Genetic and phenotypic parameter estimates for feed intake and other traits in growing beef cattle, and opportunities for selection

Growth, feed intake, and temperament indicator data, collected over 5 yr on a total of 1,141 to 1,183 mixed-breed steers, were used to estimate genetic and phenotypic parameters. All steers had a portion of Hereford, Angus, or both as well as varying percentages of Simmental, Charolais, Limousin, Gelbvieh, Red Angus, and MARC III composite. Because the steers were slaughtered on various dates each year and the animals thus varied in days on feed, BW and feed data were adjusted to a 140-d feeding period basis. Adjustment of measures of feed efficiency [G:F or residual feed intake (RFI), intake adjusted for metabolic body size, and BW gain] for body fatness recorded at slaughter had little effect on the results of analyses. Average daily gain was less heritable (0.26) than was midtest BW (MBW; 0.35). Measures of feed intake had greater estimates of heritability, with 140-d DMI at 0.40 and RFI at 0.52; the heritability estimate for G:F was 0.27. Flight speed (FS), as an indicator of temperament, had an estimated heritability of 0.34 and a repeatability of 0.63. As expected, a strong genetic (0.86) correlation was estimated between ADG and MBW; genetic correlations were less strong between DMI and ADG or MBW (0.56 and 0.71). Residual feed intake and DMI had a genetic correlation of 0.66. Indexes for phenotypic RFI and genotypically restricted RFI (no correlation with BW gain) were compared with simple economic indexes incorporating feed intake and growth to elucidate expected selection responses under different criteria. In general, few breed differences were detected across the various measurements. Heterosis contributed to greater DMI, RFI, and MBW, but it did not significantly affect ADG, G:F, or FS. Balancing output (growth) with input costs (feed) is needed in practicing selection, and FS would not be recommended as an indicator trait for selection to change feed efficiency. An index including BW gain and RFI produced the best economic outcome.     

快速型黄羽肉鸡饲料利用效率性状的基因组选择研究

旨在探究快速型黄羽肉鸡饲料利用效率性状的遗传参数,评估不同方法所得估计育种值的准确性.本研究以自主培育的快速型黄羽肉鸡E系1923个个体(其中公鸡1199只,母鸡724只)为研究素材,采用"京芯一号"鸡55K SNP芯片进行基因分型.分别利用传统最佳线性无偏预测(BLUP)、基因组最佳线性无偏预测(GBLUP)和一步法...     

Genetic and phenotypic relationships of feed intake and measures of efficiency with growth and carcass merit of beef cattle

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

Residual feed intake of purebred Angus steers: effects on meat quality and palatability

Relationships between residual feed intake (RFI) and other performance variables were determined using 54 purebred Angus steers. Individual feed intake and BW gain were recorded during a 70-d post-weaning period to calculate RFI. After the 70-d post-weaning test, steers were fed a finishing ration to a similar fat thickness (FT), transported to a commercial facility, and slaughtered. A subsample of carcasses (n = 32) was selected to examine the relationships among RFI, meat quality, and palatability. Steers were categorized into high (> 0.5 SD above the mean; n = 16), medium (mid; +/- 0.5 SD from the mean; n = 21), and low (< 0.5 SD below the mean; n = 17) RFI groups. No differences were detected in ADG, initial BW, and d 71 BW among the high, mid, and low RFI steers. Steers from the high RFI group had a greater DMI (P = 0.004) and feed conversion ratio (FCR; DMI:ADG; P = 0.002) compared with the low RFI steers. Residual feed intake was positively correlated with DMI (r = 0.54; P = 0.003) and FCR (r = 0.42; P = 0.002), but not with initial BW, d 71 BW, d 71 ultrasound FT, initial ultrasound LM area, d 71 ultrasound LM area, or ADG. The FCR was positively correlated with initial BW (r = 0.46; P = 0.0005), d 71 BW (r = 0.34; P = 0.01), and DMI (r = 0.40; P = 0.003) and was negatively correlated with ADG (r = -0.65; P = 0.001). There were no differences among RFI groups for HCW, LM area, FT, KPH, USDA yield grade, marbling score, or quality grade. Reflectance color b* scores of steaks from high RFI steers were greater (P = 0.02) than those from low RFI steers. There was no difference between high and low RFI groups for LM calpastatin activity. Warner-Bratzler shear force and sensory panel tenderness and flavor scores of steaks were similar across RFI groups. Steaks from high RFI steers had lower (P = 0.04) off-flavor scores than those from low RFI steers. Cook loss percentages were greater (P = 0.005) for steaks from low RFI steers than for those from mid RFI steers. These data support current views that RFI is independent of ADG, but is correlated with DMI and FCR. Importantly, the data also support the hypothesis that there is no relationship between RFI and beef quality in purebred Angus steers.     

The phenotypic relationship between residual intake and gain and other feed efficiency traits in Nellore cattle

This study aimed to compare feed efficiency measures of Nellore beef cattle on different residual intake and gain (RIG) classes. We used data from 610 animals weighing on average 236.33 kg and average of 283 days of age from feedlot performance tests carried out between 2005 and 2012. Animals were grouped based on RIG into three different classes: high RIG (>?mean?+?0.5 standard deviation (SD), most efficient; n?=?193), medium RIG (mean?±?0.5 SD; n?=?235), and low RIG (<?mean – 0.5 SD, least efficient; n?=?182). Residual feed intake (RFI), residual gain (RG), feed conversion ratio (FCR), feed efficiency (FE), relative growth rate (RGR), and Kleiber ratio (KR) of animals in each RIG class were compared by Tukey test at 1% of probability. Phenotypic correlations between variables were evaluated as well. Animals on high RIG class showed lower dry matter intake (P?<?0.01) and higher average daily gain (P?<?0.01) than low RIG animals. Consequently, high RIG animals had lower FCR (P?<?0.01) and higher FE (P?<?0.01) than those animals in low RIG class. The most efficient animals based on RIG were also the most efficient animals based on RG and RFI. RIG was negatively correlated to dry matter intake (P?<?0.01) and FCR (P?<?0.01), and a positive correlation was found between RIG and FE (P?<?0.01). Therefore, RIG appears to be a good parameter to select animals with reduced dry matter intake and high productive performance.

     

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.     

提高猪饲料效率的测定与选择

为提高猪饲料效率的选择,本试验测定一些与猪饲料效率相关的生产性状并进行遗传评估。方法：测定60头军牧1号白猪后备公猪的采食量、体增重、背膘厚等生产性状,用猪剩余采食量（RFI）和饲料转化率（FCR）作为评价饲料效率的两个指标,并对其遗传参数进行评估。结果：测定期内军牧1号公猪群体FCR均值为2．61,RFI的标准差为77．52。RFI与FCR的遗传力分别是0．35、0．33,RFI与ADFI（日采食量）、ADG（日增重）、BF（背膘厚）的遗传相关分别是0．89、0．12、-0．05,FCR与ADFI、ADG、BF的遗传相关分别是0．55、-0．65、-0．11。结论：军牧1号白猪品种内饲料效率存在较大的遗传差异,由于RFI与ADG遗传相关很低,因此用RFI作为选择性状可有效提高猪的饲料效率。     

Cluster and meta‐analyses of genetic parameters for feed intake traits in growing beef cattle

A data set based on 50 studies including feed intake and utilization traits was used to perform a meta‐analysis to obtain pooled estimates using the variance between studies of genetic parameters for average daily gain (ADG); residual feed intake (RFI); metabolic body weight (MBW); feed conversion ratio (FCR); and daily dry matter intake (DMI) in beef cattle. The total data set included 128 heritability and 122 genetic correlation estimates published in the literature from 1961 to 2012. The meta‐analysis was performed using a random effects model where the restricted maximum likelihood estimator was used to evaluate variances among clusters. Also, a meta‐analysis using the method of cluster analysis was used to group the heritability estimates. Two clusters were obtained for each trait by different variables. It was observed, for all traits, that the heterogeneity of variance was significant between clusters and studies for genetic correlation estimates. The pooled estimates, adding the variance between clusters, for direct heritability estimates for ADG, DMI, RFI, MBW and FCR were 0.32 ± 0.04, 0.39 ± 0.03, 0.31 ± 0.02, 0.31 ± 0.03 and 0.26 ± 0.03, respectively. Pooled genetic correlation estimates ranged from ?0.15 to 0.67 among ADG, DMI, RFI, MBW and FCR. These pooled estimates of genetic parameters could be used to solve genetic prediction equations in populations where data is insufficient for variance component estimation. Cluster analysis is recommended as a statistical procedure to combine results from different studies to account for heterogeneity.     

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two‐trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.     

Genome‐wide association study and genomic evaluation of feed efficiency traits in Japanese Black cattle using single‐step genomic best linear unbiased prediction method

The objectives of this study were to better understand the genetic architecture and the possibility of genomic evaluation for feed efficiency traits by (i) performing genome‐wide association studies (GWAS), and (ii) assessing the accuracy of genomic evaluation for feed efficiency traits, using single‐step genomic best linear unbiased prediction (ssGBLUP)‐based methods. The analyses were performed in residual feed intake (RFI), residual body weight gain (RG), and residual intake and body weight gain (RIG) during three different fattening periods. The phenotypes from 4,578 Japanese Black steers, which were progenies of 362 progeny‐tested bulls and the genotypes from the bulls were used in this study. The results of GWAS showed that a total of 16, 8, and 12 gene ontology terms were related to RFI, RG, and RIG, respectively, and the candidate genes identified in RFI and RG were involved in olfactory transduction and the phosphatidylinositol signaling system, respectively. The realized reliabilities of genomic estimated breeding values were low to moderate in the feed efficiency traits. In conclusion, ssGBLUP‐based method can lead to understand some biological functions related to feed efficiency traits, even with small population with genotypes, however, an alternative strategy will be needed to enhance the reliability of genomic evaluation.     

Genetic parameters for measures of the efficiency of gain of boars and the genetic relationships with its component traits in Duroc pigs

Genetic parameters for the efficiency of gain traits on 380 boars and the genetic relationships with component traits were estimated in 1,642 pigs (380 boars, 868 gilts, and 394 barrows) in 7 generations of a Duroc population. The efficiency of gain traits included the feed conversion ratio (FCR) and residual feed intake (RFI) and their component traits, ADG, metabolic BW (MWT), and daily feed intake (FI). The RFI was calculated as the difference between the actual and expected FI. The expected FI was predicted by the nutritional requirement and by the residual of phenotypic (RFI(phe)) and genetic (RFI(gen)) regressions from the multivariate analysis for FI on MWT and ADG. The means for RFI(phe) and RFI(gen) were close to zero, and the mean for nutritional RFI was negative (-0.11 kg/d). The traits studied were moderately heritable (ranging from 0.27 to 0.53). The genetic and phenotypic correlations between ADG and FI were moderate to high, whereas the genetic correlation between MWT and FI was moderate, and the phenotypic correlation between them was low. The corresponding correlations between RFI(phe) and RFI(gen) were > 0.95, implying that they can be regarded as the same trait. The genetic and phenotypic correlations of FCR with measures of RFI were high but lower than unity. The RFI(phe) was phenotypically independent of its component traits, MWT (r(p) = 0.01) and ADG (r(p) = 0.03). The RFI(gen) was genetically independent of MWT (r(g) = -0.04), whereas there was a weak genetic relationship (r(g) = 0.15) between RFI(gen) and ADG. Residual FI was more heritable than FCR, and the genetic and phenotypic correlations of RFI(phe) and RFI(gen) with FI were positive and stronger than that of FCR with FI. These results provide evidence that RFI(phe) or RFI(gen) should be included in breeding programs for Duroc pigs to make genetic improvement in the efficiency of gain.     

Different measures of energetic efficiency and their phenotypic relationships with growth, feed intake, and ultrasound and carcass merit in hybrid cattle

Residual feed intake (RFI) has been proposed as an index for determining beef cattle energetic efficiency. Although the relationship of RFI with feed conversion ratio (FCR) is well established, little is known about how RFI compares to other measures of efficiency. This study examined the phenotypic relationships among different measures of energetic efficiency with growth, feed intake, and ultrasound and carcass merit of hybrid cattle (n = 150). Dry matter intake, ME intake (MEI), ADG, metabolic weight (MWT), and FCR during the test averaged 10.29 kg/d (SD = 1.62), 1,185.45 kJ/(kg0.75 x d) (SD = 114.69), 1.42 kg/d (SD = 0.25), 86.67 kg0.75 (SD = 10.21), and 7.27 kg of DM/kg of gain (SD = 1.00), respectively. Residual feed intake averaged 0.00 kg/d and ranged from -2.25 kg/d (most efficient) to 2.61 kg/d (least efficient). Dry matter intake (r = 0.75), MEI (r = 0.83), and FCR (r = 0.62) were correlated with RFI (P < 0.001) and were higher for animals with high (>0.5 SD) RFI vs. those with medium (+/-0.5 SD) or low (<0.5 SD) RFI (P < 0.001). Partial efficiency of growth (PEG; energetic efficiency for ADG) was correlated with RFI (r = -0.89, P < 0.001) and was lower (P < 0.001) for high- vs. medium- or low-RFI animals. However, RFI was not related to ADG (r = -0.03), MWT (r = -0.02), relative growth rate (RGR; growth relative to instantaneous body size; r = -0.04), or Kleiber ratio (KR; ADG per unit of MWT; r = -0.004). Also, DMI was correlated (P < 0.01) with ADG (r = 0.66), MWT (r = 0.49), FCR (r = 0.49), PEG (r = -0.52), RGR (r = 0.18), and KR (r = 0.36). Additionally, FCR was correlated (P < 0.001) with ADG (r = -0.63), PEG (r = -0.83), RGR (r = -0.75), and KR (r = -0.73), but not with MWT (r = 0.07). Correlations of measures of efficiency with ultrasound or carcass traits generally were not different from zero except for correlations of RFI, FCR, and PEG, respectively, with backfat gain (r = 0.30, 0.20, and -0.30), ultrasound backfat (r = 0.19, 0.21, and -0.25), grade fat (r = 0.25, 0.19, and -0.27), lean meat yield (r = -0.22, -0.18, and 0.24), and yield grade (r = 0.28, 0.24, and -0.25). These phenotypic relationships indicate that, compared with other measures of energetic efficiency, RFI should have a greater potential to improve overall production efficiency and PEG above maintenance, and lead to minimal correlated changes in carcass merit without altering the growth and body size of different animals.     

The relationship of feeding behavior to residual feed intake in crossbred Angus steers fed traditional and no-roughage diets

Two studies were conducted to determine the relationship of feeding behavior to a phenotypic expression of residual feed intake (RFI), a measure of efficiency. In Exp. 1, a feedlot diet containing roughage was fed (traditional). In Exp. 2, a no-roughage diet was fed. Residual feed intake, a measure of feed efficiency, was calculated for both studies. In Exp. 1, six feed-efficient (low RFI) steers and six feed-inefficient steers (high RFI) were selected from a contemporary group of 80 steers, and feeding behaviors were analyzed. In Exp. 2, nine feed-efficient and eight feed-inefficient steers were selected from a contemporary group of 40 steers. There were no differences (P > 0.13) in initial or final BW or ADG between efficient and inefficient groups in either Exp. 1 or 2. In Exp. 1, DMI and average eating bouts daily differed (P < 0.001), with efficient steers consuming less feed and eating fewer times per day. In Exp. 2, efficient steers consumed less (P < 0.001) feed, and average eating bouts daily tended (P = 0.07) to be fewer in efficient animals. Limited differences were noted in feeding behavior between groups, with inefficient steers from both studies having a more variable eating pattern throughout the day. The average daily eating rate did not differ (P > 0.20) between groups in either experiment. The average number of days comprising a feeding pattern for both efficiency groups in Exp. 1 and 2 was found to be 2 to 3 d and multiples of 2 to 3 d. In Exp. 1, the feed intake pattern of efficient and inefficient steers changed once they reached a BW of approximately 391 and 381 kg, respectively. This occurred near d 47 for the efficient steers and near d 32 for inefficient steers. In Exp. 2, the feed intake pattern of both efficient and inefficient steers changed once they reached a BW of approximately 399 kg, which occurred on d 31 for the efficient steers and on d 33 for the inefficient steers. From the measured variables, there were no differences in growth and limited differences noted in feeding behavior between efficient and inefficient groups. The results of the trials suggest increased variability of feed intake throughout the day for inefficient animals.     

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.     

Selection response and genetic parameters for residual feed intake in Yorkshire swine

Residual feed intake (RFI) is a measure of feed efficiency defined as the difference between the observed feed intake and that predicted from the average requirements for growth and maintenance. The objective of this study was to evaluate the response in a selection experiment consisting of a line selected for low RFI and a random control line and to estimate the genetic parameters for RFI and related production and carcass traits. Beginning with random allocation of purebred Yorkshire littermates, in each generation, electronically measured ADFI, ADG, and ultrasound backfat (BF) were evaluated during a approximately 40- to approximately 115-kg of BW test period on approximately 90 boars from first parity and approximately 90 gilts from second parity sows of the low RFI line. After evaluation of first parity boars, approximately 12 boars and approximately 70 gilts from the low RFI line were selected to produce approximately 50 litters for the next generation. Approximately 30 control line litters were produced by random selection and mating. Selection was on EBV for RFI from an animal model analysis of ADFI, with on-test group and sex (fixed), pen within group and litter (random), and covariates for interactions of on- and off-test BW, on-test age, ADG, and BF with generations. The RFI explained 34% of phenotypic variation in ADFI. After 4 generations of selection, estimates of heritability for RFI, ADFI, ADG, feed efficiency (FE, which is the reciprocal of the feed conversion ratio and equals ADG/ ADFI), and ultrasound-predicted BF, LM area (LMA), and intramuscular fat (IMF) were 0.29, 0.51, 0.42, 0.17, 0.68, 0.57, and 0.28, respectively; predicted responses based on average EBV in the low RFI line were -114, -202, and -39 g/d for RFI (= 0.9 phenotypic SD), ADFI (0.9 SD), and ADG (0.4 SD), respectively, and 1.56% for FE (0.5 SD), -0.37 mm for BF (0.1 SD), 0.35 cm(2) for LMA (0.1 SD), and -0.10% for IMF (0.3 SD). Direct phenotypic comparison of the low RFI and control lines based on 92 low RFI and 76 control gilts from the second parity of generation 4 showed that selection had significantly decreased RFI by 96 g/d (P = 0.002) and ADFI by 165 g/d (P < 0.0001). The low RFI line also had 33 g/d lower ADG (P = 0.022), 1.36% greater FE (P = 0.09), and 1.99 mm less BF (P = 0.013). There was not a significant difference in LMA and other carcass traits, including subjective marbling score, despite a large observed difference in ultrasound-predicted IMF (-1.05% with P < 0.0001). In conclusion, RFI is a heritable trait, and selection for low RFI has significantly decreased the feed required for a given rate of growth and backfat.     

Triennial Lactation Symposium: Opportunities for improving milk production efficiency in dairy cattle

Increasing feed costs and the desire to improve environmental stewardship have stimulated renewed interest in improving feed efficiency of livestock, including that of US dairy herds. For instance, USDA cost projections for corn and soybean meal suggest a 20% increase over 2010 pricing for a 16% protein mixed dairy cow ration in 2011, which may lead to a reduction in cow numbers to maintain profitability of dairy production. Furthermore, an October 2010 study by The Innovation Center for US Dairy to assess the carbon footprint of fluid milk found that the efficiency of feed conversion is the single greatest factor contributing to variation in the carbon footprint because of its effects on methane release during enteric fermentation and from manure. Thus, we are conducting research in contemporary US Holsteins to identify cows most efficient at converting feed to milk in temperate climates using residual feed intake (RFI), a measure used successfully to identify the beef cattle most efficient at converting feed to gain. Residual feed intake is calculated as the difference between predicted and actual feed intake to support maintenance and production (e.g., growth in beef cattle, or milk in dairy cattle). Heritability estimates for RFI in dairy cattle reported in the literature range from 0.01 to 0.38. Selection for a decreased RFI phenotype can reduce feed intake, methane production, nutrient losses in manure, and visceral organ weights substantially in beef cattle. We have estimated RFI during early lactation (i.e., to 90 d in milk) in the Beltsville Agricultural Research Center Holstein herd and observed a mean difference of 3.7 kg/d (P < 0.0001) in actual DMI between the efficient and inefficient groups (±0.5 SD from the mean RFI of 0), with no evidence of differences (P > 0.20) in mean BW, ADG, or energy-corrected milk exhibited between the 2 groups. These results indicate promise for using RFI in dairy cattle to improve feed conversion to milk. Previous and current research on the use of RFI in lactating dairy cattle are discussed, as well as opportunities to improve production efficiency of dairy cattle using RFI for milk production.     

Relationships of feedlot feed efficiency, performance, and feeding behavior with metabolic rate, methane production, and energy partitioning in beef cattle

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

Genetic associations between feed efficiency measured in a performance test station and performance of growing cattle in commercial beef herds

Interest in selection for improved feed efficiency is increasing, but before any steps are taken toward selecting for feed efficiency, correlations with other economically important traits must first be quantified. The objective of this study was to quantify the genetic associations between feed efficiency measured during performance testing and linear type traits, BW, live animal value, and carcass traits recorded in commercial herds. Feed efficiency data were available on 2,605 bulls from 1 performance test station. There were between 10,384 and 93,442 performance records on type traits, BW, animal value, or carcass traits from 17,225 commercial herds. (Co)variance components were estimated using linear mixed animal models. Genetic correlations between the muscular type traits in commercial animals and feed conversion ratio (-0.33 to -0.25), residual feed intake (RFI; -0.33 to -0.22), and residual BW gain (RG; 0.24 to 0.27) suggest that selection for improved feed efficiency should increase muscling. This is further evidenced by the genetic correlations between carcass conformation of commercial animals and feed conversion ratio (-0.46), RFI (-0.37), and residual BW gain (0.35) measured in performance-tested animals. Furthermore, the genetic correlations between RFI and both ultrasonic fat depth and carcass fat score (0.39 and 0.33, respectively) indicated that selection for improved RFI will result in leaner animals. It can be concluded from the genetic correlations estimated in this study that selection for feed efficiency will have no unfavorable effects on the performance traits measured in this study and will actually lead to an improvement in performance for some traits, such as muscularity, animal price, and carcass conformation. Conversely, this suggests that genetic selection for traits such as carcass quality, muscling traits, and animal value might also be indirectly selecting for more efficient animals.     

Genetic parameters for residual feed intake in growing pigs, with emphasis on genetic relationships with carcass and meat quality traits

Data were collected over the first 4 generations of a divergent selection experiment for residual feed intake of Large White pigs having ad libitum access to feed. This data set was used to obtain estimates of heritability for residual feed intake and genetic correlations (r(a)) between this trait and growth, carcass, and meat quality traits. Individual feed intake of group-housed animals was measured by single-space electronic feeders. Upward and downward selection lines were maintained contemporarily, with 6 boars and 35 to 40 sows per line and generation. Numbers of records were 793 for residual feed intake (RFI1) of boar candidates for selection issued from first-parity (P1) litters and tested over a fixed BW range (35 to 95 kg) and 657 for residual feed intake (RFI2) and growth, carcass, and meat quality traits of castrated males and females issued from second-parity (P2) litters and tested from 28 to 107 kg of BW. Variance and covariance components were estimated using REML methodology applied to a series of multitrait animal models, which always included the criterion for selection as 1 of the traits. Estimates of heritability for RFI1 and RFI2 were 0.14 +/- 0.03 and 0.24 +/- 0.03, respectively, whereas the estimate of r(a) between the 2 traits was 0.91 +/- 0.08. Estimates of r(a) indicated that selection for low residual feed intake has the potential to improve feed conversion ratio and reduce daily feed intake, with minimal correlated effect for ADG of P2 animals. Estimates of r(a) between RFI2 and body composition traits of P2 animals were positive for traits related to the amount of fat depots (r(a) = 0.44 +/- 0.16 for carcass backfat thickness) and negative for carcass lean meat content (r(a) = -0.55 +/- 0.14). There was a tendency for a negative genetic correlation between RFI2 and carcass dressing percent (r(a) = -0.36 +/- 0.21). Moreover, selection for low residual feed intake is expected, through lower ultimate pH and lighter color, to decrease pork quality (r(a) = 0.77 +/- 0.14 between RFI2 and a meat quality index intended to predict the ratio of the weight of ham after curing and cooking to the weight of defatted and boneless fresh ham).