Advertisement

Euphytica

, Volume 196, Issue 2, pp 261–270 | Cite as

Genetic analysis of drought tolerance in adapted × exotic crosses of maize inbred lines under managed stress conditions

  • M. A. Adebayo
  • A. Menkir
  • E. Blay
  • V. Gracen
  • E. Danquah
  • S. Hearne
Article

Abstract

Introduced maize (Zea mays L.) germplasm can serve as sources of favorable alleles to enhance performance in new maize varieties and hybrids under drought stress conditions. In the present study, the combining abilities of 12 exotic maize inbred lines from CIMMYT and 12 adapted maize inbred lines from IITA were studied for grain yield and other traits under controlled drought stress. The inbred lines from each institution were separated into groups using SSR-based genetic diversity and were intercrossed using a factorial mating scheme to generate 96 hybrids. These hybrids were evaluated under both controlled drought stress and well-watered conditions at Ikenne in Nigeria in 2010 and 2011. Average mean yields of hybrids under drought stress represented 23 % of the average yield of hybrids under full irrigation. General combining ability (GCA) effects accounted for 49–85 % of the observed variation for several traits recorded under both well-watered and drought stress conditions. Specific combining ability effects for grain yield, though positive in most hybrids, were not significant under drought stress conditions. All the twelve exotic and nine adapted lines had positive GCA effects (female, male, or both) for grain yield under either drought stress or full irrigation, or both environments. EXL03 and EXL15 that had positive and significant female and male GCA effects for grain yield under both environments can be used to improve their adapted counterparts for grain yield and drought tolerance. Normalized difference vegetation index had weak but significant correlation with grain yield.

Keywords

Drought tolerance GCA Maize germplasm NDVI SCA 

Notes

Acknowledgments

This report is a part of Ph.D. thesis research fully funded by the Alliance for a Green Revolution in Africa (AGRA) at West Africa Centre for Crop Improvement (WACCI), University of Ghana, Legon, and the International Institute of Tropical Agriculture. The lead author is immensely grateful for the funding. All the staff members of the Maize Improvement Unit at the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria, are appreciated for providing technical supports during field trials.

References

  1. Adebayo, M.A, 2012. Genetic analyses of drought tolerance in crosses of adapted and exotic maize (Zea mays L.) inbred lines. A Ph.D. thesis submitted to the West Africa Centre for Crop Improvement, University of Ghana, LegonGoogle Scholar
  2. Araus JL, Sanchez C, Cabrera-Bosquet L (2010) Is heterosis in maize mediated through better water use? New Phytol 187:392–406CrossRefPubMedGoogle Scholar
  3. Banziger M, Edmeades GO, Beck D, Bellon M (2000) Breeding for drought and nitrogen stress tolerance in maize: from theory to practice. CIMMYT, MexicoGoogle Scholar
  4. Barker DW, Sawyer JE (2012) Using active canopy sensors to quantify corn nitrogen stress and nitrogen application rate. Agron J 102(3):964–971CrossRefGoogle Scholar
  5. Betran FJ, Beck D, Banziger M, Edmeades GO (2003) Secondary traits in parental inbreds and hybrids under stress and non-stress environments in tropical maize. Field Crops Res 83:51–65CrossRefGoogle Scholar
  6. Bolanos J, Edmeades GO (1996) The importance of the anthesis-silking-interval in breeding for drought tolerance in tropical maize. Field Crops Res 48:65–80CrossRefGoogle Scholar
  7. Cabrera-Bosquet L, Molero G, Stellacci AM, Bort JS, Nogués S, Araus JL (2011) NDVI as a potential tool for predicting biomass, plant nitrogen content and growth in wheat genotypes subjected to different water and nitrogen conditions. Cereal Res Commun 39(1):147–159CrossRefGoogle Scholar
  8. Campos H, Cooper M, Habben JE, Edmeades GO, Schussler JR (2004) Improving drought tolerance in maize: a view from industry. Field Crops Res 90:19–34CrossRefGoogle Scholar
  9. Chapman SC, Edmeades GO (1999) Selection improves drought tolerance in tropical maize populations: II. Direct and correlated responses among secondary traits. Crop Sci 39:1315–1324CrossRefGoogle Scholar
  10. Comstock RE, Robinson HF (1948) The components of genetic variance in population of biparental progenies and their use in estimating the average degree of dominance. Biometrics 4:254–266CrossRefPubMedGoogle Scholar
  11. Derera J, Tongoona P, Vivek BS, Laing MD (2008) Gene action controlling grain yield and secondary traits in southern African maize hybrids under drought and non-drought environments. Euphytica 162(3):411–422CrossRefGoogle Scholar
  12. Dhliwayo T, Pixley K, Menkir A, Warburton M (2009) Combining ability, genetic distances, and heterosis among elite CIMMYT and IITA tropical maize inbred lines. Crop Sci 49:1201–1210CrossRefGoogle Scholar
  13. Eberhart SA, Salhuana W, Sevilla R, Taba S (1995) Principles of tropical maize breeding. Maydica 40:339–355Google Scholar
  14. Edmeades, G.O., J. Bolanos, H.R. Lafitte (1992) Progress in breeding for drought tolerance in maize. Proceedings of the 47th Annual Corn and Sorghum Industry Research Conference, Chicago, 1992. American Seed Trade Association, 93–111Google Scholar
  15. Edmeades GO, Bolanos J, Chapman SC, Lafitte HR, Banziger M (1999) Selection improves drought tolerance in tropical maize populations: I. Gains in biomass, grain yield, and harvest index. Crop Sci 39:1306–1315CrossRefGoogle Scholar
  16. Everett LA, Eta-Ndu JT, Ndioro M, Tabi I, Kim SK (1994a) Registration of 18 first-cycle tropical midaltitude maize germplasm lines. Crop Sci 34:1422CrossRefGoogle Scholar
  17. Everett LA, Eta-Ndu JT, Ndioro M, Tabi I, Kim SK (1994b) Registration of 19 second-cycle tropical midaltitude maize germplasm lines. Crop Sci 34:1419–1420CrossRefGoogle Scholar
  18. Freeman KW, Girma K, Arnall DB, Mullen RW, Martin KL, Teal RK, Raun WR (2007) By-plant prediction of corn forage biomass and nitrogen uptake at various growth stages using remote sensing and plant height. Agron J 99:530–536CrossRefGoogle Scholar
  19. Hallauer, A.R., M.J. Carena, J.B. Miranda-Filho (2010) Testers and combining ability. In: quantitative genetics in maize breeding: Handbook of plant breeding, Iowa State University Press, Ames, 6:383–423Google Scholar
  20. Hallauer AR, Russell WA, Lamkey K (1988) Corn breeding. In: Sprague GF, Dudley JW (eds) Corn and corn improvement. Crop Science Society of America, Madison, pp 463–564Google Scholar
  21. Hao Z, Li X, Xie C, Weng J, Li M, Zhang D, Liang L, Liu L, Liu S, Zhang S (2011) Identification of functional genetic variations underlying drought tolerance in maize using SNP markers. J Integr Plant Biol 53:641–652CrossRefPubMedGoogle Scholar
  22. Islam MR, Garcia SC, Henry D (2011) Use of normalized difference vegetation index, nitrogen concentration, and total nitrogen content of whole maize plant and plant fractions to estimate yield and nutritive value of hybrid forage maize. Crop Pasture Sci 62:374–382CrossRefGoogle Scholar
  23. Kim SK, Efron Y, Khadr F, Fajemisin JM, Lee M (1987) Registration of 16 maize-streak virus resistant tropical maize parental inbred lines. Crop Sci 2:824–825CrossRefGoogle Scholar
  24. Lu Y, Hao Z, Xie C, Crossa J, Araus J-L, Gao S, Vivek BS, Magorokosho C, Mugo S, Makumbi D, Taba S, Pan G, Li X, Rong T, Zhang S, Xu Y (2011) Large-scale screening for maize drought resistance using multiple selection criteria evaluated under water-stressed and well-watered environments. Field Crops Res 124:37–45CrossRefGoogle Scholar
  25. Lu Y, Xu J, Yuan Z, Hao Z, Xie C, Li X, Shah T, Lan H, Zhang S, Rong T, Xu Y (2012) Comparative LD mapping using single SNPs and haplotypes identifies QTL for plant height and biomass as secondary traits of drought tolerance in maize. Mol Breed 30:407–418CrossRefGoogle Scholar
  26. Martin KL, Girma K, Freeman KW, Teal RK, Tubana B, Arnall DB, Chung B, Walsh O, Solie JB, Stone ML, Raun WR (2006) Expression of variability in corn as influenced by growth stage using optical sensor measurements. Agron J 99:384–389CrossRefGoogle Scholar
  27. Menkir A, Ayodele M (2005) Genetic analysis of resistance of gray leaf spot of midaltitude maize inbred lines. Crop Sci 45:163–170CrossRefGoogle Scholar
  28. Menkir A, Badu-Apraku B, The C, Adepoju A (2003) Evaluation of heterotic patterns of IITA’s lowland white maize inbred lines. Maydica 48:161–170Google Scholar
  29. Menkir A, Badu-Apraku B, Ajala SO, Kamara A, Ndiaye A (2009) Response of early maturing maize landraces and improved varieties to moisture deficit and sufficient water supply. Plant Genet Resour: Charact Utilization 7(3):205–215CrossRefGoogle Scholar
  30. Messmer R, Fracheboud Y, Banziger M, Vargas M, Stamp P, Ribaut JM (2009) Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield and secondary traits. Theor Appl Genet 119:913–930CrossRefPubMedGoogle Scholar
  31. Mir RR, Zaman-Allah M, Sreenivasulvu N, Trethowan R, Varshney RK (2012) Intregrated genomics, physiology, and breeding approaches for improving drought tolerance in crops. Theor Appl Genet 125:625–645CrossRefPubMedCentralPubMedGoogle Scholar
  32. Monneveux P, Sanchez C, Beck D, Edmeades GO (2006) Drought tolerance in tropical maize source populations: evidence of progress. Crop Sci 46:180–191CrossRefGoogle Scholar
  33. NTech Industries. 2007. Model 505 Greenseeker handheld optical sensor unit operating manual. http://www.ntechindustries.com/lit/gs/GS_Handheld_Manual_rev_K.pdf (Verified 18 Jan 2013). NTech Industries, Ukiah, CA, USA
  34. Patterson HD, Williams ER, Hunter EA (1978) Block designs for variety trials. J Agric Sci 90:395–400CrossRefGoogle Scholar
  35. Pswarayi A, Vivek BS (2008) Combining ability amongst CIMMYT’s early maturing maize (Zea mays L.) germplasm under stress and non-stress conditions and identification of testers. Euphytica 162:353–362CrossRefGoogle Scholar
  36. Raun WR, Johnson GV, Stone ML, Solie JB, Lukina EV, Thomason WE, Schepers JS (2001) In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron J 93:131–138CrossRefGoogle Scholar
  37. Rosielle AA, Hamblin J (1981) Theoretical aspects of selection for yield in stress and non-stress environments. Crop Sci 21:943–946CrossRefGoogle Scholar
  38. SAS Institute. 2009. SAS Proprietary Software Release 9.2. SAS Institute, Inc., Cary, NCGoogle Scholar
  39. Sawkins MC, DeMeyer J, Ribaut JM (2006) Drought adaptation in cereals. In: Ribaut JM (ed) Drought adaptation in maize. Haworth, New York, pp 259–299Google Scholar
  40. Sentek Pty Ltd. 2003 Sentek Diviner 2000 User Guide Version 1.2.Australia Sentek Pty Ltd, Stepney, South AustraliaGoogle Scholar
  41. Teal RK, Tubana B, Girma K, Freeman KW, Arnall DB, Walsh O, Raun WR (2006) In-season prediction of corn grain yield potential using normalizes difference vegetation index. Agron J 98:1488–1494CrossRefGoogle Scholar
  42. Toker B, Canci H, Yildirim T (2007) Evaluation of perennial wild Cicer species for drought resistance. Genet Resour Crop Biotechnol Equip 23:1410–1413Google Scholar
  43. Tuberosa R, Salvi S (2006) Genomics approaches to improve drought tolerance in crops. Trends Plant Sci 11:405–412CrossRefPubMedGoogle Scholar
  44. Verhulst N, Govaerts B (2010) The normalized difference vegetation index (NDVI) GreenseekerTM handheld sensor: toward the integrated evaluation of crop management. CIMMYT, MexicoGoogle Scholar
  45. Wen W, Araus JL, Shah T, Cairns J, Mahuku G, Banziger M, Torres JL, Sanchez C, Yan J (2011) Molecular characterization of a diverse maize inbred line collection and its potential utilization for stress tolerance improvement. Crop Sci 51(2569):2011Google Scholar
  46. Xiong L, Wang RG, Mao G, Koczan JM (2006) Identification of drought tolerance determinants by genetic analysis of root response to drought stress and abscisic acid. Plant Physiol 142:1065–1074CrossRefPubMedCentralPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • M. A. Adebayo
    • 1
    • 2
  • A. Menkir
    • 2
  • E. Blay
    • 1
  • V. Gracen
    • 1
    • 3
  • E. Danquah
    • 1
  • S. Hearne
    • 4
  1. 1.West Africa Centre for Crop Improvement (WACCI)University of GhanaLegonGhana
  2. 2.International Institute of Tropical Agriculture (IITA)IbadanNigeria
  3. 3.Cornell UniversityIthacaUSA
  4. 4.International Maize and Wheat Improvement Center (CIMMYT)TexcocoMexico

Personalised recommendations