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Data Collection

From BIF Guidelines Wiki
Revision as of 15:26, 26 November 2018 by Lhyde (talk | contribs)

Data Collection for Seedstock Producers

ID systems

Herd IDs

Tattoos

Breed Association Registration Numbers

International Registration Numbers

Breed Codes

ICAR
NAAB

Whole Herd Reporting

Basics

Timeline

Disposal and Reason Codes

Data collection by sex/age (trait lists for each) Contemporary groups by trait Data on Multiple births/twins/freemartins ETs Calves(through yearling/slaughter) Survival from birth to weaning data Disposal Disease CE scores Weights-BW (hoof tapes), WW, YW Hip height/frame? Docility Ultrasound (link to UGC website) Yearling bulls (breeding) BSE-scrotal Ultrasound Heifers (1-2 yo) Repro tract scores Pelvic measurements Exposure for HP EPDs Preg data CE scores on calves Cows (breeding) Mature weight/height Gestation length Calving interval Udder scores Foot/leg BCS Intake Stay Preg data Genomic data Commercial (in addition to seedstock data) May not collect individual data SPA data-ish Percentages Overall cowherd performance Herd, sire and cow reproductive efficiency MPPA Calving distribution Feedlot Intake/feed efficiency Health ADG Packers Carcass traits (link to good explanation of YG and QG) Data that are necessary-dates, sex, at least a sire, breed comp WBSF? (link?) Have to work with producers Herd management records (in Data Prep section) Software

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.

Beef cattle identification system

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 National Cattle Evaluations programs (NCE) 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.

Whole Herd Reporting

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 collection of annual production and performance records on all cattle within a herd.


Data to be recorded on individual cows

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 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.

Animal Performance Data

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.