<p>The conversion of feed into usable products, also known as feed efficiency (FE), is important given the necessity to increase quality food production. This concept is also important given the environmental sustainability and profitability of the beef production systems. The present thesis analysed different aspects involving FE and their inclusion in beef cattle breeding programs. Thus, this work aimed to increase the understanding of genetic variability of the FE traits and the inclusion of residual feed intake (RFI) into genomic assisted beef cattle breeding programs.</p> <p>The first research chapter was oriented to better understand the genetic variability of the main FE traits and their association with growth and meat quality traits in an Angus population. The analysed FE component traits were daily weight gain, metabolic midweight, average of daily, feed intake, feed conversion ratio, RFI, and residual gain (RG), evaluated during a 70-day feedlot test period. In this chapter, it was concluded that selection on RFI would have a negative impact in growth and carcass traits. Therefore, it was suggested that selection only for RFI would have negative impacts on growth and meat quality in the studied population.</p> <p>The second research chapter compared repeatability (REPM) and random regression models (RRM) on feed efficiency component traits during the feedlot test period. Unlike the REPM, the RRM can accommodate changes in parameters of those traits over duration of the test period. First-order RRM applied to body weight (BW) and average daily feed intake (ADFI), shown that genetic parameters tend to change during the feedlot period. By comparing these models, it was concluded that ignoring the change in parameters, regardless of feed costs, resulted in a loss of selection response of approximately 3%</p> <p>The third research chapter analysed REPM and RRM when using genomic information. Genomic variants associated with BW and ADFI variation were identified and a change of their effect during the feedlot test period was evaluated. For both traits, RRM presented the best fit and only one genomic region was detected with a constant effect throughout the 70-d feedlot test period. For BW and ADFI, the strongest associated variants were rs43350564 and rs109326204, located on chromosomes 20 and 5, respectively. These identified SNP may help to unravel the biology of FE and can be used for more accurate genomic prediction of breeding values.</p> <p>The final research chapter evaluated various realistic multi-trait selection strategies incorporating RFI, as well as including the use of genomic selection (GS). Here it was concluded that selecting on RFI via a genomic test yielded the largest increase in selection accuracy and overall responses of 0.48 and 64.9%, respectively. Finally, it was concluded that including feed efficiency increased the $ net return without compromising meat quality and cow condition score in the beef cattle breeding programs.</p>