The Experts below are selected from a list of 4845 Experts worldwide ranked by ideXlab platform
Piter Bijma - One of the best experts on this subject based on the ideXlab platform.
-
optimization of dairy cattle breeding programs for different environments with genotype by environment interaction
Journal of Dairy Science, 2006Co-Authors: H.a. Mulder, Roel F. Veerkamp, J.a.m. Van Arendonk, B J Ducro, Piter BijmaAbstract:Dairy cattle breeding organizations tend to sell semen to breeders operating in different environments and genotype x environment interaction may play a role. The objective of this study was to investigate optimization of dairy cattle breeding programs for 2 environments with genotype x environment interaction. Breeding strategies differed in 1) including 1 or 2 environments in the breeding goal, 2) running either 1 or 2 breeding programs, and 3) Progeny Testing bulls in 1 or 2 environments. Breeding strategies were evaluated on average genetic gain of both environments, which was predicted by using a pseudo-BLUP selection index model. When both environments were equally important and the genetic correlation was higher than 0.61, the highest average genetic gain was achieved with a single breeding program with Progeny-Testing all bulls in both environments. When the genetic correlation was lower than 0.61, it was optimal to have 2 environment-specific breeding programs Progeny-Testing an equal number of bulls in their own environment only. Breeding strategies differed by 2 to 12% in average genetic gain, when the genetic correlation ranged between 0.50 and 1.00. Ranking of breeding strategies, based on the highest average genetic gain, was relatively insensitive to heritability, number of Progeny per bull, and the relative importance of both environments, but was very sensitive to selection intensity. With more intense selection, running 2 environment-specific breeding programs was optimal for genetic correlations up to 0.70-0.80, but this strategy was less appropriate for situations where 1 of the 2 environments had a relative importance less than 10 to 20%. Results of this study can be used as guidelines to optimize breeding programs when breeding dairy cattle for different parts of the world.
-
effects of genotype x environment interaction on genetic gain in breeding programs
Journal of Animal Science, 2005Co-Authors: H.a. Mulder, Piter BijmaAbstract:Genotype x environment interaction (G x E) is increasingly important, because breeding programs tend to be more internationally oriented. The aim of this theoretical study was to investigate the effects of G x E on genetic gain in sib-Testing and Progeny-Testing schemes. Loss of genetic gain due to G x E was predicted for different values of heritability, number of Progeny per dam, number of Progeny per sire, proportion of selected sires, and population size in the selection environment. Two environments were considered: a selection environment (SLE) and a production environment (PDE). The breeding goal was only for performance in PDE. A pseudo-BLUP selection index was used to predict genetic gain. Recording of half-sibs or Progeny in PDE limited the loss in genetic gain in PDE due to G x E between SLE and PDE. Progeny-Testing schemes had less loss in genetic gain than sib-Testing schemes. Higher heritability increased the loss in genetic gain, whereas increasing the number of Progeny per sire in PDE decreased the loss in genetic gain. The number of Progeny per sire required to minimize loss in genetic gain due to G x E was greater for sib-Testing schemes than for Progeny-Testing schemes. More Progeny per dam slightly increased the loss in genetic gain. Genetic gains for sex-limited and carcass traits were less affected by G x E than traits measured on both sexes. Loss in genetic gain was due to decreased accuracy of selection in most situations, but it was due to decreased selection intensity in situations with small population size and a low proportion of selected sires. It was concluded that recording performance of relatives in PDE minimizes loss in genetic gain due to G x E, and that Progeny-Testing schemes rather than sib-Testing schemes are preferable in situations with low to moderate heritability (h(2) less than or equal to 0.3), relatively short generation interval of Progeny-tested sires (L-prog/L-sib less than or equal to 1.7), and moderate to severe G x E interaction (r(g) less than or equal to 0.8).
J.a.m. Van Arendonk - One of the best experts on this subject based on the ideXlab platform.
-
economic evaluation of Progeny Testing and genomic selection schemes for small sized nucleus dairy cattle breeding programs in developing countries
Journal of Dairy Science, 2017Co-Authors: E W Brascamp, C M Kariuki, Hans Komen, A K Kahi, J.a.m. Van ArendonkAbstract:In developing countries minimal and erratic performance and pedigree recording impede implementation of large-sized breeding programs. Small-sized nucleus programs offer an alternative but rely on their economic performance for their viability. We investigated the economic performance of 2 alternative small-sized dairy nucleus programs [i.e., Progeny Testing (PT) and genomic selection (GS)] over a 20-yr investment period. The nucleus was made up of 453 male and 360 female animals distributed in 8 non-overlapping age classes. Each year 10 active sires and 100 elite dams were selected. Populations of commercial recorded cows (CRC) of sizes 12,592 and 25,184 were used to produce test daughters in PT or to create a reference population in GS, respectively. Economic performance was defined as gross margins, calculated as discounted revenues minus discounted costs following a single generation of selection. Revenues were calculated as cumulative discounted expressions (CDE, kg) × 0.32 (€/kg of milk) × 100,000 (size commercial population). Genetic superiorities, deterministically simulated using pseudo-BLUP index and CDE, were determined using gene flow. Costs were for one generation of selection. Results show that GS schemes had higher cumulated genetic gain in the commercial cow population and higher gross margins compared with PT schemes. Gross margins were between 3.2- and 5.2-fold higher for GS, depending on size of the CRC population. The increase in gross margin was mostly due to a decreased generation interval and lower running costs in GS schemes. In PT schemes many bulls are culled before selection. We therefore also compared 2 schemes in which semen was stored instead of keeping live bulls. As expected, semen storage resulted in an increase in gross margins in PT schemes, but gross margins remained lower than those of GS schemes. We conclude that implementation of small-sized GS breeding schemes can be economically viable for developing countries.
-
optimization of dairy cattle breeding programs for different environments with genotype by environment interaction
Journal of Dairy Science, 2006Co-Authors: H.a. Mulder, Roel F. Veerkamp, J.a.m. Van Arendonk, B J Ducro, Piter BijmaAbstract:Dairy cattle breeding organizations tend to sell semen to breeders operating in different environments and genotype x environment interaction may play a role. The objective of this study was to investigate optimization of dairy cattle breeding programs for 2 environments with genotype x environment interaction. Breeding strategies differed in 1) including 1 or 2 environments in the breeding goal, 2) running either 1 or 2 breeding programs, and 3) Progeny Testing bulls in 1 or 2 environments. Breeding strategies were evaluated on average genetic gain of both environments, which was predicted by using a pseudo-BLUP selection index model. When both environments were equally important and the genetic correlation was higher than 0.61, the highest average genetic gain was achieved with a single breeding program with Progeny-Testing all bulls in both environments. When the genetic correlation was lower than 0.61, it was optimal to have 2 environment-specific breeding programs Progeny-Testing an equal number of bulls in their own environment only. Breeding strategies differed by 2 to 12% in average genetic gain, when the genetic correlation ranged between 0.50 and 1.00. Ranking of breeding strategies, based on the highest average genetic gain, was relatively insensitive to heritability, number of Progeny per bull, and the relative importance of both environments, but was very sensitive to selection intensity. With more intense selection, running 2 environment-specific breeding programs was optimal for genetic correlations up to 0.70-0.80, but this strategy was less appropriate for situations where 1 of the 2 environments had a relative importance less than 10 to 20%. Results of this study can be used as guidelines to optimize breeding programs when breeding dairy cattle for different parts of the world.
-
evaluation of closed adult nucleus multiple ovulation and embryo transfer and conventional Progeny Testing breeding schemes for milk production in tropical crossbred cattle
Journal of Dairy Science, 2005Co-Authors: I S Kosgey, A K Kahi, J.a.m. Van ArendonkAbstract:The potential benefits of closed adult nucleus multiple ovulation and embryo transfer (MOET) and conventional Progeny Testing (CNS) schemes, and the logistics of their integration into large-scale continuous production of crossbred cattle were studied by deterministic simulation. The latter was based on F1 (Bos taurus x Bos indicus) production using AI or natural mating and MOET, and continuous F2 production by mating of F1 animals. The gene flow and the cumulative discounted expressions (CDES) were also calculated. Both schemes had 8, 16, 32, or 64 dams with 2, 4, 8, 16, or 32 sires selected. In the MOET nucleus scheme (MNS), the test capacity was 1, 2, 8, or 16 offspring, and the number of matings per dam per year was 1, 2, or 4. A scheme of 8 sires with 64 dams and a test capacity of 4 female offspring per dam per year resulted in an annual genetic gain (in phenotypic standard deviation) of 0.324 and 0.081 for MNS and CNS, respectively. In the MNS, there was substantial genetic gain with a relatively small number of animals compared with a CNS. The F1 had the highest, and the F2 scheme the lowest CDES. However, a very large number of B. indicus females would be required in the F1 scheme. This scheme may not be practical under conditions in developing countries. The F2 scheme was logistically attractive because it produces its own replacements, and the number of B. taurus females required would be easy to attain. Accompanying technical and financial constraints of nucleus schemes should be addressed before applying them.
C E Meadows - One of the best experts on this subject based on the ideXlab platform.
-
selection of bulls for Progeny Testing using pedigree indices and characteristics of potential bull dams herds
Journal of Dairy Science, 1991Co-Authors: I L Mao, M C Dong, C E MeadowsAbstract:A total of 209 bulls selected from herds in the northeastern US by Eastern AI Coop., Inc. from 1978 to 1981 were identified. The DHI data were obtained for the 145 herds from which these bulls were sampled. Also acquired were evaluations from both Modified Contemporary Comparison and animal model on these bulls and their ancestors and on cows and their sires in the bull-dam herds. From evaluation by animal model, animals appeared to have contributed information to each other effectively through relationship matrix, and thus the accuracy of cow evaluation has been improved. Bulls selected from herds of high genetic level were genetically superior to those from herds of low genetic level. However, there was no evidence that bulls from low intraherd milk variation herds were superior to those from high variation herds in the northeastern population, as was the case in Michigan herds. Parent indices were greater than bull PTA in herds of lower genetic level but less than bull PTA in herds of higher genetic level. The correlation between herd yield average and herd genetic level and that between herd yield average and intraherd yield SD were moderate but significantly different from zero. Other correlations between phenotypic and genetic measures of bull-dam herds were negligible. None of the herd characteristics showed promise in characterizing herds that were more successful in having their sampled bulls returned by AI organization after progency test.
-
comparison of bull dam herds Progeny Testing herds and other dairy herd improvement herds
Journal of Dairy Science, 1991Co-Authors: I L Mao, A E Wilhelm, M C Dong, C E MeadowsAbstract:Abstract Michigan and Northeast dairy herds that produced young bulls for AI sampling from 1974 to 1981 and 1978 to 1981, respectively, and those involved in Progeny Testing were compared with their contemporary DHI herds. The 1985 lactation records of Michigan herds and 1980 to 1987 data of Northeast herds were acquired from respective DHIA data processing centers, and genetic evaluation results of sires and cows in those herds were obtained from USDA. Herd average milk production, intraherd SD for milk production, average sire PD of cows and average cow index in the herd, and intraherd SD of sire PD and of cow indexes were computed for each herd-year. These characteristics were used to compare the herd groups. Herds in which young bulls were sampled had greater average milk production, greater variance for milk production, and greater genetic variance than other herd groups. However, these herds were not genetically superior to other herd groups, except that the bull-dam herds in the Northeast have become a superior group since 1985, and the margin of superiority has increased over time. Herds participating in Progeny Testing of young bulls were by far the most superior group genetically in Michigan, especially those participating in the Testing program for more than 10 yr. However, Progeny Testing herds in the Northeast were similar to herds not involved in sire sampling or Testing programs in their average genetic merit.
H.a. Mulder - One of the best experts on this subject based on the ideXlab platform.
-
optimization of dairy cattle breeding programs for different environments with genotype by environment interaction
Journal of Dairy Science, 2006Co-Authors: H.a. Mulder, Roel F. Veerkamp, J.a.m. Van Arendonk, B J Ducro, Piter BijmaAbstract:Dairy cattle breeding organizations tend to sell semen to breeders operating in different environments and genotype x environment interaction may play a role. The objective of this study was to investigate optimization of dairy cattle breeding programs for 2 environments with genotype x environment interaction. Breeding strategies differed in 1) including 1 or 2 environments in the breeding goal, 2) running either 1 or 2 breeding programs, and 3) Progeny Testing bulls in 1 or 2 environments. Breeding strategies were evaluated on average genetic gain of both environments, which was predicted by using a pseudo-BLUP selection index model. When both environments were equally important and the genetic correlation was higher than 0.61, the highest average genetic gain was achieved with a single breeding program with Progeny-Testing all bulls in both environments. When the genetic correlation was lower than 0.61, it was optimal to have 2 environment-specific breeding programs Progeny-Testing an equal number of bulls in their own environment only. Breeding strategies differed by 2 to 12% in average genetic gain, when the genetic correlation ranged between 0.50 and 1.00. Ranking of breeding strategies, based on the highest average genetic gain, was relatively insensitive to heritability, number of Progeny per bull, and the relative importance of both environments, but was very sensitive to selection intensity. With more intense selection, running 2 environment-specific breeding programs was optimal for genetic correlations up to 0.70-0.80, but this strategy was less appropriate for situations where 1 of the 2 environments had a relative importance less than 10 to 20%. Results of this study can be used as guidelines to optimize breeding programs when breeding dairy cattle for different parts of the world.
-
effects of genotype x environment interaction on genetic gain in breeding programs
Journal of Animal Science, 2005Co-Authors: H.a. Mulder, Piter BijmaAbstract:Genotype x environment interaction (G x E) is increasingly important, because breeding programs tend to be more internationally oriented. The aim of this theoretical study was to investigate the effects of G x E on genetic gain in sib-Testing and Progeny-Testing schemes. Loss of genetic gain due to G x E was predicted for different values of heritability, number of Progeny per dam, number of Progeny per sire, proportion of selected sires, and population size in the selection environment. Two environments were considered: a selection environment (SLE) and a production environment (PDE). The breeding goal was only for performance in PDE. A pseudo-BLUP selection index was used to predict genetic gain. Recording of half-sibs or Progeny in PDE limited the loss in genetic gain in PDE due to G x E between SLE and PDE. Progeny-Testing schemes had less loss in genetic gain than sib-Testing schemes. Higher heritability increased the loss in genetic gain, whereas increasing the number of Progeny per sire in PDE decreased the loss in genetic gain. The number of Progeny per sire required to minimize loss in genetic gain due to G x E was greater for sib-Testing schemes than for Progeny-Testing schemes. More Progeny per dam slightly increased the loss in genetic gain. Genetic gains for sex-limited and carcass traits were less affected by G x E than traits measured on both sexes. Loss in genetic gain was due to decreased accuracy of selection in most situations, but it was due to decreased selection intensity in situations with small population size and a low proportion of selected sires. It was concluded that recording performance of relatives in PDE minimizes loss in genetic gain due to G x E, and that Progeny-Testing schemes rather than sib-Testing schemes are preferable in situations with low to moderate heritability (h(2) less than or equal to 0.3), relatively short generation interval of Progeny-tested sires (L-prog/L-sib less than or equal to 1.7), and moderate to severe G x E interaction (r(g) less than or equal to 0.8).
T J Pandian - One of the best experts on this subject based on the ideXlab platform.
-
production and Progeny Testing of androgenetic rosy barb puntius conchonius
Journal of Experimental Zoology Part A: Comparative Experimental Biology, 2004Co-Authors: Santhakumar Kirankumar, T J PandianAbstract:Protocol for androgenetic cloning of the rosy barb, Puntius conchonius, with contrasting gray and golden strains is described. At the intensity of 4.2 W/m 2 , UV irradiation for 3.0 min inactivates the maternal genome in eggs of the gray barb. Following activation by the golden barb sperm, 24-min old eggs are shocked at 41°C for 2 min to restore diploidy. Maternal genomic inactivation is confirmed by the (i) golden body color, (ii) karyotyping, and (iii) Progeny Testing of F 1 -F 3 progenies. Estimates of stage-specific mortality of haploid and diploid androgenotes indicate no change in the time scale or developmental sequence, when sperm of related strain is used for activation, and when haploid genome regulates the development. Survival of androgenetic clones remains constant for the F 1 , F 2 , and F 3 progenies and is about 15% and 7% at hatching and sexual maturity, respectively. Homozygosity of the androgenotes is shown to inflict greater mortality. Between F 1 and F 3 generations, the heterozygosity of the androgenetic clone is decreased, as evidenced by reduction in size hierarchy. Though the reproductive performance of the F 1 , F 2 , and F 3 supermales is superior to the normal ones, the realized fecundity remains equal around 80 progenies per brood. The 92 crosses involving 16 supermales and 10 normal dams yield 75-100% male progenies, confirming the possible operation of XX♀:XY♂ sex determination system. The frequency of unexpected occurrence of female progenies is about 8%, the causes for which are discussed.
-
hormonal induction of sex reversal and Progeny Testing in the zebra cichlid cichlasoma nigrofasciatum
Journal of Experimental Zoology, 1996Co-Authors: T George, T J PandianAbstract:Hormonal sex reversal was induced in the ornamental cichlid C. nigrofasciatum by dietary administration of estradiol-beta or 17 alpha-methyltestosterone. The treatments involving 200 mg estradiol-beta and 200 mg 17 alpha-methyltestosterone/kg diet for 20 days in the 4-day posthatchling C. nigrofasciatum resulted in 100% feminization and 82% masculinization, respectively Superoptimal doses led to higher mortality and stunted growth, especially among the surviving males, which resisted feminization. Progeny Testing of the feminized and masculinized individuals indicated that sex was determined by XX and XY (male heterogamety) sex chromosomes; however, the role played by autosomes in these individuals was also apparent. Live homogamous males (YY) could not be produced. Progeny Testing further showed that hormonal treatment impaired growth and reproductive performance of the sex-re versed females and males. F-1 progenies sired by the sex-reversed females as well as males also suffered higher mortality, extended interspawning period and lower fecundity. (C) 1996 Wiley-Liss, Inc.
-
production of a yy female guppy poecilia reticulata by endocrine sex reversal and Progeny Testing
Aquaculture, 1993Co-Authors: Soosamma Kavumpurath, T J PandianAbstract:Abstract A YY-female Poecilia reticulata was produced by endocrine sex reversal followed by Progeny Testing. Heterogametic females (XY) produced by endocrine sex reversal were mated with normal males (XY) and subsequently treated with an estrogen-supplemented diet, 5–10 days prior to parturition. Progenies obtained from these fish were individually mated with sex-reversed males (XX) to identify their genotype. A single female was identified to have the YY-genotype, and produced only males when mated with a sex-reversed male (XX).