Pregnancy scanning can be used as a source of data for genetic evaluation of reproductive traits of ewes

2016 ◽  
Vol 56 (4) ◽  
pp. 679 ◽  
Author(s):  
Kim L. Bunter ◽  
Andrew A. Swan ◽  
Ian W. Purvis ◽  
Daniel Brown
Keyword(s):  
Litter Size ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Genetic Evaluation ◽  
Fine Tuning ◽  
Data Sources ◽  
Inconsistency Rate ◽  
Scan Data ◽  
Time Frames

Reproductive traits generated from mothering up lambs to ewes (n = 59 603 records) were compared with data resulting from pregnancy scanning (n = 46 663 records), to examine the consistency between the two data sources for deriving specific reproductive traits and to estimate genetic parameters. The reproductive traits considered were fertility (FERT: 0/1) of ewes joined, total litter size (LSIZE: lambs born), the number of lambs surviving at weaning (LSIZEW: lambs weaned) and the percentage of lambs surviving (LSURV = LSIZEW/LSIZE) for ewes that lambed, along with the composite traits number of lambs born (NLB) and number weaned (NLW) for ewes joined. Corresponding trait values were derived from pregnancy scan data (FERT_S, LSIZE_S and NLB_S) for comparison, and were classified as inconsistent if the trait values did not match from scanning and lambing records. Data were obtained from four flocks, representing different time frames, locations, management and breeds or bloodlines. Each flock recorded scan data separately from lambing outcomes. Genetic parameters were estimated separately within each flock. Average levels of inconsistency between scan- and lambing-data values varied between 4.6% and 14.8% across flocks, tending to be highest (9.1–18.5%) for litter size of ewes scanned with multiple fetuses, and lowest (0.29–7.3%) for assignment of fertility. Inconsistencies did not have a significant impact on estimates of trait heritabilities, suggesting recording errors were independent of genetic merit. In three flocks, the genetic correlations (ra) between comparable traits derived from the different data sources were not different from unity (ra ≥ 0.99) even when phenotypic correlations (rp) were lower (rp ≥ 0.84). In the flock with the highest inconsistency rate between data sources, the range in ra varied between 0.60 (fertility) and 1.0 (litter size). Therefore, pregnancy scan data can be directly substituted for reproductive traits traditionally based on lambing data, but attention should be paid to ensuring accuracy of the data sources used. Scan data also provide no information on lamb-survival outcomes after birth, so does not constitute complete data on reproductive outcomes. Genetic evaluation systems might also benefit from fine tuning for scale-induced effects (due to litter size) on parameters to improve the accuracy of across flock prediction of breeding values for reproductive traits.

Genetic parameters for Australian maternal and dual-purpose meatsheep breeds. I. Liveweight, wool production and reproduction in Border Leicester and related types

1994 ◽  
Vol 45 (2) ◽  
pp. 459 ◽  
Author(s):  
LD Brash ◽  
NM Fogarty ◽  
SA Barwick ◽  
AR Gilmour
Keyword(s):  
Genetic Correlation ◽  
Litter Size ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Heritability Estimate ◽  
Reproductive Traits ◽  
Phenotypic Correlation ◽  
Data Set ◽  
Reproduction Traits ◽  
Fleece Weight

Analyses of two separate Border Leicester data sets are reported. In the first set, genetic parameters were estimated for 14 month liveweight and greasy fleece weight from 1312 ewe and ram records representing 75 sires of the Border Leicester and Glen Vale breeds (a related genotype) using derivative-free REML procedures. The heritability estimate for liveweight was 0.24 � 0.07 and greasy fleece weight was 0.17 � 0-05, with the genetic correlation being -0 21 � 0 -30 and phenotypic correlation 0.54 � 0.02. In the second data set, reproductive performance was analysed and genetic parameters were estimated from 7395 joining records for 1604 ewes, representing 165 sires, from two Border Leicester stud flocks. Reproduction traits analysed were fertility (ewes lambing of ewes joined), litter size (lambs born per ewe lambing) and lambs born (per ewe joined). The studs differed in performance for all reproductive traits; fertility (67 v. 82%), litter size (1-27 v. 1-43) and lambs born (85 v. 117%). The estimates of heritability and repeatability respectively for ewe performance were: fertility 0.01 � 0.01 and 0.05 � 0 01, litter size 0.01 � 0.02 and 0.05 � 0.01, lambs born 0.00 � 0.01 and 0.06 � 0.01. Estimates of heritability for average ewe lifetime performance were 0.04% 0.05 for fertility, 0-02 �0.05 for litter size and 0.03 � 0.05 for lambs born, based on averages of 4.6 joining and 3.5 litter size records for ewes. The genetic correlations between lambs born and its components fertility (0.96 � 0.18) and litter size (0.83 � 0.44) were high, with the genetic correlation between fertility and litter size being 0.65 � 0.52. Implications for breeding programs for Border Leicester flocks within LAMBPLAN are discussed.

scholarly journals Genetic parameters and genetic gains for reproductive traits of Arabi sheep

2015 ◽  
Vol 31 (1) ◽  
pp. 23-36 ◽  
Author(s):  
H. Roshanfekr ◽  
P. Berg ◽  
K. Mohammadi ◽  
Mirza Mohamadi
Keyword(s):  
Litter Size ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Least Square ◽  
Research Station ◽  
Environmental Correlations ◽  
Breeding Values ◽  
Litter Weight

The current study reports, for the first time, the genetic parameters and genetic, phenotypic and environmental correlations and trends of reproductive traits in Arabi sheep. Data were collected at Animal Science Research Station of Khuzestan Ramin Agricultural and Natural Resources University (ASRSKRANRU), south-west of Iran from 2001 to 2008. Litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB) and total litter weight at weaning (TLWW) averaged 1.11 lambs, 1.01 lambs, 3.83 kg, 19.43 kg, 4.16 kg and 20.12 kg, respectively. Genetic parameters and correlations were estimated with univariate and bivariate models using restricted maximum likelihood, breeding values of animals were estimated with best linear unbiased prediction (BLUP) and genetic- and phenotypic trends by regression of ewes? average breeding values and phenotypic least square means on year of birth respectively. Random effects were fitted by additive direct genetic effects and permanent environment related to the ewe as well as service sire effects, in addition to fixed effects of ewe age at lambing and lambing year. Heritability estimates of 0.05, 0.02, 0.13, 0.12, 0.04, and 0.06, and repeatability estimates of 0.08, 0.06, 0.17, 0.16, 0.14 and 0.21 for the six traits, respectively. Genetic correlations between traits varied from ?0.82 to 0.94. Phenotypic correlations were lower, ranging from ?0.33 to 0.52. Estimated annual genetic progress was very low; ?0.003 lambs for LSW and 15 g for TLWW. Annual phenotypic trend was only significant for LSW being 0.007 lambs. The study concluded that indirect selection based on total litter weight at weaning could be efficient for the traits studied.

scholarly journals Genetic Analysis of Basic and Composite Reproduction Traits in Guilan Sheep

2017 ◽  
Vol 17 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Bahareh Eteqadi ◽  
Navid Ghavi Hossein-Zadeh ◽  
Abdol Ahad Shadparvar
Keyword(s):  
Litter Size ◽  
Fixed Effects ◽  
Production Efficiency ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Meat Production ◽  
Environmental Correlations ◽  
Litter Weight ◽  
The North

Abstract The objective of the present study was to estimate genetic parameters for reproductive traits in Guilan sheep. Data were comprised of 14,534 records of lambs from 136 sires and 2,021 dams which were collected during 1994 to 2011 by the Agriculture Organization of Guilan Province in the north of Iran. The basic reproductive traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), and litter mean weight per lamb weaned (LMWLW). The composite reproductive traits were total litter weight at birth per ewe lambing (TLWB) and total litter weight at weaning per ewe lambing (TLWW). The general linear model procedure of SAS was used for determining the fixed effects which had significant effect on the traits under study. The flock-year-season of lambing had significant effect on studied traits (P<0.01). The genetic parameters were estimated with repeatability animal model using restricted maximum likelihood (REML) procedure of the Wombat program. Direct heritability estimates were 0.00, 0.00, 0.01, 0.01, and 0.03 for LSB, LSW, LMWLW, TLWB, and TLWW, respectively, and corresponding repeatabilities were 0.2, 0.00006, 0.01, 0.972 and 0.034, respectively. Genetic correlation estimates between traits ranged from -0.99 for LSB-LSW to 0.99 for LMWLW-TLWW. Phenotypic correlations ranged from -0.09 for LSB-TLWB to 0.98 for LMWLW-TLWW and environmental correlations ranged from -0.03 for LSW-TLWW to 0.98 for LMWLW-TLWW. The results showed that strong positive genetic correlations of LMWLB and LMWLW with other traits may improve meat production efficiency in Guilan sheep. The low estimates of heritability and repeatability obtained for ewe productivity traits indicate that selection based on the ewe’s own performance may result in slow genetic improvement.

scholarly journals Genetic Evaluation of Reproductive and Metabolic Disorders and Displaced Abomasum in Czech Holstein Cows

2019 ◽  
Vol 67 (4) ◽  
pp. 939-946
Author(s):  
Eva Kašná ◽  
Petr Fleischer ◽  
Ludmila Zavadilová ◽  
Soňa Šlosárková
Keyword(s):  
Metabolic Disorders ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Health Data ◽  
Genetic Evaluation ◽  
Holstein Cows ◽  
Retained Placenta ◽  
Cystic Ovary ◽  
On Line ◽  
Parturient Paresis

We estimated the genetic parameters of the most frequent reproductive and metabolic disorders as recorded on‑line by 55 milk producers in Czech Holstein cows in the Diary of Diseases and Treatments. The dataset covered the period from July 2015 to May 2019. The coefficients of heritability were estimated for retained placenta (h2 = 0.01), metritis (h2 = 0.04), endometritis (h2 = 0.03), cystic ovary disease (h2 = 0.03), parturient paresis (h2 = 0.01), ketosis (h2 = 0.01) and displaced abomasum (h2 = 0.03). Positive genetic correlations different from 0 were estimated between parturient paresis and displaced abomasum (rg1g2 = 0.75), retained placenta and metritis (rg1g2 = 0.61), displaced abomasum and endometritis (rg1g22 = 0.49), metritis and endometritis (rg1g2 = 0.45), and metritis and displaced abomasum (rg1g2 = 0.41). Because each farmer recorded a slightly different portfolio of health data, the genetic correlations with metabolic disorders couldn’t be estimated in most cases, since the number of observations was not sufficient.

Phenotypic and genetic parameters for reproductive performance in a synthetic line of sheep

1981 ◽  
Vol 96 (1) ◽  
pp. 107-113 ◽  
Author(s):  
T. G. Martin ◽  
D. Nicholson ◽  
C. Smith ◽  
D. I. Sales
Keyword(s):  
Reproductive Performance ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Direct Selection ◽  
Sex Distribution ◽  
Regression Methods ◽  
Litter Weight ◽  
Heritability Estimates ◽  
Synthetic Line

SUMMARYData on 902 ewes (1755 records) bom over 7 years in the synthetic ABRO Dam Line were analysed by least squares. Reproductive traits of the ewe were not affected by whether she was a single or a twin or by the age of her dam. Ewe age had major effects on all reproductive traits. Litter weight traits were affected by the sex distribution and the age of the litter when weighed.Heritability estimates, both by half sib and regression methods, were low for litter size, low to moderate for litter weights, and higher for ewe and fleece weights. Genetic correlations among the litter-weight traits were high. Together with the heritability estimates, they indicated that selection on litter weight at birth (and perhaps other traits) might give a greater change in total litter weight at weaning, the main measure of ewe productivity and the objective in improvement, than would direct selection.

Genetic correlations for reproductive and growth traits in rabbits

2020 ◽  
Vol 100 (2) ◽  
pp. 317-322 ◽  
Author(s):  
Rym Ezzeroug ◽  
Rafik Belabbas ◽  
Maria José Argente ◽  
Ali Berbar ◽  
Samir Diss ◽  
...  
Keyword(s):  
Litter Size ◽  
Coefficient Of Variation ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
High Coefficient ◽  
Genetic And Phenotypic Correlations ◽  
The Common ◽  
Large Coefficient ◽  
Size At Birth

The objective of this study was to obtain heritability estimates for reproductive (litter size at birth, number born alive, litter size at weaning) and growth traits (individual weaning weight, individual weight at the end of the fattening period), then determine the genetic correlation between them in a synthetic rabbit line. A total of 805 females, 3242 parities, and 18 472 growth records were measured from 2006 to 2017. A pentavariate animal model was used with reproductive and growth traits. Heritability ranged from 0.025 to 0.126 for reproductive traits and from 0.033 to 0.059 for growth traits. These traits showed a large coefficient of variation (from 32% to 56% for reproductive traits and from 21% to 28% for growth traits). The repeatability of reproductive traits was low and the common litter effect for growth traits was the most important component of total variance. The genetic and phenotypic correlations between reproductive and growth traits were high and negative, especially with weight at weaning (−0.848, −0.922, and −0.854 for litter size at birth, number born alive, and litter size at weaning, respectively). In conclusion, because of the high negative correlation between reproductive and growth traits, both reproductive and growth traits should be selected in independent lines and the response to selection should be due mainly to the high coefficient of variation of the traits.

Multitrait and repeatability estimates of random effects on litter size in sheep

2002 ◽  
Vol 74 (2) ◽  
pp. 209-216 ◽  
Author(s):  
C. Hagger
Keyword(s):  
Litter Size ◽  
Random Effects ◽  
Genetic Gain ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Parameter Estimates ◽  
Data Sets ◽  
Phenotypic Variance ◽  
The Third ◽  
Meat Sheep

AbstractFive data sets with records of first, second and third lambings of the White Alpine sheep (WAS1, WAS2), the Brown-Headed Meat sheep (BFS), the Black-Brown Mountain sheep (SBS) and the Valais Black-Nose sheep (SNS) of Switzerland were used to estimate phenotypic and genetic parameters for litter size using a multitrait and a repeatability model by the REML method. The sets contained litter information from 26 274, 25 165, 18 913, 14 953 and 21 726 ewes, respectively. Average numbers of litters per ewe were between 2·09 and 2·31. Average litter sizes at birth were between 1·36 and 1·57 lambs in first, between 1·52 and 1·75 in second and, between 1·56 and 1·86 in third parities. Multitrait estimates of heritability for size of first litters were 0·164, 0·157, 0·117, 0·223 and 0·116 for the WAS1, WAS2, BFS, SBS and SNS data, respectively. The corresponding estimates were 0·176, 0·165, 0·140, 0·208 and 0·134 for second and, 0·141, 0·155, 0·121, 0·145 and 0·107 for third litters. The systematic increase in phenotypic variances from first to third litter within data sets favoured the multivariate over the repeatability approach. Genetic correlations between size of the first three litters were, with one exception, above 0·927. Random flock ✕ year and sire of litter effects contributed between 2·2% and 13·2% and between 0·7% and 4·7% to the phenotypic variance of the traits, respectively. Residuals contributed between 70·6% and 84·2% to this parameter, estimates for the third litter were always highest. Heritability estimates from the repeatability model were smaller than the smallest multivariate estimates. Expected genetic gain in litter size from selection on the multitrait model was equal to the achieved response from the repeatability approach.

Within-farm estimates of genetic and phenotypic parameters for growth and reproductive traits for red deer

1993 ◽  
Vol 57 (1) ◽  
pp. 153-159 ◽  
Author(s):  
C. McManus
Keyword(s):  
Birth Weight ◽  
Maximum Likelihood ◽  
Eastern Europe ◽  
Red Deer ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
The Other ◽  
The United Kingdom ◽  
Terminal Sire

AbstractGenetic and phenotypic parameters were estimated for farmed red deer on eight farms distributed throughout the United Kingdom. Genetic parameters were estimated using restricted maximum likelihood (REML) analysis. Heritabilities for date of calving were low on seven of the eight farms (< 0–05), while repeatabilities were low to moderate (0·06 to 0·37). Heritabilities of all weights tended to be moderate to high on most farms (0·31 to 0·49; 0·22 to 0·89; 0·33 to 0·48; 0·37 to 0·45 and 0·37 to 0·90 for birth weight, weaning weight, mid-winter weight, turn-out weight and other weights respectively). The exception was farm 8 for which heritability estimates were very low (<0·08). This is attributed to inbreeding effects on this farm. Phenotypic and genetic correlations between post-weaning traits tended to be high, indicating selection at any stage of growth will be expected to lead to an increased growth at the other stages. Animals whose bloodlines originated in the forests of Eastern Europe (Yugoslavia, Hungary, Germany) were heavier at all stages indicating their usefulness as ‘terminal sire’ breeds. Hinds of mainland ‘European’ parentage also tended to calve earlier.

scholarly journals 69 A new frame score system for Nelore cattle

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 47-47
Author(s):  
Roberto D Sainz ◽  
Nayanny Guimarães ◽  
Cláudio U Magnabosco ◽  
Fernando Lopes
Keyword(s):  
Body Composition ◽  
Beef Cattle ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Subcutaneous Fat ◽  
Heritability Estimate ◽  
Reproductive Traits ◽  
Carcass Weight ◽  
Muscle Area ◽  
Nelore Cattle

Abstract Frame score (FS) systems for beef cattle generally represent the relationships among growth, body composition, reproduction and mature size, in a simple and practical form. This study aimed to: 1) develop a FS system for Nelore cattle that is biologically sound, easy to interpret, and useful for producers; and 2) estimate the genetic parameters of the FS with productive and reproductive traits. An arbitrary scale (1 to 12) was devised so that each unit corresponds to 15 kg of carcass weight (1 @), as this is a common measure used for marketing beef cattle in Brazil. Therefore, ideal carcass weight, defined as having 6 mm of backfat, would be 18 @ (269 kg) and 15 @ (224 kg) for FS = 6 males and females, respectively. Data from 36,030 animals (22,405 males, 13,565 females) raised on pasture were obtained from participating herds of the National Association of Breeders and Researchers (ANCP). Genetic parameters were estimated in uni- and bicharacteristic analyses under an animal model, using the EM-REML algorithm (AIREMLF90) and Bayesian inference (GIBBS1F90). The heritability estimate for the new FS was 0.38, and its additive genetic correlations were 0.70, 0.72, 0.77, 0.33, -0.57, 0.27, and 0.28 with BW at 365 d, BW at 450 d, hip height, longissimus muscle area, subcutaneous fat thickness, scrotal circumference at 450 d, and age at first calving, respectively. The estimated heritability and genetic correlations indicate that there is enough additive genetic variability to allow for genetic response to selection. The estimates support the notion that larger frame animals are taller, heavier, leaner and later maturing, both in body composition as well as sexually. The new frame score may be a useful tool for genetic selection of animals that are best suited to their environment.

scholarly journals Analysis of Genetic Parameters for Reproductive Traits in Crossbred Dairy Cattle Maintained at Holetta Agricultural Research Center.

2020 ◽  
Vol 39 (01) ◽  
Author(s):  
Kefale Getahun ◽  
Million Tadesse ◽  
Direba Hundie
Keyword(s):  
Dairy Cattle ◽  
Genetic Parameters ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Agricultural Research ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Breeding Value ◽  
Research Center ◽  
Phenotypic Correlation

This study was aimed to generate information on variance components and the resulting genetic parameters (heritability, repeatability, genetic and phenotypic correlations and genetic trends) of some economic traits of Borena and its crosses with Holstein Friesian dairy cattle maintained at Holetta agricultural research center dairy farm. Traits studied were age at first service (AFS), age at first calving (AFC), calving interval (CI), days open (DO) and number of service per conception (NSC). Overall, 11331 dairy cattle reproductive performance records were used for the study. WOMBAT, which is a software package for quantitative genetic analysis of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters were employed and obtained. Heritability values of reproductive traits were from very low (0.071, 0.082 and 0.012) for CI, DO and NSC to moderate (0.3 and 0.22) for AFC and AFS traits. Repeatability estimate for CI, DO and NSC were low (0.17, 0.17 and 0.129). Strong and positive genetic correlation (0.98) was appeared between AFS and AFC traits. Negative genetic correlations were observed between AFS and DO (-0.001), AFC and DO (-0.05), AFS and NSC (-0.022), AFC and NSC (-0.29) and CI and NSC (-0.31). AFS were negative phenotypic correlation with CI, DO and NSC. Similarly, AFC was negative phenotypic correlation with CI and DO. Low phenotypic correlation was observed between AFC and NSC, CI and DO, CI and NSC and, DO and NSC. Strong and positive phenotypic correlation was appeared between AFS and AFC. The regression coefficient of mean breeding value for NSC, CI, DO, AFC and AFS on year of birth were -0.0066x+13.25 times/year, -1.19x+2387.4 days/year, -1.23x+2445.6 days/year, 0.2x-410 months/year and 0.48x-980 months/year, respectively.

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