Which of the following are two methods to account for environmental differences in phenotype data?

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Multiple Choice

Which of the following are two methods to account for environmental differences in phenotype data?

Explanation:
Phenotypes reflect both genetics and the environment, so to compare animals fairly you adjust for those environmental effects. The two effective ways are adjusting records to remove environmental influences and using deviations from the contemporary group mean. Adjusting records applies correction factors so a phenotype is placed on a common environmental baseline, highlighting genetic differences rather than management or age effects. Deviations from the contemporary group mean express an individual’s performance relative to its peers raised under similar conditions, effectively canceling out shared environmental influence within that group. Together, these methods separate non-genetic variation from genetic merit, improving the accuracy of genetic evaluations. Increasing feed or restricting to young animals don’t directly account for environmental differences in the data, and ignoring environment leaves environmental noise in the results.

Phenotypes reflect both genetics and the environment, so to compare animals fairly you adjust for those environmental effects. The two effective ways are adjusting records to remove environmental influences and using deviations from the contemporary group mean. Adjusting records applies correction factors so a phenotype is placed on a common environmental baseline, highlighting genetic differences rather than management or age effects. Deviations from the contemporary group mean express an individual’s performance relative to its peers raised under similar conditions, effectively canceling out shared environmental influence within that group. Together, these methods separate non-genetic variation from genetic merit, improving the accuracy of genetic evaluations. Increasing feed or restricting to young animals don’t directly account for environmental differences in the data, and ignoring environment leaves environmental noise in the results.

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