PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 9, 2026Journal of Animal Science0 citations

Comparison of Economic Selection Indexes for Beef x Beef and Beef x Dairy Breeding Objective

View Full Paper
LMLarissa MeierMSMatthew L Spangler

Key Points

  • The study aims to develop and compare economic selection indexes for beef sires used in dairy systems against traditional beef-on-beef systems.
  • Constructed indexes using the iGENDEC platform to simulate economic outcomes.
  • Evaluated six crossbreeding systems including four beef x dairy and two beef x beef.
  • Calculated marginal economic values and relative emphasis for key traits to assess their impact on breeding objectives.
  • Economic selection indexes for beef x dairy systems showed larger marginal economic values for feed intake and carcass traits compared to beef x beef systems.
  • As mean hot carcass weight increased, marginal economic values for marbling score increased while those for fat depth became more negative.
  • Indexes suggested the need for specific tools for beef x dairy breeding due to differences in trait emphasis and performance outcomes.

Abstract

Abstract The use of beef semen in dairy herds to produce beef x dairy (BxD) terminal offspring has grown rapidly in the United States, creating a need for selection tools to rank beef bulls for use on dairy cows. This study aimed to develop economic selection indexes for ranking beef sires used in dairy systems and to benchmark their performance against traditional beef-on-beef (BxB) indexes. Indexes were constructed using the Beef Improvement Federation implementation of the iGENDEC platform to simulate economic outcomes. Six crossbreeding systems were evaluated: four BxD (Angus x Holstein, Angus x Jersey, Limousin x Holstein, Limousin x Jersey) and two BxB (Angus x Angus-Hereford, Limousin x Angus-Hereford). Traits included in the breeding objective were hot carcass weight (HCW), ribeye area (REA), fat depth (FAT), marbling score (MS), feed intake (FI), and calving ease (CE); BxB indexes additionally included weaning weight (WW) and yearling weight (YW). Economic and phenotypic parameters were derived from national reports and peer-reviewed studies to reflect prevailing U.S. market conditions and cattle performance. Marginal economic values (MEVs) and relative emphasis (RE) were calculated for each trait to quantify their weight within the indexes and relative impact on breeding objectives. Six scenarios were investigated to quantify sensitivity to average HCW, days on feed (DOF), and carcass weight discounts. The scenarios investigated were: breeding system and breed of sire specific phenotypic means (Scenario 1), assumed mean HCW of 397 kg across all systems (Scenario 2), mean HCW of 397 kg and reduced DOF for BxD (Scenario 3), increased mean HCW to 454 kg (Scenario 4), mean HCW of 454 kg with reduced DOF for BxD (Scenario 5) and scenario 5 with no HCW heavy-weight discount (Scenario 6). Overall, breeding objectives that assumed Angus sires had larger RE for REA and smaller RE for MS compared to objectives that assumed Limousin sires. Scenarios 4 and 5 had the lowest RE for HCW. Averaged over breeding systems and sire breeds, as mean HCW increased, MEVs for MS and REA increased, FAT MEVs became more negative, and the MEV for HCW decreased given the heavy weight discount that was assumed. Removing the heavy-weight discount increased HCW MEV and RE and as a consequence the RE for other traits decreased. When DOF decreased, MEVs for FI became less negative and RE for HCW, FAT, and MS increased while the RE for FI decreased. Beef x dairy systems had larger MEVs for FI (negative), REA, and HCW and smaller MEV for MS as compared to BxB. For BxD, RE were substantially larger for FI and smaller for MS as compared to BxB. These findings underscore the need for selection indexes specifically designed for BxD systems.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Meier et al. (2026) studied this question.

synapsesocial.com/papers/69fed123b9154b0b82878687https://doi.org/10.1093/jas/skag107.299
Ask AI
Helpful
Bookmark
Share
View Full Paper