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Adjusting preweaning pig weights to a standard age

B Bereskin, H W Norton

    Journal of Animal Science
    |February 1, 1982
    PubMed
    Summary

    Researchers developed quadratic regression equations to adjust piglet weights for evaluating sow productivity. These factors allow for consistent weight comparisons across different ages, improving accuracy in swine breeding programs.

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    Area of Science:

    • Animal Science
    • Swine Genetics
    • Agricultural Research

    Background:

    • Accurate evaluation of sow productivity requires standardized piglet weights.
    • Preweaning growth varies significantly due to genetics, environment, and age.
    • Existing methods may not fully capture growth curve dynamics for accurate adjustments.

    Purpose of the Study:

    • To derive adjustment factors for piglet and litter weights to uniform ages.
    • To improve the accuracy of sow productivity evaluations using standardized weights.
    • To develop a robust model for predicting piglet weights based on age.

    Main Methods:

    • Quadratic regression analysis applied to preweaning weight records of Duroc and Yorkshire pigs.
    • Data included 3,587 pigs across 533 litters, with weights recorded at birth, 21, and 42 days.
    • Weights were log-transformed, and equations fitted to litter-sex subgroups, considering year, season, breed, and sex effects.

    Main Results:

    • A quadratic regression equation (Y = .2127 + .07545(age) - .000558(age)^2) accurately modeled piglet weight in natural logarithms.
    • Significant effects of season and year x season x breed interactions necessitated the use of quadratic coefficients.
    • Multiplicative factors were calculated to adjust weights to standard ages (14, 21, 28, 35, 42 days).

    Conclusions:

    • The derived quadratic equation provides reliable factors for adjusting preweaning pig weights.
    • These adjustment factors enhance the precision of sow productivity assessments in swine breeding.
    • The study highlights the importance of considering age-related growth dynamics for accurate genetic evaluations.

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