Czech J. Genet. Plant Breed., 2020, 56(4):133-139 | DOI: 10.17221/11/2020-CJGPB

Potentials to breed for improved fibre digestibility in temperate Czech maize (Zea mays L.) germplasmOriginal Paper

Manfred Schönleben*,1, Joachim Mentschel2, Lubo¹ Støelec1
1 Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University, Brno, Czech Republic
2 Department of Global Business Development, Sano - The Animal Nutritionists, Grafenwald, Loiching, Germany

Cell wall digestibility is an important quality trait of modern silage maize cultivars. The symbiotic relationship between microbes and ruminant livestock enables the efficient upcycling of otherwise for human consumption unsuitable rumen digestible fibre or cell wall components into highly nutritious milk and meat. Before entering the Czech National List of Plant Varieties, new silage maize germplasm is extensively tested for different cell wall digestibility parameters. Recently published, the undigestible neutral detergent fibre (uNDF) cell wall digestibility approach promises even greater practical relevance. The aim of our study was, therefore, to assess the potential of the uNDF method, compared with current standard procedures, using a vast set of official Czech plant variety trial evaluations and Czech silage analyses from the 2018 cropping season. The uNDF method yielded a twice as high phenotypic standard deviation, compared with the current standard approaches. This is good news for plant breeders, official variety testing organisations, and farm professionals alike, enabeling faster variety improvement and simpler variety selection. On the other hand, due to the low differentiation potential, we discourage the use of the absolute lignin content when selecting for digestible silage maize varieties. Since between the digestibility traits enzymatic soluble organic substance (ELOS) and cellulase digestibility (DCS), a Pearson correlation close to one was observed, the substitution of one of these analytics by the uNDF method, may render valuable additional information in a highly economical manner.

Keywords: cell wall digestibility; lignin; phenotypic variation; uNDF

Published: December 31, 2020  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Schönleben M, Mentschel J, Støelec L. Potentials to breed for improved fibre digestibility in temperate Czech maize (Zea mays L.) germplasm. Czech J. Genet. Plant Breed. 2020;56(4):133-139. doi: 10.17221/11/2020-CJGPB.
Download citation

References

  1. Allen M.S., Coors J.G., Roth G.W. (2003): Corn silage. Chapter 12. In: Buxton D.R., Muck R.E., Harrison J.H. (eds.): Silage Science and Technology. Madison, American Society of Agronomy: 547-608. Go to original source...
  2. Aufrère J., Baumont R., Delaby L., Peccatte J.R., Andrieu J., Andrieu J.P., Dulphy J.P. (2007): Forecasting the digestibility of forages using the pepsin-cellulase method. Update on the proposed equations. Productions Animales, 20: 129-136. (in French) Go to original source...
  3. Barrière Y., Guillet C., Goffner D., Pichon M. (2003): Genetic variation and breeding strategies for improved cell wall digestibility in annual forage crops. A review. Animal Research, 52: 193-228. Go to original source...
  4. Falconer D.S., Mackay T.F. (1996): Quantitative Genetics. Harlow, Pearson Prentice Hall: 184-207.
  5. FAO (2010): Greenhouse Gas Emissions from the Dairy Sector: A Life Cycle Assessment. Rome, FAO Animal Production and Health Division: 10-98.
  6. Geiger H.H. (2009): Doubled haploids. Chapter 32. In: Bennetzen J., Hake S. (eds.): Handbook of Maize: Genetics and Genomics. 1 st Ed. New York, Springer-Verlag: 641-657. Go to original source...
  7. Higgs R.J., Chase L.E., Ross D.A., Van Amburgh M.E. (2015): Updating the cornell net carbohydrate and protein system feed library and analyzing model sensitivity to feed inputs. Journal of Dairy Science, 98: 6340-6360. Go to original source... Go to PubMed...
  8. Ledencan T., Simic D., Brkic I., Jambrovic A., Zdunic Z. (2003): Resistance of maize inbreds and their hybrids to fusarium stalk rot. Czech Journal of Genetics and Plant Breeding, 39: 15-20. Go to original source...
  9. Li Y.G., Jiang D., Xu L.K., Zhang S.Q., Ji P.S., Pan H.Y., Jiang B.W., Shen Z.B. (2019): Evaluation of diversity and resistance of maize varieties to Fusarium spp. causing ear rot in maize under conditions of natural infection. Czech Journal of Genetics and Plant Breeding, 55: 131-137. Go to original source...
  10. Meuwissen T.H.E., Hayes B.J., Goddard M.E. (2001): Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157: 1819-1829. Go to original source... Go to PubMed...
  11. Moe A.J., Carr S.B. (1984): Laboratory assays and nearinfrared reflectance spectroscopy for estimates of feeding value of corn silage. Journal of Dairy Science, 68: 2220-2226. Go to original source...
  12. Mudry P., Kraic J. (2007): Inter- and intra-population variation of local maize (Zea mays L.) populations from Slovakia and Czech Republic. Czech Journal of Genetics and Plant Breeding, 43: 7-15. Go to original source...
  13. National Plant Variety Office (2016): National List of Varieties. Bulletin of the Central Institute for Supervising and Testing in Agriculture: Czech Gazette for Plant Breeders Rights and National List of Plant Varieties: 9-15. (in Czech)
  14. Perry T.W. (1996): Corn as a livestock feed. Chapter 17. In: Sprague G.F., Dudley J.W. (eds.): Corn and Corn Improvement. 3rd Ed. Madison, American Society of Agronomy: 941-963.
  15. Povolny M., Vacek E., Schreiberova A. (2019): Silage Maize - Results of 2018 VCU Testing. Brno, National Plant Variety Office, CISTA: 2-135. (in Czech)
  16. R Core Team (2018): R: A Language and Environment for Statistical Computing. Vienna, R Foundation for Statistical Computing. Available at http://www.R-project.org/.
  17. Raffrenato E., Ross D.A., Van Amburgh M.E. (2018): Development of an in vitro method to determine rumen undigested aNDFom for use in feed evaluation. Journal of Dairy Science, 101: 9888-9900. Go to original source... Go to PubMed...
  18. Russell J. (2002): Rumen Microbiology and its Role in Ruminant Nutrition. New York, Cornell University Press: 3-121.
  19. Schönleben M., Mentschel J., Støelec L. (2020): Towards smart dairy nutrition: Improving sustainability and economics of dairy production. Czech Journal of Animal Science, 65: 153-161. Go to original source...
  20. Tilley J.M., Terry R.A. (1963): A two-stage technique for the in vitro digestion of forage crops. Journal of the British Grassland Society, 18: 104-111. Go to original source...
  21. Van Amburgh M.E., Collao-Saenz E.A., Higgs R.J., Ross D.A., Recktenwald E.B., Raffrenato E., Chase L.E., Overton T.R., Mills J.K., Foskolos A. (2015): The Cornell Net Carbohydrate and Protein System: Updates to the model and evaluation of version 6.5. Journal of Dairy Science, 98: 6361-6380. Go to original source... Go to PubMed...
  22. Van Soest P.J., Robertson J.B., Lewis B.A. (1991): Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. Journal of Dairy Science, 74: 3583-3597. Go to original source... Go to PubMed...

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.