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Data Collection: Difference between revisions
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===Body Condition Score=== | ===Body Condition Score=== | ||
===Teat and Udder Scores=== | ===Teat and Udder Scores=== | ||
[[Udder Scores | Udder Scores]] | |||
===Foot and Leg Scores=== | ===Foot and Leg Scores=== |
Revision as of 15:11, 3 April 2019
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
Contemporary Groups
Basics
Type of Birth
Multiple Births and Freemartins
ET Calves
Components by Trait
Data Collection on Calves
Survival to Weaning
Disposal
Disease
Weights
BW
Hoof Tapes?
Weaning Weight
YW
CE Scores
Hip Height/Frame
Discuss whether to include
Docility
Ultrasound (link to UGC website)
Data Collection on Yearling Bulls
Breeding Soundness Exam
Scrotal Circumference
Data Collection on Yearling Heifers
Pelvic Measurements
Reproductive Tract Scores
Exposure Data
Pregnancy Data
CE Scores on Calves
Data Collection on Mature Cows
Calf Record/Reason Code (for Stayability)
Exposure and Pregnancy Data
Gestation Length
Calving Interval
Mature Height and Weight
Body Condition Score
Teat and Udder Scores
Foot and Leg Scores
Intake
Genomic Data (link to Data Prep section)
Parentage
Genetic Evaluation
Data Collection for Commercial Producers
See Seedstock Data Collection (link)
Herd Measurements
Calving Distribution
Bull Measurements
Cow Measurements
MPPA
Data Collection at Feedlots
Average Daily Gain
Intake and Feed Efficiency
Health Traits
Data Collection at Packers
Carcass Traits
Cooperation Between Packer and Producer
Required Data for Genetic Evaluation
Hot Carcass Weight
Ribeye Area
Marbling Score
Fat Thickness
Other Traits (e.g. KPH)
Warner-Bratzler Shear Force (link)
Quality Grade and Yield Grade (link)
Herd Management Software (link to Data Prep section)
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 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.
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 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.
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.