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 indicators, 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, including genomic information. 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. Ear tagging and on-farm electronic identification are often implemented in place of using a full registration identifier.

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. Where possible, whole herd reporting is recommended to capture the greatest amount of complete cowherd information. Data recording on individual cows is essential for the prediction of female fertility. Cow fertility is often the most important determinant of 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.

Regardless of whether using an inventory-based reporting system or not, accurate phenotypic data collection is vital to genetic evaluation. Collection of complete and accurate data on calves, bulls, heifers, mature cows, or fed cattle (including carcass data) is critical to making genetic improvement. Producers may also be interested in working with their breed associations to provide data for novel traits, where EPDs may be under development. When reporting these data, it is also vital to include appropriate contemporary grouping information to ensure that the data is appropriately incorporated into the evaluation. 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.

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

Novel 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