Genotype by environment interactions and agronomic performance of doubled haploids testcross maize (Zea mays L.) hybrids
- 409 Downloads
In vivo production of maternal haploid plants and advancement in chromosome doubling technology has led to rapid production of doubled haploid homozygous lines. These in turn have boosted rapid advancement in most breeding programs. This has resulted in production of a large number of maize hybrids which need testing across production environments to select the most suitable hybrids for release and cultivation. The objective of this study was to assess the genotype × environment interactions (GE) for grain yield and other agronomic traits and evaluate the performance of 44 recently developed doubled haploids (DH) testcross hybrids along with six checks across five locations in Uganda. Significant mean squares for environment (E), genotype (G) and GE were observed for all studied traits. Environment explained 46.5 % of the total variance, while G and GE contributed 13.2 and 7.2 %, respectively. Genetic correlations among locations were high (0.999), suggesting little GE among environments. The 10 best testcross hybrids had a 49.2 % average grain yield advantage over the six checks at all locations. DH hybrids CKHDHH0887, CKDHH0878, CKDHH0859, WM1210, CKDHH0858, and WM1214 were the most stable, across locations. The DH testcross hybrids produced higher grain yield and possessed acceptable agronomic traits compared to the commercial hybrids developed earlier. Use of the best DH testcross hybrids, well targeted to the production environments, could boost maize production among farmers.
KeywordsDoubled haploids East Africa Genotype × environment Grain yield Maize Stability
This research was supported by the Bill and Melinda Gates and the Howard G. Buffet Foundations, and the United States Agency for International Development through the Water Efficient Maize for Africa project. We appreciate all the Zonal Agricultural Research Development Institutes (ZARDI) and Mobuku Irrigation Scheme for making their facilities available for this study. We thank Dr. Dan Makumbi for helpful comments and suggestions on the manuscript. We also appreciate the constructive comments of anonymous reviewers, who helped to improve the manuscript. Also the authors would like to thank Ochen Stephen, Solomon Kaboyo, Annet Nakayima, Majid Walusimbi, Moses Ebellu, Late Stephen Okanya, Fred Ssemazzi and Jane Alupo for data collection at the various experimental sites.
- Beyene Y, Mugo S, Pillay K, Tefera TSA, Njoka S, Karaya H, Gakunga J (2011) Testcross performance of doubled haploid maize lines derived from tropical adapted backcross populations. Maydica 56:351–358Google Scholar
- Beyene Y, Tarekegne A, Gakunga J, Mugo S, Tefera T, Karaya H, Semagn K, Gethi J, Chavangi A, Asea G, Kiula B, Trevisan W (2013) Genetic distance among doubled haploid maize lines and their testcross performance under drought stress and non-stress conditions. Euphytica 192:379–392CrossRefGoogle Scholar
- Burdon RD (1977) Genetic correlation as a concept for studying genotype-environment interaction in forest tree breeding. Silvae Genet. 26:168–175Google Scholar
- Cooper M, Delacy IH, Basford KE (1996) Relationships among analytical methods used to analyze genotypic adaptation in multi-environment trials. In: Cooper M, Hammer GL (eds) Plant adaptation and crop improvement. CAB Int, Wallingford, pp 193–224Google Scholar
- Falconer D, Mackay T (1996) Introduction to quantitative genetics. Longman, LondonGoogle Scholar
- Hallauer A, Miranda J (1981) Quantitative genetics in maize breeding. Iowa State University Press, AmesGoogle Scholar
- Hallauer AR, Carena M, Miranda Filho JB (2010) Quantitative genetics in maize breeding, 3rd edn. Iowa State University Press, AmesGoogle Scholar
- Kassa Y, Asea G, Demissew AK, Ligeyo D, Demewoz N, Saina E, Sserumaga JP, Twumais-Afriyie S, Opio F, Rwomushana I, Gelase N, Gudeta N, Wondimu F, Solomon A, Habtamu Z, Andualem WBA, Habte J, Muduruma Z (2013) Stability in performance of normal and nutritionally enhanced highland maize hybrid genotypes in Eastern Africa. Asian J Plant Sci 12:51–60CrossRefGoogle Scholar
- Munyiri S, Pathak R, Tabu I, Gemenet D (2010) Effects of moisture stress at flowering on phenotypic characters of selected local maize landraces in Kenya. J Anim Plant Sci 8:892–899Google Scholar
- Robinson P (1963) Heritability: a second look. In: Hanson WD, Robinson HF (eds) Statistical genetics and plant breeding. Publ. 982. National Academy of Science. National Research Council, Washington, DC, p 609–614Google Scholar
- SAS Institute (2008) SAS/STAT user’s guide. SAS Institute, CaryGoogle Scholar
- Tukamuhabwa P, Assiimwe M, Nabasirye M, Kabayi P, Maphosa M (2012) Genotype by environment interaction of advanced generation soybean lines for grain yield in Uganda. Afric Crop Sci J 20:107–115Google Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.