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Understanding the Genetic Basis for Slow Plant-Mediated Proteolysis in Festulolium Hybrids

  • S. A. O’Donovan
  • A. H. Kingston-Smith
  • M. W. Humphreys
Conference paper

Abstract

Inefficiencies in the rumen associated with excessive rates of degradation of forage protein have meant that resource capture is poor compared to the potential gains achievable from use of new grass cultivars. Increased rumen efficiency through improved utilization of feed protein will decrease emissions of environmentally damaging wastes and greenhouse gas emissions. New interspecific forage grass hybrids (Festulolium) derived from hybridizing ryegrass species Lolium perenne or Lolium multiflorum with the related fescue species Festuca arundinacea var glaucescens, native to mountain pastures in Mediterranean regions provide an opportunity to enhance ruminant nutrition and provide an environmental safeguard. Under rumen conditions, the fescue protein is degraded at a significantly slower rate than that of ryegrass which should lead to increased efficiency of feed N-utilization and aid livestock gain whilst also reducing N losses that contribute to greenhouse gas emissions. Procedures are underway to determine the necessary genome composition required to optimize expression of the fescue trait in a ryegrass genetic background and to determine the most effective plant breeding strategy to ensure that this is achieved. It is hypothesized that mechanisms evolved in the fescue species necessary for adaptations to high temperatures in Mediterranean locations are also functional and relevant for protein protection in stress conditions in the rumen. Combining these with ryegrass-derived traits for forage yield and quality should assist strategies for more sustainable livestock agriculture at a time of climate change.

Keywords

Protein Protection Severe Drought Stress Ruminant Nutrition Festuca Species Grass Cultivar 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This research is sponsored by EBLEX and HCC.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • S. A. O’Donovan
    • 1
  • A. H. Kingston-Smith
    • 1
  • M. W. Humphreys
    • 1
  1. 1.IBERSAberystwyth UniversityAberystwythWales

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