Luke’s Preface…
The greatest gift the ASA membership has received in the twenty-first century is the incorporation of economic selection $Indexes into our national cattle evaluation (performance database). It has literally taken us away from single trait selection and forced breeders to consider animals that are more (or less) profitable on the average farm/ranch enterprise. Developed in the 1940’s by Dr. Lanoy Hazel of Iowa State, $Indexes are what have led swine and chickens into being such masterfully efficient, high yielding meat animals compared to what they were 30 years ago. As my boss would say, “The debate is settled, $Indexes boil the suite of EPDs down into one trait…PROFIT!”
Below you’ll find Matt’s article not critical of $Indexes but somewhat skeptical on how one achieves such high yielding animals. It calls into question, are we getting the “pounds in the right package?” Is the biological composition of the animal we are developing the RIGHT composition, or are we just mashing the accelerator so hard that while we are maximizing dollars and minimizing inputs all the while making the profit unsustainable?
I guess this asks of each of you reading this blog post- Are you creating the biologically profitable Shorthorn that the industry needs, or are you just chasing an $Index at all costs? Again, the debate is over; the higher $Indexing cattle will be higher profiting for the production scenario you choose to model, BUT within that high $Indexing beast, is it the kind of Shorthorn that compliments the beef industry?
At BSG we have developed thresholds on where traits have to land in order to hit all the profit targets and make the kind of Shorthorn the industry wants. We hope you will too.
-Luke
Shorthorn Country, August 2022
by Matt Woolfolk, American Shorthorn Association
When you’re setting your destination into your Google Maps on a road trip, often you will be given multiple routes to get to the destination. Options include shortest travel time, least miles, or avoiding the toll roads and back roads. Even if you choose to ignore the guidance, it can be a helpful tool when heading to a new place. Much like directions to your destination, there are often several ways to land at the same end point when we are calculating selection indexes. To dive deeper into this subject matter, we’re going to make a U turn and go back to the basics of selection indexes to get a better grasp of the harder stuff later in the journey.
Selection indexes are essentially a complex algebraic equation with weights of importance placed on every EPD included in the index. These indexes are based on economic factors in certain production scenarios; the weightings of an EPD trait are not arbitrary. An index is usually expressed in a unit of dollars. Comparing two bulls for an index, the higher figure is projected to produce more revenue for the operation when he is used in a breeding scenario like the one the index is designed for. Situations that indexes are constructed for usually center around a commercial cow herd with a specific end point or marketing goal (replacement females, feeder steers, retained ownership, etc.). In a seedstock situation, these indexes find value in helping the genetic provider (YOU) produce cattle better suited for the commercial customers in those production scenarios.
American Shorthorn Association produces a trio of indexes for members to use in their breeding programs. The $Calving Ease index ($CEZ) is designed to identify genetics that excel in eliminating calving difficulty in heifers. Our $Feedlot index ($F) is constructed to help commercial producers find the bulls that will best work for their herds in a strictly terminal operation, focusing on growth and carcass quality. Finally, $British Maternal ($BMI) aims to identify the Shorthorns that are best suited for commercial breeders in a situation where they are retaining their own replacement females.
Much like developing a ration to feed your calves, there are multiple ways to get to the same outcome when using selection index technology in your program. While the ingredients may all be the same, the proportions and amounts can vary, all while still getting your cattle to the desired endpoint. I want to take the time to dive further into this concept, so below are some examples of how not all $BMI and $F are created equally. We’ll study how these bulls’ genetic profiles don’t necessarily look the same but can produce the same outcome from a revenue-generating perspective or index value.
$British Maternal
| Sire | CED | WW | YW | Milk | CEM | REA | MB | $BMI |
| Bull A | 18 | 31 | 41 | 30 | 10 | 0.33 | 0.10 | 145.25 |
| Bull B | 12 | 67 | 104 | 24 | 5 | 0.54 | 0.09 | 145.94 |
| Bull C | 12 | 53 | 78 | 33 | 7 | 0.42 | -0.19 | 145.68 |
There are several ways to arrive at almost equal $BMI when you study these three sires. Bull A excels in calving ease, solid carcass, and high milk, while also being low enough growth to not be penalized for (likely) larger mature sized cows. Bull B’s value in a $BMI scenario is largely in siring calves that will bring the most value at weaning through his high growth genetics. And Bull C is a combination bull that has good growth data, high milk, and solid calving ease. Obviously, these bulls take three very different paths to the same destination. With a more complex index like $BMI, there’s going to be multiple paths to the same answer. Remember, while $BMI does focus on aiding the rancher that is keeping his own females, it does not abandon the steer mates to his heifers. That is why you see growth and carcass traits involved in $BMI. A bull’s peak value may be in making top-class daughters with minimal regard to her brothers, or he may sire good females while siring killer feeder calves. Both possibilities are viable options to generate similar financial returns to the operation.
$Feedlot
| Sire | CED | WW | YW | REA | MB | $F |
| Bull 1 | 8 | 57 | 78 | 0.41 | 0.23 | 58.58 |
| Bull 2 | 15 | 60 | 84 | 0.35 | 0.12 | 58.55 |
| Bull 3 | 11 | 64 | 100 | 0.37 | -0.07 | 58.59 |
This index is designed to focus on terminal marketing, so it’s logical that growth is a driver of $Feedlot. With Bull 1, you get good growth with above average carcass values, creating value all the way through. Bull 2 is unique that his high CED is a bonus to him (CED factors in because we must have live calves to get them to grow in the feed yard). Growth is good on that bull, and carcass is acceptable. The growth data on Bull 3 are his selling point, adding pounds (and dollars) to a carcass that may not necessarily excel for quality on the grid. For cattle to rank highly in the $Feedlot metric, higher growth EPDs are important. Being elite for growth and carcass isn’t necessary, but if your bull is weaker in one area, he better be stronger in the other to be a top end $F bull.
Our final chart brings all six bulls used in this article together to compare their $BMI and $F values. You’ll notice that the high $BMI bulls don’t all translate to high $F cattle, while the high $F cattle look like stronger $BMI cattle as well. That’s likely due to the growth component factored into $BMI for the steer mates.
| Sire | $BMI | %Rank | $F | %Rank |
| Bull A | 145.25 | 3 | 44.94 | 85 |
| Bull B | 145.94 | 3 | 62.11 | 2 |
| Bull C | 145.68 | 3 | 52.04 | 30 |
| Bull 1 | 145.20 | 3 | 58.58 | 5 |
| Bull 2 | 142.95 | 4 | 58.55 | 5 |
| Bull 3 | 133.51 | 15 | 58.59 | 5 |
One important takeaway from this exercise is the making selections based solely on a selection index can be just as detrimental as making selections based on a single EPD. You may love Bull A’s $BMI, but if your customers have any market for selling or retaining feeder steers, he’s not a good option for fitting that niche. It’s still necessary to study the component traits of an index to make sure the bull you’re looking at is fine-tuned to meet your breeding goals. While it’s easy to get lost on the trip to breeding better Shorthorns, indexes can be a good guiding post for you, if you take into account the component pieces involved to make sure you stay following the little blue line on the “Google Maps” in your operation.