Strategies to subdivide a target population of environments: Results from the CIMMYT-led maize hybrid testing programs in Africa

Crop Science

Volumn 52, Issue 5, 2012, Pages 2143-2152

  Windhausen, Vanessa S ^a   Wagener, Silke ^a   Magorokosho, Cosmos ^b   Makumbi, Dan ^c   Vivek, Bindiganavile ^d   Piepho, Hans Peter ^a   Melchinger, Albrecht E ^a   Atlin, Gary N ^e  

^a UNIVERSITY OF HOHENHEIM   (Germany)

^b CIMMYT   (Zimbabwe)

^c CIMMYT   (Kenya)

^d CIMMYT   (India)

^e NONE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84864717381     PISSN: 0011183X     EISSN: 14350653     Source Type: Journal    
DOI: 10.2135/cropsci2012.02.0125     Document Type: Article

References (43)

1. Atlin, G.N., R.J. Baker, K.B. McRae, and X. Lu. 2000a. Selection response in subdivided target regions. Crop Sci. 40:7-13. doi:10.2135/cropsci2000.4017
2. Atlin, G.N., M. Cooper, and Å. Bjørnstad. 2001. A comparison of formal and participatory breeding approaches using selection theory. Euphytica 122:463-475. doi:10.1023/A:1017557307800
3. Atlin, G.N., and K.J. Frey. 1990. Selecting oat lines for yield in low-productivity environments. Crop Sci. 30:556-561. doi:10.2135/cropsci1990.0011183X003000030017x
4. Atlin, G.N., K. Kleinknecht, K.P. Singh, and H.P. Piepho. 2011. Managing genotype × environment interaction in plant breeding programs: A selection theory approach. J. Indian Soc. Agric. Stat. 65:237-247.
5. Atlin, G.N., K.B. McRae, and X. Lu. 2000b. Genotype × region interaction for two-row barley yield in Canada. Crop Sci. 40:1-6. doi:10.2135/cropsci2000.4011
6. Bänziger, M., F.J. Betrán, and H.R. Lafitte. 1997. Efficiency of high-nitrogen selection environments for improving maize for low-nitrogen target environments. Crop Sci. 37:1103-1109. doi:10.2135/cropsci1997.0011183X003700040012x
7. Bänziger, M., G.O. Edmeades, D. Beck, and M. Bellon. 2000. Breeding for drought and nitrogen stress tolerance in maize: From theory to practice. CIMMYT, Mexico, D.F.
8. Bänziger, M., P.S. Setimela, D. Hodson, and B. Vivek. 2004. Breeding for improved drought tolerance in maize adapted to southern Africa. In: T. Fischer, editor, New directions for a diverse planet: Proceedings of the 4th International Crop Science Congress, Brisbane, Australia. 26 Sept.-1 Oct. 2004. CABI Publishing, Wallingford, UK.
9. Bänziger, M., P.S. Setimela, D. Hodson, and B. Vivek. 2006. Breeding for improved abiotic stress tolerance in maize adapted to southern Africa. Agric. Water Manage. 80:212-224. doi:10.1016/j.agwat.2005.07.014
10. Basford, K.E., and M. Cooper. 1998. Genotype × environment interactions and some considerations of their implications for wheat breeding in Australia. Aust. J. Agric. Res. 49:153-174. doi:10.1071/A97035
11. Betrán, F.J., D. Beck, M. Bänziger, and G.O. Edmeades. 2003. Secondary traits in parental inbreds and hybrids under stress and non-stress environments in tropical maize. Field Crops Res. 83:51-65. doi:10.1016/S0378-4290(03)00061-3
12. Braun, H.J., G.N. Atlin, and T. Payne. 2010. Multi-location testing as a tool to identify plant response to global climate change. In: M.P. Reynolds, editor, Climate change and crop production. CABI climate change series I. CAB International, Wallingford, UK. p. 115-138.
13. Butler, D.G., B.R. Cullis, A.R. Gilmour, and B.J. Gogel. 2009. Mixed models for S language environments. ASReml-R reference manual. Version 3. Dept. of Primary Industries and Fisheries, Brisbane, Toowoomba, Australia.
14. Ceccarelli, S., S. Grando, and J. Hamblin. 1992. Relationship between barley grain yield measured in low-and highyielding environments. Euphytica 64:49-58.
15. Comstock, R.E., and R.H. Moll. 1963. Genotype-environment interaction. In: W.D. Hanson and H.F. Robinson, editors, Statistical genetics and plant breeding. Publication 982. National Academy of Sciences-National Research Council, Washington, DC. p. 164-194.
16. Cooper, M., and I.H. DeLacy. 1994. Relationships among analytical methods used to study genotypic variation and genotype-by-environment interaction in plant breeding multi-environment experiments. Theor. Appl. Genet. 88:561-572. doi:10.1007/BF01240919
17. Cooper, M., H. DeLacy, and K.E. Basford. 1996. Relationship among analytical methods used to analyse genotypic adaption in multi-environment trials. In: M. Cooper and G.L. Hammer, editors, Plant adaption and crop improvement. C.A.B. International, International Crops Research Institute for the Semi-arid Tropics, Wallingford, Oxon, UK.
18. Cooper, M., S. Rajatasereekul, S. Immark, S. Fukai, and J. Basnayake. 1999. Rainfed lowland rice breeding strategies for northeast Thailand. I. genotypic variation and genotype × environment interactions for grain yield. Field Crops Res. 64:131-151. doi:10.1016/S0378-4290(99)00056-8
19. Diallo, A.O. 1996. Lowland tropical maize: West and central Africa. In: Maize research in 1995-96. Maize program special report. CIMMYT, Mexico, D.F. p. 73-83.
20. Falconer, D.S., and T.F.C. Mackay. 1996. Introduction to quantitative genetics. Longman, London, UK.
21. FAO. 2011a. The state of food insecurity in the world. How does international price volatility affect domestic economies and food security? FAO, Rome, Italy.
22. FAO. 2011b. Statistical database of food and agriculture organization of the United Nations. FAO, Rome, Italy. http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID = 567#ancor (accessed 19 Sept. 2011).
23. Frankham, R., D.B. Ballou, and D.A. Briscoe. 2007. Introduction to conservation genetics. Cambridge Univ. Press, Cambridge, UK.
24. Hallauer, A.R., M.J. Carena, and J.B. Miranda Filho. 2010. Quantitative genetics in maize breeding. Iowa State Univ. Press, Ames, IA.
25. Haussmann, B.I.G., A.B. Obilana, A. Blum, P.O. Ayiecho, W. Schipprack, and H.H. Geiger. 1998. Hybrid performance of sorghum and its relationship to morphological and physiological traits under variable drought stress in Kenya. Plant Breed. 117:223-229. doi:10.1111/j.1439-0523.1998. tb01930.x
26. Hazel, L.N. 1943. The genetic basis for constructing selection indexes. Genetics 28:476-490.
27. Holland, J.B., W.E. Nyquist, and C.T. Cervantes Martínez. 2003. Estimating and interpreting heritability for plant breeding: An update. Plant Breed. Rev. 22:9-112.
28. Langyintuo, A.S., W. Mwangi, A.O. Diallo, J. MacRobert, and M. Bänziger. 2008. An analysis of the bottlenecks affecting the production and deployment of maize seed in eastern and southern Africa. CIMMYT, Harare, Zimbabwe.
29. Lynch, M., and J.B. Walsh. 1998. Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland, MA.
30. Mandal, N.P., P.K. Sinha, M. Variar, V.D. Shukla, P. Perraju, A. Mehta, A.R. Pathak, J.L. Dwivedi, S.P.S. Rathi, S. Bhandarkar, B.N. Singh, D.N. Singh, S. Panda, N.C. Mishra, Y.V. Singh, R. Pandya, M.K. Singh, R.B.S. Sanger, J.C. Bhatt, R.K. Sharma, A. Raman, A. Kumar, and G. Atlin. 2010. Implications of genotype × input interactions in breeding superior genotypes for favorable and unfavorable rainfed upland environments. Field Crops Res. 118:135-144. doi:10.1016/j.fcr.2010.05.004
31. Patterson, H.D. 1997. Analysis of series of variety trials. In: R.A. Kempton and P.N. Fox, editors, Statistical methods for plant variety evaluation. Chapman and Hall, London, UK. p. 139-161.
32. Piepho, H.P. 1997. Analyzing genotype-environment data by mixed models with multiplicative terms. Biometrics 53:761-766. doi:10.2307/2533976
33. Piepho, H.P., and J. Möhring. 2005. Best linear unbiased prediction of cultivar effects for subdivided target regions. Crop Sci. 45:1151-1159. doi:10.2135/cropsci2004.0398
34. Piepho, H.P., and J. Möhring. 2007. Computing heritability and selection response from unbalanced plant breeding trials. Genetics 177:1881-1888. doi:10.1534/genetics.107.074229
35. Presterl, T., G. Seitz, M. Landbeck, E.M. Thiemt, W. Schmidt, and H.H. Geiger. 2003. Improving nitrogen-use efficiency in European maize: Estimation of quantitative genetic parameters. Crop Sci. 43:1259-1265. doi:10.2135/cropsci2003.1259
36. Przystalski, M., A. Osman, E.M. Thiemt, B. Rolland, L. Ericson, H. Østergård, L. Levy, M. Wolfe, A. Büchse, H.-P. Piepho, and P. Krajewski. 2008. Comparing the performance of cereal varieties in organic and non-organic cropping systems in different European countries. Euphytica 163:417-433. doi:10.1007/s10681-008-9715-4
37. R Development Core Team. 2011. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
38. Setimela, P., Z. Chitalu, J. Jonazi, A. Mambo, D. Hodson, and M. Bänziger. 2005. Environmental classification of maize-testing sites in the SADC region and its implication for collaborative maize breeding strategies in the subcontinent. Euphytica 145:123-132. doi:10.1007/s10681-005-0625-4
39. Simmonds, N. 1991. Selection for local adaptation in a plant breeding programme. Theor. Appl. Genet. 82:363-367. doi:10.1007/BF02190624
40. Smith, H.F. 1936. A discriminant function for plant selection. Ann. Hum. Genet. 7:240-250. doi:10.1111/j.1469-1809.1936. tb02143.x
41. Venuprasad, R., M.T. Sta Cruz, M. Amante, R. Magbanua, A. Kumar, and G.N. Atlin. 2008. Response to two cycles of divergent selection for grain yield under drought stress in four rice breeding populations. Field Crops Res. 107:232-244. doi:10.1016/j.fcr.2008.02.004
42. Weber, V.S., A.E. Melchinger, C. Magorokosho, D. Makumbi, M. Bänziger, and G.N. Atlin. 2012. Efficiency of managed-stress selection for maize grain yield under optimal rainfed, low-N, and random abiotic stress conditions in southern Africa. Crop Science 52(3):1011-1020. doi:10.2135/cropsci2011.09.0486
43. Wricke, G., and W.E. Weber. 1986. Quantitative genetics and selection in plant breeding. de Gruyter, Berlin, New York.