Herrera-Ojeda JParra-Bracamonte GMLopez-Villalobos NHerrera-Camacho JOrozco-Durán KE2024-01-162024-07-252024-01-162024-07-252021-03-17Herrera-Ojeda J, Parra-Bracamonte GM, López-Villalobos N, Herrera-Camacho J, Orozco-Durán KE. (2021). Bivariate analysis for the improvement of genetic evaluations with incomplete records in Charolais cattle. Revista MVZ Cordoba. 26. 2. (pp. 01-08).0122-0268https://mro.massey.ac.nz/handle/10179/70565Objective: Estimate (co)variance components and genetic parameters of live weight traits and examine the effect of selection culling when using bivariate analysis in registered Charolais beef cattle. Materials and methods: The effect of incomplete data over accuracies was compared, expected progeny differences (EPD) and standard errors of prediction (SEP) were obtained and evaluated by comparing univariate and bivariate models for birth (BW), weaning (WW) and yearling (YW) weights. Results: Bivariate models for WW and YW, improved accuracies of EPDs and reduced the SEPs. Joint analysis for BW and WW increased in a 38% the accuracies and reduced SEP estimators for YW (p̌0.001). Accuracies of EPD for BW obtained from univariate models were improved when BW was included in bivariate models. Conclusions: The results support the use of bivariate genetic analysis in limited or incomplete live weight indicators databases that were registered after birth, such as weaning and yearling weight.(c) 2021 The Author/sCC BY-NC-SA 4.0https://creativecommons.org/licenses/by-nc-sa/4.0/Incomplete recordslive weightsculling selection (Sources: USDA, Tesauro ICYT de Biologia Animal)Journal article10.21897/rmvz.21281909-0544journal-article01-08http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000654711100014&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=c5bb3b2499afac691c2e3c1a83ef6fefARTN e2128