Enhanced comment feature has been enabled for all readers including those not logged in. Click on the Discussion tab (top left) to add or reply to discussions.
Data Collection: Difference between revisions
Line 4: | Line 4: | ||
=[[Beef cattle identification system]]= | =[[Beef cattle identification system]]= | ||
In order to keep all data collected associated with an individual animal an effective [[beef cattle identification system]] is essential. [[beef cattle identification system | Standards have been developed]] for identification methods that ensure unique and accurate identification of animals during the transmission and processing of data. Because | In order to keep all data collected associated with an individual animal an effective [[beef cattle identification system]] is essential. [[beef cattle identification system | 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]]= | =[[Whole Herd Reporting]]= |
Revision as of 13:55, 4 May 2018
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.
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 essential 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.