The American Simmental Association (ASA) launched the whole herd reporting system called, Total Herd Enrollment (THE), in April of 1999. Twenty years later, THE remains at the center of thorough data reporting to fuel the genetic evaluation. Why is whole herd reporting so beneficial to genetic evaluations and beef cattle breeders? This article dives into the merits of THE and similar systems for data-driven seedstock breeders and producers.
There are three big benefits of whole herd reporting for breeders.
1. To collect fertility and convenience trait data on the cow herd.
Reproduction is the biggest driver of profitability in the cow-calf sector and is also lowly heritable. Being lowly heritable means reproductive phenotypes are largely due to environmental influences. Therefore, to make improvements in the genetics of reproductive traits, it is imperative to use EPDs rather than making decisions based on a phenotype (i.e., pregnant vs. open). That is not to say there aren’t managerial reasons to cull an open cow, but culling because of a pregnancy status will not improve the genetics of fertility.
Cow longevity records encompass both reproductive and convenience traits into one record system — whether the cow had a calf every year (and therefore stayed in the herd). If a cow is removed from the herd, breeders have to give a reason for culling that encompasses fertility but also other structural or convenience traits.
THE herds report productivity for every single cow in the herd which indirectly provides fertility data on the entire herd. Records from THE herds are crucial for accurate prediction of Stayability (the likelihood that an animal’s daughter will remain productive in the herd up to 6 years of age). Cow longevity is a big driver of economic value to the cow-calf sector making the accurate prediction of stayability a vital component to the success of commercial cattle operations.
2. Better prediction of all remaining production traits.
By reporting records on whole contemporary groups, not just the best calves or calves that will be registered, breeders provide a much more complete picture of the genetic potential in those animals on all the traits they are recording. This benefits the herd reporting the data with more accurate within-herd selection information (for example ratios, see table). It also makes the EPDs in the IGS Multi-breed Genetic Evaluation more accurate as it better depicts the true genetic merit of the herd and the bloodlines represented within it (see tables on opposite page).
Here is an example from previous ASA staff articles where the consequences of reporting only part of a contemporary group and the resulting within-herd ratios, ranking, and EPDs were discussed.
Scenario: Using actual numbers from our database on spring 2015-born calves, we started with a set of 12 bull calves that are contemporaries from birth. Two of the calves were culled prior to weaning. The rest of the calves had birth, weaning and yearling weights submitted. Therefore, we have complete reporting on this contemporary group.
To show what happens with incomplete reporting, the weaning and yearling weights were removed on the four calves with the lowest adjusted growth measurements and we recalculated the group’s ranks, ratios, and EPDs. This would be comparable to a breeder not weighing (or submitting) data on their bottom-end bulls. The tables included show the results of performance calculations with the complete contemporary group (in white) and with incomplete reporting (in gray) and similar EPD and indexes when incomplete data is reported.
When partial data is reported, the moral of the story is clear — the best calves do not get credit for being as good as they are (incidentally, their parents won’t either.) Take a look at the 16C bull that scored a 118 ratio at weaning with a complete dataset. Its ratio went down to 110 and its WW EPD dropped from 53.8 to 49.1 when the slower-growing bulls were removed. 16C also experienced dips in its YW, $API and $TI. The same pattern exists for the other top bulls. Alternatively, the bottom bulls improved when their growth data were not included. By not reporting their growth data the system does not know how poorly they performed and can only use their birth weights and pedigrees to make growth predictions.
3. Higher return on the breeder’s time and money. By enrolling in THE, many breeders receive a kickback on prices for data, EPDs, and certificates with varying fee structures based on the needs of each operation. The real financial benefit comes from better predictions of the genetics in the herd and across the population. People pay a significant amount of money in genomic testing to try to get more accurate predictions of their cattle. High-quality phenotypes are just as valuable in genetic predictions. Consider all the time and money that has gone into raising a calf to weaning — this starts long before a calf is born. Selecting the parents, choosing the matings, synchronizing and breeding, turning out bulls, managing everyone for health, proper nutrition, calving, individual identification, taking weights, calving ease scores, making sure the calf and its dam receive all the care they need to flourish. There is work, time, and money invested in all this plus getting the records, submitting the records to your breed association, all the work that goes into the genetic evaluation. Given all this effort and expense, programs like THE ensure the breeders get the most value out of their hard-earned herd measurements.
THE requires breeders to keep a current inventory of cows in the herd and a status or production code for every cow. THE isn’t a fit for every seedstock operation which is okay. If for various reasons, THE doesn’t fit your operation, strive to submit whole contemporary group data whenever possible.
The foundation of accurate genetic evaluation is high-quality data to fuel the predictions. Thanks to all the data-focused breeders committed to the genetic improvement of their cattle in programs like THE. High-quality data helps the entire population have more accurate genetic predictions.