, 215:51 | Cite as

Genotypic variation and relationships among traits for root morphology in a panel of tropical maize inbred lines under contrasting nitrogen levels

  • Lívia Gomes Torres
  • Diego Gonçalves Caixeta
  • Wemerson Mendonça Rezende
  • Andreia Schuster
  • Camila Ferreira Azevedo
  • Fabyano Fonseca e Silva
  • Rodrigo Oliveira DeLimaEmail author


A strategy to increase nitrogen (N) use efficiency in maize is the genetic improvement of N acquisition through root morphology. Here, we quantified the genetic variation of 150 tropical maize inbred lines for root morphology and shoot traits and investigated the relationships among traits. We evaluated the inbred lines at the seedling stage in a greenhouse experiment under two treatments: high N and low N supply. A mixed model approach was used to estimate variance components. Canonical correlations were estimated between root- and shoot-related groups of traits, and the genetic diversity among inbred lines was determined. Our inbred line panel showed huge genetic variability for all traits and presented large genetic diversity under both N levels. Root dry weight (RDW) was associated with shoot dry weight (SDW) at high N, and RDW and total root length (TRL) were positively associated with SDW at low N. Based on SDW, RDW and TRL, we selected a set of the top 15 maize inbred lines to be used in maize breeding programs focusing on N-use efficiency. We therefore concluded that there is a significant diversity in tropical maize inbred lines, which have the genetic potential to produce N-efficient hybrids and maize breeding populations for N stress conditions.


N-use efficiency Abiotic stress Seedling traits Correlation Genetic diversity Selection Zea mays



We thank the National Council for Scientific and Technological Development (CNPq) and the Brazilian Federal Agency for Support and Evaluation of Graduate Education (Capes - Finance Code 001) for financial support.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10681_2019_2373_MOESM1_ESM.xlsx (372 kb)
Panel of tropical maize inbred lines under contrasting nitrogen levels - root traits data Supplementary material 1 (XLSX 372 kb)


  1. Abdel-Ghani AH, Kumar B, Reyes-Matamoros J, Gonzalez-Portilla PJ, Jansen C, Martin JPS, Lubberstedt T (2013) Genotypic variation and relationships between seedlings and adult plant traits in maize (Zea mays L.) inbred lines grown under contrasting nitrogen levels. Euphytica 189:123–133. CrossRefGoogle Scholar
  2. Abendroth LJ, Elmore RW, Boyer MJ, Marlay SK (2011) Corn growth and development. PMR 1009. Iowa State University Ext. AmesGoogle Scholar
  3. Almeida VC, Viana JMS, DeOliveira HM, Risso LA, Ribeiro AFS, DeLima RO (2018) Genetic diversity and path analysis for nitrogen use efficiency of tropical popcorn (Zea mays ssp. everta) inbred lines in adult stage. Plant Breed 137:839–847. CrossRefGoogle Scholar
  4. Almeida VC, Viana JMS, Risso LA, Ribeiro C, DeLima RO (2018) Generation mean analysis for nitrogen and phosphorus uptake, utilization and translocation indexes at vegetative stage in tropical popcorn. Euphtyica 214:103. CrossRefGoogle Scholar
  5. Bates D, Mäechler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67:1–48. CrossRefGoogle Scholar
  6. Birouste M, Zamora-Ledezma E, Bossard C, Pérez-Ramos IM, Roumet C (2014) Measurement of fine root tissue density: a comparison of three methods reveals the potential of root dry matter content. Plant Soil 374:299–313. CrossRefGoogle Scholar
  7. Bouma TJ, Nielson KL, Koutstaal BAS (2000) Sample preparation and scanning protocol for computerized analysis of root length and diameter. Plant Soil 218:185–196. CrossRefGoogle Scholar
  8. Chun L, Mi G, Li J, Chen F, Zhang F (2005) Genetic analysis of maize root characteristics in response to low nitrogen stress. Plant Soil 276:369–382. CrossRefGoogle Scholar
  9. Coque M, Martin A, Veyrieras JB, Hirel B, Gallais A (2008) Genetic variation for N-remobilization and postsilking N-uptake in a set of maize recombinant inbred lines. 3. QTL detection and coincidences. Theor Appl Genet 117: 729.
  10. Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Harlow, Longmans GreenGoogle Scholar
  11. Gallais A, Hirel B (2004) An approach to the genetics of nitrogen use efficiency in maize. J Exp Bot 55:295–306. CrossRefPubMedGoogle Scholar
  12. Gallais A, Coque M (2005) Genetic variation and selection for nitrogen use efficiency in maize: a synthesis. Maydica 50:531–547Google Scholar
  13. Gao K, Chen F, Yuan L, Zhang F, Mi G (2015) A comprehensive analysis of root morphological changes and nitrogen allocation in maize in response to low nitrogen stress. Plant Cell Environ 38:740–750. CrossRefPubMedGoogle Scholar
  14. Garnett T, Conn V, Kaiser BN (2009) Root-based approaches to improving nitrogen use efficiency in plants. Plant Cell Environ 32:1272–1283. CrossRefPubMedGoogle Scholar
  15. Hallauer AR, Miranda Filho JB, Carena MJ (2010) Quantitative genetics in maize breeding. Springer, New YorkGoogle Scholar
  16. Hirel B, Bertin P, Quilleré I, Bourdoncle W, Attagnant C, Dellay C, Gallais A (2001) Towards a better understanding of the genetic and physiological basis for nitrogen use efficiency in maize. Plant Physiol 125:1258–1270. CrossRefPubMedPubMedCentralGoogle Scholar
  17. Hirel B, Gouis JL, Ney B, Gallais A (2007) The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches. J Exp Bot 58:2369–2387. CrossRefPubMedGoogle Scholar
  18. Kumar B, Abdel-Ghani AH, Reyes-Matamoros J, Hochholdinger F, Lubberstedt T (2012) Genotypic variation for root architecture traits in seedlings of maize (Zea mays L.) inbred lines. Plant Breed 131:465–478. CrossRefGoogle Scholar
  19. Kumar B, Abdel-Ghani AH, Pace J, Reyes-Matamoros J, Hochholdinger F, Lubberstedt T (2014) Association analysis of single nucleotide polymorphisms in candidate genes with root traits in maize (Zea mays L.) seedlings. Plant Sci 224:9–19. CrossRefPubMedGoogle Scholar
  20. Li P, Chen F, Cai H, Liu J, Pan Q, Liu Z, Yuan L (2015) A genetic relationship between nitrogen use efficiency and seedling root traits in maize as revealed by QTL analysis. J Exp Bot 66:3175–3188. CrossRefPubMedPubMedCentralGoogle Scholar
  21. Liu ZH, Xie HL, Tian GW, Chen SJ, Wang CL, Hu YM, Tang JH (2008) QTL mapping of nutrient components in maize kernels under low nitrogen conditions. Plant Breed 127:279–285. CrossRefGoogle Scholar
  22. Liu J, Chen F, Olokhnuud C, Glass ADM, Tong Y, Zhang F, Mi G (2009) Root size and nitrogen-uptake in two maize (Zea mays L.) inbred lines differing in nitrogen-use efficiency. J Plant Nutr Soil Sci 172:230–236. CrossRefGoogle Scholar
  23. Lonnquist JH (1961) Progress from recurrent selection procedures for the improvement of corn populations. Nebr. Agric. Exp. Stn. Res. Bull. 197:1–33Google Scholar
  24. Manavalan LP, Musket T, Nguyen HT (2011) Natural genetic variation for root traits among diversity lines of maize (Zea mays L.). Maydica 56:1707–1717Google Scholar
  25. Matonyei TK, Cheprot RK, Liu J, Pineros MA, Shaff JE, Gudu S, Kochian LV (2014) Physiological and molecular analysis of aluminium tolerance in selected Kenyan maize lines. Plant Soil 377:357–367. CrossRefGoogle Scholar
  26. Matson P, Lohse KA, Hall SJ (2002) The globalization of nitrogen deposition: consequences for terrestrial ecosystems. Ambio 31:113–119 CrossRefGoogle Scholar
  27. Mi GH, Chen FJ, Liu JA, Tong YP (2004) Biological potential of nitrogen utilization in crops and its genetic improvement. In: Li Z, et al. (ed) Explore biological potential for soil nutrient utilization and maintain nutrient recycling in soil environment. China Agricultural Press, Beijing, pp 202–216Google Scholar
  28. Mojena R (1977) Hierarchical grouping method and stopping rules: an evaluation. Computer J 20:359–363. CrossRefGoogle Scholar
  29. Moll RH, Kamprath EJ, Jackson WA (1982) Analysis and interpretation of factors which contribute to efficiency of nitrogen utilization. Agron J 74:562–564. CrossRefGoogle Scholar
  30. Montgomery DC, Peck EA (2001) Introduction to linear regression analysis, 3rd edn. Wiley, New YorkGoogle Scholar
  31. Morosini JA, Mendonça LF, Lyra DH, Galli G, Vidotti M, Fritsche-Neto R (2017) Association mapping for traits related to nitrogen use efficiency in tropical maize lines under field conditions. Plant Soil 421:453–463. CrossRefGoogle Scholar
  32. Mu X, Chen F, Wu Q, Chen Q, Wang J, Yuan L, Mi G (2015) Genetic improvement of root growth increases maize yield via enhanced post-silking nitrogen uptake. Eur J Agron 63:55–61. CrossRefGoogle Scholar
  33. Mundim GB, Viana JMS, Maia C, Paes GP, DeLima RO (2013a) Genetic diversity and path analysis for nitrogen use efficiency in popcorn inbred lines. Euphytica 191:291–299. CrossRefGoogle Scholar
  34. Mundim GB, Viana JMS, Maia C (2013b) Early evaluation of popcorn inbred lines for phosphorus use efficiency. Plant Breed 132:613–619. CrossRefGoogle Scholar
  35. Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290. CrossRefPubMedGoogle Scholar
  36. Pestsova E, Lichtblau D, Wever C, Presterl T, Bolduan T, Ouzunova M, Westhoff P (2016) QTL mapping of seedling root traits associated with nitrogen and water use efficiency in maize. Euphytica 209:585–602. CrossRefGoogle Scholar
  37. Reif JC, Hallauer AR, Melchinger AE (2005) Heterosis and heterotic pattern in maize. Maydica 50:215–223Google Scholar
  38. Reimer R, Stich B, Melchinger AE, Schrag TA, Sorensen AP, Stamp P, Hund A (2013) Root response to temperature extremes: association mapping of temperate maize (Zea mays L.). Maydica 58:156–168Google Scholar
  39. Resende MDV (2007) Selegen-REML/BLUP: Sistema estatístico e seleção genética computadorizada via modelos lineares mistos. Embrapa Florestas, ColomboGoogle Scholar
  40. Rodrigues MC, Rezende WM, Silva MEJ, Faria SV, Zuffo LT, Galvão JCC, DeLima RO (2017) Genotypic variation and relationships among nitrogen-use efficiency and agronomic traits in tropical maize inbred lines. Genetic and Molecular Research 16:gmr16039757.
  41. Ruta N, Stamp P, Liedgens M, Fracheboud Y, Hund A (2010) Collocations of QTLs for seedling traits and yield components of tropical maize under water stress conditions. Crop Sci 50:1385–1392. CrossRefGoogle Scholar
  42. Saengwilai P, Tian X, Lynch JP (2014) Low crown root number enhances nitrogen-acquisition from low-nitrogen soils in maize. Plant Physiol 166:581–589. CrossRefPubMedPubMedCentralGoogle Scholar
  43. Sattelmacher B, Thoms K (1995) Morphology and physiology of the seminal root system of young maize (Zea mays L.) plants as influenced by a locally restricted nitrate supply. J Plant Nutr Soil Sci 158:493–497. CrossRefGoogle Scholar
  44. Silva AR, Malafaia G, Menezes IPP (2017) Biotools: an R function to predict spatial gene diversity via an individual-based approach. Genetics and Molecular Research 16:gmr16029655.
  45. Singh YP, Kumar A, Chauhan BPS (1981) Genetic divergence in pearl millet. Indian J Genet Pl Br 41:186–190Google Scholar
  46. Sokal RR, Rohlf FJ (1962) The comparison of dendrograms by objective methods. Taxon 11:30–40CrossRefGoogle Scholar
  47. Sokal RR, Michener CD (1958) A statistical method for evaluating systematic relationships. In University of Kansas Science Bulletin, pp 1409–1438Google Scholar
  48. Torres LG, Rodrigues MC, Lima NL, Trindade TFH, Silva FF, Azevedo CF, DeLima RO (2018) Multi-trait multi-environment Bayesian model reveals G × E interaction for nitrogen use efficiency components in tropical maize. PLoS ONE 13(6):e0199492. CrossRefPubMedPubMedCentralGoogle Scholar
  49. Trachsel S, Messmer R, Stamp P, Hund A (2009) Mapping of QTLs for lateral and axile root growth of tropical maize. Theor Appl Genet 119:1413–1424. CrossRefPubMedGoogle Scholar
  50. Uhart SA, Andrade FH (1995) Nitrogen deficiency in maize: I. Effects on crop growth, development, dry matter partitioning, and kernel set. Crop Sci 35:1376–1383. CrossRefGoogle Scholar
  51. United States Department of Agriculture National Agricultural Statistics Service (2018) Field crops statistics, USDANASS. Accessed 18 June 2018
  52. Uribelarrea M, Crafts-Brandner SJ, Below FE (2009) Physiological N response of field-grown maize hybrids (Zea mays L.) with divergent yield potential and grain protein concentration. Plant Soil 316:151–160. CrossRefGoogle Scholar
  53. Worku M, Bazinger M, Erley GS, Friesen D, Diallo AO, Horst WJ (2007) Nitrogen uptake and utilization in contrasting nitrogen efficient tropical maize hybrids. Crop Sci 47:519–528. CrossRefGoogle Scholar
  54. York LM, Galindo-Castañeda T, Schussler JR, Lynch JP (2015) Evolution of US maize (Zea mays L.) root architectural and anatomical phenes over the past 100 years corresponds to increased tolerance of nitrogen stress. J Exp Bot 66:2347–2358. CrossRefPubMedPubMedCentralGoogle Scholar
  55. Yu P, Li S, White PJ, Li C (2015) A large and deep roots system underlies high nitrogen use efficiency in maize production. PLoS ONE 10(e0126293):e0126293. CrossRefPubMedPubMedCentralGoogle Scholar
  56. Zhang L, Li J, Rong T, Gao S, Wu F, Xu J, Li M, Cao M, Wang J, Hu E, Liu Y, Lu Y (2014) Large-scale screening maize germplasm for low-phosphorus tolerance using multiple selection criteria. Euphytica 197:435–446. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Lívia Gomes Torres
    • 1
  • Diego Gonçalves Caixeta
    • 1
  • Wemerson Mendonça Rezende
    • 1
  • Andreia Schuster
    • 1
  • Camila Ferreira Azevedo
    • 2
  • Fabyano Fonseca e Silva
    • 3
  • Rodrigo Oliveira DeLima
    • 1
    Email author
  1. 1.Department of Plant ScienceUniversidade Federal de ViçosaViçosaBrazil
  2. 2.Department of StatisticsUniversidade Federal de ViçosaViçosaBrazil
  3. 3.Department of Animal ScienceUniversidade Federal de ViçosaViçosaBrazil

Personalised recommendations