Residual feed intake (RFI) is the difference between the actual and expected feed intake of an animal based on its BW and growth rate over a specified period. The biological mechanisms underlying the variation in feed efficiency in animals with similar BW and growth rate are not well understood. This study determined the relationship of feedlot feed efficiency, performance, and feeding behavior with digestion and energy partitioning of 27 steers. The steers were selected from a total of 306 animals based on their RFI following feedlot tests at the University of Alberta Kinsella Research Station. Selected steers were ranked into high RFI (RFI > 0.5 SD above the mean, n = 11), medium RFI (RFI +/- 0.5 SD above and below the mean, n = 8), and low RFI (RFI < -0.5 SD below the mean, n = 8). The respective BW +/- SD for the RFI groups were 495.6 +/- 12.7, 529.1 +/- 18.6, and 501.2 +/- 15.5 kg. Digestibility and calorimetry trials were performed on a corn-or barley-based concentrate diet in yr 1 and 2, respectively, at 2.5 x maintenance requirements. Mean DMI (g/kg of BW(0.75)) during the measurements for high-, medium-, and low-RFI groups, respectively, were 82.7 +/- 2.0, 78.8 +/- 2.6, and 81.8 +/- 2.5 and did not differ (P > 0.10). Residual feed intake was correlated with daily methane production and energy lost as methane (r = 0.44; P < 0.05). Methane production was 28 and 24% less in low-RFI animals compared with high- and medium-RFI animals, respectively. Residual feed intake tended to be associated (P < 0.10) with apparent digestibilities of DM (r = -0.33) and CP (r = -0.34). The RFI of steers was correlated with DE (r = -0.41; P < 0.05), ME (r = -0.44; P < 0.05), heat production (HP; r = 0.68; P < 0.001), and retained energy (RE; r = -0.67; P < 0.001; energy values are expressed in kcal/kg of BW(0.75)). Feedlot partial efficiency of growth was correlated (P < 0.01) with methane production (r = -0.55), DE (r = 0.46), ME (r = 0.49), HP (r = -0.50), and RE (r = 0.62). With the exception of HP (r = 0.37; P < 0.05), feed conversion ratio was unrelated to the traits considered in the study. Feeding duration was correlated (P < 0.01) with apparent digestibility of DM (r = -0.55), CP (r = -0.47), methane production (r = 0.51), DE (r = -0.52), ME (r = -0.55), and RE (r = -0.60). These results have practical implications for the selection of animals that eat less at a similar BW and growth rate and for the environmental sustainability of beef production.

The effects of increased pedigree inbreeding in dairy cattle populations have been well documented and result in a negative impact on profitability. Recent advances in genotyping technology have allowed researchers to move beyond pedigree analysis and study inbreeding at a molecular level. In this study, 5,853 animals were genotyped for 54,001 single nucleotide polymorphisms (SNP); 2,913 cows had phenotypic records including a single lactation for milk yield (from either lactation 1, 2, 3, or 4), reproductive performance, and linear type conformation. After removing SNP with poor call rates, low minor allele frequencies, and departure from Hardy-Weinberg equilibrium, 33,025 SNP remained for analyses. Three measures of genomic inbreeding were evaluated: percent homozygosity (FPH), inbreeding calculated from runs of homozygosity (FROH), and inbreeding derived from a genomic relationship matrix (FGRM). Average FPH was 60.5±1.1%, average FROH was 3.8±2.1%, and average FGRM was 20.8±2.3%, where animals with larger values for each of the genomic inbreeding indices were considered more inbred. Decreases in total milk yield to 205d postpartum of 53, 20, and 47kg per 1% increase in FPH, FROH, and FGRM, respectively, were observed. Increases in days open per 1% increase in FPH (1.76 d), FROH (1.72 d), and FGRM (1.06 d) were also noted, as well as increases in maternal calving difficulty (0.09, 0.03, and 0.04 on a 5-point scale for FPH, FROH, and FGRM, respectively). Several linear type traits, such as strength (-0.40, -0.11, and -0.19), rear legs rear view (-0.35, -0.16, and -0.14), front teat placement (0.35, 0.25, 0.18), and teat length (-0.24, -0.14, and -0.13) were also affected by increases in FPH, FROH, and FGRM, respectively. Overall, increases in each measure of genomic inbreeding in this study were associated with negative effects on production and reproductive ability in dairy cows.

Feeding behavior and temperament may be useful in genetic evaluations either as indicator traits for other economically relevant traits or because the behavior traits may have a direct economic value. We determined the variation in feeding behavior and temperament of beef cattle sired by Angus, Charolais, or Hybrid bulls and evaluated their associations with performance, efficiency, and carcass merit. The behavior traits were daily feeding duration, feeding head down (HD) time, feeding frequency (FF), and flight speed (FS, as a measure of temperament). A pedigree file of 813 animals forming 28 paternal half-sib families with about 20 progeny per sire was used. Performance, feeding behavior, and efficiency records were available on 464 animals of which 381 and 302 had records on carcass merit and flight speed, respectively. Large SE reflect the number of animals used. Direct heritability estimates were 0.28 +/- 0.12 for feeding duration, 0.33 +/- 0.12 for HD, 0.38 +/- 0.13 for FF, and 0.49 +/- 0.18 for FS. Feeding duration had a weak positive genetic (r(g)) correlation with HD (r(g) = 0.25 +/- 0.32) and FS (r(g) = 0.42 +/- 0.26) but a moderate negative genetic correlation with FF (r(g) = -0.40 +/- 0.30). Feeding duration had positive phenotypic (r(p)) and genetic correlations with DMI (r(p) = 0.27; r(g) = 0.56 +/- 0.20) and residual feed intake (RFI; r(p) = 0.49; r(g) = 0.57 +/- 0.28) but was unrelated phenotypically with feed conversion ratio [FCR; which is the reciprocal of the efficiency of growth (G:F)]. Feeding duration was negatively correlated with FCR (r(g) = -0.25 +/- 0.29). Feeding frequency had a moderate to high negative genetic correlation with DMI (r(g) = -0.74 +/- 0.15), FCR (r(g) = -0.52 +/- 0.21), and RFI (r(g) = -0.77 +/- 0.21). Flight speed was negatively correlated phenotypically with DMI (r(p) = -0.35) but was unrelated phenotypically with FCR or RFI. On the other hand, FS had a weak negative genetic correlation with DMI (r(g) = -0.11 +/- 0.26), a moderate genetic correlation with FCR (r(g) = 0.40 +/- 0.26), and a negative genetic correlation with RFI (r(g) = -0.59 +/- 0.45). The results indicate that behavior traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency. Feeding behavior and temperament may need to be included in the definition of beef cattle breeding goals, and approaches such as the culling of unmanageable cattle and the introduction of correct handling facilities or early life provision of appropriate experiences to improve handling will be useful.

Linkage of rumen microbial structure to host phenotypical traits may enhance the understanding of host-microbial interactions in livestock species. This study used culture-independent PCR-denaturing gradient gel electrophoresis (PCR-DGGE) to investigate the microbial profiles in the rumen of cattle differing in feed efficiency. The analysis of detectable bacterial PCR-DGGE profiles showed that the profiles generated from efficient steers clustered together and were clearly separated from those obtained from inefficient steers, indicating that specific bacterial groups may only inhabit in efficient steers. In addition, the bacterial profiles were more likely clustered within a certain breed, suggesting that host genetics may play an important role in rumen microbial structure. The correlations between the concentrations of volatile fatty acids and feed efficiency traits were also observed. Significantly higher concentrations of butyrate (P < 0.001) and valerate (P = 0.006) were detected in the efficient steers. Our results revealed potential associations between the detectable rumen microbiota and its fermentation parameters with the feed efficiency of cattle.

Feed intake and efficiency of growth are economically important traits of beef cattle. This study determined the relationships of daily DMI, feed:gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F) and therefore increases as the efficiency of gain decreases and vice versa, residual feed intake (RFI), and partial efficiency of growth (efficiency of ADG, PEG) with growth and carcass merit of beef cattle. Residual feed intake was calculated from phenotypic regression (RFIp) or genetic regression (RFIg) of ADG and metabolic BW on DMI. An F1 half-sib pedigree file containing 28 sires, 321 dams, and 464 progeny produced from crosses between Alberta Hybrid cows and Angus, Charolais, or Alberta Hybrid bulls was used. Families averaged 20 progeny per sire (range = 3 to 56). Performance, ultrasound, and DMI data was available on all progeny, of which 381 had carcass data. Phenotypic and genetic parameters were obtained using SAS and ASREML software, respectively. Differences in RFIp and RFIg, respectively, between the most and least efficient steers (i.e., steers with the lowest PEG) were 5.59 and 6.84 kg of DM/d. Heritabilities for DMI, F:G, PEG, RFIp, and RFIg were 0.54 +/- 0.15, 0.41 +/- 0.15, 0.56 +/- 0.16, 0.21 +/- 0.12, and 0.42 +/- 0.15, respectively. The genetic (r = 0.92) and phenotypic (r = 0.97) correlations between RFIp and RFIg indicated that the 2 indices are very similar. Both indices of RFI were favorably correlated phenotypically (P < 0.001) and genetically with DMI, F:G, and PEG. Residual feed intake was tendentiously genetically correlated with ADG (r = 0.46 +/- 0.45) and metabolic BW (r = 0.27 +/- 0.33), albeit with high SE. Genetically, RFIg was independent of ADG and BW but showed a phenotypic correlation with ADG (r = -0.21; P < 0.05). Daily DMI was correlated genetically (r = 0.28) and phenotypically (r = 0.30) with F:G. Both DMI and F:G were strongly correlated with ADG (r > 0.50), but only DMI had strong genetic (r = 0.87 +/- 0.10) and phenotypic (r = 0.65) correlations with metabolic BW. Generally, the phenotypic and genetic correlations of RFI with carcass merit were not different from zero, except genetic correlations of RFI with ultrasound and carcass LM area and carcass lean yield and phenotypic correlations of RFI with backfat thickness (P < 0.01). Daily DMI had moderate to high phenotypic (P < 0.01) and genetic correlations with all the ultrasound and carcass traits. Depending on how RFI technology is applied, adjustment for body composition in addition to growth may be required to minimize the potential for correlated responses to selection in cattle.