Testcross performance of doubled haploid lines from European flint maize landraces is promising for broadening the genetic base of elite germplasm
Selected doubled haploid lines averaged similar testcross performance as their original landraces, and the best of them approached the yields of elite inbreds, demonstrating their potential to broaden the narrow genetic diversity of the flint germplasm pool.
Maize landraces represent a rich source of genetic diversity that remains largely idle because the high genetic load and performance gap to elite germplasm hamper their use in modern breeding programs. Production of doubled haploid (DH) lines can mitigate problems associated with the use of landraces in pre-breeding. Our objective was to assess in comparison with modern materials the testcross performance (TP) of the best 89 out of 389 DH lines developed from six landraces and evaluated in previous studies for line per se performance (LP). TP with a dent tester was evaluated for the six original landraces, ~ 15 DH lines from each landrace selected for LP, and six elite flint inbreds together with nine commercial hybrids for grain and silage traits. Mean TP of the DH lines rarely differed significantly from TP of their corresponding landrace, which averaged in comparison with the mean TP of the elite flint inbreds ~ 20% lower grain yield and ~ 10% lower dry matter and methane yield. Trait correlations of DH lines closely agreed with the literature; correlation of TP with LP was zero for grain yield, underpinning the need to evaluate TP in addition to LP. For all traits, we observed substantial variation for TP among the DH lines and the best showed similar TP yields as the elite inbreds. Our results demonstrate the high potential of landraces for broadening the narrow genetic base of the flint heterotic pool and the usefulness of the DH technology for exploiting idle genetic resources from gene banks.
We thank Willem Molenaar for valuable suggestions to improve the manuscript. We would also like to thank the technical staff from the University of Hohenheim for excellence in conducting the field experiments. We are indebted to KWS SAAT SE for the additional field experiment in Einbeck and Thomas Presterl and Theresa Bolduan for conducting it. This research was funded by the German Federal Ministry of Education and Research (BMBF) within the scope of the funding initiative MAZE “Plant Breeding Research for the Bioeconomy” (Funding ID: 031B0195).
Compliance with ethical standards
Conflict of interest
All authors declare that they have no conflict of interest.
The experiments reported in this study comply with the current laws of Germany.
- Albrecht T (2014) Genome-based prediction of testcross performance in maize (Zea mays L.). Dissertation Technical University of Munich, Munich. https://mediatum.ub.tum.de/doc/1227384/1227384.pdf
- Andjelkovic V, Ignjatovic-Micic D (2012) Maize genetic resources—science and benefits. Serbian Genetic Society, Belgrade. https://www.researchgate.net/publication/304056743_Maize_Genetic_Resources-Science_and_Benefits-
- Barrière Y, Alber D, Dolstra O et al (2006) Past and prospects of forage maize breeding in Europe. II. History, germplasm evolution and correlative agronomic changes. Maydica 51:435–449Google Scholar
- Cochran WG, Cox GM (1957) Experimental designs, 2nd edn. Wiley, LondonGoogle Scholar
- Geiger HH, Melchinger AE, Schmidt GA (1986) Analysis of factorial crosses between flint and dent maize inbred lines for forage performance and quality traits. In: Proceeding of the 13th congress of the maize and sorghum section of EUCARPIA. Pudoc Press, Wageningen, pp 147–154Google Scholar
- Gouesnard B, Negro S, Laffray A et al (2017) Genotyping-by-sequencing highlights original diversity patterns within a European collection of 1191 maize flint lines, as compared to the maize USDA genebank. Theor Appl Genet 130:2165–2189. https://doi.org/10.1007/s00122-017-2949-6 CrossRefPubMedGoogle Scholar
- Grieder C, Dhillon BS, Schipprack W, Melchinger AE (2012) Breeding maize as biogas substrate in Central Europe: II. Quantitative-genetic parameters for inbred lines and correlations with testcross performance. Theor Appl Genet 124:981–988. https://doi.org/10.1007/s00122-011-1762-x CrossRefPubMedGoogle Scholar
- Hallauer AR, Carena MJ, Miranda Filho JB (2010) Quantitative genetics in maize breeding, 3rd edn. Springer, New YorkGoogle Scholar
- Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6:65–70Google Scholar
- Janick J, Caneva G (2005) The first images of maize in Europe. Maydica 50:71–80Google Scholar
- Larièpe A, Moreau L, Laborde J et al (2017) General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents. Theor Appl Genet 130:403–417. https://doi.org/10.1007/s00122-016-2822-z CrossRefPubMedGoogle Scholar
- Lübberstedt T, Melchinger AE, Klein D et al (1997) QTL mapping in testcrosses of European flint lines of maize: II. Comparison of different testers for forage quality traits. Crop Sci 37:1913. https://doi.org/10.2135/cropsci1997.0011183x003700060041x CrossRefGoogle Scholar
- Melchinger AE (1999) Genetic diversity and heterosis. In: Coors JG, Pandey S (eds) The genetics and exploitation of heterosis in crops. CSSA, Madison, pp 99–118Google Scholar
- Melchinger AE, Schmidt W, Geiger HH (1988) Comparison of testcrosses produced from F2 and first backcross populations in maize. Crop Sci 28:743. https://doi.org/10.2135/cropsci1988.0011183x002800050004x CrossRefGoogle Scholar
- Messmer MM, Melchinger AE, Boppenmaier J et al (1992) Relationships among early European maize inbreds: I. Genetic diversity among flint and dent lines revealed by RFLPs. Crop Sci 32:1301. https://doi.org/10.2135/cropsci1992.0011183x003200060001x CrossRefGoogle Scholar
- Messmer MM, Melchinger AE, Herrmann RG, Boppenmaier J (1993) Relationships among early European maize inbreds: II. Comparison of pedigree and RFLP data. Crop Sci 33:944. https://doi.org/10.2135/cropsci1993.0011183x003300050014x CrossRefGoogle Scholar
- Pollmer WG, Phipps RH (1980) Improvement of quality traits of maize for grain and silage use. Martinus Nijhoff, LeidenGoogle Scholar
- R Core Team (2017) A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Salhuana W, Pollak L (2006) Latin American Maize Project (LAMP) and Germplasm Enhancement of Maize (GEM) project: generating useful breeding germplasm. Maydica 51:339–355Google Scholar
- Schnell FW (1983) Probleme der Elternwahl—Ein Überblick. In: Arbeitstagung der Arbeitsgemeinschaft der Saatzuchtleiter in Gumpenstein, Austria. 22.–24. Nov. Verlag und Druck der Bundesanstalt für alpenländische Landwirtschaft, Austria, pp 1–11Google Scholar
- Schnell FW (1992) Maiszüchtung und die Züchtungsforschung in der Bundesrepublik Deutschland. In: Vorträge Pflanzenzüchtung, pp 27–44Google Scholar
- Shull GH (1908) The composition of a field of maize. Am Breeders Assoc Rep 4:296–301Google Scholar
- Smith OS (1986) Covariance between line per se and testcross performance. Crop Sci 26:540. https://doi.org/10.2135/cropsci1986.0011183X002600030023x CrossRefGoogle Scholar
- Snedecor GW, Cochran WG (1989) Statistical methods, 8th edn. Iowa State Univ Press, AmesGoogle Scholar
- Späth HR (1973) Vergleich verschiedener Einfachkreuzungen als Komplementärmaterial für ein Hybridzuchtprogramm bei Mais. Dissertation University of Hohenheim, HohenheimGoogle Scholar
- Stadler LJ (1944) Gamete selection in corn breeding. J Am Soc Agron 36:988–989Google Scholar
- Tilley JMA, Terry RA (1963) A two-stage technique for the in vitro digestion of forage crops. Grass Forage Sci 18:104–111. https://doi.org/10.1111/j.1365-2494.1963.tb00335.x CrossRefGoogle Scholar
- Utz HF (2011) A computer program for statistical analysis of plant breeding experiments. Version 3A: Univ. Hohenheim, StuttgartGoogle Scholar