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Context. Improving meat quality traits such as marbling is a well established breeding objective for many beef producers. More recently, the inclusion of feed efficiency is being considered. The main driving factors being the direct feed cost, as well as consumer concerns related to environmental sustainability of beef production. Aims. The main aim of this study was to examine modifying the definition of residual feed intake (RFI), by including an adjustment for intramuscular fat (IMF). The secondary aim was to further understand the genetic relationships between feed intake and a range of carcass traits. Methods. Using a population of 4034 Australian Angus animals, feed intake and carcass traits, along with pedigree and fixed effects, were analysed. This included the calculation of three definitions of RFI, being the standard definition, accounting for average daily gain and metabolic mid-weight, and two amended versions accounting for ultrasound IMF (RFIu), or carcass IMF (RFIi). Variance components, heritabilities, and genetic and phenotypic correlations were estimated and compared. Key results. All three definitions of RFI were moderately heritable (0.30-0.32) and highly correlated, both genetically (0.99) and phenotypically (0.99). Unfavourable genetic correlations were observed between RFI and carcass IMF (CIMF), and between RFIu and CIMF at 0.29 and 0.24 respectively. Similarly, there were unfavourable genetic correlations between RFI and ultrasound IMF (UIMF), between RFIi and UIMF, and between RFIu and UIMF at 0.30, 0,21 and 0.23 respectively. Conclusions. RFI can be redefined to account for traits, other than average daily gain and metabolic mid-weight, such as IMF. However due to limitations of phenotypic linear regression, and only small amounts of variation in feed intake being explained by the IMF traits, the redefinition of RFI was a suboptimal approach to breeding candidate selection. Furthermore, the present study confirmed the challenges with selecting for both feed efficiency and meat quality traits as they are generally genetically antagonist. Implications. For beef cattle breeding programs, the investigation of alternative selection approaches is warranted. This may include further understanding the genetic correlations among traits in the breeding objective and, according to their economic value, optimally weighting the related estimated breeding value. [ABSTRACT FROM AUTHOR]

1. Genetic (co)variances and parameters between body weights (BW) across the growth trajectory were estimated using a univariate random regression (RR) animal model. The effect of growth rates (GH) on age at first egg (AFE) and egg weight at first egg (EWFE) were explored using a series of univariate and bivariate analyses. 2. Body weights were taken from Thai native chickens at hatch day to 168 days of age. The model included interactions between age with hatch nested within year and sex as fixed effects, and random effects of direct additive genetic, direct permanent environmental, maternal genetic and maternal permanent environmental effects. All random effects were fitted as regressions to animals' age via quadratic Legendre polynomials and fitting six classes of residual variances was identified as an optimal variance structure to estimate parameters. 3. Genetic and phenotypic variances for BW increased with increasing age. Estimated heritabilities for direct additive (h2a) and maternal genetic (h2m) effects on BW traits ranged from 0.34 to 0.54, and 0.04 to 0.06, respectively. Estimated variance ratios for direct (c2ape) and maternal permanent environmental (c2mpe) effects ranged from 0.19 to 0.48 and 0.10 to 0.12, respectively. Estimated correlations between weights at different ages were high for all random effects. 4. Estimated h2a for six GH traits ranged from 0.06 to 0.28, while for AFE and EWFE these were 0.24 and 0.16, respectively. Estimated h2m and c2mpe were low for GH. Estimated genetic correlations between GH and AFE ranged from −0.22 to 0.02 and, between GH and EWFE, ranged from −0.05 to 0.40. These estimates suggested that selecting high GH chickens at 28 days of age can be expected to reduce AFE and to increase EWFE. [ABSTRACT FROM AUTHOR]

Genetic correlations between 29 wool production and quality traits and 25 meat quality and nutritional value traits were estimated for Merino sheep from an Information Nucleus (IN). Genetic correlations among the meat quality and nutritional value traits are also reported. The IN comprised 8 flocks linked genetically and managed across a range of sheep production environments in Australia. The wool traits included over 5,000 yearling and 3,700 adult records for fleece weight, fiber diameter, staple length, staple strength, fiber diameter variation, scoured wool color, and visual scores for breech and body wrinkle. The meat quality traits were measured on samples from the M. longissimus thoracis et lumborum and included over 1,200 records from progeny of over 170 sires for intramuscular fat (IMF), shear force of meat aged for 5 d (SF5), 24 h postmortem pH (pH24LL; also measured in the semitendinosus muscle, pH24ST), fresh and retail meat color and meat nutritional value traits such as iron and zinc levels, and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. Estimated heritabilities for IMF, SF5, pH24LL, pH24ST, retail meat color lightness (L*), myoglobin, iron, zinc and across the range of long-chain fatty acids were 0.58 ± 0.11, 0.10 ± 0.09, 0.15 ± 0.07, 0.20 ± 0.10, 0.59 ± 0.15, 0.31 ± 0.09, 0.20 ± 0.09, 0.11 ± 0.09, and range of 0.00 (eicosapentaenoic, docosapentaenoic, and arachidonic acids) to 0.14 ± 0.07 (linoleic acid), respectively. The genetic correlations between the wool production and meat quality traits were low to negligible and indicate that wool breeding programs will have little or no effect on meat quality. There were moderately favorable genetic correlations between important yearling wool production traits and the omega-3 fatty acids that were reduced for corresponding adult wool production traits, but these correlations are unlikely to be important in wool/ meat breeding programs because they have high SE, and the omega-3 traits have little or no genetic variance. Significant genetic correlations among the meat quality traits included IMF with SF5 (-0.76 ± 0.24), fresh meat color L* (0.50 ± 0.18), and zinc (0.41 ± 0.19). Selection to increase IMF will improve meat tenderness and color which may address some of the issues with Merino meat quality. These estimated parameters allow Merino breeders to combine wool and meat objectives without compromising meat quality. [ABSTRACT FROM AUTHOR]

Genetic correlations between 29 wool production and quality traits and 14 whole carcass measures and carcass component traits were estimated from the Information Nucleus of 8 flocks managed across a range of Australian sheep production environments and genetically linked. Wool data were from over 5,000 Merino progeny born over 5 yr, whereas carcass data were from over 1,200 wether progeny of over 176 sires, slaughtered at about 21 kg carcass weight, on average. Wool traits included yearling and adult records for wool weight, fiber diameter, fiber diameter variation, staple strength, scoured color, and visual scores for breech and body wrinkle. Whole carcass measures included HCW, dressing percentage (DP), and various measures of fat depth and eye muscle dimensions. Carcass components were obtained by dissection, and lean meat yield (LMY) was predicted. Heritability estimates for whole carcass measures ranged from 0.12 ± 0.08 to 0.35 ± 0.10 and ranged from 0.17 ± 0.10 to 0.46 ± 0.10 for carcass dissection traits, with no evidence of important genotype × environment interactions. Genetic correlations indicated that selection for increased clean wool weight will result in reduced carcass fat (−0.17 to −0.34) and DP (−0.48 ± 0.15), with little effect on carcass muscle. Selection for lower fiber diameter will reduce HCW (−0.48 ± 0.15) as well as carcass fat (0.14 to 0.27) and muscle (0.21 to 0.50). There were high genetic correlations between live animal measures of fat and muscle depth and the carcass traits (generally greater than 0.5 in size). Selection to increase HCW (and DP) will result in sheep with fewer wrinkles on the body (−0.57 ± 0.10) and barer breeches (−0.74 ± 0.12, favorable), with minor deterioration in scoured wool color (reduced brightness and increased yellowness). Selection for reduced fat will also result in sheep with fewer body wrinkles (−0.42 to −0.79). Increasing LMY in Merinos through selection would result in a large reduction in carcass fat and DP (−0.66 to −0.84), with a smaller increase in carcass muscle and some increase in wool weight and wrinkles. Although no major antagonisms are apparent between the wool and carcass traits, developing selection indexes for dualpurpose wool and meat breeding objectives will require accurate estimates of genetic parameters to ensure that unfavorable relationships are suitably considered. The findings will aid development of dual-purpose wool and meat breeding objectives. [ABSTRACT FROM AUTHOR]

Genetic correlations between 29 wool production and quality traits and live weight and ultrasound fat depth (FAT) and eye muscle depth (EMD) traits were estimated from the Information Nucleus (IN). The IN comprised 8 genetically linked flocks managed across a range of Australian sheep production environments. The data were from a maximum of 9,135 progeny born over 5 yr from 184 Merino sires and 4,614 Merino dams. The wool traits included records for yearling and adult fleece weight, fiber diameter (FD), staple length (SL), fiber diameter CV (FDCV), scoured color, and visual scores for breech and body wrinkle. We found high heritability for the major yearling wool production traits and some wool quality traits, whereas other wool quality traits, wool color, and visual traits were moderately heritable. The estimates of heritability for live weight generally increased with age as maternal effects declined. Estimates of heritability for the ultrasound traits were also higher when measured at yearling age rather than at postweaning age. The genetic correlations for fleece weight with live weights were positive (favorable) and moderate (approximately 0.5 ± 0.1), whereas those with FD were approximately 0.3 (unfavorable). The other wool traits had lower genetic correlations with the live weights. The genetic correlations for FAT and EMD with FD and SL were positive and low, with FDCV low to moderate negative, but variable with wool weight and negligible for the other wool traits. The genetic correlations for FAT and EMD with postweaning weight were positive and high (0.61 ± 0.18 to 0.75 ± 0.14) but were generally moderate with weights at other ages. Selection for increased live weight will result in a moderate correlated increase in wool weight as well as favorable reductions in breech cover and wrinkle, along with some unfavorable increases in FD and wool yellowness but little impact on other wool traits. The ultrasound meat traits, FAT and EMD, were highly positively genetically correlated (0.8), and selection to increase them would result in a small unfavorable correlated increase in FD, moderately favorable reductions in breech cover and wrinkle, but equivocal or negligible changes in other wool traits. The estimated parameters provide the basis for calculation of more accurate Australian Sheep Breeding Values and selection indexes that combine wool and meat objectives in Merino breeding programs. [ABSTRACT FROM AUTHOR]

Reducing daily methane production (DMP) via selection for lower estimated daily (pasture) feed intake (DFI) has the potential to be more cost effective than direct selection for DMP. Daily feed intake has a high heritability and high genetic correlation to DMP and has a potential lower cost of measurement. This study's main aim was to determine for a breeding nucleus the optimal proportion of randomly selected young male and female cattle in which to estimate DFI. This optimum proportion was determined by modeling the measurement costs and response to selection of Angus cattle on a (standard industry) Angus breeding index (ABI) augmented with DFI and DMP in a combined breeding objective (BO), but without DMP being measured. For the assumed herd structure and considering a 20 yr planning horizon, the highest net present value (NPV) occurred when 64% of males and no females were measured for DFI. The highest breakeven DFI test cost (A$41.51/head) and highest returns on investment (ROI) occurred when 36% of males and no females had DFI estimates. Higher ROI were achieved when all males had DFI estimates before any females had DFI estimates. There was a diminishing increase in rate of genetic gain when moving from 36% to 64% of males with DFI estimates, thus ROI decreased from 29.7% to 23.1%. When 36% of males had DFI estimates (and no females), herd DMP genetic gain was slightly positive as the DMP reduction per generation from male selection (-0.086) was more than offset by the DMP increase per generation from female selection (+0.110). The selection response for DMP only became negative when at least 40% of males had DFI estimates. Having 64% of males with DFI estimates resulted in a predicted genetic decrease in DMP (-0.018 kgCO2e/head per yr), compared to an increase of 0.052 kgCO2e/head per yr when no animals had DFI estimates. The optimum proportion of males with DFI estimates (36 to 64%) depends on the breeders attitude toward ROI and the value of genetic change for DMP. Sensitivity analysis showed that the economic value (EV), heritability and genetic variance of DFI had a higher impact on the NPV and ROI outcomes than parameters related to ABI and DMP, so future work should focus on obtaining robust estimates for DFI parameters. Higher EV for feed intake and DMP would result in higher percentages of animals being profitably measured for DFI, leading to larger reductions in DMP. [ABSTRACT FROM AUTHOR]

Merino sheep in Australia experience periods of variable feed supply. Merino sheep can be bred to be more resilient to this variation by losing less BW when grazing poor quality pasture and gaining more BW when grazing good quality pasture. Therefore, selection on BW change might be economically attractive but correlations with other traits in the breeding objective need to be known. The genetic correlations (r g ) between BW, BW change, and reproduction were estimated using records from approximately 7,350 fully pedigreed Merino ewes managed at Katanning in Western Australia. Number of lambs and total weight of lambs born and weaned were measured on approximately 5,300 2-yr-old ewes, approximately 4,900 3-yr-old ewes, and approximately 3,600 4-yr-old ewes. On a proportion of these ewes BW change was measured: approximately 1,950 2-yr-old ewes, approximately 1,500 3-yr-old ewes, and approximately 1,100 4-yr-old ewes. The BW measurements were for 3 periods. The first period was during mating period over 42 d on poor pasture. The second period was during pregnancy over 90 d for ewes that got pregnant on poor and medium quality pasture. The third period was during lactation over 130 d for ewes that weaned a lamb on good quality pasture. Genetic correlations between weight change and reproduction were estimated within age classes. Genetic correlations were tested to be significantly greater magnitude than 0 using likelihood ratio tests. Nearly all BW had significant positive genetic correlations with all reproduction traits. In 2-yr-old ewes, BW change during the mating period had a positive genetic correlation with number of lambs weaned (rg = 0.58); BW change during pregnancy had a positive genetic correlation with total weight of lambs born (rg = 0.33) and a negative genetic correlation with number of lambs weaned (rg = -0.49). All other genetic correlations were not significantly greater magnitude than 0 but estimates of genetic correlations for 3-yr-old ewes were generally consistent with these findings. The direction of the genetic correlations mostly coincided with the energy requirements of the ewes and the stage of maturity of the ewes. In conclusion, optimized selection strategies on BW changes to increase resilience will depend on the genetic correlations with reproduction and are dependent on age. [ABSTRACT FROM AUTHOR]

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnonnality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success. [ABSTRACT FROM AUTHOR]

Genetic parameters for carcass and meat quality traits of about 18-month-old Merino rams (n = 5870), the progeny of 543 sires from three research resource flocks, were estimated. The estimates of heritability for hot carcass weight (HCW) and the various fat and muscle dimension measurements were moderate and ranged from 0.20 to 0.37. The brightness of meat (colour L*, 0.18 ± 0.03 standard error) and meat pH (0.22 ± 0.03) also had moderate estimates of heritability, although meat relative redness (colour a*, 0.10 ± 0.03) and relative yellowness (colour b*, 0.10 ± 0.03) were lower. Heritability estimates for live weights were moderate and ranged from 0.29 to 0.41 with significant permanent maternal environmental effects (0.13 to 0.10). The heritability estimates for the hogget wool traits were moderate to high and ranged from 0.27 to 0.60. The ultrasound measurements of fat depth (FATUS) and eye muscle depth (EMDUS) on live animals were highly genetically correlated with the corresponding carcass measurements (0.69 ± 0.09 FATC and 0.77 ± 0.07 EMD). Carcass tissue depth (FATGR) had moderate to low genetic correlations with carcass muscle measurements [0.18 ± 0.10 EMD and 0.05 ± 0.10 eye muscle area (EMA)], while those with FATC were negative. The genetic correlation between EMD and eye muscle width (EMW) was 0.41 ± 0.08, while EMA was highly correlated with EMD (0.89 ± 0.0) and EMW (0.78 ± 0.04). The genetic correlations for muscle colour with muscle measurements were moderately negative, while those with fat measurements were close to zero. Meat pH was positively correlated with muscle measurements (0.14 to 0.17) and negatively correlated with fat measurements (−0.06 to −0.18). EMDUS also showed a similar pattern of correlations to EMD with meat quality indicator traits, although FATUS had positive correlations with these traits which were generally smaller than their standard error. The genetic correlations among the meat colour traits were high and positive while those with meat pH were high and negative, which were all in the favourable direction. Generally, phenotypic correlations were similar or slightly lower than the corresponding genetic correlations. There were generally small to moderate negative genetic correlations between clean fleece weight (CFW) and carcass fat traits while those with muscle traits were close to zero. As the Merino is already a relatively lean breed, this implies that particular attention should be given to this relationship in Merino breeding programmes to prevent the reduction of fat reserves as a correlated response to selection for increased fleece weight. The ultrasound scan traits generally showed a similar pattern to the corresponding carcass fat and muscle traits. There was a small unfavourable genetic correlation between CFW and meat pH (0.19 ± 0.07). [ABSTRACT FROM AUTHOR]

Context. Genotype by environment interaction or sire re-ranking between measurements of methane emission in different environments or from using different measurement protocols can affect the efficiency of selection strategies to abate methane emission. Aim. This study tested the hypothesis that measurements of methane emission from grazing sheep under field conditions, where the feed intake is unknown, are genetically correlated to measurements in a controlled environment where feed intake is known. Methods. Data on emission of methane and carbon dioxide and uptake of oxygen were measured using portable accumulation chambers from 499 animals in a controlled environment in New South Wales and 1382 animals in a grazing environment in Western Australia were analysed. Genetic linkage between both environments was provided by 140 sires with progeny in both environments. Multi-variate animal models were used to estimate genetic parameters for the three gas traits corrected for liveweight. Genetic groups were fitted in the models to account for breed differences. Genetic correlations between the field and controlled environments for the three traits were estimated using bivariate models. Key results. Animals in the controlled environment had higher methane emission compared to the animals in the field environment (37.0 ± s.d 9.3 and 35.3 ± s.d 9.4 for two protocols vs 12.9 ± s.d 5.1 and 14.6 ± s.d 4.8 mL/min for lambs and ewes (±s.d); P < 0.05) but carbon dioxide emission and oxygen uptake did not significantly differ. The heritability estimates for methane emission, carbon dioxide emission and oxygen uptake were 0.15, 0.06 and 0.11 for the controlled environment and 0.17, 0.27 and 0.35 for the field environment. The repeatability for the traits in the controlled environment ranged from 0.51 to 0.59 and from 0.24 to 0.38 in the field environment. Genetic correlations were high (0.85-0.99) but with high standard errors. Conclusion. Methane emission phenotypes measured using portable accumulation chambers in grazing sheep can be used in genetic evaluation to estimate breeding values for genetic improvement of emission related traits. The combined measurement protocol-environment did not lead to re-ranking of sires. Implication. These results suggest that both phenotypes could be used in selection for reduced methane emission in grazing sheep. However, this needs to be consolidated using a larger number of animals and sires with larger progeny groups in different environments. [ABSTRACT FROM AUTHOR]