This study involved 41 crossbred, black-hided beef heifers that were measured in a drylot for residual feed intake (RFI) at 11 ± 1 months of age and classified into more (LOW-RFI; n = 21; -0.96 ± 0.70 kg DM/day) or less efficient (HIGH-RFI; n = 20; 1.40 ± 1.00 kg DM/day) groups. Heifer metabolism and growth performance were evaluated from 14 ± 1 months of age (351 ± 40 kg initial body weight [BW]) across summer and winter in Western Canada. Weather conditions were characterized using the Comprehensive Climate Index (CCI). Rumen temperature (RT) was recorded every 10 minutes using an automated bolus device. Plasma and BW were collected every 18 ± 5 days from July to August and January to March to measure urea nitrogen, non-esterified fatty acids, insulin-like growth factor 1, β-hydroxybutyric acid, leptin, free triiodothyronine (fT3), haptoglobin, heat shock protein 70 (HSP70), gamma-aminobutyric acid, and serotonin, and growth performance. Data were analyzed as a completely randomized design using SAS 9.4. LOW-RFI tended to have greater fT3 and HSP70 (P = 0.08), while exhibiting lower haptoglobin concentrations (P = 0.02) in summer. Gamma-aminobutyric acid concentrations were greater in LOW-RFI during periods of no heat stress (P = 0.01) and tended to decrease in HIGH-RFI under severe risk of cold stress (P = 0.08) based on CCI. Comparatively, HIGH-RFI had higher leptin concentrations during winter (P = 0.04) than LOW-RFI. During summer, HIGH-RFI exhibited greater RT between 1:00-6:00, 10:00-12:00, and 20:00-22:00 (P = 0.002). In contrast, HIGH-RFI had lower RTs on the coldest winter days (P = 0.009). In both seasons, growth performance did not differ between RFI groups (P ≥ 0.24). In conclusion, feed efficiency measured in the drylot was associated with subsequent metabolic responses during grazing, and these responses were influenced by weather-related stress, with more efficient animals showing greater adaptability to weather fluctuations.

Utilizing genomic tools in breeding programs accelerates genetic progress, particularly for difficult/expensive to measure traits such as meat colour. This study aimed to estimate genetic parameters and identify genomic regions and candidate genes associated with meat colour traits in Canadian crossbred beef cattle. Heritability estimates for lightness ( L* ), chroma ( c* ), and hue angle ( Hu) were 0.44, 0.20, and 0.57, respectively. L* and Hu were highly phenotypically (0.86) and genetically (0.98) correlated. The genome-wide association revealed a total of 30, 24, and 25 SNP windows explaining >0.5% additive genetic variance for L*, c*, and Hu, respectively. These SNP windows collectively explained >20% of the genetic variance for the three meat colour traits. The genes GNPDA2, CALCRL, CALM1, KIT, PRKN, and PRKAA2 are the most promising candidates associated with L*, TEX37, ADAMTS9, PRKACB, TTLL7, TFAM, AGT, ACAT2, and PPP1R3C with c*, and MMP2, AKR1B1, AKR1B10, and CYP7A1 with Hu. These candidate genes are mainly involved in energy metabolism pathways, among which the most important are glucose, fatty, and lipid metabolism.

Abstract The advancement in various machine learning (ML) methods provides tools to extract features from a large data set of complex traits and to predict the outcome of the target trait. In this study, we assessed the genomic prediction accuracy using single trait models based on kernel ridge regression (ST_KRR) and linear support vector regression (STLinearSVR) for female feed intake, feed efficiency and fertility traits of Canadian crossbreed beef cattle (n = 2,834 genotyped with 83,875 single nucleotide polymorphisms) and compared their prediction performances to a single trait genomic best linear unbiased prediction (STGBLUP) method. We also evaluated the performances of multiple-trait genomic prediction methods including MAK-based KRR, MAK-based LinearSVR (MAK_MTLinearSVR), and multiple-trait genomic best linear unbiased prediction (MTGBLUP). For the single trait methods, we found that the ST_KRR model was 1.86% to 26.86% more accurate for feed intake and fertility traits including residual feed intake adjusted for backfat thickness (RFIfat), daily dry matter intake (DMI), feeding event duration (DUR), age of first calving (AFC), pre-breeding backfat at first parity (PBBF), and pre-breeding weight at first parity (PBWT) than the STGBLUP method, which had an average accuracy of 0.39 for the traits investigated. For growth and development traits including julian date of birth (JulianDt), weaning weight adjusted to 200 d (WT200d), and birth weight (BRWT) of heifers, STLinearSVR yielded a 5.44% to 9.92% greater accuracy than STGBLUP. As for the multiple trait methods, MAK_MTLinearSVR had a 1.1% to 20.42% greater accuracy for PBWT, AFC, WT200d, DUR, RFIfat, and BRWT than the single trait model of STLinearSVR, while MTGBLUP had a 0.42% to 32.64% greater accuracy for AFC, RFIfat, WT200d and PBBF than the single trait model of STGBLUP. Our results demonstrate the potential application of ML-based multiple-trait models in beef cattle to improve the effectiveness of genomic selection programs, in particular for traits with low heritability.

This study aimed to quantify the relationship between residual feed intake (RFI) measured in 500 heifers and subsequently as mid-gestation cows at the Roy Berg Kinsella Research Station (KIN; n = 227) and Lacombe Research and Development Centre (LRDC; n = 273). Heifers were initially tested for RFI adjusted for end of test rib fat (RFIfat) at 8-12 months of age and then again as 3-year-old first-calf heifers at KIN and as 4-13-year-old cows at LRDC. Heifer RFIfat measured in drylot on a forage diet was associated (R2 > 0.53; P < 0.001) with RFIfat measured again as older cows. Each 1 kg DM day-1 change in heifer RFIfat equaled 0.48 +/- 0.10 and 0.75 +/- 0.19 kg DM day-1 change in cow RFIfat for KIN and LRDC, respectively. Linear effects were also reported for RFIfat component traits, where DMI (P < 0.001), ADG (P < 0.060), mid-test metabolic weight (P < 0.001), and end of test rib fat (P < 0.001) measured as heifers were related when measured again as older cows. In addition, the linear effects of heifer RFIfat on cow RFIfat were constant across cow age groups from 4-10 years of age. These results show that selection for RFI in heifers will result in cows that are also more feed efficient.

Abstract Beef cattle have been selected for feed efficiency to reduce feeding costs and environmental impact. Still, there is a paucity of knowledge on how feed-efficient beef females maintained outdoors respond to extreme cold weather. Therefore, this research assessed blood parameters and rumen temperature (RT) of beef heifers with divergent residual feed intake (RFI) during winter in Alberta, Canada. Ccrossbred beef heifers [n = 41; body weight (BW) = 474 ± 38; approximately 21 mo of age) previously tested for RFI in drylot and classified as either more (n = 21; LOW-RFI = -1.0 ± 0.70) or less feed-efficient (n = 20; HIGH-RFI = 1.4 ± 1.00) were used in a completely randomized design for 55 d (January to March). Heifers were maintained in a single dormant pasture and received free-choice hay. A Smart Rumen Bolus (Moonsyst) was used to automatically record RT. Blood samples were collected every 18 ± 8 d based on weather conditions to determine concentrations of blood urea nitrogen (BUN), non-esterified fatty acids (NEFA), insulin-like growth factor 1 (IGF-1), β-Hydroxybutyric acid (BHBA), leptin (LEP), free triiodothyronine (fT3), haptoglobin (HP), heat shock protein 70 (HSP70), gamma-aminobutyric acid (GABA), and serotonin (5-HT). Environmental conditions were assessed by calculating the Climate Comprehensive Index (CCI) using temperature, wind speed, solar radiation, and humidity from a weather station within 1 km of the pasture. Based on CCI, daily weather conditions were considered to impose mild, moderate, severe, extreme, and extremely dangerous stress risk for 3, 15, 19, 13, and 5 d of the study, respectively. Leptin was greater in HIGH vs. LOW-RFI heifers (P = 0.05; 5.21 vs. 4.56 ng/ml). A tendency for an RFI × day interaction was detected for GABA (P = 0.09) and HP (P = 0.06), with greater concentrations in the LOW-RFI heifers on extreme and extremely dangerous cold days, respectively. However, HP concentrations were below the threshold for inflammation throughout the study. An effect of day was detected for IGF-1, LEP, BUN, NEFA, BHB, and 5-HT (P ≤ 0.001). The least concentrations of BHBA and BUN (128 nmol/L and 4.8 mg/dL, respectively) were recorded, along with the greatest NEFA concentration (0.619 mEq/L), during an extremely dangerous cold day. On extreme cold days, LEP (3.7 ug/L) was the least and 5-HT was the greatest (56.7 ng/mL). Rumen temperature was greater in LOW-RFI vs. HIGH-RFI when day imposed greater risks to cause cold stress (P = 0.01). However, no differences were detected in final BW or average daily gain (P ≥ 0.24). In summary, results indicate differential blood parameter dynamics and rumen temperature fluctuations between high and low RFI heifers under varying cold stress conditions. Greater plasma leptin concentrations and decreased rumen temperature are likely associated with heightened thermogenic activity and cold stress in less-feed-efficient heifers.

This study investigated factors influencing heifer replacement and cow-calf profitability using 361 cows (born 2011-2018) at the Lacombe Research and Development Centre, Alberta, Canada. Profitability was measured by marginal returns (MR) incorporating feed costs, heifer opportunity cost, calf and cull revenues, and a premium for cows retained in the herd. The study evaluated the linear effects of lifetime productivity, feed efficiency (residual feed intake adjusted for off-test backfat thickness; RFIfat), and genomic retained heterozygosity, an indicator of heterosis, on MR, feed costs, total costs, and net revenue (NR). Lifetime productivity, defined by the cumulative weight of calves weaned, was positively associated with MR and NR (P < 0.01). RFIfat influenced total cost, MR, and NR (P < 0.05), with MR improved by $168.50 cow-1 year-1 for each unit decrease in RFIfat, although regression and group mean comparisons were not fully consistent. Genomic retained heterozygosity positively impacted MR and NR, with a 10% increase enhanced MR and NR by $21.80 and $20.50 cow-1 year-1, respectively. Cow breed type did not affect longevity, MR, or NR. In conclusion, RFIfat and genomic diversity were important factors to consider in heifer replacement decisions when lifetime DMI was estimated as described in the present study.

Abstract Beef cattle have been selected for feed efficiency to reduce feeding costs and environmental impact, but there is a knowledge gap regarding residual feed intake (RFI) and thermotolerance in grazing beef females. Therefore, this study evaluated blood parameters, rumen temperature (RT), activity behavior, and performance of grazing lactating first-calf beef heifers with divergent RFI during summer. Crossbred beef heifers [n = 35; 432 ± 8.40 kg of body weight (BW) and 26 ± 1 mo of age] previously tested and classified for RFI as more (n = 17; LOW-RFI = -0.8 ± 0.214) or less efficient (n = 18; HIGH-RFI = 1.5 ± 0.220) were used in a completely randomized design, grazing continuously a single pasture during summer (June to August). An accelerometer-based sensor recorded lying, standing, and step counts, while RT was automatically recorded using a rumen bolus throughout the 64-d experimental period. Body weight and blood samples were collected on d 0, 13, 28, and 64, while body fat deposition was assessed via ultrasonography on 0, 13, 28, and 50 d. Plasma was analyzed for concentrations of blood urea nitrogen (BUN), non-esterified fatty acids (NEFA), free triiodothyronine (fT3), heat shock protein 70 (HSP70), and whole blood used to perform a complete blood cell count. Environmental conditions were assessed by calculating the Climate Comprehensive Index (CCI) using temperature, wind speed, solar radiation, and humidity from a weather station within 1 km of the pasture. The resulting CCI index categorized environmental stress from non-existent to imposing extreme danger risk. An RFI × day interaction was observed for NEFA (P = 0.08), with LOW-RFI showing greater concentrations vs. HIGH-RFI on a period classified as not imposing environmental stress. An effect of day (P < 0.01) was detected for BUN, fT3, and HSP70. An RFI × hour (P = 0.02) interaction was detected for RT, where RT was greater from 1400 h to 0600 h in HIGH-RFI. White blood cell counts (P = 0.04) and mean corpuscular volumes were greater (P = 0.05), while plateletcrit was less (P = 0.01) in LOW-RFI. An RFI × day interaction was found for monocytes and monocytes% (P = 0.04), with greater concentrations 24-h after severe stress in HIGH-RFI. The HIGH-RFI tended to have greater RIB fat at d 50 (P = 0.06) despite no differences in gain or BW between groups (P ≥ 0.26). An interaction between RFI × hour (P < 0.01) showed that HIGH-RFI had a greater number of steps and standing time and less lying time during the hottest hours of the day. In summary, this study revealed that RFI influenced physiological and behavioral reactions to environmental stress, favoring the more feed-efficient first-calf beef heifers.

Genomic tools and accuracy of molecular breeding values (MBVs) for economically important traits continue to improve and are being applied in commercial crossbred beef cattle. Ge­nomic breed composition and retained heterozygosity of an individual animal can be used to further improve female fertil­ity, stayability, lifetime productivity and calf health resilience. But this is just the first step. Within specific crossbred popula­tions, researchers at Livestock Gentec have used large numbers of cattle phenotypes and genotypes, combined with advanced statistical genomic analyses to generate MBVs for 18 traits with moderate to moderately-high accuracy (0.35 to 0.60). This accu­racy is equivalent to 10 to 20 progeny records. These MBVs are economically balanced into multi-trait profit indices such as the Replacement Heifer Profit Index Score and the Feeder Profit In­dex. The use of these genomic tools will improve the sustainabil­ity of beef production by improving profitability, lowering the carbon footprint, and improving an animal’s ability to adapt to changing environments. The following paper outlines the valida­tion of these genomic tools and their potential benefits.

Abstract Genomic selection has the potential to accelerate the genetic improvement rate for difficult/expensive to measure traits such as feed efficiency and fertility traits in beef cattle. To develop genomic selection tools for Canadian beef cattle, we collected or sourced phenotypic data of feed efficiency along with other traits including carcass merit, female feed intake and fertility related traits, and their genotypes from both research and commercial herds. The phenotypic data were consolidated and recorded for contemporary groups, leading to the development of data sets including 11,292 beef cattle with residual feed intake, dry matter intake, average daily gain, metabolic body weight, 7,299 to 8,081 cattle with carcass merit traits, and 1,802 to 2,792 cows with feed intake and fertility traits after quality controls. Genotype data of the animals from various single nucleotide polymorphisms (SNP) panels were merged to the same allele format of 50K, and then imputed to 770K SNPs, and eventually to whole genome sequence variants. The refined Canadian beef cattle data sets have not only allowed us to investigate genetic architectures of the beef performance traits but also enabled the development of genomic selection tools including molecular breeding values and multiple trait selection indexes with a moderate to moderately high accuracy for the traits through a cross-validation of within reference data set. The genomic selection tools have been successfully deployed to over 10,415 breeding candidates submitted by Canadian beef producers through multiple demonstration projects. The average accuracy of the molecular breeding values and multiple trait selection index of the commercial beef cattle ranged from 0.38 to 0.49 for feed efficiency and carcass merit traits, and from 0.26 to 0.38 for female feed intake and fertility traits. Current research is focusing on calibrating the genomic selection tools with larger data sets and with more advanced genomic prediction methods.

The objectives of this study were to evaluate the contribution of additive and dominance genetic effects to the phenotypic variation of carcass quality traits and to identify the underlying genetic variants associated with these traits. A total of 3958 Canadian crossbred beef cattle with phenotype and genotype data were used in two models: (1) additive and (2) joint additive and dominance genomic models that included fixed contemporary group, and covariates of slaughter age, and the eigenvectors of five principal components to account for population structure. Variance components and genome-wide association analyses were performed, and a 10% genome-wide false discovery rate (FDR) was applied to declare associations as significant. Genomic heritability ranged from 0.31 ± 0.03 for ultrasound rib eye area to 0.46 ± 0.05 for marbling score. Up to 10% dominance genetic variation was observed for ultrasound rib eye area and marbling score, indicating the contribution of dominance genetic effects to these trait variations. Eleven overlapping significant single-nucleotide polymorphism associations were identified across the studied traits and models. The identified candidate genes (e.g., BTC, SPP1, and SEPSECS) have biological functions related to tissue growth and skeletal muscle development and can be further validated in other cattle populations to determine their usefulness for beef cattle genetic improvement.

Selection for feed efficiency is crucial for improving economic and environmental sustainability in beef cattle production. Residual feed intake (RFIfat) is a commonly used measure of feed efficiency and is determined in a drylot setting by calculating the difference between observed and expected dry matter intake (DMI), where expected feed intake is adjusted for metabolic body weight (BW), average daily gain (ADG) and body fatness. Lower RFIfat cattle are more efficient animals as they eat less than predicted for the same growth, body size and body fatness. Limited studies have been conducted evaluating the role of RFIfat on the subsequent performance of cow-calf pairs on native range. Kinsella Composite cows and calves (n = 120) grazed native pasture from July 11 to Sept 12 (summer) and from Sept 13 to Nov 2 (fall) of 2023 were included in this study. All dams had previously been evaluated for RFIfat as a heifer (8 to 12 mo of age) using the GrowSafe Feed Intake System (Vytelle, Canada). Cow and calf ADG were subjected to an analysis of covariance using lm function from stats R core package (R Core Team, 2024), with cow age (2 to 8 yr of age) as the fixed effect and RFIfat as the covariate, analyzing separately by season. An unbalanced Tukey HDS post-hoc were applied for age and p-values < 0.05 were considered significant. Weight gain was assessed on cows with an initial BW on pasture of 598.4 ± 68.4 kg, and 2 to 8 yr of age, and on calves having an initial on pasture BW of 106 ± 21.5 kg, and 65 ± 14 d of age. Cow age affected (P < 0.01) cow ADG during summer, with the youngest dams (2 yr old) gaining more weight than older animals (7 yr old; Figure 1A). No effect of RFIfat was found on cow weight gain during summer grazing. However, during fall grazing, RFIfat affected (P < 0.01) cow ADG (Figure 1B). Low-RFIfat cows (efficient) had increased weight gain during fall grazing as compared with high-RFIfat cows (inefficient: Figure 1B). Calf ADG was not affected (P > 0.1) by cow age, cow RFIfat and cow ADG during summer and fall. We conclude that cows with low RFIfat exhibited superior body weight gain, during fall grazing on native range when forage nutrient quality and quantity become limiting.

Abstract Beef cattle grazing across more than 40M ha of Canada’s grasslands is economically significant yet contributes to methane (CH4) emissions. Accurately measuring CH4 emissions across diverse environments presents substantial challenges. Our study investigated CH4 and carbon dioxide (CO2) production in 3-yr-old pregnant crossbred beef cows (n = 30) across different phases of the beef production cycle, including in drylot and while grazing on native rangeland, in Western Canada’s Aspen Parkland region using the GreenFeed Emissions Monitoring System (GEM). During the January to March drylot phase, enteric CH4 and CO2 production of the cows were monitored for 63 d in consort with feed efficiency testing while consuming a mixed oat-barley silage diet. Following this, cows were categorized into three distinct groups based on the standard deviation (SD) of CH4 yield [gּ kg−1 dry matter intake (DMI)]: Low (< 0.5 SD; n = 11), Medium (± 0.5 SD; n = 10), and High (> 0.5 SD; n = 9). Post-calving, cows and calves transitioned to native pastures for CH4 and carbon dioxide (CO2) assessment across three distinct foraging conditions: high-quality, high-quantity forage in summer (SUM; 50 d); moderate-quality, high-quantity forage in September (SEP; 22 d); and finally, low-quality, low-quantity forage in October (OCT; 22 d). We hypothesize that ranking cows based on their CH4 yield (gּ kg−1 DMI) in drylot settings may have the potential to reflect their CH4 production (g/d) during grazing conditions, even without feed intake data. Data were analyzed using the PROC MIXED procedure of SAS to examine CH4 production among cows categorized by their assigned ranking. Spot CH4 and CO2 measurements totaled 1,242, 1,145, and 1,205 for the SUM, SEP, and OCT, production phases, respectively. Average daily visits to GEM units were 1.4 ± 0.1, 1.84 ± 0.1, and 1.96 ± 0.1 for the corresponding phases. While High CH4-ranked cows had methane production similar to Low CH4-ranked cows (234.8 ± 8.2 vs. 235.0 ± 6.0 g/d, respectively), the Medium group had significantly greater methane production (260.5 ± 6.2 g/d; P = 0.008) than the Low and High CH4 groups. Furthermore, significant interactions were observed between CH4 ranking groups and CH4 production during the grazing phase (P = 0.035). Cows in the Medium CH4 group emitted greater amounts of CH4 compared with the High group in SUM (288.2 ± 9.3 vs. 247.0 ± 14.1 g/d) and to the Low group in SEP and OCT (276.5 ± 6.6 vs. 238.1 ± 6.3, and 216.7 ± 7.2 vs. 191.8 ± 7.5 g/d, respectively). In conclusion, the drylot CH4 ranking may hold promise in predicting outcomes for both Low and Medium CH4-ranked groups during grazing phases. However, High CH4-ranked cows had decreased methane production, likely influenced by grazing-induced changes in feed intake and individual feeding behaviors, prompting further exploration.

The present study evaluated three strategies to find the optimum subset of DNA markers from the 50K Illumina Bovine panel to classify beef cattle into the most and the least feed-efficient groups without using individual feed intake and performance measures. Residual feed intake (RFI) and 50K single nucleotide polymorphisms (SNPs) genotype data of 4,057 beef animals from research and commercial herds were included. Initially, all cattle were ranked based on their phenotypic RFI values. Then different datasets were created by selecting animals from the 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, and 45% range of top and bottom of the ranked RFI values. SNP subsets were selected based on the top-ranked SNPs contributing to the variance of RFI (first strategy), selecting SNPs from the SNP subsets created in the first strategy (strategy 2), and extracting SNPs from 50k SNPs (strategy 3). Then eleven ML algorithms were employed to classify the most and the least feed-efficient groups using 260 datasets generated by combinations of ten RFI phenotype percentage groups and 6, 18, and 2 SNP subsets in the first, second and third strategies, respectively. There was a high degree of accuracy (>69%) for classifying animals in the range of 1% for all ML algorithms under the three strategies and different SNP subsets. Implementing the linear Support Vector Machine algorithm for 15K SNPs obtained in the first strategy predicted the 1% of the most and the least feed-efficient animals with an accuracy of 84%. In the second strategy, selecting 524 SNPs from the 15K SNPs subset outperformed the other strategies with an accuracy of 81% for 1% of the population using the Naive Bayes algorithm. It was concluded that a smaller number of SNPs (524) could be used to predict the most and the least feed-efficient animals with an acceptable accuracy to reduce the cost of selection for RFI using genomic information.

Genetic parameters were estimated for objective and subjective traits assessed after 3 and 29 days aging in meat samples of 1154 commercial beef cattle. Meat attributes [Warner-Bratzler shear force (WBSF), intramuscular fat (IMF), and pH] and sensory traits [flavor intensity (FI), off-flavor (OF), connective tissue (CT), overall tenderness (OT), sustained juiciness (SJ), and overall palatability (OP)] were available. The animal mixed model used included additive genetic and residual effects as random effects, contemporary group as fixed effect and genomic breed composition and slaughter age as covariates. Genetic parameters were estimated using airemlf90 software and single-step genomic BLUP. Heritability estimates for OT (3 and 29 d), OP (3 d) and OF (29 d) were of moderate magnitude ranging from 0.18 ± 0.07 to 0.31 ± 0.07. Heritabilities were negligible or of low magnitude for all other sensory traits with values ranging from 0.03 ± 0.05 to 0.14 ± 0.07. Among objectively measured traits, the estimate of heritability for meat pH was moderate at day 3 (0.20 ± 0.08) and negligible at 29 (0.00 ± 0.05). For IMF and WBSF the heritability estimates were 0.43 ± 0.09 and 0.54 ± 0.09, and 0.22 ± 0.07 and 0.19 ± 0.07 for day 3 and 29, respectively. Genetic correlations between days for each sensory trait tended to be of high and positive magnitude ranging from 0.54 ± 0.60 to 0.99 ± 0.28. Genetic and phenotypic correlations of subjectively assessed traits were consistent in direction and magnitude with WBSF (negative) and IMF (positive) suggesting that genetic selection based on objectively measured traits can be used for meat quality improvement and to increase consumer satisfaction. In addition, selection can be implemented using sensory traits collected after 3 days of aging.

Knowledge of genetic parameters is required to select for optimal yield of primal cuts that may be used as the selection criteria for designing future breeding programs. This study aimed to estimate the heritability, as well as genetic and phenotypic correlations of primal cut lean and fat tissue components, and carcass traits in Canadian crossbred beef cattle. All tissue component traits presented a medium to high heritability (lean 0.41 to 0.61; fat 0.46 to 0.62; bone 0.22 to 0.48), which indicates a probable increase in their response to genetic selection. In addition, high genetic correlations were found among the primal cut lean trait group (0.63 to 0.94) and fat trait group (0.63 to 0.94), as well as strong negative correlations between lean and fat component traits (-0.63 to -1). Therefore, results suggested inclusion of primal cut tissue composition traits as a selection objective in breeding programs with consideration of correlations among the traits could help in optimizing lean yield for the highest carcass value.

This study identified genomic variants and underlying candidate genes related to the whole carcass and individual primal cut lean content in Canadian commercial crossbred beef cattle. Genotyping information of 1035 crossbred beef cattle were available alongside estimated and actual carcass lean meat yield and individual primal cut lean content in all carcasses. Significant fixed effects and covariates were identified and included in the animal model. Genome-wide association analysis were implemented using the weighted single-step genomic best linear unbiased prediction (WssGBLUP). A number of candidate genes identified linked to lean tissue production were unrelated to estimated lean meat yield and were specific to the actual lean traits. Among these, 41 genes were common for actual lean traits, on specific regions of BTA4, BTA13 and BTA25 indicating potential involvement in lean mass synthesis. Therefore, the results suggested the inclusion of primal cut lean traits as a selection objective in breeding programs with consideration of further functional studies of the identified genes could help in optimizing lean yield for maximal carcass value.

Over 20 M ha of grazing land is utilized for beef production in western Canada, significantly contributing to the Canadian economy. Cattle are recognized for contributing to methane (CH4) and carbon dioxide (CO2), and individual animal contribution varies with several factors, one of them being feed efficiency as measured using residual feed intake adjusted for off-test backfat thickness (RFIfat). Given that commercial cattle spend a large portion of their production lifecycle grazing on diverse pastures in western Canada, understanding whether and how RFIfat measured in drylot and CH4 emissions reflect animal performance on pasture remains essential. This study quantified CH4 and CO2 production from beef cattle while grazing diverse diets on open-range aspen parkland pastures during fall. Cattle had been previously measured for RFIfat in drylot. Production of CH4 and CO2 (g/day) from crossbred beef cows (n = 22, with a range of -2.2 to +1.3 kg DM/day in RFIfat) and replacement heifers (n = 15; with a range of -2.6 to + 3.0 kg DM/day in RFIfat) were monitored using the GreenFeed emissions monitoring system over 40 days while grazing on native rangeland (70 ha) in the fall of 2022. Fall grazing was divided into two 20 ± 1 day' grazing periods; 20 days in September (SEP) vs. 20 days in October (OCT). Total spot measurements of CH4 and CO2 emissions in SEP and OCT were 1,096 vs. 1,054 for cows and 644 vs. 571 for heifers, respectively. The average number of daily visits per animal to the GreenFeed unit for cows and heifers were 2.8 ± 0.1 vs. 2.5 ± 0.1 in SEP, and 2.5 ± 0.1 vs. 2.0 ± 0.1 in OCT, respectively. Cows had greater average daily CH4 (SEP: 268.4 ± 6.1 vs. 196.1 ± 4.3; OCT: 243.9 ± 6.1 vs. 185.0 ± 4.3 g/day) and CO2 emission (SEP: 9,105.0 ± 143.1 vs. 6,485.3 ± 108.6; OCT: 8,544.3 ± 143.2 vs. 6,308.7 ± 108.9 g/day) than heifers (all P < 0.01). A negative relationship was evident between the CH4 emission and RFIfat in heifers (SEP: R2 = 0.043 vs. OCT: R2 = 0.014; P < 0.01), as well as CO2 emission and RFIfat (SEP: R2 = 0.083 vs. OCT: R2 = 0.020; P < 0.01), although the amount of variation explained by RFIfat is very small and is in disagreement with previous data. We speculate that the decline in CH4 and CO2 emissions from cattle in Oct might be due to various factors, including but not limited to changes in overall intake, daylight hours, air temperature, plant community, feeding and ruminating patterns, and rumen microbial profiles. Further analysis of forage quality, step counts, and GPS location, as well as rumen bacterial community, may shed more light on methane production in the fall.

There is considerable interest in improved feed efficiency to enhance sustainability in beef production, but a lack of understanding exists on the interaction between residual feed intake (RFI) and environment while grazing. Increasing variation in environmental conditions has been documented in western Canada with summers becoming warmer. This study evaluated blood parameters and rumen temperature (RT) of grazing beef heifers with divergent residual feed intake (RFI) during summer (July to August) of 2022. Forty-four crossbred beef heifers (358 ± 4.78 kg body weight; approximately 14 months of age) previously tested for RFI in drylot and classified as more (n = 21; LOW-RFI = -0.9 ± 0.70) or less feed efficient (n = 23; HIGH-RFI = 1.3 ± 1.00) were grazed at 2.72 AUM/ha over 7 wk in Alberta, Canada. Rumen temperatures were automatically recorded throughout the study using the Smart Rumen Bolus by Moonsyst. Plasma was collected every 14 ± 1 d for 42 d to determine concentrations of blood urea nitrogen (BUN), non-esterified fatty acids (NEFA), insulin-like growth factor 1 (IGF-1), β-Hydroxybutyric acid (BHBA), leptin (LEP), free triiodothyronine (fT3), haptoglobin (HP), heat shock protein 70 (HSP70), and gamma-aminobutyric acid (GABA). Environmental conditions were assessed by calculating the Climate Comprehensive Index using temperature, wind speed, solar radiation, and humidity data from a weather station within 1 km of the grazed pastures. Daily weather conditions were considered to impose risk to cause mild, moderate, severe, and extreme stress for 8, 21, 8, and 1 days, respectively. Plasma and RT data were analyzed as a completely randomized design with repeated measures. An RFI × day interaction was observed for BUN (P = 0.018). LOW-RFI had greater (P = 0.02) BUN on d 42 compared with HIGH-RFI heifers (42.5 vs. 32.6 mg/dL, respectively), while GABA tended to be greater (P ≤ 0.09) for HIGH-RFI heifers on d 0 and 42. Free T3 concentrations were greater (P = 0.04; 8.54 vs. 7.78 pmol/L, respectively), whereas HP was less (P = 0.01) in LOW-RFI heifers. However, HP concentrations were below the threshold for inflammation throughout the study. There was also an effect of day (P < 0.01) for fT3, IGF-1, LEP, NEFA, HSP70, and BHBA. Leptin and HSP70 concentrations were greatest on d 14 and 28, whereas BHBA was the greatest (P < 0.01) and IGF-1 the least on d 42 (P < 0.01). An RFI × hour interaction was detected for RT (P = 0.0003), where HIGH-RFI heifers had greater RT throughout the day. In summary, weather conditions in western Canada changed blood parameters of replacement beef heifers during summer. Feed efficient heifers had decreased RT and greater plasma concentrations of fT3, which could be associated with metabolic homeostasis and regulation of thermogenesis.

Concerns about sustainability of beef production systems generate an interest in improved feed efficiency; however, there is a lack of research evaluating cattle activity budgets in response to the interaction between residual feed intake (RFI) and environment while grazing. Lying behavior and activity can provide insight into how animals interact with the environment and serve as an indicator of animal comfort. Furthermore, exposure to severe environmental factors can change behavioral patterns and impair animal performance. Therefore, this study evaluated activity budgets and performance in grazing beef heifers with divergent residual feed intake (RFI) during the summer season. From July to August 2022, forty-four crossbred beef heifers [358 ± 4.78 kg of body weight (BW); approximately 14 months of age] previously tested for RFI in drylot and classified as more (n = 21; LOW-RFI = -0.9 ± 0.70) or less feed efficient (n = 23; HIGH-RFI = 1.3 ± 1.00) were grazed at 2.72 AUM/ha over 7 wk in Alberta, Canada. IceRoboticTM pedometers (IceQube+) were used to track 24-hr heifer activity budgets [n = 43; total steps and lying and standing time (min/d and min/h) for 36 d]. Full BW was obtained on d -1, 0, 14, 28, 42, and 43 while fat scan on rib and rump were measured by ultrasound (Aloka 500 V diagnostic real-time) on d 0 and 42. Air temperature, relative humidity, wind speed and solar radiation information were collected within 1 km of the grazed area to calculate the Comprehensive Climate Index (CCI). Based on CCI, weather conditions were considered to impose risk to cause mild, moderate, severe, and extreme stress for 5, 18, 7, and 1 days, respectively. For BW, average daily gain (ADG), rump (RF) and rib fat (RiF), the data were analyzed as a completely randomized design, while behavior activity included repeated measures. An RFI x day interaction was observed for lying and standing times (P = 0.02) and total steps (P = 0.001). Greater number of steps (P < 0.01) and an increased standing time (P < 0.01) were observed in HIGH-RFI heifers. RFI × hour interaction was observed for lying and standing times (P = 0.006), where LOW-RFI heifers spent more time lying at 10:00 am (P < 0.01). Furthermore, LOW-RFI heifers had decreased number of steps per hour throughout the study (P = 0.03; 178 vs 191 ± 4.1). No effects were observed for ADG, BW, RF, and RiF (P > 0.24). In summary, selected activity behaviors differed between beef heifers with divergent residual feed intake while summer grazing. Further studies are needed to investigate the effects of continuous changes in weather conditions to better understand the environmental impacts on animal behavior while selecting for more efficient beef cattle.

Feed costs are the largest expense in commercial beef production. Increasing cattle (Bos taurus) feed efficiency should reduce feed costs and increase beef profitability. This study used data from two years of a backgrounding trial conducted in Lacombe, Alberta, Canada. The evaluation looked at economic and predicted CH4 emission impacts of diet quality and cattle efficiency type in backgrounding systems. The hypothesis was that diet quality from use of barley (Hordeum vulgare c.v. Canmore) or triticale (xTriticosecale c.v. Bunker) silage-based diets and cattle efficiency type defined by residual feed intake would interact to affect profitability and CH4 emissions. Effects of diet and cattle efficiency type on profitability and CO2e emissions were assessed using statistical and stochastic risk simulation. The profitability of beef backgrounding was affected by cattle efficiency type and diet quality with higher quality barley silage also lowering CO2e emissions. The difference in certainty equivalent (CAD~30 steer−1) of efficient steers on barley silage and inefficient steers on barley silage or efficient or inefficient steers on triticale silage supports a beef backgrounding producer focus on diet quality and cattle efficiency type. This study did not address potential agronomic differences, including yield, which could provide nuance to forage choice.