Ullengala, Rajkumar;Prince, L. Leslie Leo;Paswan, Chandan;Haunshi, Santosh;Chatterjee, Rudranath
Animal Bioscience
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v.34
no.4
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pp.471-481
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2021
Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.
Mohammed Bedhane;Julius van der Werf;Sara de las Heras-Saldana;Leland Ackerson IV;Dajeong Lim;Byoungho Park;Mi Na Park;Seunghee Roh;Samuel Clark
Journal of Animal Science and Technology
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v.65
no.6
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pp.1180-1193
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2023
Most carcass and meat quality traits are moderate to highly heritable, indicating that they can be improved through selection. Genetic evaluation for these types of traits is performed using performance data obtained from commercial and progeny testing evaluation. The performance data from commercial farms are available in large volume, however, some drawbacks have been observed. The drawback of the commercial data is mainly due to sorting of animals based on live weight prior to slaughter, and this could lead to bias in the genetic evaluation of later measured traits such as carcass traits. The current study has two components to address the drawback of the commercial data. The first component of the study aimed to estimate genetic parameters for carcass and meat quality traits in Korean Hanwoo cattle using a large sample size of industry-based carcass performance records (n = 469,002). The second component of the study aimed to describe the impact of sorting animals into different contemporary groups based on an early measured trait and then examine the effect on the genetic evaluation of subsequently measured traits. To demonstrate our objectives, we used real performance data to estimate genetic parameters and simulated data was used to assess the bias in genetic evaluation. The results of our first study showed that commercial data obtained from slaughterhouses is a potential source of carcass performance data and useful for genetic evaluation of carcass traits to improve beef cattle performance. However, we observed some harvesting effect which leads to bias in genetic evaluation of carcass traits. This is mainly due to the selection of animal based on their body weight before arrival to slaughterhouse. Overall, the non-random allocation of animals into a contemporary group leads to a biased estimated breeding value in genetic evaluation, the severity of which increases when the evaluation traits are highly correlated.
Two different animal models, which differ in whether or not taking maternal genetic effect into account, for estimating genetic parameters of cashmere weight, live body weight, cashmere thickness, staple length, fiber diameter, and fiber length in Inner Mongolia White Cashmere Goat were compared via likelihood ratio test. The results indicate that maternal genetic effect has significant influence on live body weight and cashmere thickness, but no significant influence on the other traits. Using models suitable for each trait, both genetic parameters and trends were analyzed with the MTDFREML program. Heritability estimates from single trait models for cashmere weight, live body weight, cashmere thickness, staple length, fiber diameter and fiber length were found to be 0.30, 0.07, 0.21, 0.29, 0.28 and 0.21, respectively. Genetic correlation estimates from two-trait models between live body weight and all other traits (-0.06~0.07) was negligible, as were those between fiber diameter and all other traits (-0.01~0.03) except cashmere thickness (0.19). Cashmere weight and staple length had moderate to low genetic correlations with other traits (-0.24~0.39 and -0.24~0.34, respectively) except for live body weight and fiber diameter. Cashmere thickness had a strong genetic correlation with fiber length (0.81), and low genetic correlation with other traits (0.19~0.34) except live body weight. Genetic trend analysis suggests that selection for cashmere weight was very effective, which has led to the slow genetic progress of cashmere thickness and fiber length due to their genetic correlations with cashmere weight. The selection for live body weight was not effective, which was consistent with its low inheritability.
In order to investigate the relation of production traits and reproduction traits the data from Gyungnam heugdon(Berkshire) were analyzed. Pearson correlation coefficients of the reproductive traits including days to first farrowing, days to first breeding and no. of breeding for first litter with back fat thickness were ranged -.24 to -.26. Estimates of heritability and genetic correlation for the reproductive traits including days to first farrowing, days to first breeding and no. of breeding for first litter showed frequent and wide fluctuation due to lack of reproductive records. Pearson correlation coefficients of back fat with litter traits were low, but genetic correlation coefficients were relatively high. Genetic correlation coefficients of back fat with total litter size, pigs born alive, litter weight at birth and litter weight at weaning were .21, .24, .11 and .07 respectively. It suggests that thin back fat thickness deteriorates performance of litter traits. Genetic correlation coefficients of days to 90kg with total litter size, pigs born alive, litter weight at birth and litter weight at weaning were .14, .17, .09 and .00 respectively. This result imply that genetic improvement on the production traits reduce the litter trait performance.
Currently, boars selected for commercial use as AI sires are evaluated on grow-finish performance and carcass characteristics. If AI sires were also evaluated and selected on semen production, it may be possible to reduce the number of boars required to service sows, thereby improving the productivity and profitability of the boar stud. The objective of this study was to estimate genetic correlations between production and semen traits in the boar: average daily gain (ADG), backfat thickness (BF) and muscle depth (MD) as production traits, and total sperm cells (TSC), total concentration (TC), volume collected (SV), number of extended doses (ND), and acceptance rate of ejaculates (AR) as semen traits. Semen collection records and performance data for 843 boars and two generations of pedigree data were provided by Smithfield Premium Genetics. Backfat thickness and MD were measured by real-time ultrasound. Genetic parameters were estimated from five four-trait and one five-trait animal models using MTDFREML. Average heritability estimates were 0.39 for ADG, 0.32 for BF, 0.15 for MD, and repeatability estimates were 0.38 for SV, 0.37 for TSC, 0.09 for TC, 0.39 for ND, and 0.16 for AR. Semen traits showed a strong negative genetic correlation with MD and positive genetic correlation with BF. Genetic correlations between semen traits and ADG were low. Therefore, current AI boar selection practices may be having a detrimental effect on semen production.
Hossain, K.B.;Takayanagi, S.;Miyake, T.;Moriya, K.;Bhuiyan, A.K.F.H.;Sasaki, Y.
Asian-Australasian Journal of Animal Sciences
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v.15
no.5
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pp.627-632
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2002
Genetic parameters for dairy performance traits were estimated, breeding values for the traits of all breeding sires and cows were predicted and the genetic trends were estimated using the breeding values in the Central Cattle Breeding Station (CCBS). A total of 3,801 records for Bangladeshi Local, 756 records for Red Sindhi and 959 records for Sahiwal covering the period from 1961 to 1997 were used in this analysis. Traits considered were total milk production per lactation (TLP), lactation length (LL) and daily milk yield (DMY). The genetic parameters were estimated by the REML using MTDFREML program. The breeding values were predicted by a best linear unbiased prediction (BLUP). In all sets of data, the genetic trends for the dairy performance traits were computed as averages of breeding values for cows born in the particular year. The estimates of heritability for TLP (0.26 and 0.27) and DMY (0.28 and 0.27) were moderate in Bangladeshi local and Red Sindhi breed, respectively. Furthermore, the heritability estimate for LL (0.24) was moderate in Red Sindhi. The estimates of heritabilities for all traits were low in Sahiwal. The repeatability estimate was high for TLP, moderate for LL and moderate to high for DMY. All variances estimated in Bangladeshi Local were low, comparing the respective values estimated in both Red Sindhi and Sahiwal. On the other hand, additive genetic variances for the three traits were estimated very low in Sahiwal. The genetic trends for the three dairy production traits have not been positive except for the recent trend in Bangladeshi Local.
A model Indigenous Thai beef cattle breeding structure consisting of nucleus, multiplier and commercial units was used to evaluate the effect of changes in heritabilities of and genetic correlations between adaptation traits on genetic gain and profitability. A breeding objective that incorporated adaptation was considered. Two scenarios for improving both the production and the adaptation of animals where also compared in terms of their genetic and economic efficiency. A base scenario was modelled where selection is for production traits and adaptation is assumed to be under the forces of natural selection. The second scenario (+Adaptation) included all the information available for base scenario with the addition of indirect measures of adaptation. These measures included tick count (TICK), faecal egg count (FEC) and rectal temperature (RECT). Therefore, the main difference between these scenarios was seen in the records available for use as selection criteria and hence the level of investments. Additional genetic gain and profitability was generated through incorporating indirect measures of adaptation as criteria measured in the breeding program. Unsurprisingly, the results were sensitive to the changes in heritabilities and genetic correlations between adaptation traits. However, there were more changes in the genetic gain and profitability of the breeding program when the genetic correlations of adaptation and its indirect measures were varied than when the correlations between these measures were. The changes in the magnitudes of the genetic gain and profit per cow stresses the importance of using reliable estimates of these traits in any breeding program.
This study was conducted to determine genetic correlations among carcass traits measured by ultrasound and real carcass measurements and to estimate indirect selection responses for real carcass traits based on ultrasound measurements in Hanwoo cows. To accomplish this, 22,080 ultrasound measurement records from 17,926 cows collected from 2001 to 2012 and 11,907 carcass records obtained from fattened cattle from 2008 to 2012 were used. Genetic parameters were estimated based on eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) measured by ultrasound-scanning of live cows and using the official technique on chilled bovine half-carcasses after slaughtering. Heritability and genetic correlation for carcass traits were estimated using a mixed model equation that consisted of environmental effects as fixed parameters and additive genetic effects and residual effects as random parameters, assuming that traits were different between ultrasound and carcass measurements. This statistical method was applied to the average information restricted maximum likelihood method. The heritability of EMA, BF and MS measured by ultrasound were 0.33, 0.61 and 0.46, respectively, while the heritability estimates of the corresponding traits based on carcass measurements were 0.29, 0.40 and 0.38, respectively and the genetic correlation between ultrasound and carcass traits for EMA, BF and MS were 0.41, 0.78 and 0.67, respectively. The genetic correlation between ultrasound and carcass traits was highly positive. Additionally, the selection response for marbling score was estimated to be 0.42 per generation if the cows were selected based on the ultrasound scan marbling score with an assumed selection intensity of 0.8. Overall, these results indicate that the ultrasound scan technique would be applicable to judging cow selection for genetically improved meat quality.
Factor analysis was applied as a multivariate statistical technique to official genetic evaluations of type classification traits for 1,265,785 Holstein cows and 10,321 sires computed from data collected between August 1982 and June 1994 in Canada. Type traits included eighteen linear descriptive traits and eight major score card traits. Principal components of the factor analysis showed that only five factors explain the information of the genetic value of linear descriptive traits for both cows and sires. Factor 1 included traits related to mammary system, like texture, median suspensory, fore attachment, fore teat placement and rear attachment height and width. Factor 2 described stature, size, chest width and pin width. These two factors had a similar pattern for both cows and sires. In constrast, Factor 3 for cows involved only bone-quality, while in addition for sires, Factor 3 included foot angle, rear legs desirability and legs set. Factor 4 for cows related to foot angle, set of rear leg and leg desirability, while Factor 4 related to loin strenth and pin setting for sires. Finally, Factor 5 included loin strength and pin setting for cows and described only pin setting for sires. Two factors only were required to describe score card traits of cows and sires. Factor 1 related to final score, feet and legs, udder traits, mammary system and dairy character, while frame/capacity and rump were described by Factor 2. Communality estimates which determine the proportion of variance of a type trait that is shared with other type traits via the common factor variant were high, the highest ${\geq}$ 80% for final score, stature, size and chest width. Pin width and pin desirability had the lowest communality, 56% and 37%. Results indicated shifts in emphasis over the twelve-year period away from udder traits and dairy character, and towards size, scale and width traits. A new system that computes fmal score from type components has been initiated.
Park, Ki-Yeol;Kim, Hyun-Chul;Kim, Byoung-Hak;Choi, Nack-Joong;Moon, Tae-Seok
Korean Journal of Fisheries and Aquatic Sciences
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v.42
no.6
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pp.600-603
/
2009
Genetic and phenotypic parameter estimates for measurement traits were obtained from pacific oyster Crassostrea gigas at nine months old. For the growth-related traits among nine months old pacific oyster, heritabilities of shell length, shell height, shell width, total weight, body weight and shell weight were estimated as 0.4855, 0.5248, 0.0884, 0.7236, 0.7726 and 0.6957, respectively. Genetic correlations among the growth-related traits of pacific oyster at nines month old, shell length, shell height, shell width, total weight, body weight, shell weight were showing highly positive correlations. Breeding value on growth-related traits of pacific oyster at nine months old were estimated as shell length -7.044-11.870, shell height -11.380-18.370, shell width -1.234-2.831, total weight -8.339-17.140, body weight -1.813-3.507 and shell weight -4.422-8.837. The results show that there is quite substantial additive genetic variance for measurement traits in pacific oyster that can be exploited through selective breeding.
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