarly, AD showed a negative correlation (r = −0.22) with SA. Thus, this result suggests that TL is a more vital factor than AD for determining SA compositions. |
format | Online Article Text |
id | pubmed-8622990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86229902021-11-27 Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) Tripathi, Pooja Abdullah, Jamila S. Kim, Jaeyoung Chung, Yong-Suk Kim, Seong-Hoon Hamayun, Muhammad Kim, Yoonha Plants (Basel) Article Roots are the most important plant organ for absorbing essential elements, such as water and nutrients for living. To develop new climate-resilient soybean cultivars, it is essential to know the variation in root morphological traits (RMT) among diverse soybean for selecting superior root attribute genotypes. However, information on root morphological characteristics is poorly understood due to difficulty in root data collection and visualization. Thus, to overcome this problem in root research, we used a 2-dimensional (2D) root image in identifying RMT among diverse soybeans in this research. We assessed RMT in the vegetative growth stage (V2) of 372 soybean cultivars propagated in polyvinyl chloride pipes. The phenotypic investigation revealed significant variability among the 372 soybean cultivars for RMT. In particular, RMT such as the average diameter (AD), surface area (SA), link average length (LAL), and link average diameter (LAD) showed significant variability. On the contrary RMT, as with total length (TL) and link average branching angle (LABA), did not show differences. Furthermore, in the distribution analysis, normal distribution was observed for all RMT; at the same time, difference was observed in the distribution curve depending on individual RMT. Thus, based on overall RMT analysis values, the top 5% and bottom 5% ranked genotypes were selected. Furthermore, genotypes that showed most consistent for overall RMT have ranked accordingly. This ultimately helps to identify four genotypes (IT 16538, IT 199127, IT 165432, IT 165282) ranked in the highest 5%, whereas nine genotypes (IT 23305, IT 208266, IT 165208, IT 156289, IT 165405, IT 165019, IT 165839, IT 203565, IT 181034) ranked in the lowest 5% for RMT. Moreover, principal component analysis clustered cultivar 2, cultivar 160, and cultivar 274 into one group with high RMT values, and cultivar 335, cultivar 40, and cultivar 249 with low RMT values. The RMT correlation results revealed significantly positive TL and AD correlations with SA (r = 0.96) and LAD (r = 0.85), respectively. However, negative correlations (r = −0.43) were observed between TL and AD. Similarly, AD showed a negative correlation (r = −0.22) with SA. Thus, this result suggests that TL is a more vital factor than AD for determining SA compositions. MDPI 2021-11-21 /pmc/articles/PMC8622990/ /pubmed/34834897 http://dx.doi.org/10.3390/plants10112535 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tripathi, Pooja Abdullah, Jamila S. Kim, Jaeyoung Chung, Yong-Suk Kim, Seong-Hoon Hamayun, Muhammad Kim, Yoonha Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) |
title | Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) |
title_full | Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) |
title_fullStr | Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) |
title_full_unstemmed | Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) |
title_short | Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.) |
title_sort | investigation of root morphological traits using 2d-imaging among diverse soybeans (glycine max l.) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8622990/ https://www.ncbi.nlm.nih.gov/pubmed/34834897 http://dx.doi.org/10.3390/plants10112535 |
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