Theoretical and Applied Genetics

, Volume 126, Issue 10, pp 2587–2596 | Cite as

Genome-wide association analysis for nine agronomic traits in maize under well-watered and water-stressed conditions

  • Yadong Xue
  • Marilyn L. Warburton
  • Mark Sawkins
  • Xuehai Zhang
  • Tim Setter
  • Yunbi Xu
  • Pichet Grudloyma
  • James Gethi
  • Jean-Marcel Ribaut
  • Wanchen Li
  • Xiaobo Zhang
  • Yonglian Zheng
  • Jianbing YanEmail author
Original Paper


Drought can cause severe reduction in maize production, and strongly threatens crop yields. To dissect this complex trait and identify superior alleles, 350 tropical and subtropical maize inbred lines were genotyped using a 1536-SNP array developed from drought-related genes and an array of 56,110 random SNPs. The inbred lines were crossed with a common tester, CML312, and the testcrosses were phenotyped for nine traits under well-watered and water-stressed conditions in seven environments. Using genome-wide association mapping with correction for population structure, 42 associated SNPs (P ≤ 2.25 × 10−6 0.1/N) were identified, located in 33 genes for 126 trait × environment × treatment combinations. Of these genes, three were co-localized to drought-related QTL regions. Gene GRMZM2G125777 was strongly associated with ear relative position, hundred kernel weight and timing of male and female flowering, and encodes NAC domain-containing protein 2, a transcription factor expressed in different tissues. These results provide some good information for understanding the genetic basis for drought tolerance and further studies on identified candidate genes should illuminate mechanisms of drought tolerance and provide tools for designing drought-tolerant maize cultivars tailored to different environmental scenarios.


Quantitative Trait Locus Drought Tolerance Hundred Kernel Weight Grain Yield Maize Inbred Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was supported by the Generation Challenge Program and the National Hi-Tech Research and Development Program of China (2012AA10A307) and the National Natural Science Foundation of China (31101156).

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

122_2013_2158_MOESM1_ESM.pdf (74 kb)
Supplementary material 1 (PDF 73 kb)
122_2013_2158_MOESM2_ESM.pdf (358 kb)
Supplementary material 2 (PDF 357 kb)
122_2013_2158_MOESM3_ESM.pdf (2.6 mb)
Supplementary material 3 (PDF 2707 kb)
122_2013_2158_MOESM4_ESM.pdf (3.4 mb)
Supplementary material 4 (PDF 3471 kb)
122_2013_2158_MOESM5_ESM.pdf (63 kb)
Supplementary material 5 (PDF 62 kb)


  1. Bänziger M, Araus JL (2007) Recent advances in breeding maize for drought and salinity stress tolerance. In: Jenks MA, Hasegawa PM, Jain SM (eds) Advances in molecular breeding toward drought and salt tolerant crops. Springer Netherlands, Dordrecht, pp 587–601CrossRefGoogle Scholar
  2. Bänziger M, Edmeades GO, Beck D, Bellon M (2000) Breeding for drought and nitrogen stress tolerance in maize: from theory to practice. CIMMYT, Mexico, D.F.Google Scholar
  3. Barker T, Campos H, Cooper M, Dolan D, Edmeades G, Habben J, Schussler J, Wright D, Zinselmeier C (2010) Improving drought tolerance in maize. In: Janick J (ed) Plant breeding reviews. Wiley, Oxford, pp 173–253CrossRefGoogle Scholar
  4. Bolaños J, Edmeades GO (1993) Eight cycles of selection for drought tolerance in lowland tropical maize. I. Responses in grain yield, biomass, and radiation utilization. Field Crops Res 31:233–252. doi: 10.1016/0378-4290(93)90064-T CrossRefGoogle Scholar
  5. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635. doi: 10.1093/bioinformatics/btm308 CrossRefPubMedGoogle Scholar
  6. Brown PJ, Upadyayula N, Mahone GS, Tian F, Bradbury PJ, Myles S, Holland JB, Flint-Garcia S, McMullen MD, Buckler ES, Rocheford TR (2011) Distinct genetic architectures for male and female inflorescence traits of maize (J Flint, Ed.). PLoS Genet 7:e1002383. doi: 10.1371/journal.pgen.1002383 CrossRefPubMedGoogle Scholar
  7. Bruce WB, Edmeades GO, Barker TC (2002) Molecular and physiological approaches to maize improvement for drought tolerance. J Exp Bot 53:13–25. doi: 10.1093/jexbot/53.366.13 CrossRefPubMedGoogle Scholar
  8. Buckler ES, Holland JB, Bradbury PJ et al (2009) The genetic architecture of maize flowering time. Science 325:714–718. doi: 10.1126/science.1174276 CrossRefPubMedGoogle Scholar
  9. Campos H, Cooper M, Habben JE, Edmeades GO, Schussler JR (2004) Improving drought tolerance in maize: a view from industry. Field Crops Res 90:19–34. doi: 10.1016/j.fcr.2004.07.003 CrossRefGoogle Scholar
  10. Capelle V, Remoué C, Moreau L, Reyss A, Mahé A, Massonneau A, Falque M, Charcosset A, Thévenot C, Rogowsky P, Coursol S, Prioul JL (2010) QTLs and candidate genes for desiccation and abscisic acid content in maize kernels. BMC Plant Biol 10:2. doi: 10.1186/1471-2229-10-2 CrossRefPubMedGoogle Scholar
  11. Cook ER, Seager R, Cane MA, Stahle DW (2007) North American drought: reconstructions, causes, and consequences. Earth Sci Rev 81:93–134. doi: 10.1016/j.earscirev.2006.12.002 CrossRefGoogle Scholar
  12. Corellou F, Potin P, Brownlee C, Kloareg B, Bouget FY (2000) Inhibition of the establishment of zygotic polarity by protein tyrosine kinase inhibitors leads to an alteration of embryo pattern in Fucus. Dev Biol 219:165–182. doi: 10.1006/dbio.1999.9603 CrossRefPubMedGoogle Scholar
  13. Edmeades GO, Bolaños J, Chapman SC, Lafitte HR, Bänziger M (1999) Selection improves drought tolerance in tropical maize populations: I. Gains in Biomass, Grain Yield, and Harvest Index. Crop Sci 39:1306–1315. doi: 10.2135/cropsci1999.3951306x CrossRefGoogle Scholar
  14. Edmeades GO, Bolaños J, Elings A, Ribaut JM, Bänziger M, Westgate ME (2000) The role and regulation of the anthesis-silking interval in maize. In: Otegui ME, Slafer GA (eds) Physiological bases for maize improvement. Food Products Press, New York, pp 75–111Google Scholar
  15. Fordham-Skelton AP, Skipsey M, Eveans IM, Edwards R, Gatehouse JA (1999) Higher plant tyrosine-specific protein phosphatases (PTPs) contain novel amino-terminal domains: expression during embryogenesis. Plant Mol Biol 39:593–605. doi: 10.1023/A:1006170902271 CrossRefPubMedGoogle Scholar
  16. Fu JY, Keurentjes JJB, Bouwmeester H, America T, Verstappen FWA, Ward JL, Beale MH, Vos RCH, Dijkstra M, Scheltema RA, Johannes F, Koornneef M, Vreugdenhil D, Breitling R, Jansen RC (2009) System-wide molecular evidence for phenotypic buffering in Arabidopsis. Nat Genet 41:166–167. doi: 10.1038/ng.308 CrossRefPubMedGoogle Scholar
  17. Ganal MW, Durstewitz G, Polley A et al (2011) A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLoS One 6:e28334. doi: 10.1371/journal.pone.0028334 CrossRefPubMedGoogle Scholar
  18. Ghelis T (2011) Signal processing by protein tyrosine phosphorylation in plants. Plant Signal Behav 6:942–951. doi: 10.4161/psb.6.7.15261 CrossRefPubMedGoogle Scholar
  19. Guo J, Su G, Zhang J, Wang G (2008) Genetic analysis and QTL mapping of maize yield and associate agronomic traits under semi-arid land condition. Afr J Biotechnol 7:1829–1838Google Scholar
  20. Gutierrez-Rodriguez M, Miguel-Chavez RS, Larque-Saavedra A (1998) Physiological aspects in Tuxpeno maize with improved drought tolerance. Maydica 43:137–141Google Scholar
  21. Hao Z, Li X, Xie C, Weng J, Li M, Zhang D, Liang X, Liu L, Liu S, Zhang S (2011) Identification of functional genetic variations underlying drought tolerance in maize using SNP markers. J Integr Plant Biol 53:641–652. doi: 10.1111/j.1744-7909.2011.01051.x CrossRefPubMedGoogle Scholar
  22. Holland JB (2007) Genetic architecture of complex traits in plants. Curr Opin Plant Biol 10:156–161. doi: 10.1016/j.pbi.2007.01.003 CrossRefPubMedGoogle Scholar
  23. Kooke R, Keurentjes JJB (2011) Multi-dimensional regulation of metabolic networks shaping plant development and performance. J Exp Bot 63:3353–3365. doi: 10.1093/jxb/err373 CrossRefPubMedGoogle Scholar
  24. Li E, Hristova K (2006) Role of receptor tyrosine kinase transmembrane domains in cell signaling and human pathologies. Biochemistry 45:6241–6251. doi: 10.1021/bi060609y CrossRefPubMedGoogle Scholar
  25. Li WJ, Liu Z, Shi Y, Song Y, Wang T, Xu C, Li Y (2010) Detection of consensus genomic region of QTLs relevant to drought-tolerance in maize by QTL Meta-analysis and bioinformatics approach. Acta Agronomica Sinica 36:1457–1467. doi: 10.1016/S1875-2780(09)60072-9 CrossRefGoogle Scholar
  26. Li H, Peng Z, Yang X, Wang W, Fu J, Wang J, Han Y, Chai Y, Guo T, Yang N, Liu J, Warburton ML, Cheng Y, Hao X, Zhang P, Zhao J, Liu Y, Wang G, Li J, Yan J (2013) Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nat Genet 45:43–50. doi: 10.1038/ng.2484 CrossRefPubMedGoogle Scholar
  27. Lipka AE, Tian F, Wang Q, Peiffer J, Li M, Bradbury PJ, Gore M, Buckler ES, Zhang Z (2012) GAPIT: genome association and prediction integrated tool. Bioinformatics 28:2397–2399. doi: 10.1093/bioinformatics/bts444 CrossRefPubMedGoogle Scholar
  28. Loiselle BA, Sork VL, Nason J, Graham C (1995) Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). Am J Bot 82:1420–1425. doi: 10.2307/2445869 CrossRefGoogle Scholar
  29. Lopes MS, Araus JL, van Heerden PDR, Foyer CH (2011) Enhancing drought tolerance in C4 crops. J Exp Bot 62:3135–3153. doi: 10.1093/jxb/err105 CrossRefPubMedGoogle Scholar
  30. Lorković ZJ (2009) Role of plant RNA-binding proteins in development, stress response and genome organization. Trends Plant Sci 14:229–236. doi: 10.1016/j.tplants.2009.01.007 CrossRefPubMedGoogle Scholar
  31. Lu Y, Zhang S, Shah T, Xie C, Hao Z, Li X, Farkhari M, Ribaut JM, Cao M, Rong T, Xu Y (2010) Joint linkage–linkage disequilibrium mapping is a powerful approach to detecting quantitative trait loci underlying drought tolerance in maize. Proc Natl Acad Sci USA 107:19585–19590. doi: 10.1073/pnas.1006105107 CrossRefPubMedGoogle Scholar
  32. Messina CD, Podlich D, Dong Z, Samples M, Cooper M (2010) Yield-trait performance landscapes: from theory to application in breeding maize for drought tolerance. J Exp Bot 62:855–868. doi: 10.1093/jxb/erq329 CrossRefPubMedGoogle Scholar
  33. Monneveux P, Sánchez C, Beck D, Edmeades GO (2006) Drought tolerance improvement in tropical maize source populations. Crop Sci 46:180–191. doi: 10.2135/cropsci2005.04-0034 CrossRefGoogle Scholar
  34. Monneveux P, Sanchez C, Tiessen A (2008) Future progress in drought tolerance in maize needs new secondary traits and cross combinations. J Agric Sci 146:287–300. doi: 10.1017/S0021859608007818 CrossRefGoogle Scholar
  35. Myles S, Peiffer J, Brown PJ, Ersoz ES, Zhang Z, Costich DE, Buckler ES (2009) Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell 21:2194–2202. doi: 10.1105/tpc.109.068437 CrossRefPubMedGoogle Scholar
  36. Newton-Cheh C, Hirschhorn JN (2005) Genetic association studies of complex traits: design and analysis issues. Mutat Res 573:54–69. doi: 10.1016/j.mrfmmm.2005.01.006 CrossRefPubMedGoogle Scholar
  37. Nikolic A, Andjelkovic V, Dodig D, Ignjatovic-Micic D (2011) Quantitative trait loci for yield and morphological traits in maize under drought stress. Genetika 43:263–276. doi: 10.2298/GENSR1102263N CrossRefGoogle Scholar
  38. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904–909. doi: 10.1038/ng1847 CrossRefPubMedGoogle Scholar
  39. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC (2007) PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet 81:559–575. doi: 10.1086/519795 CrossRefPubMedGoogle Scholar
  40. Rahman H, Pekic S, Lazic-Jancic V, Quarrie SA, Shah SMA, Pervez A, Shah MM (2011) Molecular mapping of quantitative trait loci for drought tolerance in maize plants. Genet Mol Res 10:889–901. doi: 10.4238/vol10-2gmr1139 CrossRefPubMedGoogle Scholar
  41. Remington DL, Thornsberry JM, Matsuoka Y, Wilson LM, Whitt SR, Doebley J, Kresovich S, Goodman MM, Buckler ES (2001) Structure of linkage disequilibrium and phenotypic associations. PNAS 98:11479–11484. doi: 10.1073/pnas.201394398 CrossRefPubMedGoogle Scholar
  42. Ribaut JM, Bänziger M, Setter T, Edmeades G, Hoisington D (2004) Genetic dissection of drought tolerance in maize: a case study. In: Nguyen H, Blum A (eds) Physiology and biotechnology integration for plant breeding. Marcel Dekker Inc., New York, pp 571–611Google Scholar
  43. Ribaut JM, Betran J, Monneveux P, Setter T (2009) Drought tolerance in maize. Handbook of maize: its biology. Springer, New York, pp 311–344CrossRefGoogle Scholar
  44. Riedelsheimer C, Lisec J, Czedik-Eysenberg A, Sulpice R, Flis A, Grieder C, Altmann T, Stitt M, Willmitzer L, Melchinger AE (2012) Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize. Proc Natl Acad Sci 109:8872–8877. doi: 10.1073/pnas.1120813109 CrossRefPubMedGoogle Scholar
  45. Rosenberg NA, Huang L, Jewett EM, Szpiech ZA, Jankovic I, Boehnke M (2010) Genome-wide association studies in diverse populations. Nat Rev Genet 11:356–366. doi: 10.1038/nrg2760 CrossRefPubMedGoogle Scholar
  46. Saeed M, Guo WZ, Ullah I, Tabbasam N, Zafar Y, Rahman MU, Zhang TZ (2011) QTL mapping for physiology, yield and plant architecture traits in cotton (Gossypium hirsutum L.) grown under well-watered versus water-stress conditions. Electron J Biotechnol 14:3. doi: 10.2225/vol14-issue3-fulltext-3 Google Scholar
  47. Sari-Gorla M, Krajewski P, Di Fonzo N, Villa M, Frova C (1999) Genetic analysis of drought tolerance in maize by molecular markers. II. Plant height and flowering. Theor Appl Genet 99:289–295. doi: 10.1007/s001220051234 CrossRefGoogle Scholar
  48. Schauer N, Semel Y, Roessner U, Gur A, Balbo I, Carrari F, Pleban T, Perez-Melis A, Bruedigam C, Kopka J, Willmitzer L, Zamir D, Fernie AR (2006) Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat Biotechnol 24:447–454. doi: 10.1038/nbt1192 CrossRefPubMedGoogle Scholar
  49. Sekhon RS, Lin H, Childs KL, Hansey CN, Buell CR, de Leon N, Kaeppler SM (2011) Genome-wide atlas of transcription during maize development. Plant J 66:553–563. doi: 10.1111/j.1365-313X.2011.04527.x CrossRefPubMedGoogle Scholar
  50. Setter TL (2012) Analysis of constituents for phenotyping drought tolerance in crop improvement. Front Physiol 3:180. doi: 10.3389/fphys.2012.00180 CrossRefPubMedGoogle Scholar
  51. Setter TL, Flannigan BA, Melkonian J (2001) Loss of kernel set due to water deficit and shade in maize. Crop Sci 41:1530–1540. doi: 10.2135/cropsci2001.4151530x CrossRefGoogle Scholar
  52. Setter TL, Yan J, Warburton M, Ribaut JM, Xu Y, Sawkins M, Buckler ES, Zhang Z, Gore MA (2010) Genetic association mapping identifies single nucleotide polymorphisms in genes that affect abscisic acid levels in maize floral tissues during drought. J Exp Bot 62:701–716. doi: 10.1093/jxb/erq308 CrossRefPubMedGoogle Scholar
  53. Sharma PS, Sharma R, Tyagi T (2009) Receptor tyrosine kinase inhibitors as potent weapons in war against cancers. Curr Pharm Des 15:758–776. doi: 10.2174/128161209787582219 CrossRefPubMedGoogle Scholar
  54. Sulpice R, Trenkamp S, Steinfath M, Usadel B, Gibon Y, Witucha-Wall H, Pyl ET, Tschoep H, Steinhauser MC, Guenther M, Hoehne M, Rohwer JM, Altmann T, Fernie AR, Stitt M (2010) Network analysis of enzyme activities and metabolite levels and their relationship to biomass in a large panel of Arabidopsis accessions. Plant Cell 22:2872–2893. doi: 10.1105/tpc.110.076653 CrossRefPubMedGoogle Scholar
  55. Tardieu F (2011) Any trait or trait-related allele can confer drought tolerance: just design the right drought scenario. J Exp Bot 63:25–31. doi: 10.1093/jxb/err269 CrossRefPubMedGoogle Scholar
  56. Tian F, Bradbury PJ, Brown PJ, Hung H, Sun Q, Flint-Garcia S, Rocheford TR, McMullen MD, Holland JB, Buckler ES (2011) Genome-wide association study of leaf architecture in the maize nested association mapping population. Nat Genet 43:159–162. doi: 10.1038/ng.746 CrossRefPubMedGoogle Scholar
  57. Tuberosa R, Salvi S, Sanguineti MC, Landi P, Maccaferri M, Conti S (2002) Mapping QTLs regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize. Ann Bot 89:941–963. doi: 10.1093/aob/mcf134 CrossRefPubMedGoogle Scholar
  58. Wang C, Li S (2010) Assessment of limiting factors and techniques prioritization for maize production in China. Scientia Agricultrea Sinica 43:1136–1146Google Scholar
  59. Welcker C, Boussuge B, Bencivenni C, Ribaut JM, Tardieu F (2007) Are source and sink strengths genetically linked in maize plants subjected to water deficit? A QTL study of the responses of leaf growth and of anthesis-silking interval to water deficit. J Exp Bot 58:339–349. doi: 10.1093/jxb/erl227 CrossRefPubMedGoogle Scholar
  60. Weng J, Xie C, Hao Z, Wang J, Liu C, Li M, Zhang D, Bai L, Zhang S, Li X (2011) Genome-wide association study identifies candidate genes that affect plant height in chinese elite maize (Zea mays L.) inbred lines. PLoS One 6:e29229. doi: 10.1371/journal.pone.0029229 CrossRefPubMedGoogle Scholar
  61. Xia XC, Reif JC, Melchinger AE, Frisch M, Hoisington D, Pixley BK, Warlburton ML (2005) Genetic diversity among CIMMYT maize inbred lines investigated with SSR markers II. Subtropical, tropical midaltitude, and highland maize inbred lines and their relationships with elite U.S. and European maize. Crop Sci 45:2573–2582. doi: 10.2135/cropsci2005.0246 CrossRefGoogle Scholar
  62. Yan J, Shah T, Warburton ML, Buckler ES, McMullen MD, Crouch J (2009) Genetic characterization and linkage disequilibrium estimation of a global maize collection Using SNP Markers. PLoS One 4:e8451. doi: 10.1371/journal.pone.0008451 CrossRefPubMedGoogle Scholar
  63. Yan J, Warburton M, Crouch J (2011) Association mapping for enhancing maize (Zea mays L.) genetic improvement. Crop Sci 51:433–449. doi: 10.2135/cropsci2010.04.0233 CrossRefGoogle Scholar
  64. Yue B, Xue W, Xiong L, Yu X, Luo L, Cui K, Jin D, Xing Y, Zhang Q (2005) Genetic basis of drought resistance at reproductive stage in rice: separation of drought tolerance from drought avoidance. Genetics 172:1213–1228. doi: 10.1534/genetics.105.045062 CrossRefPubMedGoogle Scholar
  65. Zhang SW, Li CH, Cao J, Zhang YC, Zhang SQ, Xia YF, Sun DY, Sun Y (2009a) Altered architecture and enhanced drought tolerance in rice via the down-regulation of indole-3-acetic acid by TLD1/OsGH3.13 activation. Plant Physiol 151:1889–1901. doi: 10.1104/pp.109.146803 CrossRefPubMedGoogle Scholar
  66. Zhang Z, Buckler ES, Casstevens TM, Bradbury PJ (2009b) Software engineering the mixed model for genome-wide association studies on large samples. Brief Bioinforma 10:664–675. doi: 10.1093/bib/bbp050 CrossRefGoogle Scholar
  67. Zhang Z, Ersoz E, Lai C-Q, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu J, Arnett DK, Ordovas JM, Buckler ES (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360. doi: 10.1038/ng.546 CrossRefPubMedGoogle Scholar
  68. Zhao K, Aranzana MJ, Kim S, Lister C, Shindo C, Tang C, Toomajian C, Zheng H, Dean C, Marjoram P, Nordborg M (2007) An Arabidopsis example of association mapping in structured samples. PLoS Genet 3:e4. doi: 10.1371/journal.pgen.0030004 CrossRefPubMedGoogle Scholar
  69. Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20. doi: 10.3835/plantgenome2008.02.0089 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yadong Xue
    • 1
  • Marilyn L. Warburton
    • 2
  • Mark Sawkins
    • 3
  • Xuehai Zhang
    • 1
  • Tim Setter
    • 4
  • Yunbi Xu
    • 5
  • Pichet Grudloyma
    • 6
  • James Gethi
    • 7
  • Jean-Marcel Ribaut
    • 3
  • Wanchen Li
    • 8
  • Xiaobo Zhang
    • 1
  • Yonglian Zheng
    • 1
  • Jianbing Yan
    • 1
    Email author
  1. 1.National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
  2. 2.USDA-ARS Corn Host Plant Research Resistance UnitMississippi State UniversityStarkvilleUSA
  3. 3.Generation Challenge ProgramMexico, D.F.Mexico
  4. 4.Department of Crop and Soil SciencesCornell UniversityIthacaUSA
  5. 5.International Maize and Wheat Improvement CenterMexico, D.F.Mexico
  6. 6.Nakhon Sawan Field Crops Research Center (NSFCRC)TakfaThailand
  7. 7.Kenya Agricultural Research Institute (KARI)MtwapaKenya
  8. 8.Maize Research InstituteSichuan Agricultural UniversityYa’anChina

Personalised recommendations