Difference between revisions of "Data Collection"

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=Data Collection for Seedstock Producers=
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At the core of genetic improvement is the collection of data.  While [https://en.wikipedia.org/wiki/Data_quality data quality] is critical, the 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 | economically relevant traits]] and their [[Indicator_Traits | indicators]], accurate [[Identification Systems | identification of animals]], parents, [[Contemporary Groups | contemporary groups]], and other important details (e.g., age) are essential. (Go [[Traits | here for a list of traits and their definitions)]].
At the core of genetic improvement is the collection of data.  While [https://en.wikipedia.org/wiki/Data_quality 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.  
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=Collection of data to enter genetic evaluation=
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At the core of genetic improvement is the collection of high-quality data. Data quality can be impacted by [https://www.precisely.com/blog/data-quality/data-quality-dimensions-measure 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.  Using consistent procedures for collecting, recording, manipulating and [[Data_Processing | processing data]] at both the farm and association levels is the most important aspect to maintaining quality data. 
  
At the core of genetic improvement is the collection of high quality data. Data quality can be impacted by [https://smartbridge.com/data-done-right-6-dimensions-of-data-quality-part-1/ 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.   
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In order to keep all data collected associated with an individual animal, an effective [[Identification Systems | beef cattle identification system]] is essentialStandards have been developed for identification methods that ensure unique and accurate identification of animals during the transmission and processing of data, including [[Genomic Data | genomic information.]] Because the number of animals processed in [[Genetic Evaluation | 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.   
  
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 dataBecause the number of animals processed in [[Genetic Evaluation | 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 implementedIn addition, recording of animal identification is closely associated with the collection of [[Genomic Information | genomic information.]]
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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 herdWhere possible, [[Whole_Herd_Reporting | whole herd reporting]] is recommended to capture the greatest amount of complete cowherd information.  [[Whole Herd Reporting#Performance recording requirements | 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 | weaning weight]])The [[Whole Herd Reporting#Performance recording requirements | 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.
  
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.
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Regardless of whether using an [[Whole Herd Reporting | inventory-based reporting system]] or not, accurate phenotypic data collection is vital to genetic evaluation.  Collection of complete and accurate data on [[Whole_Herd_Reporting#Performance_record_requirements | calves, bulls, heifers, mature cows]], or fed cattle (including [[Required_Carcass_Data_Collection_for_Use_in_Genetic_Evaluations| carcass data]]) is critical to making genetic improvement.  Producers may also be interested in working with their breed associations to provide data for [[Traits | novel traits]], where EPDs may be under development. When reporting these data, it is also vital to include appropriate [[Contemporary Groups | contemporary grouping]] information to ensure that the data are 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 the consistency of data collection and reporting.  Producers are encouraged to contact their breed associations to obtain recommendations on what software may be compatible with their systems.
  
 
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[[Data Collection for Commercial Producers | Data collected by commercial cattle producers]] are, in most cases, substantially different than data collection requirements for seedstock producers.
[[Whole Herd Reporting#Performance recording requirements | 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 [[Whole Herd Reporting#Performance recording requirements | 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 | performance recording software]] helps to improve consistency of data collection and reporting.
 
 
 
==[[Identification Systems]]==
 
 
 
==[[Whole Herd 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===
 
====Disposal====
 
====Disease====
 
 
 
====[[Birth Weight | Birth Weight]]====
 
Content by Michael Gonda and Bradie Schmidt, SDSU
 
 
 
=====[[Hoof Tape | Hoof Tapes]]=====
 
 
 
====[[Weaning Weight]]====
 
 
 
====[[Yearling Weight | Yearling Weight]]====
 
Content by Michael Gonda and Bradie Schmidt, SDSU
 
 
 
===[[CE Scores | CE Scores]]===
 
 
 
===[[Hip Height/Frame | Hip Height/Frame]]===
 
 
 
===Docility===
 
===Ultrasound (link to UGC website)===
 
 
 
==Data Collection on Yearling Bulls==
 
Content by Madison Butler/Megan Rolf
 
===[[Breeding Soundness Exam | Breeding Soundness Exam]]===
 
===[[Scrotal Circumference | Scrotal Circumference]]===
 
 
 
==Data Collection on Yearling Heifers==
 
===[[Pelvic Measurements | Pelvic Measurements]]===
 
 
 
Content by Dave Patterson
 
 
 
===[[Reproductive Tract Scores | Reproductive Tract Scores]]===
 
 
 
Content by Dave Patterson
 
 
 
===[[Exposure Data | Exposure Data]]===
 
 
 
Content by Dave Patterson?
 
 
 
===[[Pregnancy Data | Pregnancy Data]]===
 
 
 
Content by Dave Patterson?
 
 
 
===[[CE Scores | CE Scores]]===
 
 
 
Content by Dave Patterson?
 
 
 
==Data Collection on Mature Cows==
 
===[[Stayability | Stayability]]===
 
 
 
Content by Warren Snelling
 
 
 
===Calf Record/Reason Code (for Stayability)===
 
===[[Pregnancy Data | Pregnancy Data]]===
 
 
 
===Gestation Length===
 
===Calving Interval===
 
===[[Mature Height and Weight | Mature Height and Weight]]===
 
content by Heather Bradford
 
 
 
===[[Body Condition Scores | Body Condition Scores]]===
 
 
 
Content by Dave Lalman
 
 
 
===[[Teat and Udder Scores | Teat and Udder Scores]]===
 
 
 
Content by David Riley
 
 
 
===[[Foot and Leg Scores | Foot and Leg Scores]]===
 
content by Lane Giess
 
 
 
===Intake===
 
 
 
==Adaptability-Related Traits==
 
===[[PAP Scores | PAP Scores]]===
 
Content by Mark Enns, Milt Thomas, and Scott Speidel
 
 
 
===[[Hair Shedding | Hair Shedding]]===
 
Content by Trent Smith
 
 
 
==Genomic Data==
 
Use of genomic data requires quality [http://guidelines.thetasolutionsllc.com/index.php/Genotyping sample collection].  Once samples are acquired and processed according to breed association specifications, the data can be incorporated into reporting systems for breed associations, including reporting schemes for [http://guidelines.thetasolutionsllc.com/index.php/Monogenic_Traits monogenic traits] such as horned/polled genotype or [http://guidelines.thetasolutionsllc.com/index.php/Recessive_Genetic_Defects genetic abnormality] carrier status as well as for quantitative traits, which will be utilized within either [http://guidelines.thetasolutionsllc.com/index.php/Single-step_Genomic_BLUP single-step genomic BLUP] or [http://guidelines.thetasolutionsllc.com/index.php/Single-step_Hybrid_Marker_Effects_Models single-step hybrid marker effects models] for genetic prediction. Genotype data can also be utilized for other applications, as detailed below.
 
 
 
===[[Parentage Testing| Parentage Testing]]===
 
content by Megan Rolf
 
 
 
=Data Collection for Commercial Producers=
 
Content by Jackie Atkins and Chip Kemp
 
 
 
===See Seedstock Data Collection (link)===
 
===Herd Measurements===
 
===Calving Distribution===
 
===Bull Measurements===
 
===Cow Measurements===
 
===MPPA===
 
 
 
=Data Collection at Feedlots=
 
Content by Larry Kuehn
 
===Average Daily Gain===
 
===Intake and Feed Efficiency===
 
===Health Traits===
 
 
 
=Carcass Data Collection at the Packing Plant=
 
 
 
Content by Tommy Perkins
 
 
 
===[[Cooperation Between Packer, Feedlot and Producer | Cooperation Between Packer, Feedlot and Producer]]===
 
 
 
===[[Dressed Carcass Yield, Quality Grade and Yield Grade |  Dressed Carcass Yield, Quality Grade and Yield Grade]]===
 
 
 
===[[Recommended Carcass Data Collection Traits | Recommended Carcass Data Collection Traits]]===
 
 
 
===[[Measures of Tenderness | Measures of Tenderness]]===
 
====[[Slice Shear Force | Slice Shear Force]]====
 
====[[Warner-Bratzler Force | Warner-Bratzler Force]]====
 
 
 
===[[Required Carcass Data Collection for Use in Genetic Evaluations | Required Carcass Data Collection for Use in Genetic Evaluations]]===
 
 
 
=Herd Management Software (link to Data Prep section)=
 

Revision as of 15:47, 29 August 2020

At the core of genetic improvement is the collection of data. While data quality is critical, the 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. (Go here for a list of traits and their definitions).

Collection of data to enter genetic evaluation

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. Using consistent procedures for collecting, recording, manipulating and processing data 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 are 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 the consistency of data collection and reporting. Producers are encouraged to contact their breed associations to obtain recommendations on what software may be compatible with their systems.

Data collected by commercial cattle producers are, in most cases, substantially different than data collection requirements for seedstock producers.