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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #359638
Research Project: Improving Dairy Animals by Increasing Accuracy of Genomic Prediction, Evaluating New Traits, and Redefining Selection Goals

Location: Animal Genomics and Improvement Laboratory

Title: Ranking sires using genetic selection indices based on financial investment methods versus lifetime net merit

Author
item SCHMITT, MICHAEL - University Of Florida
item Vanraden, Paul
item DE VRIES, ALBERT - University Of Florida

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/29/2019
Publication Date: 10/1/2019
Citation: Schmitt, M.R., Van Raden, P.M., De Vries, A. 2019. Ranking sires using genetic selection indices based on financial investment methods versus lifetime net merit. Journal of Dairy Science. 102(10):9060-9075. https://doi.org/10.3168/jds.2018-16081.
DOI: https://doi.org/10.3168/jds.2018-16081

Interpretive Summary: We applied financial investment methods to genetic merit predictions of 1,500 Holstein sires to create two new economic selection indices. One new index contained the opportunity cost of delaying replacement with increasingly superior sires, while the other did not. Sire rankings by these two indices were highly correlated to sire ranking for Lifetime Net Merit, but some individual sires showed large rank changes. Rank changes were meaningful enough that the new indices warrant consideration for use in practice.

Technical Abstract: Current USDA selection indices such as Lifetime Net Merit (NM$) estimate lifetime profit differences which are accurately approximated by a linear combination of 13 traits. In these indices, every animal gets credit for 2.78 lactations of the traits expressed per lactation, such as fat and protein, independent of its productive life (PL). This formulation may over or underestimate the net revenue from traits expressed per lactation depending on PL. The objective was to develop two genetic selection indices using financial investment methods to account for differences in PL, and to compare them to the 2017 NM$ for marketed Holstein sires. Selection among animals with different PL is an example of investment in mutually exclusive projects that have unequal duration. Financial investment theory says that such projects are best compared with the annualized net present value (ANPV) method when replacement occurs with technologically equal assets. However, genetic progress implies that future available replacement animals are technologically improved assets. Asset replacement theory with improved assets results in an annualized value including genetic opportunity cost (AVOC) for each animal. We developed the ANPV and AVOC and compared these with the NM$ for 1,500 marketed Holstein sires from the December 2017 genetic evaluation. The lowest Pearson correlation coefficient was 0.980 between AVOC and NM$, while the highest was 0.999 between ANPV and NM$ among the 1,500 sires. Correlations for the top 300 sires were lower. Although we found high correlations between indices, the 95th and 5th percentile of individual rank changes between AVOC and NM$ were +131 and -163 positions, while these changes between ANPV and NM$ were +27 and -45 positions, respectively. The relative emphasis of PL in the AVOC index was half of the relative emphasis in NM$. These results show that financial investment methods applied to value differences in genetic merit of animals changes their rankings compared to the NM$ formulation. Rank changes were meaningful enough that the new indices warrant consideration for use in practice.