BET
ON
RED
continued from page 66
We have always
strong, there will be some animals that happen to move in a
consistently favorable or unfavorable direction in a number of
EPDs. Because indexes are comprised of several EPDs, even though
movement in individual EPDs may be considered small, movement
in the same direction across EPDs may yield sizable movements in the
index value. This is particularly true for animals that have consistent
movement in traits that are drivers of a particular index. Though in
a large population like ours we would expect to see several animals
with substantial index movement, these animals will be the exception
to the rule.
had a passion for
Red Limousin cattle.
These three females
are keeping us on
the cutting-edge of
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ENGD
Zenana
Homo Polled • Purebred
s: Wulfs Well Suited
d: ENGD Xtra Fine 022X
CE: 9 BW: 0.9 WW: 59
YW: 85 MK: 15 DC: 15
RE: 1.06 MB: -.46 $MI: 36
Golden
Jubilee
CJLA
Het Polled • Purebred
s: RPY Paynes Cracker 17E
d: Limolyn Colette
CE: 9 BW: -0.1 WW: 64
YW: 96 MK: 25 DC: 13
RE: 1.00 MB: -.36
COLE
Miss Xrated
571C
Homo Polled • Purebred
s: MRL X-Rated 014X
d: COLE Miss Justice 772T
CE: 8 BW: 2.5 WW: 69
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RE: 1.02 MB: -.50 $MI: 38
CONTACT US TODAY FOR PREMIUM RED GENETICS
499A HOLLAND RD., JAVA VILLAGE, NY 14083
KYLE SMITH • 716.560.8682
[email protected]
70
9. H
ow does BOLT improve our calculation of accuracy?
“True” accuracy can be thought of as the gold standard of accuracy.
It is statistically unbiased, and therefore the ultimate measure of
accuracy. True accuracy is the accuracy resulting from direct calculation.
Unfortunately, even with the massively powerful computing capacity
now in existence, the direct calculation of accuracy is not possible on
datasets the size of ours.
Because we cannot calculate accuracy directly, other approaches to
accuracy calculation have been developed. In our Cornell evaluation
platform, and all others in existence other than BOLT, the calculation
of the accuracy associated with each EPD is achieved through
“approximation” methods. It has long been known these methods
are a very crude approach to the calculation of accuracy—tending to
overestimate accuracy.
Another approach to the calculation of accuracy is via “sampling”
methodology. Sampling is shown to be a more accurate predictor of
accuracy. In fact, the results of this method were reported to be virtually
identical to true accuracy. Unfortunately, due to its computationally
intense nature, sampling has long been thought an infeasible approach
to the calculation of accuracy on large databases.
BOLT, however, has changed the landscape in this area. By
employing unique computing strategies that leverage both software
and hardware efficiencies, BOLT performs what was previously
unthinkable—utilizing a sampling methodology to calculate what is
essentially true accuracy.
Because BOLT can calculate true accuracy, we can put more
confidence in our accuracy metrics. Put another way, unlike with
approximation, we can count on the predicted movements associated
with possible change holding true over time. This was not the case
with our Cornell system nor any other system in existence.
10. Why do the carcass EPDs generally have an increase in
accuracy with BOLT while this is not a case for other traits?
You will notice that while the Multi-breed Genetic Evaluation
powered by BOLT will generally produce lower accuracies than the
Cornell system for growth and calving-ease traits, the opposite is true
for carcass traits. One reason behind the differing accuracy outcomes
is several years ago the evaluation team developed a way to temper
inflated accuracies in the Cornell carcass evaluation. Unfortunately,
this was not possible for growth traits. Another reason is that the
Cornell system only used the carcass and its corresponding ultrasound
trait (e.g., marbling score and IMF) to predict carcass EPDs, while
• JANUARY 2020