首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 31 毫秒
1.
The aim of this study was to estimate genetic parameters for lactation yields of milk (MY), fat (FY), protein (PY), and somatic cell score (SCS) of New Zealand dairy goats. The analysis used 64,604 lactation records from 23,583 does, kidding between 2004 and 2017, distributed in 21 flocks and representing 915 bucks. Estimates of genetic and residual (co) variances, heritabilities, and repeatabilities were obtained using a multiple‐trait repeatability animal model. The model included the fixed effects of contemporary group (does kidding in the same flock and year), age of the doe (in years), and as covariates, kidding day, proportion of Alpine, Nubian, Toggenburg, and “unknown” breeds (Saanen was used as the base breed), and heterosis. Random effects included additive animal genetic and doe permanent environmental effects. Estimates of heritabilities were 0.25 for MY, 0.24 for FY, 0.24 for PY, and 0.21 for SCS. The phenotypic correlations between MY, FY, and PY ranged from 0.90 to 0.96, and the genetic correlations ranged from 0.81 to 0.93. These results indicate lactation yield traits exhibit useful heritable variation and that multiple trait selection for these traits could improve milk revenue produced from successive generations of New Zealand dairy goats.  相似文献   

2.
Heritabilities and genetic correlations for milk production traits were estimated from first‐parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Legm) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits.  相似文献   

3.
Icelandic Cattle is a local dairy cattle breed in Iceland. With about 26,000 breeding females, it is by far the largest among the indigenous Nordic cattle breeds. The objective of this study was to investigate the feasibility of genomic selection in Icelandic Cattle. Pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) were compared. Accuracy, bias, and dispersion of estimated breeding values (EBV) for milk yield (MY), fat yield (FY), protein yield (PY), and somatic cell score (SCS) were estimated in a cross validation-based design. Accuracy (r^) was estimated by the correlation between EBV and corrected phenotype in a validation set. The accuracy (r^) of predictions using ssGBLUP increased by 13, 23, 19, and 20 percentage points for MY, FY, PY, and SCS for genotyped animals, compared with PBLUP. The accuracy of nongenotyped animals was not improved for MY and PY, but increased by 0.9 and 3.5 percentage points for FY and SCS. We used the linear regression (LR) method to quantify relative improvements in accuracy, bias (Δ^), and dispersion (b^) of EBV. Using the LR method, the relative improvements in accuracy of validation from PBLUP to ssGBLUP were 43%, 60%, 50%, and 48% for genotyped animals for MY, FY, PY, and SCS. Single-step GBLUP EBV were less underestimated (Δ^), and less overdispersed (b^) than PBLUP EBV for FY and PY. Pedigree-based BLUP EBV were close to unbiased for MY and SCS. Single-step GBLUP underestimated MY EBV but overestimated SCS EBV. Based on the average accuracy of 0.45 for ssGBLUP EBV obtained in this study, selection intensities according to the breeding scheme of Icelandic Cattle, and assuming a generation interval of 2.0 yr for sires of bulls, sires of dams and dams of bulls, genetic gain in Icelandic Cattle could be increased by about 50% relative to the current breeding scheme.  相似文献   

4.
Most studies on lactation curves only consider milk yield and describe a standard lactation curve of dairy cows, showing a peak or maximum daily yield occurring between 4 and 8 weeks after calving, followed by a daily decrease in milk yield until the cow is dried off. Wood's model is a widely used lactation curve function. Wood's model was fitted to test-day records of 95,405 lactations of parities lower than 5. Milk traits were milk yield (MY), fat percentage (F%), protein percentage (P%), fat yield (FY) and protein yield (PY), and the lactation curve was individually considered as a cluster of five linked curves. Milk trait and parity influence the goodness of fit of Wood's model. In 19.3% of the lactations, the shape of the MY, FY and PY curves follows the standard lactation curve while F% and P% have the reversed standard shape. The initial phase of lactation with the FY and PY curves contributes to the high variability of shapes.  相似文献   

5.
Genetic variability and genetic trends for 305-day milk yield (MY), 305-day fat yield (FY), and average 305-day fat percent (FP) were evaluated using monthly test-day records from first-lactation cows collected from 1991 to 2005 in 92 farms located in Central Thailand. Estimates of variance and covariance components and breeding values (EBV) were obtained using a multiple-trait animal model. Fixed effects were contemporary group (herd–year–season), calving age, additive genetic group as a function of Holstein fraction, and non-additive genetic group as function of heterosis effect. Random effects were animal and residual. Program ASREML was used to perform computations. Estimates of heritabilities were 0.38 ± 0.10 for MY, 0.25 ± 0.11 for FY, and 0.22 ± 0.11 for FP. Although the difference between the mean MY for cows in 1991 and 2005 was 324.1 kg, the regression of mean cow EBV for MY on year was 6.5 kg/year. Differences between mean cow EBV for FY and FP in 1991 and 2005 and their corresponding regressions of mean FY and FP on year were all near zero. Similarly, mean EBV for sires and dams of cows also showed near zero trends during these years. A factor contributing to the near complete absence of genetic trends was likely the variety of criteria used by producers to choose sires and to keep dams in addition to EBV (e.g., availability of semen, reproductive ability, adaptation to hot and humid conditions). It also appears that high percent Holstein cows failed to reach their production potential under the management, nutrition, and hot and humid climatic conditions in this tropical region. Changes in nutrition and management would be needed for high percent Holstein cows to show an upward trend in Central Thailand.  相似文献   

6.
The test‐day milk fat‐to‐protein ratio (TD‐FPR) could serve as a measure of energy balance status and might be used as a criterion to improve metabolic stability and fertility through genetic selection. Therefore, genetic parameters for fertility traits, test‐day milk yield (TD‐MY) and TD‐FPR, as well as, their relationships during different stages of lactation, were estimated on data collected from 25 968 primiparous Thai dairy crossbred cows. Gibbs sampling algorithms were implemented to obtain (co)variance components using both univariate linear and threshold animal models and bivariate linear‐linear and linear‐threshold animal models with random regression. Average TD‐MY and TD‐FPR were 12.60 and 1.15. Heritability estimates for TD‐MY, TD‐FPR and selected fertility traits ranged from 0.31 to 0.58, 0.17 to 0.19 and 0.02 to 0.05, respectively. Genetic correlations among TD‐FPR and TD‐MY, TD‐FPR and fertility traits, and TD‐MY and fertility traits ranged from 0.05 to ‐0.44, from ‐0.98 to 0.98 and ‐0.22 to 0.79, respectively. Selection for lower TD‐FPR would decrease numbers of inseminations per conception and increase conception at first service and pregnancy within 90 days. In addition, cow selection based only on high milk production has strong effects to prolong days to first service, days open and calving interval.  相似文献   

7.
The effects of test-day somatic cell scores (SCS) variations on milk and protein yields, and calving to first service and calving to conception intervals were studied in Tunisian Holsteins. There were 34,129, 25,700, and 18,077 test-day production records collected on first, second, and third parity cows, respectively. Records were of cows calving between 1996 and 2004 in 160 herds. Somatic cell scores and milk and protein yields were analysed using a linear model that included herd-test-day date and herd–year interactions, calving season, calving age, and calving to conception interval. Reproductive trait model included herd–year interaction, calving season, calving age, and month of insemination. Effects of SCS on milk and protein yields were studied by regressing current test-day yields on corresponding and preceding test-day SCS, while effects of SCS on fertility traits were investigated by separately regressing calving to first service and calving to conception intervals corrected for environmental and management factors on SCS corrected for actual milk yield. A cow produced around 19.0 kg (SD = 8.0 kg) and 0.6 kg (SD = 0.3 kg) milk and protein yields on a daily basis and had an average of 3.8 (SD = 2.1) SCS in the first three lactations. SCS varied consistently (p < 0.05) with herd-test-day date and herd–year interactions in all lactations. Days in milk, calving age, and calving to conception interval were all together important sources of variation (p < 0.05) for SCS mainly in the first and second parities. Test-day milk and protein yields were unfavourably affected by high SCS recorded in the same test-day and with a lesser degree by SCS observed in the nearest preceding test-day. Reduction in milk and protein productions from increased SCS varied from 0.23 to 1.76 kg and from 6 to 75 g, respectively. Likewise, increased test-day SCS lengthened both calving to first service (mean interval = 94.9 days; SD = 49.1 days) and calving to conception (mean interval = 161 days; SD = 69.6 days) intervals by 1.3 to 2.0 days for each unit increase in SCS. Using SCS in addition to milk traits as a criterion to select semen and improving veterinary care should result in increased milk and protein yields and in satisfactory fertility measures.  相似文献   

8.
Genetic parameters and genetic trends for weaning weight adjusted to 240 d of age (WW240), and weight gain from weaning to 24 mo of age (GW730) were estimated in a Colombian beef cattle population composed of Blanco Orejinegro, Romosinuano, Angus, and Zebu straightbred and crossbred animals. Calves were born and weaned in a single farm, and moved to 14 farms postweaning. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 2-trait model included the fixed effects of contemporary group (herd–year–season–sex), age of dam (WW240 only), breed direct genetic effects (as a function of breed fractions of calves), breed maternal genetic effects (as a function of breed fractions of dams; WW240 only), individual heterosis (as a function of calf heterozygosity), and maternal heterosis (as a function of dam heterozygosity; WW240 only). Random effects for WW240 were calf direct genetic, dam maternal genetic, permanent environmental maternal, and residual. Random effects for GW730 were calf direct genetic and residual. All relationships among animals were accounted for. Program AIREML was used to perform computations. Estimates of heritabilities for additive direct genetic effects were 0.20 ± 0.003 for WW240, and 0.32 ± 0.004 for GW730. Maternal heritability was 0.14 ± 0.002 for WW240. Estimates of heritability suggest that selection for preweaning and postweaning growth in this population is feasible. Low direct and maternal preweaning heritabilities suggest that nutrition and management should be improved to allow fuller expressions of calf direct growth and cow maternal ability. The genetic correlation between direct additive and maternal additive effects for WW240 was − 0.42 ± 0.009, indicating an antagonistic relationship between these effects. The correlation between additive direct genetic effects for WW240 and GW730 was almost zero (− 0.04 ± 0.009), suggesting that genes affecting growth preweaning may differ from those influencing growth postweaning. Trends were negative for direct WW240 and GW730 weighted yearly means of calves, sires, and dams from 1995 to 2006. Maternal WW240 showed near zero trends during these years. Trends for calf direct WW240 and GW730 followed sire trends closely, suggesting that more emphasis was placed on choosing sires than on dam replacements.  相似文献   

9.
Two experiments were conducted to measure the apparent ileal digestibility coefficients (AID) of protein and amino acids from canola meal (CM) and a pelleted canola meal (PCM) and their effect on specific activity (SA) of pancreatic proteases in weaned piglets and growing pigs. In experiment one, 24 piglets weaned at 17 days and weighing 5.5 kg were used. Treatments were a reference diet with 200 g of crude protein (CP) kg− 1 elaborated with casein (C) as the sole protein source, a diet containing C–CM and a diet containing C–PCM. These diets were obtained using the reference diet plus 100 g kg− 1 of CM or PCM that substituted an isoproteic mixture of casein and maize starch from reference diet, so that the AID coefficients for their protein and amino acids could be calculated by difference. In experiment two, nine castrated pigs weighing 39.5 kg were used. Treatments were a reference diet with 160 g of CP kg− 1 elaborated with casein (C) as the sole protein source, diet C–CM and diet C–PCM. These diets were obtained using the reference diet plus 300 g kg− 1 of CM or PCM that substituted an isoproteic mixture of casein and maize starch from reference diet. In piglets, the AID coefficients for casein were highest (P < 0.05), those of PCM were intermediate, and those of CM were the lowest. In older pigs, the AID coefficients for casein were highest, and those of CM and PCM were similar (P > 0.05). The SAs of chymotrypsin, trypsin and carboxypeptidases A and B were lower in piglets than in heavier pigs. Moreover, the SAs of trypsin, chymotrypsin, and carboxypeptidase B were lower (P > 0.05) in animals fed casein. The results showed in piglets that whereas CM was less digestible, pelleted canola meal improved protein and amino acid ileal digestibility, resulting in similar AID coefficients to those of growing pigs.  相似文献   

10.
The detection and mapping of genetic markers linked to quantitative trait loci (QTL) can be utilized to enhance genetic improvement of livestock populations. With the completion of the bovine genome sequence assembly, single nucleotide polymorphisms (SNP) assays spanning the whole bovine genome and research work on large scale identification, validation and analysis of genotypic variation in cattle has become possible. The objective of the present study was to perform a whole genome scan to identify and map QTL affecting milk production traits and somatic cell scores using linkage disequilibrium (LD) regression and 1536 SNP markers. Three and 18 SNP were found to be associated with only milk yield (MY) at a genome and chromosome wise significance (p < 0.05) level respectively. Among the 21 significant SNP, 16 were in a region reported to have QTL for MY in other dairy cattle populations and while the rest five were new QTL finding. Four SNP out of 21 are significant for the milk production traits (MY, fat yield, protein yield (PY), and milk contents) in the present study. Six and nine SNP were associated with PY at a genome and chromosome wise significant (p < 0.05) level respectively. Three and 17 SNP were found to be associated with FY at a genome and chromosome wise significant (p < 0.05) level. Five and seven SNP were mapped with somatic cell score at a genome and chromosome wise significant (p < 0.05) level respectively. The results of this study have revealed QTL for MY, PY, protein percentage, FY, fat percentage, somatic cell score and persistency of milk in the Canadian dairy cattle population. The chromosome regions identified in this study should be further investigated to potentially identify the causative mutations underlying the QTL.  相似文献   

11.
W.X. Wu  J.X. Liu  G.Z. Xu  J.A. Ye   《Livestock Science》2008,117(1):7-14
Forty multiparous Holstein dry cows on d 21 prepartum were randomly allocated to four blocks of 10 cows to examine the effects of reducing the dietary cation–anion difference (DCAD) on calcium homeostasis, acid–base balance, health status, and subsequent lactation performance. The reduced DCADs (Na + K − Cl − S, mEq/kg DM) of + 150,+ 50, − 50, and − 150 were obtained by addition of anionic salts. Reducing DCAD resulted in mild metabolic acidosis as indicated by the sharp decline in urinary pH, and minor reductions in blood pH and HCO3− concentration. Greater plasma calcium concentration was observed in cows fed diets of − 50 and − 150 DCAD (P < 0.05) than those on + 50 and + 150 DCAD diets. The nadir of plasma calcium level on the day of calving was lower (P < 0.05) than the highest level on d 14 prepartum (8.33 vs. 9.30 mg/dL). Composite colostrum calcium concentration was decreased (P < 0.05) with time on d 1 relative to d 2 postpartum (0.212 vs. 0.174%), and feeding of diet − 150 DCAD induced higher (P < 0.05) composite colostrum calcium content than other three DCAD diets. No case of milk fever occurred for any diets, but feeding the two negative DCAD diets reduced (P < 0.05) retained placenta incidence compared with diet of + 150 DCAD. Dry matter intake, milk yield and compositions of fat, protein, and lactose were non-significantly affected (P > 0.05) by dietary treatments. In conclusion, urinary pH is an effective indicator of extracellular fluid acid–base balance, and feeding negative DCAD in late gestation period is beneficial for dairy cows in blood calcium homeostasis and improvement of health status.  相似文献   

12.
Quantitative trait loci (QTL) in Danish Jersey and Danish Red cattle were independently mapped by least squares regression analysis. For Jersey breed, five grandsire families were genotyped for 186 markers on 16 chromosomes (BTAs). Eight traits analysed were milk yield (MY), fat percentage (FP), protein percentage (PP), clinical mastitis (CM), somatic cell score (SCS), maternal stillbirth, maternal calf size (MCS) and maternal calving difficulty. For Red breed, nine grandsire families were genotyped for 166 markers on 18 BTAs. Six traits analysed were MY, FP, PP, CM, SCS and female fertility. Nine and five QTL were detected in Jersey and Red breed, respectively, in across family tests. In Jersey breed, the results indicate QTL for CM and MCS on BTA 3. Additionally, there is an indication of QTL for MCS and FP on BTA 1 and a tentative evidence for a QTL for MY on BTA 26. There is a high risk of detected QTL being false positives. The detected QTL in Jersey breed indicate interesting results from a breeding perspective, but a practical application should await genome-wide association studies.  相似文献   

13.
Genetic parameters were estimated for protein yield (PY), clinical mastitis (CM), somatic cell score, number of inseminations (NI) and days from calving to first insemination (CFI) in first‐parity Swedish Red cows by series of tri‐variate linear animal models. The heritability of PY was moderate (0.34 ± 0.004), and the heritabilities of the functional traits were all low (0.014 ± 0.001–0.14 ± 0.004). The genetic correlation between CM and CFI (0.38 ± 0.05) was stronger than the correlation between CM and NI (0.05 ± 0.06), perhaps because CM and CFI usually are observed in early lactation when the cow is likely to be in negative energy balance, whereas NI generally is recorded when the cow is not in negative energy balance any more. The genetic correlation between NI and CFI was very close to zero (?0.002 ± 0.05), indicating that these two fertility traits have different genetic backgrounds. All genetic correlations between PY and the functional traits were moderate and unfavourable, ranging from 0.22 ± 0.02 to 0.47 ± 0.03. In addition, the effect of including genetic and phenotypic correlations between the trait groups milk production, udder health and female fertility on the accuracy of the selection index was quantified for a heifer, a cow and a proven bull. The difference between the accuracy obtained by multi‐trait and single‐trait evaluations was largest for the cow (0.012) and small for the heifer and the bull (0.006 and 0.004) because the phenotype of the cow for one trait could assist in predicting the Mendelian sampling term for a correlated trait.  相似文献   

14.
A total of 4007 lactation records from 1520 Saanen goats kidding from 1999 to 2006 and obtained from 10 herds in Guanajuato, Mexico, were analyzed to estimate the heritabilities, repeatabilities, as well as genetic, environmental and phenotypic correlations for milk yield (MILK), fat yield (FAT), protein yield (PROT), fat content (%FAT), protein content (%PROT) and age at fist kidding (AFK). A five-trait repeatability model was used to estimate (co)variances for milk traits, and a four-trait animal model for first lactation records was used to estimate (co)variances involving AFK. For MILK, FAT, PROT, %FAT, %PROT and AFK, heritability estimates were 0.17 ± 0.04, 0.19 ± 0.05, 0.17 ± 0.04, 0.32 ± 0.06, 0.38 ± 0.07 and 0.31 ± 0.09, respectively. Repeatabilities for MILK, FAT, PROT, %FAT and %PROT were 0.43 ± 0.02, 0.42 ± 0.02, 0.42 ±0.02, 0.64 ± 0.02, and 0.63 ± 0.02, respectively. The genetic correlations between MILK and FAT, and between MILK and PROT, were high and positive (0.72 ± 0.08 and 0.87 ± 0.04, respectively). Genetic correlations between MILK and %FAT, between MILK and %PROT and between MILK and AFK, were − 0.24 ± 0.16, − 0.30 ± 0.15 and − 0.18 ± 0.23, respectively. Genetic correlations between AFK and FAT and between AFK and PROT were − 0.09 ± 0.24 and − 0.17 ± 0.25, respectively; and genetic correlations between AFK and %FAT and between AFK and %PROT were 0.29 ± 0.35 and 0.14 ± 0.27, respectively. Selection for milk traits is possible using a repeatability animal model. Selection for milk production traits would probably not increase AFK, but more precise estimates of the genetic correlations are required. Selection to lower AFK is possible. These (co)variance estimates would make it possible to predict the selection responses from different economic indices in order to maximize the economic responses for the local markets.  相似文献   

15.
An understanding of influencing factors and genetic principles affecting the growth traits is needed to implement optimal breeding and selection programs. In this study, heritabilities (direct additive and maternal) of body weights at birth (BW0), 90 days (BW90) and 300 days (BW300) of age and average daily gains from birth to 90 days (ADG0-90), birth to 300 days (ADG0-300) and 90 days to 300 days (ADG90–300) of age in Boer goats were estimated on the basis of 1520 Boer goats at Boer Goat Breeding Station in Yidu, China, during 2002–2007. The parameters were estimated using a DFREML procedure by excluding or including maternal genetic or permanent maternal environmental effects, four analysis models were fitted in order to optimize the model for each trait. Influencing factors such as parity, litter size, kidding year and season, as well as sex of kids and some significant interactions among these factors were investigated as the fixed effects for the models. The results showed that the birth year and maternal genetic effects such as parity and litter size of dam were important determinants of the genetic parameter estimates for pre-weaning growth traits, and environmental effects such as birth year, season and sex of kids had some significant effect on post-weaning growth traits. The mean values and standard errors (SE) of direct additive heritability estimates calculated with the optimum model were 0.17 ± 0.07, 0.22 ± 0.08, 0.07 ± 0.07, 0.10 ± 0.08, 0.30 ± 0.12 and 0.08 ± 0.10 for BW0, BW90, ADG0-90, BW300, ADG0-300 and ADG90–300, respectively. For pre-weaning weights, correlation estimates between direct additive and maternal genetic (ra–m) effect were high and negative ranging from − 0.74 to − 0.86.  相似文献   

16.
Abstract

Genetic parameters were estimated for lactation average somatic cell score (SCS) and clinical mastitis (CM) for the first three lactations of multiparous Finnish Ayrshire cows. A multi-trait linear sire model was used for estimation of covariance components, and the efficiencies of single- versus multi-trait multi-lactation (MT) sire evaluations were compared. Heritability of SCS and CM in the first three lactations ranged from 0.11 to 0.13 and 0.02 to 0.03, respectively. Within lactation, genetic correlations between SCS and CM ranged from 0.68 to 0.72. Within both traits, across-lactation genetic correlations were lowest between 1 and 3, and highest between 2 and 3, with estimates ranging from 0.75 to 0.86 and from 0.81 to 0.98 for CM and SCS, respectively. Residual and phenotypic correlations were low and ranged from 0.09 to 0.13 and from 0.10 to 0.13, respectively. The absolute difference between genetic and residual correlations was from 0.5 to 0.6. Within-lactation genetic correlations between traits that are much less than unity suggest a multi-trait model for genetic evaluation of mastitis resistance. Comparison of model prediction performance between single-trait (ST) and MT models using a data splitting method showed that the MT model was more stable in predicting breeding values in future records of animals. Especially, for young sires and CM, the SD of EBVs from the MT model was 14 to 23% higher than the ST model, indicating more effective use of information in terms of revealing more genetic variation.  相似文献   

17.
The objective of this study was to estimate genetic parameters for milk yield, stayability, and the occurrence of clinical mastitis in Holstein cows, as well as studying the genetic relationship between them, in order to provide subsidies for the genetic evaluation of these traits. Records from 5,090 Holstein cows with calving varying from 1991 to 2010, were used in the analysis. Two standard multivariate analyses were carried out, one containing the trait of accumulated 305-day milk yields in the first lactation (MY1), stayability (STAY) until the third lactation, and clinical mastitis (CM), as well as the other traits, considering accumulated 305-day milk yields (Y305), STAY, and CM, including the first three lactations as repeated measures for Y305 and CM. The covariance components were obtained by a Bayesian approach. The heritability estimates obtained by multivariate analysis with MY1 were 0.19, 0.28, and 0.13 for MY1, STAY, and CM, respectively, whereas using the multivariate analysis with the Y305, the estimates were 0.19, 0.31, and 0.14, respectively. The genetic correlations between MY1 and STAY, MY1 and CM, and STAY and CM, respectively, were 0.38, 0.12, and ?0.49. The genetic correlations between Y305 and STAY, Y305 and CM, and STAY and CM, respectively, were 0.66, ?0.25, and ?0.52.  相似文献   

18.
Genetic parameters for average daily gain between the age of 5 and 10 weeks (ADG), the average cross-sectional area of the m. Longissimus dorsi (L) (between the 2nd–3rd and 4th–5th lumbar vertebrae-based on in vivo computerized tomography (CT)) and dressing out percentage (DoP) were estimated in a group of 28,686 Pannon White rabbits reared in 5044 litters and born between 2000 and 2003. Using multivariate animal models with Bayesian procedures, estimated heritabilities were moderate and moderately high for ADG, L and DoP (0.21 to 0.29, 0.25 to 0.42 and 0.19 to 0.71, respectively). Litter effects were moderate for ADG, L and DoP estimates (0.20 to 0.22, 0.10 to 0.18 and 0.09 to 0.30, respectively). Genetic correlation coefficient estimates between ADG and L and ADG and DoP were moderate and negative (− 0.41 to − 0.01, − 0.70 to + 0.10). A moderately high positive genetic correlation was found between L and DoP (0.13 to 0.83).  相似文献   

19.
Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross‐bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick‐resistant animals.  相似文献   

20.
Birth weight and calving difficulty were analyzed with Bayesian methodology using univariate linear models, a bivariate linear model, a threshold model for calving difficulty, and a joint threshold-linear model using a probit approach. Field data included 26,006 records of Gelbvieh cattle. Simulated populations were generated using parameters estimated from the field data. The Gibbs sampler was used to obtain estimates of the marginal posterior mean and standard deviation of the (co)variance components, heritabilities, and correlations. In the univariate analyses, the posterior mean of direct heritability for calving difficulty was .23 with the threshold model and .18 with the linear model. Maternal heritabilities were .10 and .08, respectively. In the bivariate analysis, posterior means of direct heritability for calving difficulty were .21 and .18 for the bivariate linear-threshold and linear-linear model, respectively. Maternal heritabilities were .09 and .06, respectively. Direct heritability for birth weight was .25 for the univariate model and .26 for bivariate models. Maternal heritability was .05 for the linear-threshold model and the univariate model and .06 for the bivariate linear model. Genetic correlation between direct genetic effects in both traits was .81 for the linear-threshold model and .79 for the bivariate linear. Residual correlation was .35 for the bivariate linear model and .50 for the bivariate linear-threshold. A simulation study confirmed that the posterior mean of the marginal distribution was suitable as a point estimate for univariate threshold and bivariate linear-threshold models.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号