Evaluation of feed efficiency traits in different Hereford populations and their effect on variance component estimation
Maria Isabel Pravia
A * , Elly Ana Navajas A , Ignacio Aguilar A and Olga Ravagnolo A
A Instituto Nacional de Investigación Agropecuaria (INIA), Estación Experimental Las Brujas, Ruta 48 Km. 10, Canelones, Uruguay.
Animal Production Science 62(17) 1652-1660 https://doi.org/10.1071/AN21420
Submitted: 24 August 2021 Accepted: 10 June 2022 Published: 1 August 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing
Abstract
Context: Residual feed intake is a relevant trait for beef cattle, given the positive impact on reducing feeding costs and greenhouse gas emissions. The lack of large databases is a restriction when estimating accurate genetic parameters for dry matter intake (DMI) and residual feed intake (RFI), and combining different data sets could be an alternative to increase the amount of data and achieve better estimations.
Aim: The main objective was to compare Uruguayan data (URY; 780 bulls) and Canadian data (CAN; 1597 bulls), and to assess the adequacy of pooling both data sets (ALL) for the estimation of genetic parameters for DMI and RFI.
Methods: Feed intake and growth traits phenotypes in both data sets were measured following the same protocols established by the Beef Improvement Federation. Pedigree connections among data sets existed, but were weak. Performance data were analysed for each data set, and individual partial regression coefficients for each energy sink on DMI were obtained and compared. Univariate and multivariate variance components were estimated by the restricted maximum likelihood (REML) for DMI, RFI and their energy sinks traits (average daily gain, metabolic mid weight and back fat thickness).
Key results: There were some differences in phenotypic performance among data (P < 0.01); however, no differences (P > 0.1) were observed for phenotypic values of RFI between sets. Heritability estimates for DMI were 0.42 (URY), 0.41 (CAN) and 0.45 for ALL data, whereas heritability estimates for RFI were 0.34 (URY), 0.20 (CAN) and 0.25 for ALL data. The results obtained indicate selection on reducing RFI could lead to a decrease in DMI, without compromising other performance traits, as genetic correlations between RFI, growth and liveweight were low or close to 0 (−0.12–0.07).
Conclusions: As genetic parameters were similar between national data sets (URY, CAN), pooling data (ALL) provided more accurate parameter estimations, as they presented smaller standard deviations, especially in multivariate analysis.
Implications: Parameters estimated here may be used in international or national genetic evaluation programs.
Keywords: across country evaluation, beef cattle, feed intake, genetic correlations, heritability, multiple trait model, residual feed intake, variance component estimation.
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