Genomic evaluation of feed efficiency in US Holstein heifers

There is growing interest in improving feed efficiency traits in dairy cattle. The objectives of this study were to estimate the genetic parameters of residual feed intake (RFI) and its component traits [dry matter intake (DMI), metabolic body weight (MBW), and average daily gain (ADG)] in Holstein heifers, and to develop a system for genomic evaluation for RFI in Holstein dairy calves. The RFI data were collected from 6,563 growing Holstein heifers (initial body weight = 261 ± 52 kg; initial age = 266 ± 42 d) for 70 d, across 182 trials conducted between 2014 and 2022 at the STgenetics Ohio Heifer Center (South Charleston, OH) as part of the EcoFeed program, which aims to improve feed efficiency by genetic selection. The RFI was estimated as the difference between a heifer's actual feed intake and expected feed intake, which was determined by regression of DMI against midpoint MBW, age, and ADG across each trial. A total of 61,283 SNPs were used in genomic analyses. Animals with phenotypes and genotypes were used as training population, and 4 groups of prediction population, each with 2,000 animals, were selected from a pool of Holstein animals with genotypes, based on their relationship with the training population. All traits were analyzed using univariate animal model in DMU version 6 software. Pedigree information and genomic information were used to specify genetic relationships to estimate the variance components and genomic estimated breeding values (GEBV), respectively. Breeding values of the prediction population were estimated by using the 2-step approach: deriving the prediction equation of GEBV from the training population for estimation of GEBV of prediction population with only genotypes. Reliability of breeding values was obtained by approximation based on partitioning a function of the accuracy of training population GEBV and magnitudes of genomic relationships between individuals in the training and prediction population. Heifers had DMI (mean ± SD) of 8.11 ± 1.59 kg over the trial period, with growth rate of 1.08 ± 0.25 kg/d. The heritability estimates (mean ± SE) of RFI, MBW, DMI, and growth rate were 0.24 ± 0.02, 0.23 ± 0.02, 0.27 ± 0.02, and 0.19 ± 0.02, respectively. The range of genomic predicted transmitted abilities (gPTA) of the training population (-0.94 to 0.75) was higher compared with the range of gPTA (-0.82 to 0.73) of different groups of prediction population. Average reliability of breeding values from the training population was 58%, and that of prediction population was 39%. The genomic prediction of RFI provides new tools to select for feed efficiency of heifers. Future research should be directed to find the relationship between RFI of heifers and cows, to select individuals based on their lifetime production efficiencies.

Effects of Feeding and Drinking Behavior on Performance and Carcass Traits in Beef Cattle

Feed and water efficiency are important traits to improve beef cattle production’s economic and environmental sustainability. This study evaluated residual feed intake (RFI) and residual water intake (RWI) and their relationship with performance, ingestive behavior, and carcass traits in Caracu beef cattle. The data were analyzed using a generalized linear model with least squares means. The ingestive behavior, performance, and carcass traits were influenced by sex (p < 0.05). Males showed higher dry matter intake (DMI), average daily gain (ADG), mid-test metabolic weight (BW0.75), rib eye area, and rump fat thickness than females, besides spending more time drinking and eating. Low RFI animals exhibited higher DMI than high RFI animals. Low RWI animals ingested 3.89 L/d of water further than high RWI animals. The interaction between sex and RWI influenced the DMI, BW0.75, and backfat thickness. The ingestive behavior of low and high RFI animals was similar, although high RWI animals visited a smaller number of drinkers than low RWI animals. Water intake positively affects productive efficiency, and the combined use of RWI and RFI may help improve the selection of more efficient animals contributing to reducing the costs of beef cattle production and improving environmental sustainability.

Characterization of grazing behaviour microstructure using point-of-view cameras

Grazing patterns, intake structure, and diet selection are dynamic responses to animals' feeding environment. This study uses video sequences from animal-borne cameras to capture time- and scale-dependent grazing behaviour variables related to sward explanatory conditions. We observed grazing 'through' the sheep's eyes using point-of-view (POV) cameras coupled with event logging software. Time-specific sward features were measured by sampling 'really' grazed patches identified by applying a global navigation satellite system (GNSS) precision-grazing approach. Sward variables on a Mediterranean native sward were measured for two years during the active spring plant-growth cycle. Overall, the results demonstrate that POV cameras were able to capture grazing behaviour fine-tuning to changes in sward characteristics. Sheep compensate for the decrease in sward quantity and nutritive value by increasing the size and duration at each behavioural scale (i.e., meal, bout, and station) while increasing the bout rate and decreasing the station rate. Diet composition also changed as sward matured. The proportion of forbs in the diet remained high in early and late spring, and forbs and legumes were preferred to grasses in early spring. Grazing selectivity was more pronounced in late spring, with sheep favouring the middle stratum of the sward's vertical structure, preferring green vegetative material, while enlarging the feeding niches' span and spending more time at each niche, consequently reducing the station rate. Although data collected by individual animal-borne POV cameras were representative of the flock behaviour, they may underestimate the total grazing time outside major meals. The results indicate that the use of animal-borne video cameras is suitable for assessing variations in sheep grazing behaviour patterns in complex swards.

Effects of nutritional management regimen and residual feed intake (RFI) classification on RFI reranking and feeding behaviour for finishing beef steers

Over 2 years, 207 steers were fed an alfalfa/corn silage diet to determine growing phase (GP) residual feed intake (RFI) classification (low, medium, and high) for individual cattle. Steers were then allocated to two finishing management regimens (MR): MR 1 cattle gradually adjusted to an 84.7% concentrate (dry matter (DM) basis) diet; MR 2 included backgrounding on pasture before finishing using the same diet as MR 1 cattle. Treatment differences in growth performance were examined using GP and finishing phase (FP) RFI classifications. Based on GP RFI classification, FP average daily gain was greater in MR 2 cattle (P = 0.01) with no RFI classification differences for most FP performance traits. However, low-RFI steers had lower FP dry matter intake (DMI) and greater G:F (P ≤ 0.05) than high-RFI steers based on FP RFI classification. Low-RFI steers had fewer visits to the feeder with a lower eating rate than high-RFI steers in both production phases (P ≤ 0.05). Extensive RFI reranking occurred between production phases with 64.3% of steers changing RFI classification. Given extensive reranking in the present study, RFI classification was poorly repeatable between growing and finishing production phases when diverse diets are fed and does not accurately predict feed efficiency.

Genetic variability in the feeding behavior of crossbred growing cattle and associations with performance and feed efficiency

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e., lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait.

Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

The improvement of efficiency traits, such as protein efficiency (PE), digestible energy efficiency (EnE) and lipid gain (LipG), are relevant given their associations with environmental pollution, cost of production, and the quality of meat. However, these traits are difficult to measure and usually require slaughtering of pigs. Efficiency traits are complex, and several factors, such as genetic predisposition, feed composition, but also individual feeding behaviour may contribute to efficiency. The objective of this study was therefore to evaluate the potential of using feeding behaviour traits to predict efficiency traits under dietary protein restriction. A total of 587 Swiss Large White pigs, consisting of 312 females and 275 castrated males, had ad libitum access to feed and water, and were fed a protein-reduced diet (80% of recommended digestible protein and essential amino acids) from 22.5 ± 1.6 to 106.6 ± 4.6 kg BW. Individual feed intake was monitored and carcass composition (lean and fat mass) at slaughter was determined by dual-energy X-ray absorptiometry. The PE and EnE were calculated as the ratio of protein or energy in the carcass (estimated by dual-energy X-ray absorptiometry) to the total protein or energy consumed. Feeding behaviour traits monitored were daily feed intake, feed intake per meal, number of daily meals, duration per meal, feeding rate, and feeder occupation. A partial least square (PLS) regression was used to predict PE, EnE and LipG from feeding behaviour traits, while including farrowing series (for PE only), age at slaughter and BW at slaughter. Accuracy of PLS regression was assessed based on RMSE and R² for calibration and validation sets, and on concordance correlation coefficient, which were estimated over 100 replicates of calibration and validation sets. Models with a number of latent variables of 5, 2 and 3 were identified as optimal for PE, EnE, and LipG, which explained 34.64%, 55.42% and 82.68% of the total variation in PE, EnE, and LipG, respectively. Significant concordance correlation coefficient was found between predicted and observed values for PE (0.50), EnE (0.70), and LipG (0.90). In conclusion, individual feeding behaviour traits can better predict EnE and LipG than for PE under dietary protein restriction when fed ad libitum.

Genetic association among feeding behavior, feed efficiency, and growth traits in growing indicine cattle

This study aimed to estimate genetic parameters, including genomic data, for feeding behavior, feed efficiency, and growth traits in Nellore cattle. The following feeding behavior traits were studied (861 animals with records): time spent at the feed bunk (TF), duration of one feeding event (FD), frequency of visits to the bunk (FF), feeding rate (FR), and dry matter intake (DMI) per visit (DMIv). The feed efficiency traits (1,543 animals with records) included residual feed intake (RFI), residual weight gain (RWG), and feed conversion (FC). The growth traits studied were average daily gain (ADG, n = 1,543 animals) and selection (postweaning) weight (WSel, n = 9,549 animals). The (co)variance components were estimated by the maximum restricted likelihood method, fitting animal models that did (single-step genomic best linear unbiased prediction) or did not include (best linear unbiased prediction) genomic information in two-trait analyses. The direct responses to selection were calculated for the feed efficiency traits, ADG, and WSel, as well as the correlated responses in feed efficiency and growth by direct selection for shorter TF. The estimated heritabilities were 0.51 ± 0.06, 0.35 ± 0.06, 0.27 ± 0.07, 0.34 ± 0.06, and 0.33 ± 0.06 for TF, FD, FF, FR, and DMIv, respectively. In general, TF and FD showed positive genetic correlations with all feed efficiency traits (RFI, RWG, and FC), ADG, DMI, and WSel. Additionally, TF showed high and positive genetic and phenotypic correlations with RFI (0.71 ± 0.10 and 0.46 ± 0.02, respectively) and DMI (0.56 ± 0.09 and 0.48 ± 0.03), and medium to weak genetic correlations with growth (0.32 ± 0.11 with ADG and 0.14 ± 0.09 with WSel). The results suggest that TF is a strong indicator trait of feed efficiency, which exhibits high heritability and a weak positive genetic correlation with growth. In a context of a selection index, the inclusion of TF to select animals for shorter TF may accelerate the genetic gain in feed efficiency by reducing RFI but with zero or slightly negative genetic gain in growth traits.

Phenotypic and genetic correlations between feeding behaviours and feed efficiency in crossbred beef replacement females

The objectives of this study were to identify the phenotypic and genetic relationships and heritability (h2) of feeding behaviours (FB) in replacement beef females. Between 2005 and 2017, heifers (N = 1394) were tested for feed intake using an electronic feed bunk system. The various FB were feeding duration (DUR; min d−1), head down time (HD; min d−1), feeding frequency (FREQ; events d−1), time-to-bunk (TTB; min). Dry matter intake (DMI; kg d−1), and residual feed intake adjusted for off-test ultrasound back fat thickness (RFIFAT) were also reported. The h2 estimates for DUR, HD, FREQ, TTB, DMI, and RFIFAT were 0.25 ± 0.05, 0.26 ± 0.06, 0.27 ± 0.05, 0.29 ± 0.06, 0.26 ± 0.05, and 0.40 ± 0.07, respectively. These are the first h2 to be presented for these FB among developing replacement heifers on a high-forage diet.

Large variability in feeding behavior among crossbred growing cattle

The purpose of this study was to define an extensive suite of feeding behavior traits in growing crossbred cattle and to investigate their phenotypic inter-relationships as well as relationships with other performance and efficiency traits. Time-series feeding behavior data, as well as feed intake and liveweight records, were available for 624 growing crossbred cattle, of which 445 were steers and 179 were heifers. Feeding behavior repeatability estimates were calculated using linear mixed models. Additionally, partial Spearman correlations were estimated among 14 feeding behavior traits, as well as between feeding behavior with both performance and feed efficiency traits, using residuals retained from linear mixed models. The marginal contribution of several feeding behavior traits to the variability in metabolizable energy intake (MEI) was also determined. Repeatability estimates of 0.57, 0.36, and 0.48 were calculated for the number of feed events per day, the total time spent feeding per day, and the feeding rate, respectively. Cattle that ate more frequently each day, ate at a faster rate and consumed less energy in each visit to the feed bunk. More efficient cattle fed less often per day and fed for a shorter duration per day; they also had a slower feeding rate and fed for longer in each visit to the feed bunk. Moreover, heavier cattle fed for a longer duration per day had a faster feeding rate, but fed less often per day; heavier animals also fed first in the pen after the fresh feed was offered. The number of feed events per day and feeding time per day together explained an additional 13.4 percentage points of the variability in MEI above that already explained by all of growth rate, liveweight, and backfat depth. The results from the present study suggest that several repeatable time-series-related feeding behavior traits, that are less resource intensive to measure, may have a role as useful predictor traits of important but relatively difficult to record traits, such as feed intake and efficiency.

Phenotypic and genetic correlations of beef replacement heifer feeding behaviour, feed intake and feed efficiency with cow performance and lifetime productivity

Objectives were to quantify the phenotypic (r_p ) and genetic (r_g ) correlations between early-life feeding behaviours, dry matter intake, and feed efficiency and measures of cow performance and lifetime productivity traits. Traits were measured on 1,145 crossbred replacement beef heifers and then on cows over parities one to four. Feeding event duration (FD) was phenotypically correlated with cow prebreeding body weight (PBWT; r_p 0.29-0.45), cow prebreeding back fat thickness (PBBF; r_p 0.35-0.49), progeny weaning weight (WW; r_p 0.09-0.31) and progeny birthweight (BW; r_p -0.06 to 0.17). Feeding event frequency (FF) was phenotypically correlated with PBBF (r_p 0.16-0.30). Dry matter intake (DMI) was phenotypically correlated with PBWT (r_p 0.16-0.20) and PBBF (r_p -0.22 to -0.05). Feeding event duration was genetically correlated with PBWT (r_g 0.38-0.41). Feeding event frequency was genetically correlated with PBWT (r_g -0.43 to -0.39). Dry matter intake was genetically correlated with PBWT (r_g -0.27 to 0.14). Days in herd (DIH) was phenotypically correlated with FD and DMI (r_p  = 0.12, 0.20, respectively). Lifetime productivity was phenotypically correlated with FD and FF (r_g  = 0.25, 0.22, respectively). Calving interval was phenotypically correlated with FD and FF (r_p  = -0.12, -0.14, respectively) and genetically correlated with FF (r_g  = -0.41). Due to moderate positive correlations with cow weight, caution would be required in selection to prevent an increase in mature cow size. Use of FF, FD, DMI and a measure of feed efficiency such as residual feed intake adjusted for back fat (RFI_FAT ) in a balanced selection index is recommended.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Feed efficiency and carcass metrics in growing cattle1

Some definitions of feed efficiency such as residual energy intake (REI) and residual gain (RG) may not truly reflect production efficiency. The energy sinks used in the derivation of the traits include metabolic live-weight; producers finishing cattle for slaughter are, however, paid on the basis of carcass weight, as opposed to live-weight. The objective of the present study was to explore alternative definitions of REI and RG which are more reflective of production efficiency, and quantify their relationship with performance, ultrasound, and carcass traits across multiple breeds and sexes of cattle. Feed intake and live-weight records were available on 5,172 growing animals, 2,187 of which also had information relating to carcass traits; all animals were fed a concentrate-based diet representative of a feedlot diet. Animal linear mixed models were used to estimate (co)variance components. Heritability estimates for all derived REI traits varied from 0.36 (REICWF; REI using carcass weight and carcass fat as energy sinks) to 0.50 (traditional REI derived with the energy sinks of both live-weight and ADG). The heritability for the RG traits varied from 0.24 to 0.34. Phenotypic correlations among all definitions of the REI traits ranged from 0.90 (REI with REICWF) to 0.99 (traditional REI with REI using metabolic preslaughter live-weight and ADG). All were different (P < 0.001) from one suggesting reranking of animals when using different definitions of REI to identify efficient cattle. The derived RG traits were either weakly or not correlated (P > 0.05) with the ultrasound and carcass traits. Genetic correlations between the REI traits with carcass weight, dressing difference (i.e., live-weight immediately preslaughter minus carcass weight) and dressing percentage (i.e., carcass weight divided by live-weight immediately preslaughter) implies that selection on any of the REI traits will increase carcass weight, lower the dressing difference and increase dressing percentage. Selection on REICW (REI using carcass weight as an energy sink), as opposed to traditional REI, should increase the carcass weight 2.2 times slower but reduce the dressing difference 4.3 times faster. While traditionally defined REI is informative from a research perspective, the ability to convert energy into live-weight gain does not necessarily equate to carcass gain, and as such, traits such as REICW and REICWF provide a better description of production efficiency for feedlot cattle.

Genetic parameters for feed efficiency in Romane rams and responses to single-generation selection

Feeding costs represent one of the highest expenditures in animal production systems. Breeding efficient animals that express their growth potential while eating less is therefore a major objective for breeders. We estimated the genetic parameters for feed intake, feed efficiency traits (residual feed intake (RFI) and feed conversion ratio (FCR)), growth and body composition traits in the Romane meat sheep breed. In these traits, selection responses to single-generation divergent selection on RFI were evaluated. From 2009 to 2016, a total of 951 male lambs were tested for 8 weeks starting from 3 months of age. They were weighed at the beginning and at the end of the testing period. Backfat thickness and muscle depth were recorded at the end of the testing period through ultrasound measurements. Feed intake was continuously recorded over the testing period using the automatic concentrate feeders. The heritability of RFI was estimated at 0.45 ± 0.08, which was higher than the heritability of FCR (0.30 ± 0.08). No significant genetic correlations were observed between RFI and growth traits. A favourable low negative genetic correlation was estimated between RFI and muscle depth (-0.30 ± 0.15), though additional data are needed to confirm these results. The selection of low RFI sires based on their breeding values led to the production of lambs eating significantly less concentrate (3% decrease in the average daily feed intake), but with the same growth as lambs from sires selected based on high RFI breeding values. We concluded that in meat sheep, RFI is a heritable trait that is genetically independent of post-weaning growth and body composition traits. A one-generation divergent selection based on RFI breeding values highlighted that substantial gains in feeding costs can be expected in selection schemes for meat sheep breeds.

Detailed genetic analysis of feeding behaviour in Romane lambs and links with residual feed intake

Breeding strategies based on feed efficiency are now implemented in most animal species using residual feed intake (RFI) criteria. Although relevant, the correlated responses of feeding behaviour traits resulting from such selection on RFI are poorly documented. We report the estimated feeding behaviour at three time levels (visit, meal and day) and genetic parameters between the feeding behaviour traits and their links with RFI and its components. Feed intake, feeding duration at three time levels (per visit, meal and day), feeding rate, number of visits and time-between-visits were estimated for 951 Romane lambs fed via automatic concentrate feeders. Heritability estimates of feeding behaviour traits ranged from 0.19 to 0.54 with higher estimates for the day level than the visit level. Daily feed intake was not genetically linked to feed intake at the visit level, whereas feeding duration between visit and day levels was moderately correlated (R_g  = +0.41 ± 0.12). RFI was not significantly correlated with feeding rate, but was positively linked to feed intake and feeding duration at the day level (+0.73 ± 0.09 and +0.41 ± 0.13, respectively) and negatively at the visit level (-0.33 ± 0.14 and -0.22 ± 0.17, respectively). Selecting animals with lower RFI values might modify their feeding behaviour by increasing feed intake and feeding duration at the visit level but decrease the number of visits per day (+0.51 ± 0.14).

Comparison of feeding behavior between black and red Angus feeder heifers

The objective of this study was to compare feeding behavior between red and black Angus heifers during a 161-d finishing period as a potential explanation for performance differences. Sixty-eight single-sourced purebred red (n = 35) and black (n = 33) Angus heifers, leptin genotype TT, and average starting weight 360 kg (±19 kg) were used. Heifers were randomly and equally allocated into one of two feedlot pens, equipped with five feed bunks that recorded feeding behavior. Individual time spent at the feed bunk, interval between feeding events, feed intake, and meal frequency were recorded daily, and eating rate was calculated. Heifers were fed a barley-based diet (>75% concentrate). After 161 d, at the end of the feeding period, feedlot performance was calculated as average daily gain (ADG) and gain to feed conversion rate. Additionally, carcass data were obtained from the abattoir. Overall, black Angus heifers ate more, spent more time at the feed bunk, and had more meals compared with red Angus (P < 0.001). Red Angus heifers had better gain to feed ratios (P < 0.02) and significantly more red heifers were assigned to Canadian yield category 1 (≥59% lean meat) compared with black heifers (P = 0.02), whereas black heifers had higher back fat thickness throughout the study (P ≤ 0.04). All other performance parameters (ADG and carcass weight) were not different.

Impact of selection for residual feed intake on production traits and behavior of mule ducks

A divergent selection experiment of Muscovy sires based on the residual feed intake (RFI) of their male mule progeny was initiated in 2009. Using electronic feeders, the aim of this study was to establish whether 3 generations of selection for RFI had an impact on feeding behavior traits and general behavior, and to examine its effect on liver and meat quality. Eighty mule ducks, issued from 8 Muscovy drakes per line with extreme RFI, were tested in a pen equipped with 4 electronic feeders. Feeding behaviors were recorded from 3 to 7 wk after hatching under ad libitum feeding conditions. Then animals were prepared for overfeeding with a 3-week period of restricted feeding, and overfed during 12 d before slaughter. The RFI was significantly lower in the low RFI line than in the high RFI line (−5.4 g/d, P = 0.0005) and daily feed intake was reduced both over the entire test period (−5 g/d, P = 0.049) and on a weekly basis (P = 0.006). Weekly and total feed conversion ratios were also significantly lower (−0.08, P = 0.03 and −0.06, P = 0.01, respectively). Low RFI ducks had more frequent meals, spent as much time eating as high RFI ducks, and their feeding rate was lower when analyzed at the wk level only. Additionally no significant correlation between feed efficiency and feeding behavior traits was evidenced, indicating only limited relationships between RFI and feeding patterns. Some differences in behavioral responses to stressors (open field test combined with a test measuring the response to human presence) suggested that a lower RFI is associated with less fearfulness. Selection for RFI had no effect on liver weight and quality and a slightly deleterious impact on meat quality (decreased drip loss and L*). Finally, low RFI animals had higher body weights after restricted feeding from wk 10 to wk 12 and after overfeeding than high RFI ducks. This suggests that selection for reduced RFI until 7 wk of age increases the feed efficiency up to slaughter.

Genetic parameters for residual feed intake in a random population of Pekin duck

OBJECTIVE

The feed intake (FI) and feed efficiency are economically important traits in ducks. To obtain insight into this economically important trait, we designed an experiment based on the residual feed intake (RFI) and feed conversion ratio (FCR) of a random population Pekin duck.

METHODS

Two thousand and twenty pedigreed random population Pekin ducks were established from 90 males mated to 450 females in two hatches. Traits analyzed in the study were body weight at the 42th day (BW42), 15 to 42 days average daily gain (ADG), 15 to 42 days FI, 15 to 42 days FCR, and 15 to 42 days RFI to assess their genetic inter-relationships. The genetic parameters for feed efficiency traits were estimated using restricted maximum likelihood (REML) methodology applied to a sire-dam model for all traits using the ASREML software.

RESULTS

Estimates heritability of BW42, ADG, FI, FCR, and RFI were 0.39, 0.38, 0.33, 0.38, and 0.41, respectively. The genetic correlation was high between RFI and FI (0.77) and moderate between RFI and FCR (0.54). The genetic correlation was high and moderate between FCR and ADG (-0.80), and between FCR and BW42 (-0.64), and between FCR and FI (0.49), respectively.

CONCLUSION

Thus, selection on RFI was expected to improve feed efficiency, and reduce FI. Selection on RFI thus improves the feed efficiency of animals without impairing their FI and increase growth rate.

Alternative strategies for genetic analyses of milk flow in dairy cattle

Measurements for average milk flow (AMF) in kilograms of milk per minute of milking time from 629,161 Holstein cows from calving years 1990 to 2008 were used to estimate genetic covariance components using a variety of statistical models. For bivariate linear-threshold model applications, Gaussian-distributed AMF (linear sire model) was categorized into 2 distinct classes (threshold sire model) by setting arbitrary thresholds for extremely slow or extremely fast milking cows. In different bivariate runs with the 2 traits, Gaussian AMF and binary AMF, within a Bayesian framework, thresholds for the binary trait were 1.2, 1.6, 2.6, and 2.8 kg/min. Posterior heritabilities for AMF from the linear and the threshold models in all runs were in a narrow range and close to 0.26, and the posterior genetic correlation between AMF, defined as either a Gaussian or binary trait, was 0.99. A data subset was used to infer genetic and phenotypic relationships between AMF with test-day traits milk yield, fat percentage, protein percentage, somatic cell score (SCS), fat-to-protein ratio, and energy-corrected milk using recursive linear sire models, standard multiple trait linear sire models, and multiple trait linear sire models accounting for the effect of a trait 1 on a trait 2, and of trait 2 on trait 3, via linear regressions. The time-lagged 3-trait system focused on the first test-day trait after calving (trait 1), on AMF (trait 2), and on the test-day trait (trait 3) after the AMF measurement. Posterior means for heritabilities for AMF from linear and recursive linear models used for the reduced data set ranged between 0.29 and 0.38, and were slightly higher than heritabilities from the threshold models applied to the full data set. Genetic correlations from the recursive linear model and the linear model were similar for identical trait combinations including AMF and test-day traits 1 and 3. The largest difference was found for the genetic correlation between AMF and fat percentage from the first test day (i.e., -0.31 from the recursive linear model vs. -0.26 from the linear model). Genetic correlations from the linear model, including an additional regression coefficient, partly differed, especially when comparing correlations between AMF and SCS and between AMF and fat-to-protein ratio recorded after the AMF measurement data. Structural equation coefficients from the recursive linear model and corresponding regression coefficients from the linear model with additional regression, both depicting associations on the phenotypic scale, were quite similar. From a physiological perspective, all models confirmed the antagonistic relationship between SCS with AMF on genetic and phenotypic scales. A pronounced recursive relationship was also noted between productivity (milk yield and energy-corrected milk) and AMF, suggesting further research using physiological parameters as indicators for cow stress response (e.g., level of hormones) should be conducted.

Relationships of feeding behaviors with efficiency in RFI-divergent Japanese Black cattle

New approaches to limit expenses associated with input, without compromising profit, are needed in the beef industry. Residual feed intake (RFI) is an efficiency trait that measures variation in feed intake beyond maintenance, growth, and body composition. The addition of feeding behavior analysis to standard RFI tests may provide an approach to more readily identify feed-efficient cattle. The current study analyzes 7 feeding behaviors (BVFREQ: bunk visit frequency, BVDUR: bunk visit duration, FBFREQ: feed bout frequency, FBDUR: feed bout duration, MFREQ: meal frequency, MDUR: meal duration, and AMINT: average meal intake) and their relationships with RFI, ADG, and DMI in Japanese Black (Wagyu) cattle. Three cohorts of yearling Wagyu animals were studied using a standard 70-d RFI test, and data from divergent ( ± 0.5 SD from population RFI mean) subsets of animals were analyzed for feeding behaviors [n = 58, bulls on high-concentrate diet (C1); n = 36, bulls on a lower-concentrate diet (C2); n = 34, heifers on a lower-concentrate diet (C3)]. The following behaviors were correlated with ADG: BVFREQ (r = 0.32, P = 0.01; C1 bulls), BVDUR (r = 0.42, P = 0.01, C2 bulls), FBFREQ (r = 0.37, P < 0.01; C1 bulls), FBDUR (r = 0.46, P < 0.01, C1 bulls), and MFREQ (r = 0.42, P < 0.01, C2 bulls). Behaviors were trending or significantly correlated with DMI for all cases except for MFREQ for C3 and AMINT for C2. Residual feed intake was positively correlated with MDUR across all cohorts (r = 0.31, P = 0.02; r = 0.38, P = 0.02; r = 0.54, P ≥ 0.01, respectively). For C2 bulls and C3 heifers, RFI was positively correlated with behavior frequency categories (BVFREQ; r = 0.44, P = 0.01; r = 0.60, P ≤ 0.01, respectively, and FBFREQ r = 0.46, P ≤ 0.01; r = 0.60, P ≤ 0.01, respectively). Bunk visit frequency and FBFREQ were highly correlated with RFI status (high or low) in C2 bulls and C3 heifers. Behavior duration categories (BVDUR, FBDUR, and MDUR) were most correlated with efficiency status in C1 bulls. However, behavior frequency categories (BVFREQ and FBFREQ), as well as MDUR, were most correlated with efficiency status in C2 bulls and C3 heifers. Inclusion of meal duration measurements when evaluating RFI provides an additional tool in understanding the drivers of variation in this important trait in Wagyu cattle. The present study provides new insights into feed intake patterns of a beef breed for which there are few reports of feeding behavior.

Estimation of genetic and phenotypic parameters for ultrasound and carcass merit traits in crossbred beef cattle

Miar, Y., Plastow, G. S., Bruce, H. L., Moore, S. S., Durunna, O. N., Nkrumah, J. D. and Wang, Z. 2014. Estimation of genetic and phenotypic parameters for ultrasound and carcass merit traits in crossbred beef cattle. Can. J. Anim. Sci. 94: 273–280. Ultrasound measurements of 852 crossbred steers along with carcass merit measurements on 756 of them were used to examine their genetic and phenotypic parameters. Traits including ultrasound backfat thickness (UBF), ultrasound ribeye area (UREA), ultrasound marbling (UMAR), carcass weight (CWT), carcass grade fat (CGF), carcass average backfat thickness (CABF), carcass ribeye area (CREA), carcass marbling score (CMAR), and carcass lean meat yield (CLMY) were measured on 6 yr of residual feed intake trials from 2003 to 2008. Pairwise bivariate animal models were performed for each combination of traits using ASReml software to estimate heritability, phenotypic and genetic correlations among the traits. Significant fixed effects (contemporary group, and sire breed), covariates (age of dam, slaughter weight, and start test age of animal), and random additive effect were fitted in the models. The heritability estimates for UBF, UREA, UMAR, CWT, CGF, CABF, CREA, CMAR, and CLMY were 0.31, 0.17, 0.37, 0.40, 0.22, 0.25, 0.24, 0.38, and 0.28, respectively. Most of the phenotypic correlations were significant (P<0.05). CWT had low to moderate phenotypic correlations with most of the traits. Results show that heavier CWT tends to have more UREA, CGF, CABF, and CREA. Genetic correlations among these traits varied from weak to strong, but most of them were not significantly different from zero. Greater CREA may lead to decreased UMAR, and UBF due to negative genetic correlations (−0.56±0.32, and −0.45±0.23, respectively). The results support the potential value of ultrasound technology in crossbreed beef cattle breeding programs to generate indicator traits for carcass quality. In addition, carcass lean meat yield correlated favourably with backfat thickness and rib eye area but correlated unfavourably with UMAR. The estimated genetic parameters for ultrasound and carcass merit traits can be incorporated into breeding programs that emphasize carcass quality in Canadian crossbred beef cattle populations.

Effect of residual feed intake on hypothalamic gene expression and meat quality in Angus-sired cattle grown during the hot season

The relationship between heat stress, meat quality, and residual feed intake (RFI) is unknown in growing steers. To address this issue, high RFI (HRFI) and low RFI (LRFI) individuals were compared by assessing RFI in 48 Angus-sired steers during a 70-d feeding trial conducted during July through September to identify steers with calculated RFI at least 2 SD apart. The association of RFI with indices of meat quality and expression of genes within hypothalamic and adipose tissue was then determined in LRFI and HRFI steers. While on test, feed intake was recorded daily with BW and hip heights recorded every 14 d. Ultrasound measurements of rib eye area (REA) and backfat (BF) were recorded initially and before harvest. Carcass and growth data were analyzed using a mixed model with RFI level (LRFI and HRFI) as the independent variable. The least square means for RFI were -1.2 and 0.99 kg DMI/d, respectively, for the LRFI and HRFI cohorts (P < 0.0001). Dry matter intake was higher for the HRFI individuals versus the LRFI steers (P < 0.0001) while on-test gain was not different (P < 0.95). Marbling score was greater in LRFI than HRFI steers (P < 0.05). However, there were no differences in REA (P < 0.53), BF (P < 0.65), yield grade (P < 0.24), or objective Hunter color measures between LRFI and HRFI steers indicating there was no consistent relationship between RFI and indices of meat quality. Hypothalamic neuropeptide Y (NPY), agouti related protein (AGRP), relaxin-3 (RLN3), melanocortin 3 receptor, and relaxin/insulin-like family peptide receptor 1 (RXFP1) mRNA were expressed 280, 185, 202, 183, and 163% greater, respectively (P < 0.01), while proopiomelanocortin (POMC) mRNA was expressed 42% lower in LRFI than HRFI animals (P < 0.05). Hypothalamic GnRH mRNA expression was 67% lower while gonadotropin inhibiting hormone (GnIH) mRNA was 209% higher in LRFI than HRFI animals (P < 0.01). Pituitary expression of FSHβ and LHβ correlated to hypothalamic GnRH levels (P < 0.05) indicating changes in gene expression within the hypothalamus had functional consequences. Leptin mRNA expression levels were not different between adipose tissue of LRFI or HRFI steers (P < 0.84). These data indicate that animals with superior RFI evaluated during warm conditions have higher expression of orexigenic neuropeptide genes independent of the expression of adipose-derived leptin. Furthermore, the gonadotropin axis may also influence feed efficiency under these conditions.

Residual feed intake studies in Angus-sired cattle reveal a potential role for hypothalamic gene expression in regulating feed efficiency

Mechanisms underlying variation in residual feed intake (RFI), a heritable feed efficiency measure, are poorly understood while the relationship between RFI and meat quality is uncertain. To address these issues, 2 divergent cohorts consisting of High (HRFI) and Low (LRFI) RFI individuals were created by assessing RFI in 48 Angus-sired steers during a 70 d feeding trial to identify steers with divergent RFI. The association of RFI with indices of meat quality and expression of genes within hypothalamic and adipose tissue was then determined in LRFI and HRFI steers. While on test, feed intake was recorded daily with BW and hip heights recorded at 14 d intervals. Ultrasound measurements of rib eye area (REA) and backfat (BF) were recorded initially and before harvest. Carcass and growth data were analyzed using a mixed model with RFI level (LRFI, HRFI) as the independent variable. The least-square means (lsmeans) for RFI were -1.25 and 1.51 for the LRFI and HRFI cohorts (P < .0001). Dry matter intake was higher for the HRFI individuals versus the LRFI steers (P < .0001) while on test BW gain was not different between the 2 groups (P < 0.73). There were no differences detected in marbling score (P < 0.93), BF (P < 0.61), REA (P < 0.15), yield grade (P < 0.85) or objective Hunter color measures between LRFI and HRFI steers indicating that there was no relationship between RFI and meat quality. Neuropeptide-Y (NPY), relaxin-3 (RLN3), melanocortin 4 receptor (MC4R), and GnRH mRNA expression was 64%, 59%, 58%, 86% lower (P < 0.05), respectively, while gonadotropin inhibiting hormone (GnIH) and pro-opiomelanocortin (POMC) mRNA expression was 198% and 350% higher (P < 0.01) in the arcuate nucleus of LRFI steers. Expression of agouti-related protein (AGRP), relaxin/insulin-like family peptide receptor 1 (RXFP1), and melanocortin 3 receptor mRNA was similar between LRFI and HRFI animals. Pituitary expression of FSHβ (P < 0.03) and LHβ (P < 0.01) was correlated to hypothalamic GnRH levels suggesting that changes in gene expression within the arcuate nucleus had functional consequences. Leptin mRNA expression was 245% higher in the adipose tissue of LRFI steers consistent with lower levels of NPY and higher expression of POMC in their hypothalami. These data support the hypothesis that differences in hypothalamic neuropeptide gene expression underlie variation in feed efficiency in steers while the gonadotropin axis may also influence feed efficiency.

Relationship between feed intake, feeding behaviors, performance, and ultrasound carcass measurements in growing purebred Angus and Hereford bulls

The objectives of this study were to examine the growth, DMI, and feeding behaviors of Angus and Hereford bulls; identify the relationships between feeding behaviors and variation in DMI and residual feed intake (RFI); and determine the value of feeding behaviors in predicting DMI. Individual DMI was measured in Angus bulls (n=189; initial BW=427±3.4 kg) and Hereford bulls (n=146; initial BW=411±4.1 kg) fed a grower ration for 71 d in 2009, 78 d in 2010, and 74 d in 2011 using a GrowSafe intake monitoring system. Feeding frequency (FF, meals/d), head down duration (HDD, s/d), head down duration per meal (HDDM, HDD/FF, s/meal), average meal size [AMS, kg/(meal·d)], and feeding rate (FR, g/s) were also measured or calculated using behavior data collected by the GrowSafe system. Ultrasound measures of 12th-rib fat thickness (UFT), longissimus muscle area (ULMA), and intramuscular fat (IMF) were determined during the midtest-weight event of every trial. The data from 3 yr were pooled to generate mean differences between the breeds. Residual feed intake was calculated using a linear regression of DMI on ADG and midtest BW0.75 (MMWT). Animals were classified into 3 RFI groups based on their RFI score as Low (>0.5 SD below the mean), Average (±0.5 SD from the mean), or High RFI (>0.5 SD above the mean). Angus bulls in the Low RFI group consumed 17% (P<0.0001) less DM than the bulls in the High RFI group, while in the Hereford bulls there was a 14% (P<0.0001) difference in DMI between Low and High RFI groups. Significant phenotypic correlations were observed between RFI and DMI (0.83, 0.77), G:F (-0.65, -0.51), HDD (0.41, 0.59), HDDM (0.40, 0.53), AMS (0.52, 0.36), and FR (-0.31, -0.51) in Angus and Hereford bulls, respectively. The HDD, HDDM, and FR were significantly correlated with DMI. The feeding behavior traits, HDD, HDDM, and FR when added to the RFI base model, explained 18, 17, and 13%, respectively, of the variation in DMI not explained by ADG and MMWT in Angus bulls. Similarly, in Hereford bulls, HDD, HDDM, and FR explained 35, 26, and 24%, respectively, of the variation in DMI not explained by ADG and MMWT. These data suggest that feeding behaviors are related to DMI of growing Angus and Hereford bulls.

Relationships between residual feed intake, average daily gain, and feeding behavior in growing dairy heifers

Residual feed intake (RFI) is a measure of an individual's efficiency in utilizing feed for maintenance and production during growth or lactation, and is defined as the difference between the actual and predicted feed intake of that individual. The objective of this study was to relate RFI to feeding behavior and to identify behavioral differences between animals with divergent RFI. The intakes and body weight (BW) of 1,049 growing dairy heifers (aged 5-9 mo; 195 ± 25.8 kg of BW) in 5 cohorts were measured for 42 to 49 d to ascertain individual RFI. Animals were housed in an outdoor feeding facility comprising 28 pens, each with 8 animals and 1 feeder per pen, and were fed a dried, cubed alfalfa diet. This forage diet was chosen because most dairy cows in New Zealand are grazed on ryegrass-dominant pastures, without grain or concentrates. An electronic feed monitoring system measured the intake and feeding behavior of individuals. Feeding behavior was summarized as daily intake, daily feeding duration, meal frequency, feeding rate, meal size, meal duration, and temporal feeding patterns. The RFI was moderately to strongly correlated with intake in all cohorts (r=0.54-0.74), indicating that efficient animals ate less than inefficient animals, but relationships with feeding behavior traits (meal frequency, feeding duration, and feeding rate) were weak (r=0.14-0.26), indicating that feeding behavior cannot reliably predict RFI in growing dairy heifers. Comparison of the extremes of RFI (10% most and 10% least efficient) demonstrated similar BW and average daily gain for both groups, but efficient animals ate less; had fewer, longer meals; shorter daily feeding duration; and ate more slowly than the least-efficient animals. These groups also differed in their feeding patterns over 24h, with the most efficient animals eating less and having fewer meals during daylight (0600 to 2100 h), especially during the afternoon (1200 to 1800 h), but ate for a longer time during the night (0000-0600 h) than the least-efficient animals. In summary, correlations between RFI and feeding behavior were weak. Small differences in feeding behavior were observed between the most- and least-efficient animals but adverse behavioral effects associated with such selection in growing dairy heifers are unlikely.

Genetic parameters for production and feeding behaviour traits in crossbred steers fed a finishing diet at different ages

Durunna, O. N., Mujibi, F. D. N., Nkrumah, D. J., Basarab, J. A., Okine, E. K., Moore, S. S. and Wang, Z. 2013. Genetic parameters for production and feeding behaviour traits in crossbred steers fed a finishing diet at different ages. Can. J. Anim. Sci. 93: 79–87. Because cattle can be raised postweaning under several feeding regimes, this study examined the consistency of phenotypic and genetic parameters of some production and feeding behaviour traits between two feeding periods that beef cattle received a finisher diet. Crossbred steers (n=851) were used for feeding trials from 2002 to 2009 where the steers received a finisher diet either during the fall–winter season (FP1) or during the winter–spring season (FP2). The steers evaluated in FP2 received a backgrounding diet in FP1. Traits examined include dry matter intake (DMI), average daily gain (ADG), gain: feed ratio (G:F), residual feed intake (RFI), and ultrasound measures of backfat thickness (UBF), rib-eye area (UREA) and marbling (UMB). Others include feeding duration (FD), headdown time (HDT) and feeding frequency (FF). As expected, there was no difference (P=0.90) between the RFI measured in the two periods. The two periods were similar for UBF (P=0.87) and UREA (P=0.25),while DMI, ADG and UMB were greater (P<0.04) in FP2 than in FP1. The FD, HDT and FF were greater (P<0.0001) in FP1 compared with FP2. Heritability estimates were calculated in FP1 and FP2, respectively, for ADG (0.38, 0.28), DMI (0.52, 0.42), RFI (0.16, 0.27), G:F (0.18, 0.33), HDT (0.35, 0.18) and FF (0.26, 0.46). More importantly, genetic correlations between FP1 and FP2 were estimated for DMI (0.61), RFI (0.65) and G:F (0.60). The results may indicate the influence of age or feeding period or both on these traits, which may suggest the need for multi-environment genetic evaluations to identify superior animals.

Evidence of residual feed intake reranking in crossbred replacement heifers

The objective of the study was to examine whether residual feed intake (RFI) reranking exists between 2 consecutive periods in replacement heifers fed the same diet. The study collected feed intake and BW data from 190 crossbred heifers over a 3-yr period (61 in 2007, 68 in 2008, and 61 in 2009) during the winter-spring season. The heifers were fed a roughage-based diet (90% barley silage and 10% rolled barley grain) throughout the feeding trial, which was broken down into 2 feeding periods with ADG of 0.94 and 0.90 kg•d(-1) in the first and second periods, respectively. The RFI was calculated for the entire period using different models, which included ADG, mid-metabolic BW, body composition, and feeding activity. Gain:feed ratio and Kleiber ratio were also calculated. Rank correlations among the RFI calculated from different models were obtained, as well as rank correlations between the 2 feeding periods for the feed efficiency measures. Including body composition and feeding activity only improved the R(2) by 1 to 5%. The rank correlations among the different models were high (90 to 95%) for RFI calculated for the entire feeding period. However, the RFI calculated within the second feeding period had greater rank correlation than the RFI calculated from the entire feeding period. Compared with G:F and Kleiber ratio, RFI gave lesser reranking between periods 1 and 2. About 49% of the heifers maintained their RFI class, whereas 51% of the heifers had a different RFI class in period 2. Furthermore, 41% of the heifers changed their RFI in period 2 by <0.5 SD, whereas the rest of the heifers changed by ≥0.5 SD. These results indicate that reranking exists in heifers despite receiving the same diet in the 2 feeding periods and that the reranking may be more serious in heifers (28%) with extreme RFI performances in each period.

Genetic parameters and genotype x environment interaction for feed efficiency traits in steers fed grower and finisher diets

The objective of this study was to examine the genetic parameters and genetic correlations of feed efficiency traits in steers (n = 490) fed grower or finisher diets in 2 feeding periods. A bivariate model was used to estimate phenotypic and genetic parameters using steers that received the grower and finisher diets in successive feeding periods, whereas a repeated animal model was used to estimate the permanent environmental effects. Genetic correlations between the grower-fed and finisher-fed regimens were 0.50 ± 0.48 and 0.78 ± 0.43 for residual feed intake (RFI) and G:F, respectively. The moderate genetic correlation between the 2 feeding regimens may indicate the presence of a genotype × environment interaction for RFI. Permanent environmental effects (expressed in percentage of phenotypic variance) were detected in the grower-fed steers for ADG (38%), DMI (30%), RFI (18%), and G:F (40%) and also in the finisher-fed steers for ADG (28%), DMI (35%), metabolic mid-weight (23%), and RFI (10%). Heritability estimates were 0.08 ± 0.10 and 0.14 ± 0.15 for the grower-fed steers and 0.42 ± 0.16 and 0.40 ± 17 for the finisher-fed steers for RFI and G:F, respectively. The dependency of the RFI on the feeding regimen may have serious implications when selecting animals in the beef industry. Because of the higher cost of grains, feed efficiency in the feedlot might be overemphasized, whereas efficiency in the cow herd and the backgrounding segments may have less emphasis. These results may also favor the retention (for subsequent breeding) of cows whose steers were efficient in the feedlot sector. Therefore, comprehensive feeding trials may be necessary to provide more insight into the mechanisms surrounding genotype × environment interaction in steers.