Longevity in Dairy Cattle (original) (raw)
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Genetic evaluation of longevity in dairy cattle
Applied Science Reports
Longevity is a highly desirable trait that considerably affects overall profitability. With increased longevity, the mean production of the herd increases because a greater proportion of the culling decisions are based on production. Longevity did not receive adequate attention in breeding programs because genetic evaluation for this trait is generally difficult as some animals are still alive at the time of genetic evaluation. Therefore, three basic strategies were suggested to evaluate longevity for cows: Firstly, cow survival to a specific age, which can be analyzed as a binary trait by either linear or threshold models. Secondly, estimating life expectancy of live cows and including these records in a linear model analysis. Thirdly, survival analysis: a method of combining the information of dead (uncensored) and alive (censored) cows in same analysis. This review represents an attempt to shed a light on different strategies of genetic evaluation of longevity in dairy cattle in most of developed countries.
The genetic structure of longevity in dairy cows
Journal of dairy science, 2015
Longevity of dairy cows is determined by culling. Previous studies have shown that culling of dairy cows is not an unambiguous trait but rather the result of several reasons including diseases and selection decisions. The relative importance of these reasons is not stable over time, implying that genetic background of culling may vary over lifetime. Data of 7.6 million German Holstein cows were used to assess the detailed genetic correlation structure among 18 survival traits defined for the first 3 parities. Differences of genetic factors which determine survival of different production periods were found, showing a pattern with 3 genetically distinct periods within each parity: early lactation (calving until d 59), mid lactation (d 60 to 299), and late lactation (d 300 until next calving). Survival in first and later parities were found to be slightly genetically different from each other. The identified patterns were in good accordance with distributions of reasons for disposal, ...
Breeding for longevity and survival in dairy cattle
Thc aim of dairy cattle brceding should be to improvc lifetime profit, rattrer than longevity in itsclf. It is most likcly, though, O16t traits rhar dercrmine longevity will be selccad for, and thus the ability to livc longer will improve. Health and rcproductive traits are describcd as the most imporrant in dercrmining longevity. The main focus of the articlc is on describing methods used as indicators of longevity: sayabilities, sundval scores, and failure time analysis. Mcasurcs of prcduction ard involuntary cdting (c.g. mastitis, reproduaion) are suggested for usc as selection criterion, if measured in the population. If not, other indicalor traits, such as somatic cell counts, could bc used irsrcad. If no or few hcalth and reproduction traits arc available in a population, breeding values for length of pmductivc lifc adjustcd for thc within-herd milk production deviuion, analyzed with failure time analysis' could bc used as a complement to milk production.
Animal Science Journal, 2013
Genetic parameters for longevity in Slovenian Holstein (H), Simmental (S) and Brown Swiss (B) cattle were estimated with sire-mgs (maternal grandsire) model using survival analysis, applying a proportional hazard function following a Weibull distribution. Longevity was described as length of productive life (LPL), that is as number of days from first calving to the culling or to the moment of data collection (completeduncensored and censored records). Truncation date was January 1, 1991 while August 1, 2008 was date of data collection. Estimated sire variances were 0.050 (H), 0.021 (S) and 0.034 (B). Herd variances were 0.191 (H), 0.299 (S) and 0.318 (B). Heritabilities estimates were 0.161 (H), 0.064 (S) and 0.101 (B).
Genetic evaluation of length of productive life including predicted longevity of live cows
Journal of dairy science, 1993
Complete longevity data are available too late for most sire selection. Earlier selection is possible using correlated traits, nonlinear evaluation of censored data, or predicted longevities for live cows in addition to completed longevity data. Completed longevity was defined as total months in milk by 84 mo of age. Predicted longevity was computed by multiple regression from cows alive at six different ages. Variables included age at first calving, standardized first lactation milk yield (optional), lactation status (dry or milking), current months in milk, current months dry, and cumulative months in milk. Completed longevity data for dead cows were then merged with predicted longevity data for live cows. A total of 1,984,038 Holstein cows born from 1979 to 1983 were included and represented 1911 sires, each with at least 70 daughters. Heritability of longevity increased gradually from .03 at 36 mo to .08 at 84 mo. Phenotypic correlations of early with completed longevity ranged ...
First Results of a MAS Study in Dairy Cattle with Respect to Longevity (short communication)
Archiv fur Tierzucht
Dedicated to Professor Dr. D. Simon on the occasion ofhis 70lh birthday Summary A study where Casein loci were used to be markers for improving milk yield, fat content and protein yield in a marker assisted selection experiment focused on possible side effects of this process on longevity traits. Using the data of two samples of cows a Simulation on the data was carried out evaluating the selection differences in period of use, period of life and production of the whole life indirectly. The selection criteria were flexible using one of the milk production traits each as well as marker information. During the investigated period no negative effect of simulated selection using EBV for milk yield, fat content and protein yield alone or in combination with the Casein loci used as markers on longevity traits occurred in the population. There are no significant differences regarding the longevity traits caused by selection for Single milk trait based on pure EBV and MAS.
Evaluating markers in selected genes for association with functional longevity of dairy cattle
BMC Genetics, 2011
Background: Longevity expressed as the number of days between birth and death is a trait of great importance for both human and animal populations. In our analysis we use dairy cattle to demonstrate how the association of Single Nucleotide Polymorphisms (SNPs) located within selected genes with longevity can be modeled. Such an approach can be extended to any genotyped population with time to endpoint information available. Our study is focused on selected genes in order to answer the question whether genes, known to be involved into the physiological determination of milk production, also influence individual's survival. Results: Generally, the highest risk differences among animals with different genotypes are observed for polymorphisms located within the leptin gene. The polymorphism with a highest effect on functional longevity is LEP-R25C, for which the relative risk of culling for cows with genotype CC is 3.14 times higher than for the heterozygous animals. Apart from LEP-R25C, also FF homozygotes at the LEP-Y7F substitution attribute 3.64 times higher risk of culling than the YY homozygotes and VV homozygotes at LEP-A80V have 1.83 times higher risk of culling than AA homozygotes. Differences in risks between genotypes of polymorphisms within the other genes (the butyrophilin subfamily 1 member A1 gene, BTN1A1; the acyl-CoA:diacylglycerol acyltransferase 1 gene, DGAT1; the leptin receptor gene, LEPR; the ATP-binding cassette sub-family G member 2, ABCG2) are much smaller.
Understanding the genetics of survival in dairy cows
Premature mortality and culling causes great wastage in the dairy industry, as a large number of heifers born never become productive or are culled before their full lactation potential is reached. The objectives of this study were to characterize survival and estimate genetic parameters for alternative longevity traits that considered (1) the survival of replacement heifers and (2) functional longevity of milking cows in the UK Holstein Friesian population, using combined information from the British Cattle Movement Service and milk recording organizations. Mortality of heifers was highest in the first month of life and was proportionately highest in calves born during winter months. Heifer mortality tended to decrease with age until about 16 mo onward; it then gradually increased, expected to be associated with culls due to reproductive failure or problems during pregnancy and calving. In milking cows, days of productive life (DPL) was analyzed as an alternative to the current trait lifespan score. Cows that died in 2009 on average lived for 6.8 yr with an average production of 4.3 yr. Heritability estimates were low for both heifer and cow survival and were ~0.01 and ~0.06, respectively. The positive genetic correlation between heifer survival with lifespan score (0.31) indicates that bulls that sire daughters with longer productive lives are also likely to have calves that survive and become replacement heifers. However, the magnitude of the genetic correlation suggests that survival in the rearing period and the milking herd are different traits. Genetic correlations were favorable between DPL with somatic cell count and fertility traits indicating that animals with a longer productive life tend to have lower somatic cell count, a shorter calving interval, fewer days to first service, and require fewer inseminations. However, an antagonistic relationship existed between DPL with milk and fat yield traits.
Effect of non-genetic factors on longevity traits in Simmental cows
Biotehnologija u stocarstvu
The effects of fixed non-genetic factors (farm, season of birth, year of birth, total number of lactations) and a continuous non-genetic factor (age at first conception) on the expression and variability of longevity traits such as age at culling, length of productive life, days in milk and cow efficiency index were investigated in 2548 Simmental cows in three farming areas. Based on the model used for the analysis of the effects of non-genetic factors, including the environment and cow age at first conception, on the expression and variability of longevity traits, the overall means for age at culling, length of productive life, days in milk and cow efficiency index were 2445.21?17.49 days, 1562.55?17.71 days, 1094.17?12.28 days and 58.68?0.32%, respectively. The effect of farming area, year of birth and lactation group on longevity traits was very significant (P<0.01), whereas the effect of season of birth was significant (P<0.05). Age at first conception had a highly signifi...
Genetic selection strategies to improve longevity in Chianina beef cattle
Italian Journal of Animal Science, 2010
Longevity in beef cattle is an important economic trait. Including this trait in a breeding scheme increases profit and has a positive impact on the well-being and welfare of the animals. The aim of the present study was to evaluate the consequences of alternative selection strategies to include longevity in different breeding schemes using deterministic simulation. Different schemes were compared and economic (EcW) and empirical weights (EmW) were used to evaluate the responses. The empirical weights of average daily gain (ADG) and muscularity (MU) were identical because both traits have an identical importance for the breeders. Economic weights have been derived from profit equations. Traits used in the Base scenarios were: average daily gain pre-performance test (ADG1), average daily gain during the performance test (ADG2) and muscularity (MU); longevity (L) was included in the alternative schemes. When longevity was included both in the breeding index and in the breeding goal (scenario A-2), the total longevity response using EmW and EcW was +2.97 d/yr and +4.92 d/yr, respectively. The total economic response for scenario A-2 using EmW and EcW were 3.020 €/yr and 3.342 €/yr, respectively, and the total response in units of Bull Selection Index were +0.699 and +0.678, respectively. Longevity decreased when it was not included in either the breeding goal or in the breeding index (scenario Base), and economic response was the lowest found. The results of the current study indicate that the highest total response using either economic weights or empirical weights was found when information on longevity was included both in the breeding index and in the breeding goal (scenario A-2).