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Feedlot Data Linked to Quality Data on the Rail

Even the simple process of using data to affirm and sustain current management and breeding efforts is difficult.
BeefTalk BeefTalk
 

By Kris Ringwall
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NDSU Extension Beef Specialist
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One of the biggest challenges for beef producers is to engage
the data they collect within their operations. Even the simple
process of using data to affirm and sustain current management
and breeding efforts is difficult. The concept of using data
to cause change is scary and foreign to many.

The Dickinson Research Extension Center has retained data for
all steer calves since 1997. Each year's data is always fun to
evaluate. It is important to evaluate data in a manner that
makes sense. Statistical methods applied to the data are
important, but not at the expense of losing the logic for the
producer.

Initially, the feedlot data should be placed in common sense
groupings to see if anything important jumps out. In 2005,
five of the lots of calves born or purchased were above the
feedlot average in returning money back to the ranch. One of
the lots was below average.

The above-average lots started at $925 per head net return to
the ranch, followed by $883, $857, $815 and $803 per head. The
one lot that was below average came in at $724-per-head net
return to the ranch. The average net return was $757. Finding
the traits that linked positively to the overall dollar return
to the ranch is not simple, but starting with one logical
trait helps to, at least, generate some points to think about.

For today, the concept of quality comes to mind. The quality
grades of beef are traits that have been talked about for
years. The fact is well-established that various genetics are
available to produce cattle that have a greater percentage of
Choice grade versus those breeds that are noted for producing
a greater percentage of Select grade cattle.

Depending on the current price and marketing options, the
values associated with quality traits will vary from season to
season. Cattle that have excelled in quality are those cattle
that are predicted to be more palatable, based on maturity
indicators of the carcass, as well as the amount and
distribution of the intramuscular fat evident in the ribeye.

A closer look at the data shows that of the six lots the
center had on feed quality did have some impact on the net
return back to the ranch. Lot 4425 returned the most dollars
back to the ranch. This lot also had the greatest percentage
of Choice steer calves (77.3 percent) and the least percentage
of Select steer calves (22.7 percent).

Lot 4557 was also above average in percentage Choice steer
calves (43.7 percent), followed by lot 4528, with 45.6 percent
of Choice steers, and lot 4562, with 51.8 percent of Choice
steers. This is not an exhaustive statistical exercise, but
the top four lots for net return to the center were all above
average in the percentage of steer calves that graded Choice.

The fifth lot of calves was below average in the percentage of
Choice steer calves (21.7 percent). However, the lot was still
an above-average lot in net return to the center.

Lot 4359 was below average in net return to the center. This
set of calves had obvious difficulties. Only 17.9 percent
graded Choice and 64.3 percent graded Select. A dismal 17.9
percent of Lot 4359 was side railed to the no-roll section in
the packing plant. (No-rolls are cattle that are not graded
because the apparent quality is not evident in the meat.
No-rolls are sold without placing an official USDA grading
stamp on the carcass.)

The bottom line is obvious: Carcass quality has an impact on
the value of cattle.

May you find all your NAIS-approved ear tags.

Your comments are always welcome at www.BeefTalk.com. For more
information, contact the NDBCIA Office, 1133 State Ave.,
Dickinson, ND 58601 or go to www.CHAPS2000.COM on the
Internet.

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NDSU Agriculture Communication

:Source: Kris Ringwall, (701) 483-2427, kringwal@ndsuext.nodak.edu
:Editor: Rich Mattern, (701) 231-6136, richard.mattern@ndsu.edu

Feedlot Performance Feedlot Performance
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