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Instrumentation of Near-term Fetal Sheep for Multivariate Chronic Non-anesthetized Recordings
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A preference-based approach to deriving breeding objectives: applied to sheep breeding.

T J Byrne1, P R Amer, P F Fennessy

  • 1AbacusBio Limited, PO Box 5585, Dunedin, New Zealand. tbyrne@abacusbio.co.nz

Animal : an International Journal of Animal Bioscience
|May 8, 2012
PubMed
Summary

Irish sheep farmers prioritize lamb value and survival. Preference-based tools can help define breeding objectives when economic data is scarce, revealing differences between farmer groups and experts.

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Area of Science:

  • Agricultural Science
  • Animal Breeding
  • Behavioral Economics

Background:

  • Sheep production in Ireland is divided into lowland and hill systems.
  • Defining breeding objectives requires understanding trait importance.
  • Economic data may not always be available for trait valuation.

Purpose of the Study:

  • To determine the relative importance of target traits for Irish sheep breeding objectives.
  • To compare farmer and expert preferences for breeding traits.
  • To assess the utility of preference-based tools in defining breeding objectives.

Main Methods:

  • Choice-experiment surveys administered via 1000Minds software to experts and farmers.
  • Experts surveyed as both lowland and hill farmers.
  • Part-worth utilities converted to preference economic values (pEVs) and compared to bio-economic models.

Main Results:

  • Lamb value and survival were top priorities for experts (lowland and hill, respectively).
  • Foot baths and anthelmintic treatments were least important traits.
  • Significant differences in pEVs were found between farmer groups and experts for several traits.

Conclusions:

  • Preference-based tools are valuable for defining sheep breeding objectives, especially with limited economic data.
  • Understanding differing preferences between farmer types and experts is crucial for effective breeding strategies.
  • The study highlights the potential of incorporating stakeholder preferences into genetic improvement programs.