Carcass data can be a gold mine of information to improve your herd.
Without summary carcass statistics, it's difficult to draw rational conclusions.
A total of $358! That's the average dollar difference the Iowa Beef Center found between the most and least valuable carcasses in a demonstration project with 29 Iowa beef producers marketing 66 groups of cattle. Upon further sorting, it was found that the bottom 25% of lots for uniformity had an average top-to-bottom value difference of $474.
These are exciting times for many cow/calf producers. Due to carcass data collection programs and the many grid market programs they participate in, these producers are getting either the first, second or third set of data on their production.
Depending on the investment, producers will receive at least the minimum data, which consists of hot carcass weight, quality grade and yield grade (YG). Most likely, this won't be tied to individual animal identification (ID).
For further cost, the returned data will be tied to animal ID and will likely include ribeye area; fat thickness; percent kidney; heart and pelvic fat; calculated YG; marbling score and maturity (physiological age of the carcass).
In most cases, this data is listed on a page with one line representing an animal and no attempt at data analysis. Without summary statistics, it's difficult to draw rational conclusions.
|Hot Carcass Weight||Less than 600 lbs.||600 to 750 lbs.||750 to 900 lbs.||900 to 950 lbs.||Over 900 lbs.||Average|
|Yield Grade||YG 1||YG 2||YG 3||YG 4||YG 5||Average|
|USDA Quality Grade||Prime||Upper 2/3 Choice||Low Choice||Select||Off Grades||Average|
|Fat Thickness||Less than 0.2"||0.2" to 0.4"||0.4" to 0.6"||0.6" to 0.8"||Over 0.8"||Average|
|Ribeye Area||Less than 11"||11" to 13"||13" to 15"||15" to 17"||Over 17"||Average|
There are two ways, however, to get this done. You can use some type of summarization form like that shown in Fig. 1 or acquire a computer program to summarize your data in a fashion similar to Figs. 2 and 3. Whichever method you choose, it's imperative that the data is converted into information that allows comparisons or benchmarking to take place.
Our goal from summarization is to determine positive and negative trends in our production system in order to make changes. Figs. 2 and 3 give the producer two types of data summary. Summaries like Fig. 2 allow you to benchmark how cattle similar to these will perform in various grid markets.
For instance, if one is trying to target these cattle into a high-quality grid, many questions can be answered with this information. Among them:
Are there enough Prime and upper Choice cattle to compete successfully in a selected grid?
Is 88.5% YG 1, 2 and 3 good enough to overcome the 11.5% YG 4s?
Will 34.6% Select and below compete successfully in the targeted grid?
Secondly, summary data presented in Fig. 3 allows one to more accurately pinpoint particular performance strengths and weaknesses. As this example shows, more than 40% of these cattle weigh in excess of 850 lbs. and the percent Choice and better is less than 66%.
Some might ask if more quality can be fed into these cattle? The answer is no. More than 33% of the cattle already carry 0.6 in. of fat cover and carcass weight is getting close to big discount levels. If the cattle averaged 0.35 in. of back fat, weighed 800 lbs. on average and had the same quality grade average, then perhaps additional weight would improve carcass quality.
Insight Into Uniformity
Summaries like Fig. 3 also tell you a great deal about your market group uniformity and the accuracy of your sorting eye. In this group, the cattle had carcass weights ranging from 650-950 lbs., which translates into a live weight range of about 1,050 to more than 1,500 lbs.
|Prime||Up ⅔ Ch |
|Up ⅔ Ch |
|Choise-||Select||Standard & Off Grades||Totals|
|Hot Carcass |
|Sum||43,383 lbs.||Sum||716 sq. in.||Sum||26.1 in.|
|Average||834.3 lbs.||Average||13.8 sq. in.||Average||0.50 in.|
Were the overweight cattle also overfat? The individual data will tell us, but it's not unusual for the situation to go either way.
The next step is to see if genetic bases differ. This type of analysis may fit with either specific sources of genetics or actual sire differences. However, it's important to keep in mind on sire analysis that one is accounting for any differences that might exist due to the female side or if the sire groups were managed differently.
Fig. 4 gives a summary of two sires over two years' time. Sire 1 is achieving 72% low Choice and better while sire 2 comes in at about 43%. Although sire 2 excels in YG 1 and 2s, sire 1 gives acceptable performance in that category.
Both sires have similar progeny feedlot gain and ending live and carcass weights. If one is targeting a lean market that accepts lower quality grades and rewards handsomely for better red meat yield, then sire 2 comes out the winner. However, if one targets a high-quality grid, sire 2 fails because of an unacceptable amount of Standard and off grading carcasses.
What Is A Grid-Type Carcass?
So, what type of carcass performance does it take to succeed in grid markets? First, let's clarify that all grid/formula markets are not alike, nor should they be. What carcass performance is needed to succeed in one grid may be far different than that necessary to succeed in another.
In 1999, the Iowa Beef Center compared 66 market groups of cattle in four different grid markets utilizing a grid market analyzer program. What we found is summarized in Fig. 5.
Groups that made it into the top quartile for premiums per head exceeded the average for percents low Choice, upper two-thirds Choice and Prime. Additionally, they were better in YG 1 and 2 and had only about half as many YG 4 and 5s. Cattle that fell into the bottom quartile were substantially lower in quality grade, had fewer YG 1 and 2s, had more discounts due to YG 4 and 5s, and had overweight carcasses.
The ultimate in carcass data collection and analysis is the development of expected progeny differences (EPDs) that has taken place from both actual carcass data collection and ultrasound measurements. Both are extremely useful and should be used to their fullest potential.
Most exciting currently is the use of real-time ultrasound to measure yearling bulls and then process that information into interim EPDs. This new technique incorporates pedigree ultrasound data as well as individual ultrasound performance into EPDs that more accurately predict future carcass performance than just individual ultrasound data and “the old eye ball.” Both commercial and seedstock producers must study their herd needs and move fast to incorporate this new tool into their selection war chest.
|Quality Grade||Sire 1||Sire 2|
|Upper 2/3 Choice||12.0%||0.0%|
|Yield Grade||Sire 1||Sire 2|
|Number of Head||25||50|
|Average Final Weight (Lbs.)||1,180||1,198|
|Average ADG (Lbs./Day)||2.85||2.89|
|Average Hot Carcass Wt.||731.5 lbs.||732.9 lbs.|
Is this trend toward producing a high red meat yield with optimum quality going to fade away? It's doubtful. One only needs to look at the competing protein markets for what lies ahead. If anything, beef producers will likely see the list of carcass traits that we need to select for expand. Currently, the American Simmental Association is providing tenderness EPDs and they will be followed by other traits as new technologies come on board.
|$ Premium/Head||Top |
|% Upper ⅔ Choice||30.9%||18.0%||24.2%|
|% Low Choice||51.9%||43.9%||50.4%|
|% Standard & Off Grades||0.1%||3.8%||1.2%|
|% Yield Grade 1 & 2s||64.1%||58.4%||61.1%|
|% Yield Grade 3s||33.3%||33.8%||34.4%|
|% Yield Grade 4 & 5s||2.6%||7.8%||4.5%|
Is this bad for the U.S. beef business? Quite the contrary, this puts our production in a world leadership role and improves its competitive advantage.
Daryl Strohbehn is a professor of animal science at Iowa State University Beef Center in Ames. He can be reached at 515/294-3020; e-mail: [email protected] .