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1.
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   

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.
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   

4.
Data were collected in the course of a divergent selection experiment for residual feed intake (RFI) of Large White growing pigs. This data set was used to estimate (i) heritability for RFI and genetic correlations of RFI with growth and carcass traits within the three sexes (male, castrate and female) and (ii) genetic correlations between sexes for these traits. Individual feed intake of animals raised in collective pens was measured by single-place electronic feeders on 1121 males (candidates for selection), 508 females and 535 castrates (sibs of candidates). Variance components were estimated using the REML methodology applied to a multitrait animal model. Estimates of heritability for RFI were 0.16 ± 0.04, 0.16 ± 0.08 and 0.23 ± 0.10 for males, females and castrates, respectively. Estimates of genetic correlations between sexes for homologous traits were not significantly different from 1 (0.88 to 0.99 for RFI, 0.79 to 0.99 for growth traits and 0.65 to 0.99 for carcass composition traits). The relatively low genetic correlations between castrates and males or females for backfat thickness (0.65 and 0.69, respectively) suggest the presence of genotype by sex interactions for this trait.  相似文献   

5.
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   

6.
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.  相似文献   

7.
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   

8.
Breeding goals in pigs are subject to change and are directed much more toward retail carcass yield and meat quality because of the high economic value of these traits. The objective of this study was to estimate genetic parameters of growth, carcass, and meat quality traits. Carcass components included ham and loin weights as primal cuts, which were further dissected into boneless subprimal cuts. Meat quality traits included pH, drip loss, purge, firmness, and color and marbling of both ham and loin. Phenotypic measurements were collected on a commercial crossbred pig population (n = 1,855). Genetic parameters were estimated using REML procedures applied to a bivariate animal model. Heritability estimates for carcass traits varied from 0.29 to 0.51, with 0.39 and 0.51 for the boneless subprimals of ham and loin, respectively. Heritability estimates for meat quality traits ranged from 0.08 to 0.28, with low estimates for the water holding capacity traits and higher values for the color traits: Minolta b*(0.14), L* (0.15), a* (0.24), and Japanese color scale (0.25). Heritability estimates differed for marbling of ham (0.14) and loin (0.31). Neither backfat nor ADG was correlated with loin depth (r(g) = 0.0), and their mutual genetic correlation was 0.27. Loin primal was moderately correlated with ham primal (r(g) = 0.31) and more strongly correlated with boneless ham (r(g) = 0.58). Backfat was negatively correlated with (sub)primal cut values. Average daily gain was unfavorably correlated with subprimals and with most meat quality characteristics measured. Genetic correlations among the color measurements and water-holding capacity traits were high (average r(g) = 0.70), except for Minolta a* (average r(g) = 0.17). The estimated genetic parameters indicate that meat quality and valuable cut yields can be improved by genetic selection. The estimated genetic parameters make it possible to predict the response to selection on performance, carcass, and meat quality traits and to design an effective breeding strategy fitting pricing systems based on retail carcass and quality characteristics.  相似文献   

9.
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   

10.
Genetic parameters for feed intake and performance traits of 514 bulls and carcass traits of 22 099 of their progeny, and the relationships of measures of feed intake with performance and carcass traits were estimated. Feed intake traits were dry matter intake (DMI), concentrate intake (CONI), roughage intake, ratio of roughage intake to DMI, metabolizable energy intake (MEI) and digestible crude protein intake (DCPI). Performance traits included daily gain, metabolic weight, live weight at the end of test, dry matter conversion ratio and residual feed intake. Progeny carcass traits were carcass weight, percentage of meat yield, rib eye area (REA), subcutaneous fat, marbling score, meat colour (MCS), fat colour (FCS) and meat quality grade. All the feed intake and performance traits were moderately heritable. The heritabilities for REA and MCS were moderate, and that for FCS was low, while those for the other carcass traits were high. Selection against DMI, CONI and DCPI would reduce excessive intake of feed, but would have undesirable effects on growth and most of the carcass traits. Selection against MEI would lead to improvements in feed efficiency and growth traits. Selection against DCPI would also improve feed efficiency; however, responses in growth traits would decrease. Results indicate that selection against MEI might be better than any other measures of feed intake to improve feed efficiency with simultaneous improvement in growth and most of the carcass traits.  相似文献   

11.
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   

12.
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.  相似文献   

13.
Records on 1,180 young Angus bulls and heifers involved in performance tests were used to estimate genetic and phenotypic parameters for feed intake, feed efficiency, and other postweaning traits. The mean age was 268 d at the start of the performance test, which comprised 21-d adjustment and 70-d test periods. Traits studied included 200-d weight, 400-d weight, scrotal circumference, ultrasonic measurements of rib and rump fat depths and longissimus muscle area, ADG, metabolic weight, daily feed intake, feed conversion ratio, and residual feed intake. For all traits except the last five, additional data from the Angus Society ofAustralia pedigree and performance database were included, which increased the number of animals to 27,229. Genetic (co)variances were estimated by REML using animal models. Direct heritability estimates for 200-d weight, 400-d weight, rib fat depth, ADG, feed conversion,and residual feed intake were 0.17 +/- 0.03, 0.27 +/- 0.03, 0.35 +/- 0.04, 0.28 +/- 0.04, 0.29 +/- 0.04, and 0.39 +/- 0.03, respectively. Feed conversion ratio was genetically (r(g) = 0.66 ) and phenotypically (r(p) = 0.53) correlated with residual feed intake. Feed conversion ratio was correlated (r(g) = -0.62, r(p) = -0.74) with ADG, whereas residual feed intake was not (rg = -0.04, r(p) = -0.06). Genetically, both residual feed intake and feed conversion ratio were negatively correlated with direct effects of 200-d weight (r(g) = -0.45 and -0.21) and 400-d weight (r(g) = -0.26 and -0.09). The correlations between the remaining traits and the feed efficiency traits were near zero, except between feed intake and feed conversion ratio (r(g) = 0.31, r(p) = 0.23), feed intake and residual feed intake (r(g) = 0.69, r(p) = 0.72), and rib fat depth and residual feed intake (r(g) = 0.17, r(p) = 0.14). These results indicate that genetic improvement in feed efficiency can be achieved through selection and, in general, correlated responses in growth and the other postweaning traits will be minimal.  相似文献   

14.
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   

15.
Leptin is the hormone product of the obese gene that is synthesized and predominantly expressed by adipocytes. This study estimated the genetic variation in serum leptin concentration and evaluated the genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit. There were 464 steers with records for serum leptin concentration, performance, and efficiency of gain and 381 steers with records for carcass traits. The analyses included a total of 813 steers, including those without phenotypic records. Phenotypic and genetic parameter estimates were obtained using SAS and ASREML, respectively. Serum leptin concentration was moderately heritable (h2 = 0.34 +/- 0.13) and averaged 13.91 (SD = 5.74) ng/mL. Sire breed differences in serum leptin concentration correlated well with breed differences in body composition. Specifically, the serum leptin concentration was 20% greater in Angus-sired steers compared with Charolais-sired steers (P < 0.001). Consequently, ultrasound backfat (27%), carcass 12th-rib fat (31%), ultrasound marbling (14%), and carcass marbling (15%) were less in Charolais- than Angus-sired steers (P < 0.001). Conversely, carcass LM area (P = 0.05) and carcass lean meat yield (P < 0.001) were greater in Charolais- compared with Angus-sired steers. Steers with greater serum leptin concentration also had greater DMI (P < 0.001), greater residual feed intake (P = 0.04), and partial efficiency of growth (P = 0.01), but did not differ in feed conversion ratio (P > 0.10). Serum leptin concentration was correlated phenotypically with ultrasound backfat (r = 0.41; P < 0.001), carcass 12th-rib fat (r = 0.42; P < 0.001), ultrasound marbling (r = 0.25; P < 0.01), carcass marbling (r = 0.28; P < 0.01), ultrasound LM area (r = -0.19; P < 0.01), carcass LM area (r = -0.17; P < 0.05), lean meat yield (r = -0.38; P < 0.001), and yield grade (r = 0.32; P < 0.001). The corresponding genetic correlations were generally greater than the phenotypic correlations and included ultrasound backfat (r = 0.76 +/- 0.19), carcass 12th-rib fat (r = 0.54 +/- 0.23), ultrasound marbling (r = 0.27 +/- 0.22), carcass marbling (r = 0.76 +/- 0.21), ultrasound LM area (r = -0.71 +/- 0.19), carcass LM area (r = -0.75 +/- 0.20), lean meat yield (r = -0.59 +/- 0.22), and yield grade (r = 0.39 +/- 0.26). Serum leptin concentration can be a valuable tool that can be incorporated into appropriate selection programs to favorably improve the carcass merit of cattle.  相似文献   

16.
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.  相似文献   

17.
Breeding strategies based on feed efficiency are now implemented in most animal species using residual feed intake (RFI) criteria. Although relevant, the correlated responses of feeding behaviour traits resulting from such selection on RFI are poorly documented. We report the estimated feeding behaviour at three time levels (visit, meal and day) and genetic parameters between the feeding behaviour traits and their links with RFI and its components. Feed intake, feeding duration at three time levels (per visit, meal and day), feeding rate, number of visits and time‐between‐visits were estimated for 951 Romane lambs fed via automatic concentrate feeders. Heritability estimates of feeding behaviour traits ranged from 0.19 to 0.54 with higher estimates for the day level than the visit level. Daily feed intake was not genetically linked to feed intake at the visit level, whereas feeding duration between visit and day levels was moderately correlated (Rg = +0.41 ± 0.12). RFI was not significantly correlated with feeding rate, but was positively linked to feed intake and feeding duration at the day level (+0.73 ± 0.09 and +0.41 ± 0.13, respectively) and negatively at the visit level (?0.33 ± 0.14 and ?0.22 ± 0.17, respectively). Selecting animals with lower RFI values might modify their feeding behaviour by increasing feed intake and feeding duration at the visit level but decrease the number of visits per day (+0.51 ± 0.14).  相似文献   

18.
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.  相似文献   

19.
Correlated responses in reproductive and carcass traits were studied in 181 litters and 218 pigs from a line of Landrace pigs selected six generations for increased weight at 70 d of age and a contemporaneous, randomly selected control line. The reproductive and maternal traits studied included litter sizes born, born alive, and alive at 21 d and litter weight at birth and at 21 d. Carcass traits studied were carcass length, longissimus muscle area, average backfat thickness, 10th-rib backfat thickness, specific gravity, weights of closely trimmed ham, loin, and shoulder, belly weight, subjective scoring of the longissimus muscle for color and marbling, estimated percentage of muscle, and lean gain per day. Total weighted cumulative selection differential for 70-d weight was 30.2 kg. The realized heritability for 70-d weight was .13 +/- .06, and the change in 70-d weight was .65 +/- .29 kg per generation. The regression coefficient of litter size at 21 d on generation was .24 +/- .10 (P less than .10) pigs per generation. None of the other regression coefficients for the reproductive traits differed from zero. Carcass length, specific gravity, and ham weight decreased (P less than .10) -.075 +/- .036 cm, -.00054 +/- .00027, and -.102 +/- .048 kg, respectively, per generation. Color score and lean gain per day increased .046 +/- .021 points and .0032 +/- .0013 kg/d, respectively, each generation in response to the selection.(ABSTRACT TRUNCATED AT 250 WORDS)  相似文献   

20.
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1 923个个体(其中公鸡1 199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(SSGBLUP)3种方法,基于加性效应模型进行遗传参数估计,通过10倍交叉验证比较3种方法所得估计育种值的准确性。研究性状包括4个生长性状和4个饲料利用效率性状:42日龄体重(BW42D)、56日龄体重(BW56D)、日均增重(ADG)、日均采食量(ADFI)和饲料转化率(FCR)、剩余采食量(RFI)、剩余增长体重(RG)、剩余采食和增长体重(RIG)。结果显示,4个饲料利用效率性状均为低遗传力(0.08~0.20),其他生长性状为中等偏低遗传力(0.11~0.35);4个饲料利用效率性状间均为高度遗传相关,RFI、RIG与ADFI间为中度遗传相关,RFI与ADG间无显著相关性,RIG与ADG间为低度遗传相关。本研究在获得SSGBLUP方法的最佳基因型和系谱矩阵权重比基础上,比较8个性状的估计育种值准确性,SSGBLUP方法获得的准确性分别比传统BLUP和GBLUP方法提高3.85%~14.43%和5.21%~17.89%。综上,以RIG为选择指标能够在降低日均采食量的同时保持日均增重,比RFI更适合快速型黄羽肉鸡的选育目标;采用最佳权重比进行SSGBLUP分析,对目标性状估计育种值的预测性能最优,建议作为快速型黄羽肉鸡基因组选择方法。  相似文献   

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