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1.
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.  相似文献   

2.
Variance components and genetic parameters were estimated using data recorded on 740 young male Japanese Black cattle during the period from 1971 to 2003. Traits studied were feed intake (FI), feed‐conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG), metabolic body weight (MWT) at the mid‐point of the test period and body weight (BWT) at the finish of the test (345 days). Data were analysed using three alternative animal models (direct, direct + maternal environmental, and direct + maternal genetic effects). Comparison of the log likelihood values has shown that the direct genetic effect was significant (p < 0.05) for all traits and that the maternal environmental effects were significant (p < 0.05) for MWT and BWT. The heritability estimates were 0.20 ± 0.12 for FI, 0.14 ± 0.10 for FCR, 0.33 ± 0.14 for RFI, 0.19 ± 0.12 for ADG, 0.30 ± 0.14 for MWT and 0.30 ± 0.13 for BWT. The maternal effects (maternal genetic and maternal environmental) were not important in feed‐efficiency traits. The genetic correlation between RFI and ADG was stronger than the corresponding correlation between FCR and ADG. These results provide evidence that RFI should be included for genetic improvement in feed efficiency in Japanese Black breeding programmes.  相似文献   

3.
Interest in improving feed efficiency in cattle is intensifying. Residual feed intake (RFI), which is the difference between expected intake and that predicted based on energy demands, is now the most commonly used measure of feed efficiency over a given time period. However, RFI, as commonly defined, is independent of growth rate, which may affect its acceptance by industry. Residual BW gain (RG) has also been proposed as a measure of feed efficiency and is represented as the residuals from a multiple regression model regressing ADG on both DMI and BW. In this study, we propose a new trait, residual intake and BW gain (RIG), which retains the favorable characteristic of both RFI and RG being independent of BW, but animals superior for RIG have, on average, both greater ADG and reduced DMI. Phenotypic and genetic analyses were undertaken on up to 2,605 purebred performance-tested bulls. Clear phenotypic differences in DMI and ADG existed between animals divergent for RIG. The heritability of RIG was 0.36 ± 0.06, which is consistent with the heritability estimates of RFI and other feed efficiency traits measured in the study. The RIG trait was both phenotypically and genetically negatively correlated with DMI and positively correlated with ADG; no correlation existed between RIG and BW. The advantages of both reduced daily DMI and greater ADG in animals superior for RIG are demonstrated compared with animals superior for either RFI or RG.  相似文献   

4.
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   

5.
Genetic parameters of average daily gain (ADG), metabolic body weight (MWT), body weight at finish (BWF), daily feed intake (DFI), feed conversion ratio (FCR), and residual feed intake (RFI) were estimated in 740 Japanese Black bulls. RFI was calculated as the difference between actual and expected feed intake predicted by the residual of multiple regression (RFIphe) and genetic regression (RFIgen) from the multivariate analysis for DFI, MWT, and ADG. The estimations were made for the test periods of 140 days (77 bulls) and 112 days (663 bulls). The mean for RFIphe was close to zero and RFIgen was negative. Most of the traits studied were moderately heritable (ranging from 0.24 to 0.49), except for ADG and FCR (0.20 and 0.15, respectively). The genetic correlations among growth traits (ADG, MWT and BWF) and between DFI and growth traits were high, while the phenotypic correlations between them were moderate to high. The genetic and phenotypic correlations between RFIphe and RFIgen were > 0.95 implying that they are regarded as the same trait and the genetic correlations of RFI (RFIphe and RFIgen) with FCR and DFI were favorably high. RFIphe was phenotypically independent of its component traits, MWT (rp = − 0.01) and ADG (rp = 0.01). RFIgen was genetically independent of MWT (rg = − 0.07), while there was a weak genetic relationship (rg = 0.18) between RFIgen and ADG. These results provide evidence that RFIgen should be included for genetic improvement of feed efficiency in Japanese Black breeding program.  相似文献   

6.
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   

7.
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.  相似文献   

8.
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   

9.
This study was conducted to evaluate the utilisation of the residual feed intake (RFI ) as a feed efficiency selection tool and its relationship with methane emissions. Eighteen Murrah buffalo (Bubalus bubalis ) heifers were fed ad libitum with total mixed ration (TMR ) for 120 days. Based on linear regression models involving dry matter intake (DMI ), average daily gain (ADG ) and mid‐test metabolic body size (MBW 0.75), heifers were assigned into low and high RFI groups. The RFI varied from ?0.09 to +0.12 kg DM /day with average RFI of ?0.05 and 0.05 kg DM /day in low and high RFI heifers respectively. Low RFI heifers ate 11.6% less DM each day, yet average daily gain (ADG ) and feed utilisation were comparable among low and high RFI groups. Low RFI heifers required significantly (< .05) less metabolizable energy for maintenance (ME m) compared to high RFI heifers. Apparent nutrient digestibility showed non‐significant difference (p >  .05) among low and high RFI groups. Although the nitrogen balance was similar among heifers of low and high RFI groups, nitrogen metabolism was significantly higher (> .05) in high RFI heifers. Comparison of data from heifers exhibiting the low (n  = 9) and high (n  = 9) RFI showed that the low RFI heifers have lower enteric methane production and methane losses than high RFI heifers. In conclusion, results of this study revealed that selection of more efficient buffalo heifers has multiple benefits, such as decreased feed intake and less emission of methane.  相似文献   

10.
Our objective was to estimate genetic parameters for feed intake, feeding behavior, and ADG in composite ram lambs ((1/2) Columbia, (1/4) Hampshire, (1/4) Suffolk). Data were collected from 1986 to 1997 on 1,239 ram lambs from approximately 11 to 17 wk of age at the U.S. Meat Animal Research Center near Clay Center, NE. Feeding equipment consisted of an elevated pen with an entrance chute that permitted access to the feeder by only one ram lamb at a time, with disappearance of feed measured by an electronic weighing system. Ram lambs were grouped 11 per pen from 1986 to 1989, and nine per pen from 1990 to 1997. Data were edited to exclude invalid feeding events, and approximately 80% of the data remained after edits were applied. Traits analyzed were daily feed intake (DFI), event feed intake (EFI), residual feed intake (RFI), daily feeding time (DFT), event feeding time (EFT), number of daily feeding events (DFE), and ADG. Feed intake traits of DFI and EFI had estimated heritabilities of 0.25 and 0.33, respectively, whereas estimated heritability of RFI was 0.11. Heritability estimates for feeding behavior traits, including DFT, EFT, and DFE, ranged from 0.29 to 0.36. Average daily gain had an estimated heritability of 0.26. Genetic correlations were positive between all pairs of traits, except for RFI and ADG, and that estimate was essentially zero. Phenotypic correlations were generally similar to genetic correlations. Genetic correlations were large (0.80) between DFI and ADG, intermediate between DFI and RFI (0.61) and between DFT and DFE (0.55), and low (0.17 to 0.31) for the other pairs of traits, with the exception of RFI and ADG (-0.03). Genetic correlations between behavioral traits were greater than correlations between behavioral traits and measures of feed intake or ADG; however, selection for ADG and/or feed intake would be expected to cause some changes in feeding behavior.  相似文献   

11.
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   

12.
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   

13.
1. The objectives of the present study were to estimate heritability and genetic correlations for feed efficiency and body weight (BW) in Japanese quail.

2. Recorded traits during different weeks of the growing period were BW from hatch to 35 d, feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI) from hatch to 28 d of age.

3. Genetic parameters were estimated by restricted maximum likelihood method using ASREML software. The results showed that heritability estimates for BW ranged from 0.11 to 0.22, and maternal permanent environmental effect was the highest at hatch (0.45). FCR, RFI and FI showed moderate heritabilities ranging from 0.13 to 0.40.

4.Genetic correlations of BW28 with FI0–28 (0.88) and RFI0–28 (0.1) and genetic correlation of FI0–28 with FCR0–28 (0.13) and RFI0–28 (0.52) were positive. A negative genetic correlation was found between BW28 and FCR0–28 (?0.49). There was a high positive genetic correlation (0.67) between RFI0–28 and FCR0–28.

5. In conclusion, selection for increased BW and reduced FI in a selection index could be recommended to improve feed efficiency traits including FCR and RFI in Japanese quail.  相似文献   

14.
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   

15.
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   

16.
The objective of this study was to examine the genetic parameters and genetic correlations of feed efficiency traits in steers (n = 490) fed grower or finisher diets in 2 feeding periods. A bivariate model was used to estimate phenotypic and genetic parameters using steers that received the grower and finisher diets in successive feeding periods, whereas a repeated animal model was used to estimate the permanent environmental effects. Genetic correlations between the grower-fed and finisher-fed regimens were 0.50 ± 0.48 and 0.78 ± 0.43 for residual feed intake (RFI) and G:F, respectively. The moderate genetic correlation between the 2 feeding regimens may indicate the presence of a genotype × environment interaction for RFI. Permanent environmental effects (expressed in percentage of phenotypic variance) were detected in the grower-fed steers for ADG (38%), DMI (30%), RFI (18%), and G:F (40%) and also in the finisher-fed steers for ADG (28%), DMI (35%), metabolic mid-weight (23%), and RFI (10%). Heritability estimates were 0.08 ± 0.10 and 0.14 ± 0.15 for the grower-fed steers and 0.42 ± 0.16 and 0.40 ± 17 for the finisher-fed steers for RFI and G:F, respectively. The dependency of the RFI on the feeding regimen may have serious implications when selecting animals in the beef industry. Because of the higher cost of grains, feed efficiency in the feedlot might be overemphasized, whereas efficiency in the cow herd and the backgrounding segments may have less emphasis. These results may also favor the retention (for subsequent breeding) of cows whose steers were efficient in the feedlot sector. Therefore, comprehensive feeding trials may be necessary to provide more insight into the mechanisms surrounding genotype × environment interaction in steers.  相似文献   

17.
Genetic parameters for feed efficiency traits of 740 Wagyu bulls and growth and carcass traits of 591 of their progeny, and the genetic relationship between the traits of bulls and their progeny were estimated with the residual maximum likelihood procedure. The estimations were made for the test periods of 140 days (77 bulls), 112 days (663 bulls) and 364 days (591 steer progeny). Feed efficiency traits of bulls included feed conversion ratio (FCR), phenotypic residual feed intake (RFIphe) and genetic residual feed intake (RFIgen). Progeny traits were bodyweight at the start of the test (BWS), bodyweight at finish (BWF), average daily gain (ADG), rib eye area (REA), marbling score (MSR), dressing percentage (DRS) and subcutaneous fat thickness (SFT). The estimated heritability for MSR (0.52) was high and for BWS (0.35), BWF (0.40) and ADG (0.30) were moderate, whereas REA, DRS and SFT were low. Positive genetic correlations among BWS, BWF, ADG and SFT and negative genetic correlations between MSR and DRS and between REA and SFT were found. The genetic correlations between residual feed intake (RFIphe and RFIgen) of bulls and bodyweights (BWS and BWF) of their progeny ranged from ?0.27 to ?0.61. Residual feed intake was positively correlated with REA and DRS and negatively correlated with MSR and SFT. No responses in ADG and weakly correlated responses in REA and DRS of progeny were found to select against feed efficiency traits of bulls. The present experiment provides evidence that selection against lower RFI (higher feed efficiency) would be better than selection against lower FCR for getting better correlated responses in bodyweights.  相似文献   

18.
The purpose of this study was to estimate genetic parameters for ADG, backfat thickness and loin eye area (LEA), and measures of feed intake and efficiency for purebred Large White boars born from 1990 to 1997. Boars from 60% of the litters were culled at weaning based on a maternal breeding value (index) of the dam, and remaining boars (n = 26,706) were grown to 100 d of age. Selection of boars for individual pen testing was based on a combination of growth and maternal indices. Boars were fed a corn-soybean meal diet that was 1.14% lysine, 19% protein, and 3,344 kcal/kg ME for approximately 77 d. Boars were weighed at the beginning and end of the test, and feed intake was recorded. Daily feed intake (DFI), ADG, and feed:gain ratio (FG) were computed. Four measures of residual feed intake (RFI) were estimated as the difference between actual feed intake and that predicted from models that included 1) initial test age and weight and test ADG (RFI1); 2) initial test age and weight, test ADG, and backfat (RFI2); 3) initial test age and weight, test ADG, and LEA (RFI3); and 4) initial test age and weight, test ADG, backfat, and LEA (RFI4). Genetic parameters were estimated using an animal model and single- or multiple-trait DFREML procedures. Models included fixed effects of contemporary groups and initial test age as a covariate and random animal and litter effects. Heritability estimates for test ADG, DFI, FG, backfat, LEA, RFI1, RFI2, RFI3, and RFI4 were .24, .23, .16, .36, .24, .17, .11, .15, and .10, respectively. Genetic correlations between ADG and backfat, ADG and LEA, ADG and DFI, and ADG and FG were .37, .36, .82, and -.32, respectively. Genetic correlations between ADG and measures of residual feed intake ranged from .11 to .18. Genetic correlations of backfat with LEA, DFI, and FG were -.27, .64, and .40, respectively. Genetic correlations of backfat with RFI measures were higher when backfat was not included in the estimation of RFI. Genetic correlations for LEA with DFI and FG were 0 and -.52, respectively. Genetic correlations for LEA with RFI measures were all negative and ranged from -.31 to -.51. Genetic correlations indicate that selection for reduced RFI could be made without adversely affecting ADG. Backfat should also decrease, and LEA should increase. The amount of change in backfat or LEA would depend on the measure of RFI used.  相似文献   

19.
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   

20.
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).  相似文献   

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