Genetic improvement programs in livestock: swine testing and genetic evaluation system (stages) (original) (raw)
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Livestock Science, 2012
The purpose of this study was to determine the genetic and phenotypic relationships between litters per sow per year (LSY) and other economically important reproductive and postweaning traits from data collected in a commercial swine breeding company. Determining the genetic and phenotypic correlations among traits can help breeders evaluate the expected impacts their selection decisions have on other economically important production traits when they are included in a selection index. This is particularly important when considering reproductive and post-weaning traits due to possible undesirable genetic relationships. A total of 32,653 litter records from 7674 sows from 4 herds within a single production system (same genetics, same animal feeding specifications, same management procedures, etc.) were used in this study. The sows were born between 1992 and 2009. Post-weaning traits were recorded on male and female pigs (44,040 records), including sows and their progeny. The reproductive traits collected included number born alive (NBA), and wean to estrus (W2E). Number born alive and wean to estrus interval were recorded for every litter. Back fat between the 3rd and 4th last lumbar vertebrae and back fat and muscle thickness between the 3rd and 4th last rib were measured. Adjusted back fat (BF), percent lean (PCL), days to 100 kg (D100), and litters per sow per year (LSY) were calculated based on recorded information. Genetic parameters were estimated using ASREML. The heritability estimates for NBA, LSY, W2E, BF, D100, and PCL were 0.15, 0.03, 0.03, 0.41, 0.28, and 0.36, respectively. The genetic correlation between LSY and W2E was large, numerically negative, and favorable. The genetic correlations between LSY and the three post-weaning traits (BF, D100, and PCL) had large standard errors and were unclear in direction. Some economically important traits can be improved indirectly with selection on LSY; however, a selection index will be needed to ensure that post-weaning traits are not adversely affected by selection for LSY in a maternal line breeding program.
The purpose of this study was to determine the genetic and phenotypic correlations between maternal and postweaning traits from a seedstock swine breeding system. The strongest phenotypic correlation was between percent lean and backfat at -0.72 (P<0.05). The genetic correlations between annualized farrowing interval and each of the postweaning traits (BF, PCL, and D100) were 0.41, -0.53, and 0.49 (P<0.05), respectively. The correlations between annualized farrowing interval and post-weaning traits suggest that selecting based on annualized farrowing interval would negatively impact the post-weaning traits in the herd. The direction of the correlation between number born alive and post-weaning traits could not be concluded from this study.
https://www.ijrrjournal.com/IJRR\_Vol.7\_Issue.10\_Oct2020/Abstract\_IJRR008.html, 2020
Until now, continuous selection and breeding of swine is done to take advantage of increase reproductive efficiency. Litter size at birth and weaning are important traits of interest by pig breeders as it affects farm productivity. However, factors such as uterine capacity, fetal survival, stillborn, individual birth weight, and post-natal interaction of piglets and sow limits improvement of this trait. Although continues conventional breeding and selection facilitates progress in lowly heritable reproductive traits, success has a consequence of non-uniform piglet with lower birth weight which led to increase pre - weaning mortality. Pig breeders therefore shift selection strategy from large litter size at birth to increase in litter size at weaning. On the other hand, rapid improvement in reproductive trait observed in the past decades is due to extensive effort of record keeping, conventional and genomic selection, Genome Wide Association Study/Analysis that determine potential candidate gene and use of Best Linear Unbiased Prediction (BLUP) that account the genetic merit of certain breed across generation. Innovations brought by this reproductive strategy further optimize breeding scheme efficiency which speed up genetic progress, allowing only breeds with superior reproductive traits to reproduce for the next generation. Today, it is possible to produce more than 30 piglets weaned/sow/year due to improved genetics. Further development would be expected in the future for litter size and piglets born alive with the utilization of ESR gene, crossing of Meishan to white breeds and with application of genomic selection, GWAS and BLUP.
A data set including 2,002 purebred litter records and 14,583 crossbred litter records from a swine production unit with a defined great-grandparent (GGP), grandparent, and parent stock genetic system structure was used to examine the gains in accuracy of breeding value estimation of the purebred GGP animals through inclusion of crossbred information with purebred information. Other objectives were to determine if a change in ranking of the purebred GGP animals occurred and to determine if this new information would cause a change in the selection decisions of the producer. The traits used in this evaluation were number of pigs born alive, adjusted litter weaning BW, and the interval from weaning to first service. Animals were ranked based on 2 indices, one calculated using only purebred information and the other calculated using combined purebred and crossbred information. Gains in mean accuracy ranged from 7.3 to 8.7% for the GGP sows. Spearman rank correlations were less than 0.85 for the GGP sows and less than 0.90 for the 1 To whom correspondence should be addressed: jmabry@iastate.edu GGP sires. It was concluded that improvement was made in accuracy of breeding value estimation with the inclusion of crossbred information. There was a highly significant (P < 0.01) re-ranking of both the sows and sires in the GGP. Rankings based on the 2 indices also suggest that selection decisions may change based on the inclusion of the crossbred information.
Purebred-crossbred genetic parameters for reproductive traits in swine
Journal of Animal Science, 2021
For swine breeding programs, testing and selection programs are usually within purebred (PB) populations located in nucleus units that are generally managed differently and tend to have a higher health level than the commercial herds in which the crossbred (CB) descendants of these nucleus animals are expected to perform. This approach assumes that PB animals selected in the nucleus herd will have CB progeny that have superior performance at the commercial level. There is clear evidence that this may not be the case for all traits of economic importance and, thus, including data collected at the commercial herd level may increase the accuracy of selection for commercial CB performance at the nucleus level. The goal for this study was to estimate genetic parameters for five maternal reproductive traits between two PB maternal nucleus populations (Landrace and Yorkshire) and their CB offspring: Total Number Born (TNB), Number Born Alive (NBA), Number Born Alive > 1 kg (NBA>1kg),...
Swine Feed Efficiency: Genetic Impact
2012
Feed costs have traditionally been the highest contributor to cost of production in swine, representing 2/3 of the cost to produce a market hog. Feed efficiency is a trait that is significantly influenced by genetics, with a heritability in the moderate range (30%-40% of the differences between animals in feed efficiency are due to genetics). The genetic system that a swine producer utilizes can have a significant impact on herd feed efficiency and the operation’s feed costs. The genetic system is comprised of the genetic composition of the sire and dam lines, plus, the crossbreeding system. The critical aspects for the sire and dam lines include a combination of the genetic supplier used by the producer, the specific lines utilized for the terminal sire lines and maternal dam lines, and the genetic improvement program of the genetic supplier. It is important to remember that the genetic composition of each market hog is derived equally from the sire and from the dame of the pigs.
Phenotypic and Genetic Change for Lean Growth Rate and its Components in U.S. Landrace Pigs
2000
Records on 65,536 Landrace pigs collected between 1985 and 1999 in herds on the National Swine Registry STAGES program were used to estimate genetic change in lean growth rate, days to 250 lb, backfat, and loin eye area. Genetic change was measured as the change in average estimated breeding value (EBV) over years. Analysis was by a multitrait best linear unbiased prediction (BLUP) animal model with fixed effects of contemporary group and sex, and random effects of animal, litter, and residual error. The annual phenotypic trends from 1990 to 1999 were 0.008 lb, -0.85 d, -0.019 in., and 0.12 in. 2 for lean growth rate, days to 250 lb, backfat, and loin eye area. The overall genetic trends from 1990 to 1999 were 0.85, 0.28, 2.1, 0.95% of their means, respectively. The current rate of genetic improvement in the U.S. Landrace pigs is significant and offers the potential for considerable economic benefit.
Genetic parameters for a joint genetic evaluation of production and reproduction traits in pigs
Czech Journal of Animal Science, 2005
The covariance structure was estimated by REML for a joint genetic evaluation of production and reproduction traits for Czech Landrace (58 258 records) and Czech Large White (167 161 records) pigs using fourtrait animal models. The following traits were analysed: lean mean percentage at the end of the performance test in the field, estimated from ultrasonic measurements unadjusted for live weight (LM), average daily gain in field test (in g/day) calculated as weight at the end of the test divided by age at the end of the test (ADG), number of piglets born alive in parity 1 (NBA1) and number of piglets born alive in parity 2 and subsequent parities (NBA2+). The heritabilities were in the range from 0.30 to 0.37 for LM, from 0.13 to 0.18 for ADG, from 0.09 to 0.13 for NBA1 and from 0.10 to 0.14 for NBA2+, depending on the breed and on the model (herd-year-season random or fixed). Genetic correlations between production and reproduction traits were estimated to be non-zero. Correlations between traits caused by the herd-year-season effect were mostly positive. As a general conclusion, the joint genetic evaluation of production and reproduction traits is recommended. The herd-year-season effect should be preferably considered as random.