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Comparison of maturity rate for bull daughters in the United States and Canada H.D. Norman 1 , J.R. Wright 1 ,* R.L. Powell 1 , P.M. VanRaden 1 , and F. Miglior 2,3 1 Animal Improvement Programs Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
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Comparison of maturity rate for bull daughters in the United States and Canada H.D. Norman1, J.R. Wright1,* R.L. Powell1, P.M. VanRaden1, and F. Miglior2,3 1Animal Improvement Programs Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350 2Agriculture and Agri-Food Canada – Dairy and Swine Research and Development Centre, Lennoxville, QC, Canada 3Canadian Dairy Network, Guelph, ON Canada Abstr. M20 INTRODUCTION • Many countries in Interbull calculate genetic evaluations for individual parities to consider differences in rate of maturity. • In Canada, genetic evaluations are calculated with a multi-trait parity model. • In the U.S., official genetic evaluations are calculated with a single-trait repeatability model. • Recent U.S. studies show that apparent differences in maturity rate of bulls’ daughters are contributing to variation in USDA PTAs across time. • Examining apparent differences in rate of maturity in two populations should provide evidence to determine whether the observed differences are genetic. DATA & METHODS (cont.) Canada data: • Estimated Breeding Values (EBV) from published November 2004 CDN evaluation using test day model converted to predicted transmitting ability (divided by 2) • Standardized first parity (CAN1) • Standardized second parity (CAN2) • Standardized third parity (CAN3) Methods Genetic evaluation subsets: Analysis was run on three groups of bulls: • 20 or more daughters in both countries (804 bulls) • 100 or more daughters in both countries (403 bulls) • 500 or more daughters in both countries (131 bulls) Within birth year correlations between parity specific evaluations (bulls with >=100 daughters above the diagonal, those with >=500 below Within birth year correlations of parity differences between countries by number of daughters Min. no. of daus. Trait differences Corr. Reg. 20 US2 - US1 and CAN2 - CAN10.63 0.63 US3 - US1andCAN3 - CAN1 0.53 0.55 US3 – US2andCAN3 – CAN2 0.14 0.08 100 US2 - US1 and CAN2 - CAN1 0.81 0.83 US3 - US1andCAN3 - CAN1 0.75 0.78 US3 – US2andCAN3 – CAN2 0.24 0.14 500 US2 - US1 and CAN2 - CAN1 0.89 0.98 US3 - US1andCAN3 - CAN1 0.84 0.91 US3 – US2andCAN3 – CAN2 0.55 0.50 RESULTS • Correlations were highest between parity 2 and 3 within (0.92 to 0.98) and across countries (0.89 To 0.92). • Correlations were lowest between parity 1 and 3 within (0.83 to 0.88) and across countries (0.79 to 0.86). • Correlation were high between evaluations for the same parity across countries (0.90 to 0.96) • Correlations between Canadian parity EBVs were higher than between US parity PTAs, due in part to the genetic correlations matrix assumed between lactations. • Correlations observed between parities were considerably higher than those assumed in the evaluation model. • Regressions (not shown) were from 0.90 to 1.00, and slightly higher for US PTAs than for Canadian EBVs. Standard errors ranged from 0.01 to 0.04. RESULTS (cont.) • Correlations between parity differences were highly related to number of daughters and records included. • Evaluations of parities with the highest genetic correlations had the lower correlations between their differences across countries OBJECTIVES • Compare apparent differences in maturity rate of bulls’ daughters across countries to determine if they are consistent. RESULTS • Average number of lactations or test days DATA & METHODS US data: • Three predicted transmitting abilities (PTA) were created using current USDA-DHIA animal model methodology • Data were Holstein cows first calving 1960-1998 • PTAs included either first parity (US1,), first and second parity (US1,2), or first, second and third parity records (US1,2,3) • Contributions of second and third parity alone (US2, US3) were derived from the other three by weighting for the numbers of daughters/records in each parity CONCLUSIONS • Correlations between genetic evaluations from the two countries were high. • Differences in apparent rate of maturity observed were highly correlated, providing convincing evidence that the differences observed are genetic.