Download Selection of Breeding Program # 2

Genetics – Trait
Selection
An S 426
Fall 2007
Genetics – Trait Selection
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Has led to development of Economically Relevant Traits (ERT)
and Indicator Trait (IT)
Distinguish between two by asking question about the trait of
interest: if that trait changes one unit, either up or down
with no changes in other traits, will there be a direct effect on
income or expense
Genetics – Trait Selection
1. Birth weight and calving ease: does a 1 lb. change in
birth weight directly influence expense or income
a. May or may not result in increased /decreased
calving difficulty
b. Calving ease, a 1% decrease (meaning one extra
animal assisted for every 100 calving) has a direct impact on
profitability
c. Thus birth weight is an IT and calving ease is an ERT
and thus select for calving ease
Genetics – Trait Selection
2. Instances where traits can be both an IT and ERT
a. Cow mature weight; selling cull cows – a 1 lb. change
in mature weight directly influences income
b. Mature weight also influences maintenance feed
requirements; a mature weight increases of 1 lb. may not
increase maintenance requirements
c. Thus mature weight when selling cull cows is an ERT
and when considering maintenance is an IT
Genetics – Trait Selection
Why EPD for IT:
1.
2.
3.
Genetics – Trait Selection
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Guidelines for using ERT and IT
1. Many ERT still being developed by breed associations
2. Suggested procedure:
a. Identify ERT for your production and marketing system
b. Make selection decisions based on EPD with the following
order of preference
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Genetics – Trait Selection
b. Make selection decisions based on EPD with the following
order of preference
1.) Select using EPD for the ERT when available
2.) Select using EPD for the IT when ERT are unavailable
When phenotypic information is available, but not EPD:
3.) Select from within a herd on phenotype or ratios for the
ERT
4.) Select from within a herd on phenotype or ratios for the
IT
Sire Selection
An S 426
Fall 2007
Sire Selection
Represents the greatest opportunity for making genetic
improvement
Sire Selection
Example:
100 cow herd
5 year generation interval –
90% conception rate –
80% conception rate in heifers –
1 bull saved per year
Sire Selection
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AI permits more rapid genetic improvement –
Selection of bulls is more accurate
Genetic improvement is slow and depends on h2, but it is
permanent
Management decisions can be changed rapidly and are not
permanent