Abstract
The second step of a procedure to partially circumvent the voluminous calculations for some BLUP (Best Linear Unbiased Prediction) computing algorithms for genetic evaluation is presented. In addition, the procedure allows timely evaluations of each contemporary group. This procedure is pertinent especially for polytocous species such as swine and poultry, for which the occurrence of full-sib families makes the inclusion of dam effects in the model necessary and tests are completed throughout the year. Formulas are developed for a model including sires, dams, individuals within full-sib families and records within individuals. This model has a fundamentally hierarchical structure but includes some cross-classification. The formulas for predictors combine information across contemporary groups within a herd and incorporate relationships between sires and(or) dams in that herd. Formulas to approximate prediction error variances also are developed.
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