Genetic and Agronomic Analysis of Latvian Fescue (Festuca Spp.), Ryegrass (Lolium Spp.) Accessions and their Hybrids

Open access

Abstract

The development of ecologically adaptable fodder crop varieties is of increasing importance, particularly in the context of climate change. New varieties should be phenotypically and ecologically plastic and able to adapt to differing climactic and soil conditions, ensuring high yields and persistence. Combining Festuca and Lolium species and the development of hybrid (Festulolium) cultivars can be a promising method of combining high yield, high feed quality, persistence, as well as cold, frost and drought tolerance. Breeders at the Institute of Agriculture of Latvia University of Life Sciences and Technologies have been utilizing Festulolium germplasm for several decades. Currently, in cooperation with the molecular genetics laboratory and Latvian gene bank at the Latvian State Forest Research Institute “Silava”, analysis of Festuca, Lolium and their hybrids with DNA markers has been initiated, in order to gain additional knowledge about the breeding material and to increase the efficiency of the breeding process. Results of the assessment of morphological and agronomic traits in long-term field trials are combined with DNA markers analyses in order to determine the correlation of genetic and phenotypic traits.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • Becker T. Isselstein J. Benke M. Kayser M. (2018). Persistence of modern varieties of Festuca arundinacea L. and Phleum pratense L. as an alternative to Lolium perenne L. in intensively managed sown grasslands. In: Sustainable Meat and Milk Production from Grasslands. Proceedings of the 27th General Meeting of the European Grassland Federation Cork Ireland 17–21 June 2018. Teagasc Animal & Grassland Research and Innovation Centre pp. 117–119.

  • Berzins P. Jansone S. Rancane S. Stesele V. Dzene I. (2015). The evaluation of perennial grass cultivars in Latvia condition. In: Proceedings of the 25th NJF Congress “Nordic View to Sustainable Rural Development” Riga Latvia 16–18 June 2015 pp. 141–147.

  • Berzins P. Rungis D. Rancane S. Gailite A. Belevica V. Stesele V. Vezis I. Jansons A. (2018a). Yield and genetic composition of Latvian × Festulolium cultivars and breeding material. In: Brazauskas G. et al. (eds.). Breeding Grasses and Protein Crops in the Era of Genomics. Springer pp. 62–67.

  • Berzins P. Rancane S. Stesele V. Vezis I. (2018b). Performance of Lolium spp. Festuca spp. and their mutual hybrids in Latvian conditions. Sustainable meat and milk production from grasslands. In: Horan B. Hennessy D. O’Donovan M. et al. (eds.). Proceedings of the 27th General Meeting of the European Grassland Federation Cork Ireland 17–21 June 2018 pp. 123–126.

  • Casler M. D. Peterson P. R. Hoffman L. D. Ehlke N. J. Brummer E. C. Hansen J. L. Mlynarek M. J. Sulc M. R. Henning J. C. Undersander D. J. Pitts P. G. Bilkey P. C. Rose-Fricker C. A. (2002). Natural selection for survival improves freezing tolerance forage yield and persistence of Festulolium. Crop Sci. 42 1421–1426.

  • Cougnon M. Baert J. Van Waes C. Reheul D. (2013). Performance and quality of tall fescue (Festuca arundinacea Schreb.) and perennial ryegrass (Lolium perenne L.) and mixtures of both species grown with or without white clover (Trifolium repens L.) under cutting management. Grass and Forage Sci. 69 666–677.

  • Dieringer D. Schlötterer C. (2003). Microsatellite Analyser (MSA): A platform independent analysis tool for large microsatellite data sets. Mol. Ecol. Notes3 (1) 167–169.

  • Earl D. A. vonHoldt B. M. (2012). STRUCTURE harvester: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Gen. Res. 4 (2) 1–3.

  • Lemežienė N. Kanapeckas J. Tarakanovas P. Nekrošas S. (2004). Analysis of dry matter yield structure of forage grasses. Plant Soil Environ. 50 2004 (6) 277–282.

  • Moser I. E. Buxton D. R. Casler M. D. (eds.) (1996). Cool Season Forage Grasses. Agron. Monogr. Vol. 34. American Society of Agronomy Crop Science Society of America Soil Science Society of America Madison Wisconsin. 841 pp.

  • Østrem L. Volden B. Larsen A. (2013a). Morphology dry matter yield and phenological characters at different maturity stages of Festulolium compared with other grass species. Acta Agricult. Scand. Section B. Soil Plant Sci. 63 (6) 531–542.

  • Østrem L. Novoa-Garrido M. Larsen A. (2013b). Festulolium: An interesting forage grass for high-latitude regions? Grassland Sci. Eur. 18 270–272.

  • Peakall R. Smouse P. E. (2006). GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes6 (1) 288–295.

  • Porebski S. Bailey L. G Baum B. R. (1997). Modification of a CTAB DNA extraction protocol for plants containing high polysaccharide and polyphenol components. Plant Mol. Biol. Rep. 15 8–15.

  • Porras-Hurtado L. Ruiz Y. Santos C. Phillips C. Carracedo Į. Lareu M. V. (2013). An overview of STRUCTURE: Applications parameter settings and supporting software. Frontiers Genet. 4 98.

  • Pritchard J. K. Stephens M. Donnelly P. (2000). Inference of population structure using multilocus genotype data. Genetics55 (2) 945–959.

  • Studer B. Asp T. Frei U. Hentrup S. Meally H. Guillard A. Barth S. Muylle H. Roldán-Ruiz I. Barre P. Koning-Boucoiran C. Uenk-Stunnenberg G. Dolstra O. Skøt L. Skøt K. P. Turner L. B. Humphreys M. O. Kölliker R. Roulund N. Nielsen K. K. Lübberstedt T. (2008). Expressed sequence tag-derived microsatellite markers of perennial ryegrass (Lolium perenne L.). Mol. Breed. 21 (4). 533–548.

  • Thomas H. Humphreys M. O. (1991). Progress and potential of interspecific hybrids of Lolium and Festuca. Agr. Sci. 117 1–8.

  • Thomas H. M. Morgan W. G. Humphreys M. W. (2003). Designing grasses with a future — combining the attributes of Lolium and Festuca. Euphytica133 19–26.

  • Wilkins P. W. Humphreys M. O. (2003). Progress in breeding perennial forage grasses for temperate agriculture. J. Agr. Sci. 140 129–150.

Search
Journal information
Impact Factor


CiteScore 2018: 0.3

SCImago Journal Rank (SJR) 2018: 0.137
Source Normalized Impact per Paper (SNIP) 2018: 0.192

Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 51 51 17
PDF Downloads 67 67 24