Skip to main content
SpringerLink
Log in

Investigation of root phenotype in soybeans (Glycine max L.) using imagery data

  • Original Research
  • Published:
Journal of Crop Science and Biotechnology Aims and scope Submit manuscript

Abstract

Roots are the most essential plant part owing to the uptake of water and nutrients. Therefore, phenotyping of root features is vital for improving soybean cultivars. This study evaluated the root morphological and architectural traits of six soybean cultivars using two-dimensional (2D) root imaging. The cultivars were selected from a previous experiment, based on 6 root phenotypes (total root length [TRL], surface area [SA], average diameter [AD], number of tips, number of forks, and main total length [MTL]) in 372 soybean cultivars, (3 each from the highest 5% and lowest 5%). When plants reached two trifoliate leaves stage, both root and shoot parts were harvested and analyzed. According to the analysis of variance, significant variability was observed between the two groups (highest 5% and lowest 5%) for root and shoot morphological traits, but no significant difference was found regarding most root architectural traits. Among three root phenotypes (TRL, SA, and RV [root volume]), IT 21595 and IT 165432 were the highest and lowest, respectively. TRL exhibited a significant positive correlation with other root and shoot morphological traits, such as SA, RV, leaf area, leaf length, and leaf width. Contrastingly, AD showed a significant negative correlation with those parameters. TRL and SA of all the cultivars were classified based on root diameter classes (0–0.5 mm, 0.5–1.0 mm, and 1.0–1.5 mm). A segment of TRL < 0.5-mm root diameter was observed from 74.0 to 75.6% in the highest 5% cultivars and 63.7–75.3% in the lowest 5% cultivars. A segment of SA < 0.5-mm root diameter was observed from 42.0 to 46.9% in the highest 5% cultivars and a relatively reduced ratio (34.5–44.7%) in the lowest 5% cultivars. Conclusively, this research highlighted the characterization of root morphological and architectural traits and some soybean cultivars.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Asfaw A, Blair MW (2012) Quantitative trait loci for rooting pattern traits of common beans grown under drought stress versus non-stress conditions. Mol Breed 30(2):681–695

    Article  Google Scholar 

  • Biscarini F, Cozzi P, Casella L, Riccardi P, Vattari A, Orasen G, Perrini R, Tacconi G, Tondelli A, Biselli C, Gattivelli L, Spindel J, McCouch S, Abbruscato P, Valé G, Piffanelli P, Greco R (2016) Genome-wide association study for traits related to plant and grain morphology, and root architecture in temperate rice accessions. PLoS ONE 11(5):e0155425

    Article  Google Scholar 

  • Christopher J, Christopher M, Jennings R, Jones S, Fletcher S, Borrell A, Manschadi AM, Jordan D, Mace E, Hammer G (2013) QTL for root angle and number in a population developed from bread wheats (Triticum aestivum) with contrasting adaptation to water-limited environments. Theor Appl Genet 126(6):1563–1574

    Article  CAS  Google Scholar 

  • Chung YS, Kim K-S, Hamayun M, Kim Y (2020a) Silicon confers soybean resistance to salinity stress through regulation of reactive oxygen and reactive nitrogen species. Front Plant Sci. https://doi.org/10.3389/fpls.2019.01725

    Article  PubMed  PubMed Central  Google Scholar 

  • Chung YS, Lee U, Heo S, Silva RR, Na C-I, Kim Y (2020b) Image-based machine learning characterizes root nodule in soybean exposed to silicon. Front Plant Sci 11:520161. https://doi.org/10.3389/fpls.2020.520161

    Article  PubMed  PubMed Central  Google Scholar 

  • Comas LH, Becker SR, von Cruz MV, Byrne PF, Dierig DA (2013) Root traits contributing to plant productivity under drought. Fron Plant Sci 4:442. https://doi.org/10.3389/fpls.2013.00442

    Article  Google Scholar 

  • Dayoub E, Lamichhane JR, Schoving C, Debaeke P, Maury P (2021) Early-stage phenotyping of root traits provides insights into the drought tolerance level of soybean cultivars. Agronomy 11(1):188

    Article  CAS  Google Scholar 

  • Fenta BA, Beebe SE, Kunert KJ, Burridge JD, Barlow KM, Lynch JP, Foyer CH (2014) Field phenotyping of soybean roots for drought stress tolerance. Agronomy 4(3):418–435

    Article  Google Scholar 

  • Foyer C, Lam H, Nguyen H, Siddique K, Varshney R, Colmer T, Cowling W, Bramley H, Mori T, Hodgson J (2016) Neglecting legumes has compromised human health and sustainable food production. Nat Plants 2:16112

    Article  Google Scholar 

  • Friendly M (2002) Corrgrams: exploratory displays for correlation matrices. Am Stat 56(4):316–324

    Article  Google Scholar 

  • Ghosh D, Xu J (2014) Abiotic stress responses in plant roots: a proteomics perspective. Front Plant Sci. https://doi.org/10.3389/fpls.2014.00006

    Article  PubMed  PubMed Central  Google Scholar 

  • Guerrero-Campo J, Fitter AH (2001) Relationships between root characteristics and seed size in two contrasting floras. Acta Oecologica 22(2):77–85

    Article  Google Scholar 

  • Hertel D, Strecker T, Müller-Haubold H, Leuschner C (2013) Fine root biomass and dynamics in beech forests across a precipitation gradient–is optimal resource partitioning theory applicable to water-limited mature trees? J Ecol 101(5):1183–1200

    Article  Google Scholar 

  • Hungria M, Bohrer T (2000) Variability of nodulation and dinitrogen fixation capacity among soybean cultivars. Biol Fertil Soils 31(1):45–52

    Article  CAS  Google Scholar 

  • Kim K-S, Kim S-H, Kim J, Tripathi P, Lee J-D, Chung YS, Kim Y (2021) A large root phenome dataset wide-opened the potential for underground breeding in soybean. Front Plant Sci. https://doi.org/10.3389/fpls.2021.704239

    Article  PubMed  PubMed Central  Google Scholar 

  • Kim Y, Chung YS, Lee E, Tripathi P, Heo S, Kim K-H (2020) Root response to drought stress in rice (Oryza sativa L.). Int J Mol Sci 21(4):1513

    Article  CAS  Google Scholar 

  • Le DT, Nishiyama R, Watanabe Y, Tanaka M, Seki M, Ham LH, Yamaguchi-Shinozaki K, Shinozaki K, Tran L-SP (2012) Differential gene expression in soybean leaf tissues at late developmental stages under drought stress revealed by genome-wide transcriptome analysis. PLoS ONE 7(11):e49522

    Article  CAS  Google Scholar 

  • López-Bucio J, Cruz-Ramırez A, Herrera-Estrella L (2003) The role of nutrient availability in regulating root architecture. Curr Opin Plant Biol 6(3):280–287

    Article  Google Scholar 

  • Manavalan LP, Guttikonda SK, Nguyen VT, Shannon JG, Nguyen HT (2010) Evaluation of diverse soybean germplasm for root growth and architecture. Plant Soil 330(1):503–514

    Article  CAS  Google Scholar 

  • Park Y-G, Park S-M, Na C-I, Kim Y (2019) Identification of optimal concentration of silicon application and its roles in uptake of essential nutrients in soybean (Glycine max L.). J Crop Sci Biotechnol 22(1):1–10

    Article  Google Scholar 

  • Prince SJ, Murphy M, Mutava RN, Durnell LA, Valliyodan B, Shannon JG, Nguyen HT (2017) Root xylem plasticity to improve water use and yield in water-stressed soybean. J Exp Bot 68(8):2027–2036

    CAS  PubMed  PubMed Central  Google Scholar 

  • Reis L, Santos e Silva CM, Bezerra B, Mutti P, Spyrides MH, Silva P, Magalhães T, Ferreira R, Rodrigues D, Andrade L (2020) Influence of climate variability on soybean yield in MATOPIBA, Brazil. Atmosphere 11(10):1130

    Article  Google Scholar 

  • Rincon CA, Raper J, David C, Patterson RP (2003) Genotypic differences in root anatomy affecting water movement through roots of soybean. Int J Plant Sci 164(4):543–551

    Article  Google Scholar 

  • Tripathi P, Na C-I, Kim Y (2021) Effect of silicon fertilizer treatment on nodule formation and yield in soybean (Glycine max L.). Eur J Agronomy 122:126172

    Article  CAS  Google Scholar 

  • Turner NC, Wright GC, Siddique K (2001) Adaptation of grain legumes (pulses) to water-limited environments: selection for physiological, biochemical, and yield component characteristics for improved drought resistance. In: Saxena NP (ed) Management of agricultural drought: agronomic and genetic options. Science Publishers, Inc., USA, pp 43–80

  • Uga Y, Sugimoto K, Ogawa S, Rane J, Ishitani M, Hara N, Kitomi Y, Inukai Y, Ono K, Kanno N (2013) Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nat Genet 45(9):1097–1102

    Article  CAS  Google Scholar 

  • Xiong R, Liu S, Considine MJ, Siddique KH, Lam HM, Chen Y (2021) Root system architecture, physiological and transcriptional traits of soybean (Glycine max L.) in response to water deficit: a review. Physiol Plant 172(2):405–418

    Article  CAS  Google Scholar 

  • Xu W, Cui K, Xu A, Nie L, Huang J, Peng S (2015) Drought stress condition increases root to shoot ratio via alteration of carbohydrate partitioning and enzymatic activity in rice seedlings. Acta Physiol Plant 37(2):9

    Article  Google Scholar 

  • Zhao C, Liu B, Piao S, Wang X, Lobell DB, Huang Y, Huang M, Yao Y, Bassu S, Ciais P (2017) Temperature increase reduces global yields of major crops in four independent estimates. Proc Natl Acad Sci 114(35):9326–9331

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was supported by Kyungpook National University Research Fund, 2021.

Author information

Authors and Affiliations

  1. Department of Applied Biosciences, Kyungpook National University, Daegu, 41566, Republic of Korea

    Pooja Tripathi & Yoonha Kim

Authors
  1. Pooja Tripathi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yoonha Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoonha Kim.

Ethics declarations

Conflict of interest

The authors declare no conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tripathi, P., Kim, Y. Investigation of root phenotype in soybeans (Glycine max L.) using imagery data. J. Crop Sci. Biotechnol. 25, 233–241 (2022). https://doi.org/10.1007/s12892-021-00126-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12892-021-00126-0

Keywords

Search

Navigation