ArticlePlants (Basel, Switzerland)2021
Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (
Article in Plants (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Exogenous 6-Benzyladenine and Kinetin Restrict Rice Seedling Root Growth, andPlants (Basel, Switzerland) · 2026Article
- Quantitative analysis of root system architecture and fresh weight biomass traits highlight phenotypic variation in radish (Raphanus sativus L.) germplasm.Scientific reports · 2026Article
- Understanding the genetics of root system architecture in pigeonpea [Cajanus cajan (L.) Millsp.].TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data.International journal of molecular sciences · 2024Article
- High-Throughput Phenotypic Characterization and Diversity Analysis of Soybean Roots (Plants (Basel, Switzerland) · 2022Article
- Advanced High-Throughput Root Phenotyping and GWAS Identifies Key Genomic Regions in Cowpea During Vegetative Growth Stage.Physiologia plantarumArticle
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7 authors.
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Abstract
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.
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