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1.
Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle.  相似文献   

2.
Genetic parameters for carcass traits of 1774 field progeny (1281 steers and 493 heifers), and their genetic relationships with feed efficiency traits of their sire population (740 bulls) were estimated with REML. Feed efficiency traits included feed conversion ratio (FCR) and residual feed intake (RFI). RFI was calculated by the residual of phenotypic (RFIphe) and genetic (RFIgen) regression from the multivariate analysis of feed intake on metabolic weight and daily gain. Progeny traits were carcass weight (CWT), rib eye area (REA), rib thickness (RBT), subcutaneous fat, yield estimate (YEM), marbling score (MSR), meat quality grade, meat color, fat color, meat firmness and meat texture. The estimated heritability for CWT (0.70) was high and heritabilities for all the other traits were moderate (ranged from 0.32 to 0.47), except for meat and fat color and meat texture which were low (ranged from 0.02 to 0.25). The high genetic correlation (0.62) between YEM and MSR suggests that simultaneous improvement of high carcass yield and beef marbling is possible. Estimated genetic correlations of RFI (RFIphe and RFIgen) of sires with CWT (− 0.60 and − 0.53) and MSR (− 0.62 and − 0.50) of their progeny were favorably negative indicating that the selection against RFI of sires may have contributed to produce heavier carcass and increase in beef marbling. The correlated responses in CWT, REA and RBT of progeny were higher to selection against RFI than those to selection against FCR of sires. This study provides evidence that selection against RFI is preferred over selection against FCR in sire population for getting better correlated responses in carcass traits of their progeny.  相似文献   

3.
Because feed is the major input in pork production, conversion of feed into lean tissue at minimum costs has been a focus for improvement. Several researchers have proposed using residual feed intake (RFI) rather than feed conversion ratio (FCR) for genetic improvement of feed efficiency. Little is known about the variation in RFI in pigs. As several studies suggest a greater RFI is related to greater animal activity levels, the current study investigated the phenotypic relationship between RFI and feed intake (FI) behavior of 104 group-housed growing Duroc barrows allowed ad libitum access to feed. Feed intake, BW gain, feeding time (TIME), feeding frequency (VISITS), RFI, and FCR were calculated for 5 periods of 14, 23, 28, 21, or 23 d in length (periods 1 through 5, respectively) on animals that were between 73 to 95 d of age at the start of the testing period. Barrows that grew faster consumed more feed (P < 0.001), and barrows that consumed more feed were fatter (P < 0.01). There were no correlations between VISITS and TIME, between VISITS and FI, or between VISITS and RFI. Barrows that spent more time at the feeder, however, consumed more feed (P < 0.05) and had greater RFI in periods 1, 3, and 5 (P < 0.05). As expected, FI and FCR were highly correlated with RFI (P < 0.001). These results suggest that a greater FI rather than greater feed intake activity resulted in greater RFI values.  相似文献   

4.
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.  相似文献   

5.
Genetic parameters for feed efficiency traits of 380 boars and growth and carcass traits of 1642 pigs (380 boars, 868 gilts and 394 barrows) in seven generations of Duroc population were estimated. Feed efficiency traits included the feed conversion ratio (FCR), and nutritional (RFI(nut)), phenotypic (RFI(phe)) and genetic (RFI(gen)) residual feed intake. Growth and carcass traits were the age to reach 105-kg body weight (A105), loin eye muscle area (EMA), backfat (BF), intra-muscular fat (IMF) and meat tenderness. The mean values for RFI(phe) and RFI(gen) were close to zero and for RFI(nut) was negative. All the measures of feed efficiency were moderately heritable (h(2) = 0.31, 0.38, 0.40 and 0.27 for RFI(nut), RFI(phe), RFI(gen) and FCR respectively). The heritabilities for all growth and carcass traits were moderate (ranged from 0.37 to 0.45), except for BF, which was high (0.72). The genetic correlations of RFI(phe) and RFI(gen) with A105 were positive and high. Measures of RFI were correlated negatively with EMA. BF was more strongly correlated with measures of RFI (r(g) > or = 0.73) than with FCR (r(g) = 0.52). Selection for daily gain, EMA, BF and IMF caused favourable genetic changes in feed efficiency traits. Results of this study indicate that selection against either RFI(phe) or RFI(gen) would give a similar correlated response in carcass traits.  相似文献   

6.
We report the identification and fine mapping of QTL for birth weight (BWT), preweaning ADG (PWADG), and postweaning ADG on feed (ADGF) in a commercial line of Bos taurus using an identical-by-descent haplotype sharing method. One hundred seventy-six calves of 12 bulls (9 to 30 male calves from each sire) of the Beefbooster, Inc., M1 line were typed using 71 genetic markers from bovine chromosomes (BTA) 2, 6, 14, 19, 21, and 23 (8 to 16 markers from each chromosome). Sixteen haplotypes were found to have significant (P <0.05) associations with BWT at the comparison-wise threshold. The 16 haplotypes span 13 chromosomal regions, two on BTA 2 (9.1 to 22.5 cM and 95.0 to 100.3 cM), three on BTA 6 (8.2 to 11.8 cM, 35.5 to 49.7 cM, and 83.0 to 86.2 cM), three on BTA 14 (26.0 to 26.7 cM, 36.2 to 46.2 cM, and 52.0 to 67.7 cM), one on BTA 19 (52.0 to 52.7 cM), two on BTA 21 (9.9 to 20.4 cM and 28.2 to 46.1 cM), and two on BTA 23 (23.9 to 36.0 cM and 45.1 to 50.9 cM). Thirteen haplotypes spanning seven chromosomal regions significantly affected (P <0.05) PWADG at the comparison-wise threshold. The seven chromosomal regions include two regions on BTA 6 (11.8 to 44.2 cM and 83.0 to 86.2 cM), one on BTA 14 (26.7 to 50.8 cM), one on BTA 19 (4.8 to 15.9 cM), one on BTA 21 (9.9 to 20.4 cM), and two on BTA 23 (17.3 to 36.0 cM and 45.1 to 50.9 cM). For ADGF, 11 haplotypes were identified to have significant associations (P <0.05) at the comparison-wise threshold. The 11 haplotypes represented eight chromosomal regions, one on BTA 2 (9.1 to 22.5 cM), two on BTA 6 (49.7 to 50.1 cM and 59.6 to 63.6 cM), two on BTA 14 (17.0 to 24.0 cM and 36.2 to 46.2 cM), two on BTA 19 (52.0 to 52.7 cM and 65.1 to 65.7 cM), and one on BTA 21 (46.1 to 53.1 cM). The QTL regions identified and fine mapped in this study will provide a reference for future positional candidate gene research and marker-assisted selection of various growth traits.  相似文献   

7.
We used a half-sib family of purebred Japanese Black (Wagyu) cattle to locate economically important quantitative trait loci. The family was composed of 348 fattened steers, 236 of which were genotyped for 342 microsatellite markers spanning 2,664 cM of 29 bovine autosomes. The genome scan revealed evidence of 15 significant QTL (<5% chromosome-wise level) affecting growth and carcass traits. Of the 15 QTL, six QTL were significant at the 5% experiment-wise level and were located in bovine chromosomes (BTA) 4, 5, and 14. We analyzed these three chromosomes in more detail in the 348 steers, with an average marker interval of 1.2 cM. The second scan revealed that the same haplotype of the BTA 4 region (52 to 67 cM) positively affected LM area and marbling. We confirmed the QTL for carcass yield estimate on BTA 5 in the region of 45 to 54 cM. Five growth-related QTL located on BTA 14, including slaughter and carcass weights, were positively affected by the same region of the haplotype of BTA 14 (29-51 cM). These data should provide a useful reference for further marker-assisted selection in the family and positional cloning research. The research indicates that progeny design with moderate genotyping efforts is a powerful method for detecting QTL in a purebred half-sib family.  相似文献   

8.
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.  相似文献   

9.
Records on 514 bulls from the sire population born from 1978 to 2004, and on 22,099 of their field progeny born from 1997 to 2003 with available pedigree information (total number = 124,458) were used to estimate genetic parameters for feed intake and energy efficiency traits of bulls and their relationships with carcass traits of field progeny. Feed intake and energetic efficiency traits were daily feed intake, TDN intake, feed conversion ratio (FCR), TDN conversion ratio (TDNCR), residual feed intake (RFI), partial efficiency of growth, relative growth rate, and Kleiber ratio. Progeny carcass traits were carcass weight (CWT), yield estimate, ribeye area, rib thickness, subcutaneous fat thickness (SFT), marbling score (MSR), meat color standard (MCS), fat color standard (FCS), and meat quality grade. All measures of feed intake and energetic efficiency were moderately heritable (ranged from 0.24 to 0.49), except for partial efficiency of growth and relative growth rate, which were high (0.58) and low (0.14), respectively. The phenotypic and genetic correlations between FCR and TDNCR were >or=0.93. Selection for Kleiber ratio will improve all of the energetic efficiency traits with no effect on feed intake measures (daily feed intake and TDN intake). The genetic correlations of FCR, TDNCR, and RFI of bulls with most of the carcass traits of their field progeny were favorable (ranged from -0.24 to -0.72), except with fat color standard (no correlation), MCS, and SFT. Positive (unfavorable) genetic correlations of MCS with FCR, TDNCR, and RFI (0.79, 0.70, and 0.51, respectively) were found. The SFT was negatively genetically correlated with FCR and TDNCR (-0.32 and -0.20, respectively); however, the genetic correlation between RFI and SFT was not significantly different from zero (r(g) = -0.08 +/- 0.12). Favorable correlated responses in CWT, yield estimate, ribeye area, rib thickness, MSR, and meat quality grade would be predicted for selection against any measure of energetic efficiency. The correlated responses in CWT and MSR of progeny were greater for selection against RFI than for selection against any other energetic efficiency trait. Results of this study indicate that RFI should be preferred over other measures of energetic efficiency to include in selection programs.  相似文献   

10.
Pigs from the F(2) generation of a Duroc x Pietrain resource population were evaluated to discover QTL affecting growth and composition traits. Body weight and ultrasound estimates of 10th-rib backfat, last-rib backfat, and LM area were serially measured throughout development. Estimates of fat-free total lean, total body fat, empty body protein, empty body lipid, and ADG from 10 to 22 wk of age were calculated, and random regression analyses were performed to estimate individual animal phenotypes representing intercept and linear rates of increase in these serial traits. A total of 510 F(2) animals were genotyped for 124 micro-satellite markers evenly spaced across the genome. Data were analyzed with line cross, least squares regression, interval mapping methods using sex and litter as fixed effects. Significance thresholds of the F-statistic for single QTL with additive, dominance, or imprinted effects were determined at the chromosome- and genome-wise levels by permutation tests. A total of 43 QTL for 22 of the 29 measured traits were found to be significant at the 5% chromosome-wise level. Of these 43 QTL, 20 were significant at the 1% chromosome-wise significance threshold, 14 of these 20 were also significant at the 5% genome-wise significance threshold, and 10 of these 14 were also significant at the 1% genome-wise significance threshold. A total of 22 QTL for the animal random regression terms were found to be significant at the 5% chromosome-wise level. Of these 22 QTL, 6 were significant at the 1% chromosome-wise significance threshold, 4 of these 6 were also significant at the 5% genome-wise significance threshold, and 3 of these 4 were also significant at the 1% genome-wise significance threshold. Putative QTL were discovered for 10th-rib and last-rib backfat on SSC 6, body composition traits on SSC 9, backfat and lipid composition traits on SSC 11, 10th-rib backfat and total body fat tissue on SSC 12, and linear regression of last-rib backfat and total body fat tissue on SSC 8. These results will facilitate fine-mapping efforts to identify genes controlling growth and body composition of pigs that can be incorporated into marker-assisted selection programs to accelerate genetic improvement in pig populations.  相似文献   

11.
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.  相似文献   

12.
Background: The feed conversion ratio(FCR) and residual feed intake(RFI) are common indexes in measuring feed efficiency for livestock. RFI is a feed intake adjusted for requirements for maintenance and production so these two traits are related. Similarly, FCR is related to feed intake and weight gain because it is their ratio. Cholecystokinin type A receptor(CCKAR) plays an important role in animal digestive process. We examined the interplay of these three parameters in a local Chinese chicken population.Results: The feed intake(FI) and body weights(BW) of 1,841 individuals were monitored on a daily basis from 56 to 105 d of age. There was a strong correlation between RFI and average daily feed intake(ADFI) and a negative correlation between the FCR and daily gain(r_g=-0.710). Furthermore, we identified 51 single nucleotide polymorphisms(SNPs) in the CCKAR and 4 of these resulted in amino acid mutations. The C334A mutation was specifically associated with FI and the expected feed intake(EFI)(P 0.01) and significantly associated with the average daily gain(ADG)(P 0.05). G1290A was significantly associated with FI and EFI(P 0.05).Conclusion: FCR is apply to weight selecting, and RFI is more appropriate if the breeding focus is feed intake. And C334A and G1290A of the CCKAR gene can be deemed as candidate markers for feed intake and weight gain.  相似文献   

13.
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.  相似文献   

14.
Residual feed intake (RFI) is a measure of feed efficiency defined as the difference between observed and predicted feed intake based on average requirements for growth and maintenance. The objective of this study was to evaluate the effect of selection for decreased RFI on feeding behavior traits and to estimate their relationships with RFI. Three data sets from the 4th and 5th generations of a selection experiment with a line selected for reduced RFI (LRFI) and a randomly selected control line (CTRL) were analyzed. Lines were mixed in pens of 16 and evaluated for feeding behavior traits obtained from a single-space electronic feeder over a growing period of ~3 mo before ~115 kg. The following traits were evaluated as averages over the entire test period and over the first and second half of the test period: number of visits per day and hour; occupation time per day, visit, and hour; feed intake (FI) per day, visit, and hour; and FI rate per visit. Models used included fixed effects of line and feeder, covariates of on-test age and FI per day, and random effects of pen, on-test group, sire, and litter. Repeated measures models were used to analyze feeding patterns during the day. The LRFI pigs had significantly less FI per day than CTRL pigs for all 3 data sets. With adjustment for FI per day, line differences of all traits were in the same direction for all 3 data sets but differed in significance and size. Feed intake per visit and hour and visits per day and hour did not differ between lines, but the trend was for LRFI pigs to have fewer visits, in particular during peak eating times. The LRFI pigs had a greater feeding rate and less occupation time per day, visit, and hour than CTRL pigs, but this was not significant for all data sets. Correlations of RFI with FI per day and visit and visits per day were positive. Average daily gain was positively correlated with FI per day and visit and occupation time per visit but negatively correlated with visits per day. Feed intake per day was positively correlated with backfat. In conclusion, feed efficiency may be affected by FI behavior because selection for decreased RFI has resulted in pigs that spend less time eating and eat faster.  相似文献   

15.
提高猪饲料效率的测定与选择   总被引：1，自引：0，他引：1  
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。  相似文献   

16.
Feeding behavior and temperament may be useful in genetic evaluations either as indicator traits for other economically relevant traits or because the behavior traits may have a direct economic value. We determined the variation in feeding behavior and temperament of beef cattle sired by Angus, Charolais, or Hybrid bulls and evaluated their associations with performance, efficiency, and carcass merit. The behavior traits were daily feeding duration, feeding head down (HD) time, feeding frequency (FF), and flight speed (FS, as a measure of temperament). A pedigree file of 813 animals forming 28 paternal half-sib families with about 20 progeny per sire was used. Performance, feeding behavior, and efficiency records were available on 464 animals of which 381 and 302 had records on carcass merit and flight speed, respectively. Large SE reflect the number of animals used. Direct heritability estimates were 0.28 +/- 0.12 for feeding duration, 0.33 +/- 0.12 for HD, 0.38 +/- 0.13 for FF, and 0.49 +/- 0.18 for FS. Feeding duration had a weak positive genetic (r(g)) correlation with HD (r(g) = 0.25 +/- 0.32) and FS (r(g) = 0.42 +/- 0.26) but a moderate negative genetic correlation with FF (r(g) = -0.40 +/- 0.30). Feeding duration had positive phenotypic (r(p)) and genetic correlations with DMI (r(p) = 0.27; r(g) = 0.56 +/- 0.20) and residual feed intake (RFI; r(p) = 0.49; r(g) = 0.57 +/- 0.28) but was unrelated phenotypically with feed conversion ratio [FCR; which is the reciprocal of the efficiency of growth (G:F)]. Feeding duration was negatively correlated with FCR (r(g) = -0.25 +/- 0.29). Feeding frequency had a moderate to high negative genetic correlation with DMI (r(g) = -0.74 +/- 0.15), FCR (r(g) = -0.52 +/- 0.21), and RFI (r(g) = -0.77 +/- 0.21). Flight speed was negatively correlated phenotypically with DMI (r(p) = -0.35) but was unrelated phenotypically with FCR or RFI. On the other hand, FS had a weak negative genetic correlation with DMI (r(g) = -0.11 +/- 0.26), a moderate genetic correlation with FCR (r(g) = 0.40 +/- 0.26), and a negative genetic correlation with RFI (r(g) = -0.59 +/- 0.45). The results indicate that behavior traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency. Feeding behavior and temperament may need to be included in the definition of beef cattle breeding goals, and approaches such as the culling of unmanageable cattle and the introduction of correct handling facilities or early life provision of appropriate experiences to improve handling will be useful.  相似文献   

17.
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.  相似文献   

18.
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.  相似文献   

19.
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.  相似文献   

20.
This study was conducted to investigate relationships between mitochondrial respiratory chain complex activities, feed efficiency, and carcass traits in sheep. A group of Ghezel male lambs sired by a single ram were randomly allotted to individual pens. The lambs were fed ad libitum with a fattening diet containing 30% roughage (corn silage and alfalfa hay) and 70% concentrate for 70 d to individually phenotype each lamb for feed conversion ratio (FCR), adjusted FCR (aFCR), and residual feed intake (RFI). The lambs were then humanely killed and the liver, abdominal fat, pelvic fat, cardiac fat, warm carcass weight, and cold carcass weight, as well as the cross-sectional area of the LM and the fat depth over the 12th rib, were determined. A portion of LM was obtained to determine mitochondrial protein and respiratory chain complex activities (complexes I to V). Statistical analysis was carried out based on lambs exhibiting high and low RFI (n = 8), FCR (n = 8), or aFCR (n = 8) phenotypes. The lambs exhibiting the high-RFI phenotype consumed 110 g more feed daily (P < 0.05) than did the phenotype exhibiting low RFI, with no difference in ADG. Conversely, there was no difference in feed intake between the low- or high-FCR groups, but sheep exhibiting the low-FCR phenotype gained 70 g more (P < 0.05) per day compared with those exhibiting the high-FCR phenotype. It was determined that all 5 respiratory chain complex activities were greater (P < 0.05) in sheep exhibiting the low-RFI phenotype compared with those exhibiting the high-RFI phenotype, with significant (P < 0.001) negative correlation coefficients between RFI and respiratory chain complex activity. When efficiency was assessed using FCR, only activities of respiratory chain complexes III, IV, and V were less (P < 0.05) in the low-FCR phenotype compared with the high-FCR phenotype, and there were no differences (P > 0.1) in respiratory chain complex activities between groups when FCR was adjusted for metabolic BW (aFCR). There were no differences (P > 0.1) in carcass traits among any of the feed efficiency phenotypes. The results suggest that the inclusion of respiratory chain complex activities in breeding programs may be helpful in selecting for sheep exhibiting the low-RFI phenotype.  相似文献   

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