D. H. Crews

Effect of divergence in residual feed intake on feeding behavior, blood metabolic variables, and body composition traits in growing beef heifers

This study examined the relationship of feed efficiency and performance with feeding behavior, blood metabolic variables, and various body composition measurements in growing beef heifers. Individual DMI and growth were measured in yearling Limousin x Holstein-Friesian heifers [n = 86; initial BW = 191.8 (SD = 37) kg] fed a TMR diet comprising 70:30 concentrate:corn silage on a DM basis (ME of 2.65 Mcal/kg of DM; DM of 580 g/kg) for 82 d. Meal duration (min/d) and meal frequency (events/d) were calculated for each animal on a daily basis using an Insentec computerized feeding system. Physical measurements as well as ultrasonic fat and muscle depths were recorded on 3 equally spaced occasions during the experimental period. Blood samples were collected by jugular venipuncture on 4 equally spaced occasions and analyzed for plasma concentrations of IGF-I, insulin, leptin, and various metabolites. Phenotypic residual feed intake (RFI) was calculated for all animals as the residuals from a multiple regression model regressing DMI on ADG and midtest BW(0.75). Overall, ADG, DMI, feed conversion ratio (FCR), and RFI were 1.51 (SD = 0.13), 6.74 (SD = 0.99), 4.48 (SD = 0.65), and 0.00 (SD = 0.48) kg/d, respectively. Residual feed intake was positively correlated with DMI (r = 0.47) and FCR (r = 0.46), but not with ADG or midtest BW. Positive correlations (ranging from r = 0.27 to r = 0.63) were estimated between ultrasonic measures of final lumbar fat and lumbar fat accretion over the test period and DMI, FCR, and RFI. The inclusion of gain in lumbar fat to the base RFI model increased R(2) (0.77 vs. 0.80) value for the degree of variation in DMI not explained by midtest BW and ADG alone. The Pearson rank correlation between RFI and carcass-adjusted RFI (RFI(c)) was high (r = 0.93). From the plasma analytes measured, NEFA (r = -0.21; P < 0.05) and beta-hydroxybutyrate (r = 0.37; P < 0.05) concentrations were correlated with RFI. Plasma leptin (r = 0.48), glucose:insulin (r = -0.23), NEFA (r = -0.32), and beta-hydroxybutyrate (r = 0.25) were associated with FCR. However, systemic IGF-I and insulin were unrelated (P > 0.05) to any measure of feed efficiency. The feeding behavior traits of eating rate, daily feeding events, and nonfeeding events were positively correlated (P < 0.05) with RFI and RFI(c). This multifactorial study provides new information on some of the biological processes responsible for variation in feed efficiency in beef cattle.

Phenotypic and genetic parameters for different measures of feed efficiency in different breeds of Irish performance-tested beef bulls

No genetic parameters for performance and feed efficiency traits are available for Irish performance-tested bulls. The objective of this study was to determine the phenotypic and genetic variation for feed intake, BW, ADG, and measures of feed efficiency including feed conversion ratio (FCR), relative growth rate, Kleiber ratio, residual BW gain (RG), and residual feed intake (RFI). Observations were available on up to 2,605 bulls for each trait from one test station across 24 yr; breeds included in the analyses were Aberdeen Angus (AN), Charolais (CH), Hereford, Limousin (LI), and Simmental. The test period was at least 70 d. Bulls were individually offered concentrates ad libitum, with a restricted forage allowance. Differences in performance and feed efficiency existed among breeds. For example, AN, on average, ate 0.04 kg of DM/d more than CH but had ADG of 0.14 kg/d less over the 70-d test period. Results showed LI and CH were the most efficient breeds when efficiency was defined as FCR or RFI. When animals were partitioned into groups based on high, medium, or low RFI, the low RFI (i.e., most efficient) group were also the more efficient as defined by RG and FCR. The low RFI group had the same ADG as the medium group and a greater ADG (P < 0.01) than the high group (1.67 vs. 1.66 and 1.63 kg/d); yet they ate 0.67 kg of DM/d less (P < 0.001) than the medium RFI group and 1.22 kg of DM/d less (P < 0.001) than the high RFI (i.e., least efficient) group. Genetic parameters for all performance and efficiency measures were estimated across breeds using linear animal mixed models; heritability estimates for feed efficiency traits ranged from 0.28 +/- 0.06 (RG) to 0.45 +/- 0.06 (RFI). An additional series of analyses included a maternal component in the model; maternal heritability estimates for feed efficiency traits ranged from 0.05 +/- 0.03 (RG) to 0.11 +/- 0.05 (relative growth rate). Genetic correlations between most of the different feed efficiency measures were strong. Results from this study indicate significant genetic differences in performance and some measures of feed efficiency among performance-tested beef bulls.

Characterization of feed efficiency traits and relationships with feeding behavior and ultrasound carcass traits in growing bulls

The objectives of this study were to characterize feed efficiency traits and to examine phenotypic correlations between performance and feeding behavior traits, and ultrasound measurements of carcass composition in growing bulls. Individual DMI and feeding behavior traits were measured in Angus bulls (n=341; initial BW=371.1+/-50.8 kg) fed a corn silage-based diet (ME=2.77 Mcal/kg of DM) for 84 d in trials 1 and 2 and for 70 d in trials 3 and 4 by using a GrowSafe feeding system. Meal duration (min/d) and meal frequency (events/d) were calculated for each bull from feeding behavior recorded by the GrowSafe system. Ultrasound measures of carcass 12th-rib fat thickness (BF) and LM area (LMA) were obtained at the start and end of each trial. Residual feed intake (RFIp) was computed from the linear regression of DMI on ADG and midtest BW(0.75) (metabolic BW, MBW), with trial, trial by ADG, and trial by midtest BW(0.75) as random effects (base model). Overall ADG, DMI, and RFIp were 1.44 (SD=0.29), 9.46 (SD=1.31), and 0.00 (SD=0.78) kg/d, respectively. Stepwise regression analysis revealed that inclusion of BW gain in BF and LMA in the base model increased R(2) (0.76 vs. 0.78) and accounted for 9% of the variation in DMI not explained by MBW and ADG (RFIp). Residual feed intake and carcass-adjusted residual feed intake (RFIc) were moderately correlated with DMI (0.60 and 0.55, respectively) and feed conversion ratio (FCR; 0.49 and 0.45, respectively), and strongly correlated with partial efficiency of growth (PEG; -0.84 and -0.78, respectively), but not with ADG or MBW. Gain in BF was weakly correlated with RFIp (0.30), FCR (-0.15), and PEG (-0.11), but not with RFIc. Gain in LMA was weakly correlated with RFIp (0.17) and FCR (-0.19), but not with PEG or RFIc. The Spearman rank correlation between RFIp and RFIc was high (0.91). Meal duration (0.41), head-down duration (0.38), and meal frequency (0.26) were correlated with RFIp and accounted for 35% of the variation in DMI not explained by MBW, ADG, and ultrasound traits (RFIc). These results suggest that adjusting residual feed intake for carcass composition will facilitate selection to reduce feed intake in cattle without affecting rate or composition of gain.

Repeatability of feed efficiency, carcass ultrasound, feeding behavior, and blood metabolic variables in finishing heifers divergently selected for residual feed intake

This study examined the relationship between feed efficiency and performance, and feeding behavior, blood metabolic variables, and various ultrasonic measurements in finishing beef heifers. Within-animal repeatability estimates of feed intake and behavior, performance, feed efficiency, ultrasonic body measures, and plasma analytes across the growing and finishing stages of the lifespan of the animal were also calculated. Fifty heifers previously ranked as yearlings on phenotypic residual feed intake (RFI) were used. Animals [initial BW = 418 (SD = 31.5) kg] were offered a TMR diet consisting of 70:30 concentrate and corn silage on a DM basis (ME 10.7 MJ/kg of DM; DM 530 g/kg) for 84 d. Feeding duration (min/d) and feeding frequency (events/d) were calculated for each animal on a daily basis using a computerized feeding system. Ultrasonic kidney fat and lumbar and rump fat and muscle depths were recorded on 3 equally spaced occasions during the experimental period. Blood samples were collected by jugular venipuncture on 4 occasions during the experimental period and analyzed for plasma concentrations of IGF-I, insulin, and various metabolites. Phenotypic RFI was calculated for all animals as the residuals from a regression model regressing DMI on ADG and midtest BW(0.75). Repeatability was calculated for several traits both within and between production phase using intraclass correlation and Pearson correlation coefficients as appropriate. Overall ADG, DMI, G:F, and RFI were 1.17 kg/d (SD = 0.19), 10.81 kg/d (SD = 1.02), 0.11 kg of BW gain/kg of DM (SD = 0.02), and 0.00 kg of DM/d (SD 0.59). Daily feeding events and eating rate tended to be positively correlated (P = 0.08) with RFI. Ultrasonic kidney fat depth tended to be related to G:F (r = -0.28; P = 0.07), and kidney fat accretion tended to be related to RFI (r = 0.29; P = 0.08). Plasma urea (r = 0.38; P < 0.01), β-hydroxybutyrate (r = 0.40; P < 0.01), and insulin (r = 0.23; P = 0.07) concentrations were correlated with RFI. Plasma glucose (r = -0.25; P = 0.07), glucose:insulin (r = 0.33; P < 0.05), and insulin (r = -0.30; P < 0.05) were associated with G:F. However, systemic IGF-I was unrelated (P > 0.10) to any measure of feed efficiency. Repeatability estimates within the finishing period for DMI, feeding duration, feeding events, feed intake/feeding event, and eating rate were 0.34, 0.37, 0.60, 0.62, and 0.56, respectively. Repeatability estimates (P < 0.001) between the growing and finishing phases for DMI, G:F, and RFI were r = 0.61, r = 0.37, and r = 0.62, respectively. Moderate to strong repeatability values (ranging from r = 0.40 to 0.76; P < 0.001) were obtained for feeding behavior traits between the yearling and finishing phases. We conclude that RFI and feeding behavior are repeatable traits and that some plasma analytes may be potential indicators of RFI in beef cattle.

Phenotypic and genetic relationships of residual feed intake with performance and ultrasound carcass traits in Brangus heifers.

The objective of this study was to characterize residual feed intake (RFI) and to estimate phenotypic and genetic correlations with performance and ultrasound carcass traits in growing heifers. Four postweaning feed efficiency trials were conducted using 468 Brangus heifers. The complete Brangus pedigree file from Camp Cooley Ranch (Franklin, TX), which included 31,215 animals, was used to generate genetic parameter estimates. The heifer progeny from 223 dams were sired by 36 bulls, whereas the complete pedigree file contained 1,710 sires and 8,191 dams. Heifers were individually fed a roughage-based diet (ME = 1.98 Mcal/kg of DM) using Calan gate feeders for 70 d. Heifer BW was recorded weekly and ultrasound measures of 12th- to 13th-rib fat thickness (BF) and LM area (LMA) obtained at d 0 and 70. Residual feed intake (RFIp) was computed as actual minus predicted DMI, with predicted DMI determined by linear regression of DMI on mid-test BW(0.75) (MBW) and ADG with trial, trial x MBW, and trial x ADG as random effects. Overall means for ADG, DMI, and RFI were 1.01 (SD = 0.15), 9.51 (SD = 1.02), and 0.00 (SD = 0.71) kg/d, respectively. Stepwise regression analysis revealed that inclusion of gain in BF and final LMA into the base model increased the R(2) (0.578 vs. 0.534) and accounted for 9% of the variation in DMI not explained by MBW and ADG (RFIp). Residual feed intake and carcass-adjusted RFI (RFIc) were strongly correlated phenotypically and genetically with DMI and FCR, but not with ADG or MBW. Gain in BF was phenotypically correlated (P < 0.05) with RFIp (0.22), but not with FCR or RFIc; however, final BF was genetically correlated (P < 0.05) with RFIp (0.36) and RFIc (0.39). Gain in LMA was weakly phenotypically correlated with FCR, but not with RFIp or RFIc; however, gain in LMA was strongly genetically correlated with RFIp (0.55) and RFIc (0.77). The Spearman rank correlation between RFIp and RFIc was high (0.96). These results suggest that adjusting RFI for ultrasound carcass composition traits will facilitate selection phenotypically independent of growth, body size, and carcass composition; however, genetic relationships may still exist between RFI and carcass composition.

Grass silage intake, rumen and blood variables, ultrasonic and body measurements, feeding behavior, and activity in pregnant beef heifers differing in phenotypic residual feed intake.

The objectives of this study were to quantify the phenotypic variation in residual feed intake (RFI) in pregnant beef heifers offered a grass silage diet and to characterize their productivity. Seventy-three pregnant (mean gestation d 198, SD = 27 d) Simmental and Simmental × Holstein-Friesian heifers (mean initial BW 548, SD = 47.5 kg) were offered grass silage ad libitum. Heifer DMI, BW, BCS, skeletal measurements, ultrasonic fat and muscle depth, visual muscularity score, rumen fermentation, total tract digestibility, blood metabolite and hematology variables, feeding, and activity behavior were measured during an 84-d feed intake study. After parturition calf birth weight, calving difficulty, cow serum IgG, hematology variables, and calf humoral immune status were measured. In a subset of cows (n = 28), DMI, milk yield and various body composition variables were also measured approximately 3 wk postpartum. Phenotypic RFI was calculated for each animal as the difference between actual DMI and expected DMI. Expected DMI was computed for each animal by regressing average daily DMI on conceptus-adjusted mean BW(0.75) and conceptus-adjusted ADG over an 84-d period. Within breed, heifers were ranked by RFI into low (efficient), medium, and high (inefficient) groups by dividing them into thirds. Heifers with high RFI had 8.8 and 17.1% greater (P < 0.001) DMI than medium and low RFI groups, respectively. The RFI groups did not differ in ADG or BW (P > 0.05). Residual feed intake was positively correlated with DMI (r = 0.85) but not with feed conversion ratio, ADG, or BW. The RFI groups did not differ (P > 0.05) in skeletal size, BCS, ultrasonic fat depth, total tract digestibility, calf birth weight, calving difficulty, serum IgG concentrations, or milk yield. Visual muscularity scores, initial test and postpartum ultrasonic muscle depth were negatively correlated with RFI (P < 0.05). Including mean ultrasonic muscle depth into the base RFI regression model increased its R(2) (0.29 to 0.38). Pearson rank correlation between RFI and muscle-adjusted RFI was 0.93. The results show that efficient RFI heifers consumed less feed without any compromise in growth, body composition, or maternal traits measured.

Genetic relationships between feed efficiency in growing males and beef cow performance

Most studies on feed efficiency in beef cattle have focused on performance in young animals despite the contribution of the cow herd to overall profitability of beef production systems. The objective of this study was to quantify, using a large data set, the genetic covariances between feed efficiency in growing animals measured in a performance-test station, and beef cow performance including fertility, survival, calving traits, BW, maternal weaning weight, cow price, and cull cow carcass characteristics in commercial herds. Feed efficiency data were available on 2,605 purebred bulls from 1 test station. Records on cow performance were available on up to 94,936 crossbred beef cows. Genetic covariances were estimated using animal and animal-dam linear mixed models. Results showed that selection for feed efficiency, defined as feed conversion ratio (FCR) or residual BW gain (RG), improved maternal weaning weight as evidenced by the respective genetic correlations of -0.61 and 0.57. Despite residual feed intake (RFI) being phenotypically independent of BW, a negative genetic correlation existed between RFI and cow BW (-0.23; although the SE of 0.31 was large). None of the feed efficiency traits were correlated with fertility, calving difficulty, or perinatal mortality. However, genetic correlations estimated between age at first calving and FCR (-0.55 ± 0.14), Kleiber ratio (0.33 ± 0.15), RFI (-0.29 ± 0.14), residual BW gain (0.36 ± 0.15), and relative growth rate (0.37 ± 0.15) all suggest that selection for improved efficiency may delay the age at first calving, and we speculate, using information from other studies, that this may be due to a delay in the onset of puberty. Results from this study, based on the estimated genetic correlations, suggest that selection for improved feed efficiency will have no deleterious effect on cow performance traits with the exception of delaying the age at first calving.

Accuracy of predicting genomic breeding values for residual feed intake in Angus and Charolais beef cattle.

In beef cattle, phenotypic data that are difficult and/or costly to measure, such as feed efficiency, and DNA marker genotypes are usually available on a small number of animals of different breeds or populations. To achieve a maximal accuracy of genomic prediction using the phenotype and genotype data, strategies for forming a training population to predict genomic breeding values (GEBV) of the selection candidates need to be evaluated. In this study, we examined the accuracy of predicting GEBV for residual feed intake (RFI) based on 522 Angus and 395 Charolais steers genotyped on SNP with the Illumina Bovine SNP50 Beadchip for 3 training population forming strategies: within breed, across breed, and by pooling data from the 2 breeds (i.e., combined). Two other scenarios with the training and validation data split by birth year and by sire family within a breed were also investigated to assess the impact of genetic relationships on the accuracy of genomic prediction. Three statistical methods including the best linear unbiased prediction with the relationship matrix defined based on the pedigree (PBLUP), based on the SNP genotypes (GBLUP), and a Bayesian method (BayesB) were used to predict the GEBV. The results showed that the accuracy of the GEBV prediction was the highest when the prediction was within breed and when the validation population had greater genetic relationships with the training population, with a maximum of 0.58 for Angus and 0.64 for Charolais. The within-breed prediction accuracies dropped to 0.29 and 0.38, respectively, when the validation populations had a minimal pedigree link with the training population. When the training population of a different breed was used to predict the GEBV of the validation population, that is, across-breed genomic prediction, the accuracies were further reduced to 0.10 to 0.22, depending on the prediction method used. Pooling data from the 2 breeds to form the training population resulted in accuracies increased to 0.31 and 0.43, respectively, for the Angus and Charolais validation populations. The results suggested that the genetic relationship of selection candidates with the training population has a greater impact on the accuracy of GEBV using the Illumina Bovine SNP50 Beadchip. Pooling data from different breeds to form the training population will improve the accuracy of across breed genomic prediction for RFI in beef cattle.

Relationship between feeding behavior and performance of feedlot steers fed barley-based diets

The relationship between feeding behavior and performance of 274 feedlot cattle was evaluated using Charolais cross steers from 2 consecutive years averaging 293 ± 41 kg for yr 1 (n = 115) and 349 ± 41 for yr 2 (n = 159). Steers were blocked by BW and assigned to 3 (yr 1) or 4 (yr 2) feedlot pens equipped with a radio frequency identification system (GrowSafe Systems). Each pen contained 5 feeding stalls that allowed individual animal access to a feed tub suspended on load cells. The system recorded animal identification, duration, and frequency of feedings as well as the amount of feed consumed during each visit. Daily variation in DMI (DVI), calculated as the absolute difference in DMI from one day to the next, as well as eating rate were determined for each steer. Barley-based diets were delivered to meet steer ad libitum intake over the 213- and 181-d feeding periods for yr 1 and 2 of the study, respectively. The backgrounding periods included the first 85 and 56 d of yr 1 and 2, respectively, in which steers were fed a 14 to 30% concentrate diet, whereas the finishing periods included the last 116 and 101 d of feeding in yr 1 and 2, respectively, with the diet consisting of 77.9% concentrate. Steers were weighed individually every 14 d. To relate feeding behavior to performance, steers were grouped by ADG and G:F and categorized as high, average, or low (based on 1 SD greater than and less than the mean). In the backgrounding and finishing periods of both years of the study, steers classified as having high ADG exhibited greater (P < 0.001) DVI than steers classified as having average or low ADG. Total daily DMI was also greater (P < 0.001) for steers in the high ADG group than those in the low ADG group. Overall, those steers with the greatest G:F also tended (P = 0.15) to have greater DVI than average or low G:F steers. Compared with average or low G:F steers, DMI by high G:F steers in both years of the study was less during backgrounding, finishing, and overall (P = 0.02). Bunk visits and bunk attendance duration were less frequent and shorter (P ≤ 0.01) overall for high compared with low G:F steers. In this study, steers with more variable eating patterns exhibited greater ADG and tended to have greater G:F, a finding that is contrary to industry perception.

Genetic parameters for calving ease, gestation length, and birth weight in Charolais cattle.

In this study, a 3-trait linear model was used to obtain genetic parameters for direct and maternal components of calving ease (CE), gestation length (GEST), and birth weight (BWT). Calving ease scores were transformed into Snell scores and expressed as percent unassisted calving (SC), ranging from 0 to 100% (least to greatest ease). A total of 40,420 records (n = 14,403 for CE) were obtained from the Canadian Charolais Association field database. The animal model included fixed effects of contemporary group (herd x year of birth combinations), age of heifer, and sex of calf (only for CE), whereas random effects included direct and maternal genetic effects, residual error, and permanent environmental effects (for CE). The BWT and GEST were preadjusted for age of dam and sex of calf effects. Variance components were estimated using REML. Mean SC was 83.31% (SD = 23.30) and ranged from 3.44 to 100%. Mean BWT was 46.54 kg (SD = 4.79), whereas mean GEST was 286.48 d (SD = 4.93). Direct heritability estimates for SC, BWT, and GEST were 0.14 +/- 0.02, 0.46 +/- 0.03, and 0.62 +/- 0.04, respectively, and maternal heritability estimates were 0.06 +/- 0.02, 0.14 +/- 0.02, and 0.10 +/- 0.02, respectively. The permanent environmental effect as a proportion of SC phenotypic variance was 0.35 +/- 0.11, indicating a large influence on CE. Genetic correlations of direct SC with direct BWT and GEST were -0.93 +/- 0.04 and -0.38 +/- 0.08, respectively, whereas maternal correlations were -0.69 +/- 0.14 and -0.49 +/- 0.17, respectively, illustrating the importance of including both traits in CE evaluations. Within trait direct x maternal genetic correlations were substantial and negative. Regression of average direct and average maternal EBV on year of birth yielded significant genetic trends for the direct effects of BWT, GEST, and CE, whereas no trends were detected for maternal effects. Even though CE is routinely analyzed, no study has evaluated transformed CE scores with 2 correlated traits. In these data, the large negative genetic correlation between BWT and CE suggests that increasing SC would also decrease BWT. Genetic improvement programs, therefore, should consider both CE and growth.