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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, 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 | 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)]]. | ||
=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 [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. | |||
In order to keep all data collected associated with an individual animal, an effective [[Identification Systems | 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 Data | genomic information.]] Because the number of animals processed in [[:Category: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. | |||
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 | 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. | |||
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. | |||
[[Data Collection for Commercial Producers | Data collected by commercial cattle producers]] are, in most cases, substantially different than data collection requirements for seedstock producers. | |||
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Latest revision as of 17:48, 12 April 2021
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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.
