Skip to main content
SpringerLink
Log in

QTL mapping of stalk bending strength in a recombinant inbred line maize population

  • Original Paper
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

Stalk bending strength (SBS) is a reliable indicator for evaluating stalk lodging resistance of maize plants. Based on biomechanical considerations, the maximum load exerted to breaking (F max), the breaking moment (M max) and critical stress (σ max) are three important parameters to characterize SBS. We investigated the genetic architecture of SBS by phenotyping F max, M max and σ max of the fourth internode of maize plants in a population of 216 recombinant inbred lines derived from the cross B73 × Ce03005 evaluated in four environments. Heritability of F max, M max and σ max was 0.81, 0.79 and 0.75, respectively. F max and σ max were positively correlated with several other stalk characters. By using a linkage map with 129 SSR markers, we detected two, three and two quantitative trait loci (QTL) explaining 22.4, 26.1 and 17.2 % of the genotypic variance for F max, M max and σ max, respectively. The QTL for F max, M max and σ max located in adjacent bins 5.02 and 5.03 as well as in bin 10.04 for F max were detected with high frequencies in cross-validation. As our QTL mapping results suggested a complex polygenic inheritance for SBS-related traits, we also evaluated the prediction accuracy of two genomic prediction methods (GBLUP and BayesB). In general, we found that both explained considerably higher proportions of the genetic variance than the values obtained in QTL mapping with cross-validation. Nevertheless, the identified QTL regions could be used as a starting point for fine mapping and gene cloning.

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

Similar content being viewed by others

Abbreviations

SBS:

Stalk bending strength

RPR:

Rind penetrometer resistance

NIRS:

Near-infrared reflectance spectroscopy

FIAG:

The fourth internode above ground

F max :

The maximum load exerted to breaking

M max :

Breaking moment

σ max :

Critical stress

Ld:

Larger diameter of cross section

Sd:

Smaller diameter of cross section

InL:

Internode length

FreW:

Fresh weight of the internode

DryW:

Dry weight of the internode

InW:

Internode water content

FreW/V:

Fresh weight of internode per unit volume

DryW/V:

Dry weight of internode per unit volume

ADL/V:

Acid detergent lignin content per unit volume

CEL/V:

Cellulose content per unit volume

References

  • Appenzeller L, Doblin M, Barreiro R, Wang H, Niu X, Kollipara K, Carrigan L, Tomes D, Chapman M, Dhugga KS (2004) Cellulose synthesis in maize: isolation and expression analysis of the cellulose synthase (CesA) gene family. Cellulose 11:287–299

    Article  CAS  Google Scholar 

  • Bai Q (2005) Inheritance of stover quality traits and their determination by near-infrared reflectance spectroscopy (NIRS) in silage maize. Dissertation, China Agricultural University

  • Bohn M, Groh S, Khariallah MM, Hoisington DA, Utz HF, Melchinger AE (2001) Re-evaluation of the prospects of marker-assisted selection for improving insect resistance to Diatraea spp. in tropical maize by cross validation and independent validation. Theor Appl Genet 103:1059–1067

    Article  Google Scholar 

  • Broman KW, Sen S (2009) A Guide to QTL Mapping with R/qtl. Springer

  • Charcosset A, Gallais A (1996) Estimation of the contribution of quantitative trait loci (QTL) to the variance of a quantitative trait by means of genetic markers. Theor Appl Genet 93:1193–1201

    Article  Google Scholar 

  • Ching A, Rafalski JA, Luck S, Butruilie MG (2010) Genetic loci associated with mechanical stalk strength in maize. United States Patent Publication. No. US2010/0015623A1

  • Colbert TR, Darrah LL, Zuber MS (1984) Effect of recurrent selection for stalk crushing strength of agronomic characteristics and soluble stalk solids in maize. Crop Sci 24:473–478

    Article  Google Scholar 

  • Doerge RW, Churchill GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142:285–294

    PubMed  CAS  Google Scholar 

  • Flint-Garcia SA, Jampatong C, Darrah LL, Mcmullen MD (2003) Quantitative trait locus analysis of stalk strength in four maize populations. Crop Sci 43:13–22

    Article  CAS  Google Scholar 

  • Gao M, Guo K, Yang Z, Li X (2003) Study on mechanical properties of corn stalk. Trans CSAM 34:47–49

    Google Scholar 

  • Gere JM, Timoshenko SP (1984) Mechanics of Materials. Van Nostrand Reinhold Company Ltd, New York

    Google Scholar 

  • Gou L, Huang J, Zhang B, Li T, Sun Y, Zhao M (2007) Effect of population density on stalk lodging resistant mechanism and agronomic characteristics of maize. Acta Agronomica Sinia 33:1688–1695

    Google Scholar 

  • Haley CS, Knott SA (1992) A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69:315–324

    Article  PubMed  CAS  Google Scholar 

  • Hallauer AR, Carena MJ, Miranda Filho JB (2010) Quantitative Genetics in Maize Breeding. Springer, New York

    Google Scholar 

  • Hansey CN, Leon N (2011) Biomass yield and cell wall composition of corn with alternative morphologies planted at variable densities. Crop Sci 51:1005–1015

    Article  Google Scholar 

  • Hu H, Meng Y, Wang H, Liu H, Chen S (2012) Identifying quantitative trait loci and determining closely related stalk traits for rind penetrometer resistance in a high-oil maize population. Theor Appl Genet 124:1439–1447

    Article  PubMed  CAS  Google Scholar 

  • Jannink J, Lorenz AJ, Iwata H (2010) Genomic selection in plant breeding: from theory to practice. Brief Funct Genomics 9:166–177

    Article  PubMed  CAS  Google Scholar 

  • Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136:1447–1455

    PubMed  CAS  Google Scholar 

  • Jia Z, Bai Y (1992) Study on identification of lodging in maize inbred line. China seeds 3:30–32

    Google Scholar 

  • Kärkkäinen H, Sillanpää M (2012) Back to basics for Bayesian model building in genomic selection. Genetics 191:969–987

    Article  PubMed  Google Scholar 

  • Kokubo A, Kuraishi S, Sakurai N (1989) Culm strength of barley correlation among maximum bending stress, cell wall dimensions, and cellulose content. Plant Physiol 91:876–882

    Article  PubMed  CAS  Google Scholar 

  • Kokubo A, Sakurai N, Kuraishi S, Takeda K (1991) Culm brittleness of barley (Hordeum vulgare L.) mutants is caused by smaller number of cellulose molecules in cell wall. Plant Physiol 97:509–514

    Article  PubMed  CAS  Google Scholar 

  • Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756

    PubMed  CAS  Google Scholar 

  • Lauer J (1995) High-Oil Corn: advantages and risks. Field Crops 28.31–3

    Google Scholar 

  • Li Y, Qian Q, Zhou Y, Yan M, Sun L, Zhang M, Fu Z, Wang Y, Han B, Pang X, Chen M, Li J (2003) BRITTLE CULM1, which encodes a COBRA-like protein, affects the mechanical properties of rice plants. Plant Cell 15:2020–2031

    Article  PubMed  CAS  Google Scholar 

  • Lorenz AJ, Chao S, Asoro FG, Heffner EL, Hayashi T, Iwata H, Smith HI, Sorrells ME, Jannink JL (2011) Genomic selection in plant breeding: knowledge and prospects. Adv Agron 110:77–123

    Article  Google Scholar 

  • Ma Q (2009) The expression of caffeic acid 3-O-methyltransferase in two wheat genotypes differing in lodging resistance. J Exp Botany 60:2763–2771

    Article  CAS  Google Scholar 

  • Melchinger AE, Utz HF, Piepho HP, Zeng Z, Schön CC (2007) The role of epistasis in the manifestation of heterosis: a system-oriented approach. Genetics 177:1815–1825

    Article  PubMed  CAS  Google Scholar 

  • Meuwissen TH, Hayes BJ, Goddard M (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    PubMed  CAS  Google Scholar 

  • Mode CJ, Robinson HF (1959) Pleiotropism and the genetic variance and covariance. Biometrics 15:518–537

    Article  Google Scholar 

  • Ordas B, Malvar R, Santiago R, Butron A (2010) QTL mapping for Mediterranean corn borer resistance in European flint germplasm using recombinant inbred lines. BMC Genomics 11:174–183

    Article  PubMed  Google Scholar 

  • Papst C, Bohn M, Utz HF, Melchinger AE, Klein D, Eder J (2004) QTL mapping for European corn borer resistance (Ostrinia nubilalis Hb.), agronomic and forage quality traits of testcross progenies in early-maturing European maize (Zea mays L.) germplasm. Theor Appl Genet 108:1545–1554

    Article  PubMed  CAS  Google Scholar 

  • Piepho H-P, Mohring J, Schulz-Streek T, Ogutu JO (2012) A stage-wise approach of the analysis of multi-environment trials. Biometrical J 00:1–17

    Google Scholar 

  • SAS Institute Inc (2008) SAS user’s guide, version9.2. SAS institute Cary, NC

  • Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464

    Article  Google Scholar 

  • Shenk JS, Westerhaus MO (1991) Population structuring of near infrared spectra and modified partial least square regression. Crop Sci 31:1548–1555

    Article  CAS  Google Scholar 

  • Sibale EM, Darrah LL, Zuber MS (1992) Comparison of two rind penetrometers for measurement of stalk strength in maize. Maydica 37:111–114

    Google Scholar 

  • Stojsin R, Ivanovic M, Kojic L, Stojsin D (1991) Inheritance of grain yield and several stalk characteristics significant in resistance to stalk lodging maize (Zea mays L.). Maydica 36:75–81

    Google Scholar 

  • Sun X (1987) Studies on the resistance of the culms of rice to lodging. Scientia Agricultura Scinica 20:32–37

    Google Scholar 

  • R Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org/

  • Technow F, Melchinger AE (2013) Genomic prediction of dichotomous traits with Bayesian logistic models. Theor Appl Genet 126:1133–1143

    Article  PubMed  Google Scholar 

  • Technow F, Bürger A, Melchinger AE (2013) Genomic prediction of northern corn leaf blight resistance in maize with combined or separated training sets for heterotic groups. G3 3:197–203

    Google Scholar 

  • Thompson DL (1963) Stalk strength of corn as measured by crushing strength and rind thickness. Crop Sci 3:323–329

    Article  Google Scholar 

  • Utz HF (2010) PLABSTAT: a computer program for statistical analysis of plant breeding experiments. Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, Stuttgart, Germany

  • Utz HF, Melchinger AE, Schön CC (2000) Bias and sampling error of the estimated proportion of genotypic variance explained by quantitative trait loci determined from experimental data in maize using cross validation and validation with independent samples. Genetics 154:1839–1849

    PubMed  Google Scholar 

  • Wang H (2009) QTL analysis and genetic relationship between kernel compositions and stalk nutrition quality traits in high oil maize population. Dissertation, China Agricultural University

  • Wang J, Li H, Zhang L, Li C, Meng L (2010) Users’ Manual of QTL IciMapping V3.0, Beijing

  • Würschum T, Liu W, Gowda M, Maurer HP, Fischer S, Schechert, Reif JC (2012) Comparison of biometrical models for joint linkage association mapping. Heredity 108:332–340

  • Xu S (2008) Quantitative trait locus mapping can benefit from segregation distortion. Genetics 180:2201–2208

    Article  PubMed  Google Scholar 

  • Yuan Z, Feng B, Zhao A, Liang A (2002) Dynamic analysis and comprehensive evaluation of crop-stem lodging resistance. Trans CSAE 18(6):30–31

    Google Scholar 

  • Zeng Z (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468

    PubMed  CAS  Google Scholar 

  • Zhang L, Wang S, Li H, Deng Q, Zheng A, Li S, Li P, Li Z, Wang J (2010) Effects of missing marker and segregation distortion on QTL mapping in F2 populations. Theor Appl Genet 121:1071–1082

    Article  PubMed  Google Scholar 

  • Zuber MS, Grogan CO (1961) A new technique for measuring stalk strength in corn. Crop Sci 1:378–380

    Article  Google Scholar 

  • Zuber MS, Colbert TR, Bauman LF (1977) Effect of brown-midrib-3 mutant in maize (Zea mays) on stalk strength. Z Pflanzenzuecht 79:310–314

    Google Scholar 

  • Zuber MS, Colbert TR, Darrah LL (1980) Effect of recurrent selection for crushing strength on several stalk components in maize. Crop Sci 20:711–717

    Article  Google Scholar 

Download references

Acknowledgments

We thank Lianying Yu, Baohua Liu and Yan Luo of China Agricultural University for their help in the three-point bending test. We also thank H. Fritz Utz, Tobias Schrag and Xuefei Mi for their suggestions on the data analysis. This research was supported by grants from the Modern Maize Industry Technology System Foundation of China (No. nycytx-02) to S. Chen, DFG, Grant No. 1070/1, International Research Training Group “Sustainable Resource Use in North China” to A.E. Melchinger and National Natural Science Foundation of China (No. 10972234) to Z. Fu.

Author information

Authors and Affiliations

  1. National Maize Improvement Center of China, China Agricultural University (West Campus), 2# Yuanmingyuan West Road, Beijing, 100193, China

    Haixiao Hu, Wenxin Liu & Shaojiang Chen

  2. Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University (West Campus), 2# Yuanmingyuan West Road, Beijing, 100193, China

    Wenxin Liu & Shaojiang Chen

  3. Applicational Mechanics Department, College of Science, China Agricultural University (East Campus), 17# Qinghua East Road, Beijing, 100083, China

    Zhiyi Fu, Chengliang Song & Shitu Li

  4. Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, 70599, Stuttgart, Germany

    Haixiao Hu, Linda Homann, Frank Technow & Albrecht E. Melchinger

  5. Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12# Zhongguancun South Street, Beijing, 100081, China

    Hongwu Wang

Authors
  1. Haixiao Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenxin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhiyi Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Linda Homann
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Frank Technow
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hongwu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chengliang Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Shitu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Albrecht E. Melchinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Shaojiang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Albrecht E. Melchinger or Shaojiang Chen.

Additional information

Communicated by N. de Leon.

H. Hu and W. Liu contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 213 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hu, H., Liu, W., Fu, Z. et al. QTL mapping of stalk bending strength in a recombinant inbred line maize population. Theor Appl Genet 126, 2257–2266 (2013). https://doi.org/10.1007/s00122-013-2132-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-013-2132-7

Keywords

Search

Navigation