Data Collection

Data Collection for Seedstock Producers

At the core of genetic improvement is the collection of data. While data quality is critical, quantity of data collected can sometimes overcome the limitations on data quality that inherently occur in farm and ranch operations. Along with weights and scores for economically relevant traits and their indicator traits, accurate identification of animals, parents, contemporary groups, and other important details (e.g., age) are essential.

At the core of genetic improvement is the collection of high quality data. Data quality can be impacted by several clearly identified factors. While completeness, timeliness, accuracy, and conformity are all essential, consistency is often the least understood and most overlooked consideration for quality data. Collecting, recording, manipulating and processing data using consistent procedures at both the farm and association levels is the most important aspect to maintaining quality data.

In order to keep all data collected associated with an individual animal an effective beef cattle identification system is essential. Standards have been developed for identification methods that ensure unique and accurate identification of animals during the transmission and processing of data. Because the number of animals processed in genetic evaluation is routinely in the millions, it is not practical to routinely use registration number information for on-farm data collection. Standards for ear tagging and on-farm electronic identification have also been implemented. In addition, recording of animal identification is closely associated with the collection of genomic information.

Historically, many beef breed genetic evaluations were based on progeny weaned and/or registered and did not require that data be recorded from females that failed to reproduce or whose progeny were not registered.  By contrast, inventory-based Whole Herd Reporting (WHR) requires the collection of annual production and performance records on all cattle within a herd.

Data recording on individual cows is essential for the prediction of female fertility. Cow fertility is often the most impactful factor on profitability in the beef herd. Additionally, accurate and complete cow data are essential for the prediction of traits with a maternal influence (e.g. weaning weight).

The female production data to be recorded on each cow must be standardized because it is often the most complex data that a producer deals with.

Data collection of complete and accurate data on individual calf performance through slaughter or breeding is critical to making genetic improvement. Using consistent methods for taking animals' weights, measures, and scores is key to accurate data. Additionally, using a commercial or breed association supplied performance recording software helps to improve consistency of data collection and reporting.

Contemporary Groups

content by Jennifer Bormann

Basics

One of the most important aspects of an accurate genetic evaluation is proper contemporary grouping. Environment and management have a large effect on calf performance. When animals are exposed to variable environments or management practices (feed, pasture, shelter, vaccination, etc), it is impossible to determine if their differences in performance are due to genetics or environment. Selecting the highest performing animals in this situation is likely to result in selecting animals that had an advantageous environment. Because environment is not inherited, genetic progress is drastically decreased. When every calf is treated as uniformly as possible, the differences between them are more likely to be due to their genetics. In other words, the higher performing animals are more likely to be the genetically superior animals. Selecting the genetically superior animals results in greater genetic progress. The creation of contemporary groups is the mechanism that allows us to account for management and environmental differences between animals. A contemporary group is a set of same-sex calves that were born within a relatively short window of time and have been managed the same since birth. Each calf in the group has received the same opportunity to express its genetic merit for traits of interest.

If a subset of calves from a group receive different treatment, then those calves should be recoded as a different contemporary group. An example might be a small group of bulls from the larger group sent to a bull test, or perhaps being pulled out to fit for a show. Those bulls should have their data coded with a different contemporary group than the larger group from which they came. Another example might be if a group of calves is large enough that they can’t be weaned/weighed on the same day, they may be broken into separate contemporary groups and weighted on different days. Once animals are separated into a different group, they can never be recombined with the original group.

Every piece of performance data recorded should have the proper contemporary group attached to it. To optimize the amount of information that can be obtained from each performance record, it is best to keep contemporary groups as large as possible while still maintaining equal management and environment for all calves. Single animal contemporary groups add no information to the genetic evaluation. While keeping contemporary groups as large as possible is useful, every animal must receive equal management. It is better to have 2 smaller groups that are truly managed the same within group than one large group with unequal management. Improper contemporary grouping can lead to inaccurate and biased genetic evaluations.

In general, ET calves, multiple births, and freemartins are separated into their own contemporary groups. These situations result in different rearing environments for the calf that make it impossible to fairly compare them to other animals.

Components by Trait

Contemporary group definitions by trait (See BIF Guidelines)*

Calving ease and birth weight: Breeder herd code, Year, Season, Sex, Management code, ET or not

Weaning weight: Calving ease/birth weight contemporary group criteria, Management code (include pasture), Weigh date, Weaning sex

Yearling weight: Weaning weight contemporary group criteria, Management code, Weight date, Yearling sex

Ultrasound traits: Yearling weight contemporary group criteria, Management code (if different than yearling management), Scan date

Carcass traits: Yearling contemporary group criteria, Management code (if different than yearling management), On feed date, Harvest date, Days on feed, Grading date, Carcass sex, Breed of dam

Heifer pregnancy: Yearling weight contemporary group criteria, Breeding management code, Breeding season start and end dates, Exposure, Breeding pasture/sire

Mature cow weight, height, and body condition score: Breeder herd code, Year, Date measured, Cow age at measurement, Birth management code

Stayability: Breeder herd code, Birth year, Herd code in which cow produced a calf

Feed Efficiency: Yearling contemporary group criteria, Feed efficiency management code, Date on feed, Scan or harvest date, Sex

• Depending on the type of evaluation (single breed, multi-breed, animal model, sire model) breed composition of the calf or dam may be part of the contemporary group definition.

Data Collection on Calves

Survival to Weaning

Birth Weight

Content by Michael Gonda and Bradie Schmidt, SDSU

Yearling Weight

Content by Michael Gonda and Bradie Schmidt, SDSU

Data Collection on Yearling Bulls

Content by Madison Butler/Megan Rolf

Data Collection on Yearling Heifers

Pelvic Measurements

Content by Dave Patterson

Reproductive Tract Scores

Content by Dave Patterson

Exposure Data

Content by Dave Patterson?

Pregnancy Data

Content by Dave Patterson?

CE Scores

Content by Dave Patterson?

Data Collection on Mature Cows

Stayability

Content by Warren Snelling

Mature Height and Weight

content by Heather Bradford

Body Condition Scores

Content by Dave Lalman

Teat and Udder Scores

Content by David Riley

Foot and Leg Scores

content by Lane Giess

Adaptability-Related Traits

PAP Scores

Content by Mark Enns, Milt Thomas, and Scott Speidel

Hair Shedding

Content by Trent Smith

Genomic Data

Parentage Testing

content by Megan Rolf

Data Collection for Commercial Producers

Content by Jackie Atkins and Chip Kemp

Data Collection at Feedlots

Content by Larry Kuehn

Carcass Data Collection at the Packing Plant

Content by Tommy Perkins