Heritability and correlations among body condition score loss,body condition score,production and reproductive performance

The objectives of this study were to estimate the heritability of body condition score loss (BCSL) in early lactation and estimate genetic and phenotypic correlations among BCSL, body condition score (BCS), production, and reproductive performance. Body condition scores at calving and postpartum, mature equivalents for milk, fat and protein yield, days to first service, and services per conception were obtained from Dairy Records Management Systems in Raleigh, NC. Body condition score loss was defined as BCS at calving minus postpartum BCS. Heritabilities and correlations were estimated with a series of bivariate animal models with average-information REML. Herd-year-season effects and age at calving were included in all models. The length of the prior calving interval was included for all second lactation traits, and all nonproduction traits were analyzed with and without mature equivalent milk as a covariable. Initial correlations between BCS and BCSL were obtained using BCSL and BCS observations from the same cows. Additional genetic correlation estimates were generated through relationships between a group of cows with BCSL observations and a separate group of cows with BCS observations. Heritability estimates for BCSL ranged from 0.01 to 0.07. Genetic correlation estimates between BCSL and BCS at calving ranged from -0.15 to -0.26 in first lactation and from -0.11 to -0.48 in second lactation. Genetic correlation estimates between BCSL and postpartum BCS ranged from -0.70 to -0.99 in first lactation and from -0.56 to -0.91 in second lactation. Phenotypic correlation estimates between BCSL and BCS at calving were near 0.54, whereas phenotypic correlation estimates between BCSL and postpartum BCS were near -0.65. Genetic correlations between BCSL and yield traits ranged from 0.17 to 0.50. Genetic correlations between BCSL and days to first service ranged from 0.29 to 0.68. Selection for yield appears to increase BCSL by lowering postpartum BCS. More loss in BCS was associated with an increase in days to first service.     

Heritabilities and correlations among body condition score,dairy form and selected linear type traits

The objectives of this study were to estimate the heritability of body condition score (BCS) with data that could be used to generate genetic evaluations for BCS in the US, and to estimate the relationship among BCS, dairy form and selected type traits. Body condition score and linear type trait records were obtained from Holstein Association USA Inc. Because BCS was a new trait for classifiers, scoring distribution and accuracy was not normal. Records from 11 of 29 classifiers were eliminated to generate a data set that should represent BCS data recorded in the future. Edited data included 128,478 records for analysis of first lactation cows and 207,149 records for analysis of all cows. Heritabilities and correlations were estimated with ASREML using sire models. Models included age at calving nested within lactation, 5th order polynomials of DIM, fixed herd-classification visit effects and random sire and error. Genetic correlation estimates were generated between first lactation data that had records from 11 classifiers removed and data with no classifiers removed. Genetic correlation estimates were 0.995 and above between data with and without classifiers removed for scoring distributions, but heritability estimates were higher with the classifiers edited from the data. Heritability estimates for type traits and final score were similar to previously reported estimates. The heritability estimate for BCS was 0.19 for first lactation cows and 0.22 for all cows. The genetic correlation estimate for first lactation cows between BCS and dairy form was -0.73, whereas the genetic correlation estimate between BCS and strength was 0.72. Genetic correlation estimates were nearly identical when cows from all lactations were included in the analyses. Body condition score had a genetic correlation with final score closer to zero (0.08) than correlations of final score with dairy form, stature or strength.     

Genetic and Phenotypic Relationships Between Lactation Cell Counts and Milk Yield and Composition of Holstein Cows

Monthly somatic cell count data were collected between February 1977 and February 1982 for Holstein cows in 928 herds enrolled on the Quebec Dairy Herd Analysis Service. The geometric mean of the log monthly cell counts was calculated for each lactation. Official lactation records for 305-day milk, fat, and protein yields, and fat and protein percents were obtained for same cows. There were 18,189 cows in first lactation representing 257 sires, 13,225 in second lactation representing 206 sires, and 8,683 in third lactation representing 151 sires. Heritabilities of yield traits and protein percent increased across three lactations. Heritability of fat percent was similar in first and third lactations but decreased slightly in second lactations. Heritability of lactation cell count was small, being least in second lactations. Genetic correlations between lactation cell count and yield traits were positive in first lactations, small and negative in second lactations, and small and positive in third lactations. Genetic correlations between lactation cell count and fat and protein contents were small in the three lactations. Phenotypic correlations between lactation cell count and production traits were small in each of the three lactations. Genetic correlations between yield traits in early lactation and lactation cell count in a subsequent lactation were positive. The genetic correlation between protein percent in an early lactation and cell count in a later lactation was large between first and second lactations, decreased between second and third lactation, and small between first and third lactations. Genetic correlations were small and negative for fat percent.     

Milk urea nitrogen concentration: heritability and genetic correlations with reproductive performance and disease

The objectives of this study were to estimate the heritability of milk urea nitrogen (MUN) concentration and describe the genetic relationship between MUN and reproductive performance and between MUN and diseases in Holsteins. Dairy Records Management Systems (Raleigh, NC) provided lactation data. The Danish Agricultural Advisory Center provided breeding value estimates for diseases. Infrared (IR) and wet chemistry (WC) data were analyzed separately. Heritabilities and genetic correlations for 2 different measures of MUN and reproductive performance were estimated with an animal model using ASREML. Heritabilities for MUN were estimated using all lactations combined (lactations 1 through 5) and separately for first lactation and second lactation. Genetic correlations with reproduction and health were estimated separately for parities 1 and 2. Herd-test-day or herd-year-season along with age at calving and days in milk were included as fixed effects in all models. Heritability estimates for all lactations combined were 0.15 for WC MUN and 0.22 for IR MUN. Genetic correlations between WC MUN and 2 measures of reproductive performance, days to first service, and first service conception were not different from zero. In contrast, the genetic correlation between WC MUN and days open of 0.21 in first lactation and 0.41 in second lactation indicated that higher WC MUN values were associated with increased days open. Correlations among estimated breeding values for MUN and estimated breeding values for Danish diseases identified no significant relationships. Although the results of this study indicate that heritable variation for MUN exists, the inability to identify significant genetic relationships with several measures of disease or reproductive performance appears to limit the value of MUN in selection for disease resistance and improved reproduction.     

Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.     

Correlations among first and second lactation milk yield and calving interval

Estimates of genetic correlations were .17 between first lactation milk yield and concurrent calving interval, .10 between second lactation milk yield and first calving interval, and .82 between first and second milk yields. Corresponding phenotypic correlations were .27, .16, and .58. Heritability estimates were .27 and .25 for first and second lactations and .15 for calving interval. Estimates were averages of two samples of 15 New York State herds averaging 144 AI-sired Holstein cows and 30 sires. Milk yields were 305-d, mature equivalent. Calving interval was days between first and second freshening. First milk records without a second freshening were included. Multiple-trait animal model included separate herd-year-season effects for first and second milk yields and calving interval. Numerator relationships among animals within herd, except for daughter-dam relationships, were included. The REML with the expectation-maximization algorithm was used to estimate (co)variance matrices among genetic values and environmental effects for the three traits. Results indicate a need to adjust milk records for the phenotypic effects of current and previous calving interval. The genetic association, however, between fertility and milk yield appears small. Genetic improvement of 450 kg of milk yield may result in 2 added d to first calving interval.     

Multitrait estimation of relationships of first-lactation yields to body weight changes in Holstein heifers

An experimental population of 994 Holstein heifers from 56 sires was used to estimate simultaneously heritabilities and genetic and phenotypic correlations between first-lactation yields and prepartum and postpartum weight changes. Variance and covariance components were estimated by the multitrait restricted maximum likelihood method. Heritability estimates were .09, .15, and .32 for first-lactation milk, protein, and fat yields. Heritability estimates ranged from .20 to .34 for prepartum and postpartum body weights and weight changes of first lactation. Weight gain from 350 to 462 d of age was highly correlated, genetically and phenotypically, with first-lactation milk, protein, and fat yields. Genetic and phenotypic correlations between first-lactation yields and body weights at calving and at 56, 112, 168, 224, and 280 d postpartum were positive, suggesting that the larger heifers had higher lactation yields. In contrast, genetic and phenotypic correlations between yields and weight gains during the first lactation were negative, indicating that high-producing heifers gained less weight during lactation than low-producing heifers. Heifers lost an average of 23 kg from calving to 56 d postpartum and gained weight thereafter. On genetic and phenotypic scales, larger heifers at first calving lost more weight from calving to 56 d postpartum and gained less weight from 56 d postpartum onward than smaller heifers.     

Genetic relationships between body condition score and reproduction traits in Canadian Holstein and Ayrshire first-parity cows

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and reproduction traits for first-parity Canadian Ayrshire and Holstein cows. Body condition scores were collected by field staff several times over the lactation in herds from Québec, and reproduction records (including both fertility and calving traits) were extracted from the official database used for the Canadian genetic evaluation of those herds. For each breed, six 2-trait animal models were run; they included random regressions that allowed the estimation of genetic correlations between BCS over the lactation and reproduction traits that are measured as a single lactation record. Analyses were undertaken on data from 108 Ayrshire herds and 342 Holstein herds. Average daily heritabilities of BCS were close to 0.13 for both breeds; these relatively low estimates might be explained by the high variability among herds and BCS evaluators. Genetic correlations between BCS and interval fertility traits (days from calving to first service, days from first service to conception, and days open) were negative and ranged between −0.77 and −0.58 for Ayrshire and between −0.31 and −0.03 for Holstein. Genetic correlations between BCS and 56-d nonreturn rate at first insemination were positive and moderate. The trends of these genetic correlations over the lactation suggest that a genetically low BCS in early lactation would increase the number of days that the primiparous cow was not pregnant and would decrease the chances of the primiparous cow to conceive at first service. Genetic correlations between BCS and calving traits were generally the strongest at calving and decreased with increasing days in milk. The correlation between BCS at calving and maternal calving ease was 0.21 for Holstein and 0.31 for Ayrshire and emphasized the relationship between fat cows around calving and dystocia. Genetic correlations between calving traits and BCS during the subsequent lactation were moderate and favorable, indicating that primiparous cows with a genetically high BCS over the lactation would have a greater chance of producing a calf that survived (maternal calf survival) and would transmit the genes that allowed the calf to be born more easily (maternal calving ease) and to survive (direct calving ease).     

Genetic parameters for female fertility, locomotion, body condition score, and linear type traits in Czech Holstein cattle

The aim of this study was to estimate genetic parameters for fertility traits and linear type traits in the Czech Holstein dairy cattle population. Phenotypic data regarding 12 linear type traits, measured in first lactation, and 3 fertility traits, measured in each of first and second lactation, were collected from 2005 to 2009 in the progeny testing program of the Czech-Moravian Breeders Corporation. The number of animals for each linear type trait was 59,467, except for locomotion, where 53,436 animals were recorded. The 3-generation pedigree file included 164,125 animals. (Co)variance components were estimated using AI-REML in a series of bivariate analyses, which were implemented via the DMU package. Fertility traits included days from calving to first service (CF1), days open (DO1), and days from first to last service (FL1) in first lactation, and days from calving to first service (CF2), days open (DO2), and days from first to last service (FL2) in second lactation. The number of animals with fertility data varied between traits and ranged from 18,915 to 58,686. All heritability estimates for reproduction traits were low, ranging from 0.02 to 0.04. Heritability estimates for linear type traits ranged from 0.03 for locomotion to 0.39 for stature. Estimated genetic correlations between fertility traits and linear type traits were generally neutral or positive, whereas genetic correlations between body condition score and CF1, DO1, FL1, CF2 and DO2 were mostly negative, with the greatest correlation between BCS and CF2 (−0.51). Genetic correlations with locomotion were greatest for CF1 and CF2 (−0.34 for both). Results of this study show that cows that are genetically extreme for angularity, stature, and body depth tend to perform poorly for fertility traits. At the same time, cows that are genetically predisposed for low body condition score or high locomotion score are generally inferior in fertility.     

Genetic relationships among body condition score,body weight,milk yield,and fertility in dairy cows

Genetic (co)variances between body condition score (BCS), body weight (BW), milk production, and fertility-related traits were estimated. The data analyzed included 8591 multiparous Holstein-Friesian cows with records for BCS, BW, milk production, and/or fertility from 78 seasonal calving grass-based farms throughout southern Ireland. Of the cows included in the analysis, 4402 had repeated records across the 2 yr of the study. Genetic correlations between level of BCS at different stages of lactation and total lactation milk production were negative (-0.51 to -0.14). Genetic correlations between BW at different stages of lactation and total lactation milk production were all close to zero but became positive (0.01 to 0.39) after adjusting BW for differences in BCS. Body condition score at different stages of lactation correlated favorably with improved fertility; genetic correlations between BCS and pregnant 63 d after the start of breeding season ranged from 0.29 to 0.42. Both BW at different stages of lactation and milk production tended to exhibit negative genetic correlations with pregnant to first service and pregnant 63 d after the start of the breeding season and positive genetic correlations with number of services and the interval from first service to conception. Selection indexes investigated illustrate the possibility of continued selection for increased milk production without any deleterious effects on fertility or average BCS, albeit, genetic merit for milk production would increase at a slower rate.     

The genetic relationship between calving interval, body condition score and linear type and management traits in registered Holsteins

The trend to poorer fertility in dairy cattle with rising genetic merit for production over the last decade suggests that breeding goals need to be broadened to include fertility. This requires reliable estimates of genetic (co)variances for fertility and other traits of economic importance. In the United Kingdom at present, reliable information on calving dates and hence calving intervals are available for most dairy cows. Data in this study consisted of 44,672 records from first lactation heifers on condition score, linear type score, and management traits in addition to 19,042 calving interval records. Animal model REML was used to estimate (co)variance components. Genetic correlations of body condition score (BCS) and angularity with calving interval were -0.40 and 0.47, respectively, thus cows that are thinner and more angular have longer calving intervals. Genetic correlations between calving interval and milk, fat, and protein yields were between 0.56 and 0.61. Records of phenotypic calving interval were regressed on sire breeding values for BCS estimated from records taken at different months of lactation and breeding values for BCS change. Genetic correlations inferred from these regressions showed that BCS recorded 1 mo after calving had the largest genetic correlation with calving interval in first lactation cows. It may be possible to combine information on calving interval, BCS, and angularity into an index to predict genetic merit for fertility.     

Genetic analysis of milk production traits of polish black and white cattle using large-scale random regression test-day models

Genetic parameters for milk, fat, and protein yield and persistency in the first 3 lactations of Polish Black and White cattle were estimated. A multiple-lactation model was applied with random herd-test-day effect, fixed regressions for herd-year and age-season of calving, and random regressions for the additive genetic and permanent environmental effects. Three data sets with slightly different edits on minimal number of days in milk and the size of herd-year class were used. Each subset included more than 0.5 million test-day records and more than 58,000 cows. Estimates of covariance components and genetic parameters for each trait were obtained by Bayesian methods using the Gibbs sampler. Due to the large size and a good structure of the data, no differences in estimates were found when additional criteria for record selection were applied. More than 95% of the genetic variance for all traits and lactations was explained by the first 2 principal components, which were associated with the mean yield and lactation persistency. Heritabilities of 305-d milk yield in the first 3 lactations (0.18, 0.16, 0.17) were lower than those for fat (0.12, 0.11, 0.12) and protein (0.13, 0.14, 0.15). Estimates of daily heritabilities increased in general with days in milk for all traits and lactations, with no apparent abnormalities at the beginning or end of lactation. Genetic correlations between yields in different lactations ranged from 0.74 (fat yield in lactations 1 and 3) to 0.89 (milk yield in lactations 2 and 3). Persistency of lactation was defined as the linear regression coefficient of the lactation curve. Heritability of persistency increased with lactation number for all traits and genetic correlations between persistency in different lactations were smaller than those for 305d yield. Persistency was not genetically correlated with the total yield in lactation.     

Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish holstein cows

Using a mixed linear animal model, genetic parameters were estimated for clinical mastitis (MAST), lactation average somatic cell score (LSCS), and milk production traits in the first 3 lactations of more than 200,000 Swedish Holstein cows with first calving from 1995 to 2000. Heritability estimates for MAST (0.01 to 0.03) were distinctly lower than those for LSCS (0.10 to 0.14) and production traits (0.23 to 0.36). The genetic correlation between MAST and LSCS was high for all lactations (mean 0.70), implying that selection for low LSCS will reduce the incidence of mastitis. Undesirable genetic relationships with production were found for both MAST and LSCS with genetic correlations ranging from 0.01 to 0.45. This emphasizes the need for including udder health traits in the breeding goal. Genetic correlations across lactations for the same trait were positive and high for both MAST (>0.7), LSCS (>0.8), and production traits (>0.9), with the strongest correlations between second and third parity for all traits (>0.9 for udder health traits and close to unity for production traits).     

Random herd curves in a test-day model for milk, fat, and protein production of dairy cattle in The Netherlands

With random regression models, genetic parameters of test-day milk production records of dairy cattle can be estimated directly from the data. However, several researchers that used this method have reported unrealistically high variances at the borders of the lactation trajectory and low genetic correlations between beginning and end of lactation. Recently, it has been proposed to include herd-specific regression curves in the random regression model. The objective was to study the effect of including random herd curves on estimated genetic parameters. Genetic parameters were estimated with 2 models; both included random regressions for the additive genetic and permanent environmental effect, whereas the second model also included a random regression effect for herd x 2-yr period of calving. All random regressions were modeled with fourth-order Legendre polynomials. Bayesian techniques with Gibbs sampling were used to estimate all parameters. The data set comprised 857,255 test-day milk, fat, and protein records from lactations 1, 2, and 3 of 43,990 Holstein cows from 544 herds. Genetic variances estimated by the second model were lower in the first 100 d and at the end of the lactation, especially in lactations 2 and 3. Genetic correlations between d 50 and the end of lactation were around 0.25 higher in the second model and were consistent with studies where lactation stages are modeled as different traits. Subsequently, estimated heritabilities for persistency were up to 0.14 lower in the second model. It is suggested to include herd curves in a random regression model when estimating genetic parameters of test-day production traits in dairy cattle.     

Genetic analysis of clinical mastitis, milk fever, ketosis, and retained placenta in three lactations of Norwegian red cows

The objectives were to infer heritability and genetic correlations between clinical mastitis (CM), milk fever (MF), ketosis (KET), and retained placenta (RP) within and between the first 3 lactations and to estimate genetic change over time for these traits. Records of 372,227 daughters of 2411 Norwegian Red (NRF) sires were analyzed with a 12-variate (4 diseases × 3 lactations) threshold model. Within each lactation, absence or presence of each of the 4 diseases was scored based on the cow's health recordings. Each disease was assumed to be a different trait in each of the 3 lactations. The model for liability had trait-specific effects of year-season of calving and age of calving (first lactation) or month-year of calving and calving interval (second and third lactations), herd-5-yr, sire of the cow, and a residual. Posterior means of heritability of liability in first, second, and third lactations were 0.08, 0.07, and 0.07, respectively, for CM; 0.09, 0.11, and 0.13 for MF; 0.14, 0.16, and 0.15 for KET, and 0.08 in all 3 lactations for RP. Posterior means of genetic correlations between liability to CM, MF, KET, and RP, within disease between lactations, ranged from 0.19 to 0.86, and were highest between KET in different lactations. Correlations involving first lactation MF were low and had higher standard deviations. Genetic correlations between diseases were low or moderate (from −0.10 to 0.40), within as well as between lactations; the largest estimates were for MF and KET, and the lowest involved MF or KET and RP. Positive genetic correlations between diseases suggest that some general disease resistance factor with a genetic component exists. Trends of average sire posterior means by birth-year of daughters were used to assess genetic change, and the results indicated genetic improvement of resistance to CM and KET and no genetic change for MF and RP in the NRF population.     

Short communication: Genetic relationship between calving traits and body condition score before and after calving in Canadian Ayrshire second-parity cows

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and calving traits (including calving ease and calf survival) for Ayrshire second-parity cows in Canada. The use of random regression models allowed assessment of the change of genetic correlation from 100 d before calving to 335 d after calving. Therefore, the influence of BCS in the dry period on subsequent calving could be studied. Body condition scores were collected by field staff several times over the lactation in 101 herds from Québec and calving records were extracted from the official database used for Canadian genetic evaluation of calving ease. Daily heritability of BCS increased from 0.07 on d 100 before calving to 0.25 at 335 d in milk. Genetic correlations between BCS at different stages ranged between 0.59 and 0.99 and indicated that genetic components for BCS did not change much over lactation. With the exception of the genetic correlation between BCS and direct calving ease, which was low and negative, genetic correlations between BCS and calving traits were positive and moderate to high. Correlations were the highest before calving and decreased toward the end of the ensuing lactation. The correlation between BCS 10 d before calving and maternal calving ease was 0.32 and emphasized the relationship between fat cows before calving with dystocia. Standards errors of the genetic correlations estimates were low. Genetic correlations between BCS and calf survival were moderate to high and favorable. This indicates that cows with a genetically high BCS across lactation would have a greater chance of producing a calf that survived (maternal calf survival) and that they would transmit genes that allow the calf to survive (direct calf survival).     

Genetic parameters for level and change of body condition score and body weight in dairy cows

(Co)variance components for body condition score (BCS), body weight (BW), BCS change, BW change, and milk yield traits were estimated. The data analyzed included 6646 multiparous Holstein-Friesian cows with records for BCS, BW, and(or) milk yield at different stages of lactation from 74 dairy herds throughout Southern Ireland. Heritability estimates for BCS ranged from 0.27 to 0.37, while those for BCS change ranged from 0.02 to 0.10. Heritability estimates for BW records varied from 0.39 to 0.50, while heritabilities for BW change were similar to those observed for BCS change (0.03 to 0.09). The genetic correlations between BCS and BW at the same days in milk deviated little from 0.50, and the genetic correlations between BCS change and BW change over the same period ranged from 0.42 to 0.55. BCS and BW directly postpartum were both phenotypically and genetically negatively correlated with both BW change and BCS change in early lactation. The genetic correlations between BCS and milk yield were negative. The results of the present study show that animals that lose most BCS in early lactation tend to gain most BCS in late lactation, a trend also exhibited by BW.     

Estimates of genetic and environmental (co)variances for first lactation on milk yield, survival, and calving interval

Variance and covariance components for milk yield, survival to second freshening, calving interval in first lactation were estimated by REML with the expectation and maximization algorithm for an animal model which included herd-year-season effects. Cows without calving interval but with milk yield were included. Each of the four data sets of 15 herds included about 3000 Holstein cows. Relationships across herds were ignored to enable inversion of the coefficient matrix of mixed model equations. Quadratics and their expectations were accumulated herd by herd. Heritability of milk yield (.32) agrees with reports by same methods. Heritabilities of survival (.11) and calving interval(.15) are slightly larger and genetic correlations smaller than results from different methods of estimation. Genetic correlation between milk yield and calving interval (.09) indicates genetic ability to produce more milk is lightly associated with decreased fertility.     

Clinical ketosis: phenotypic and genetic correlations between occurrences and with milk yield.

The repeatability and heritability of ketosis were estimated using data from 28,277 Finnish Ayrshire cows. A four-trait linear model including community-year, calving age and month, genetic group, and random sire effects was used to describe first and second lactation milk yields and veterinary diagnoses of ketosis. Variance components were estimated using REML. The disease traits were also analyzed with a categorical model including the same effects except that community and year were separate factors. Variance components were estimated with marginal maximum likelihood. Genetic relationships between 339 sires analyzed were included in models. The phenotypic correlation between the first and second lactation was defined as a repeatability of trait. The lactational incidence risk of ketosis was .05 in both the first and the second lactation. Average milk production was 4956 and 5547 kg in the first and second lactations, respectively. Estimates of heritabilities were .09 and .07 for ketosis and .23 and .19 for milk in the first and second lactations, respectively. Genetic correlations between first and second lactation recordings were .64 for ketosis and .93 for milk. Repeatabilities between subsequent lactations were .36 (.13 in linear analysis) for ketosis and .68 for milk. In the first lactation, genetic relationship between milk yield and ketosis was unfavorable, but in the second lactation ketosis and milk yield were genetically and phenotypically unrelated.     

Multivariate threshold model analysis of clinical mastitis in multiparous norwegian dairy cattle

A Bayesian multivariate threshold model was fitted to clinical mastitis (CM) records from 372,227 daughters of 2411 Norwegian Dairy Cattle (NRF) sires. All cases of veterinary-treated CM occurring from 30 d before first calving to culling or 300 d after third calving were included. Lactations were divided into 4 intervals: -30 to 0 d, 1 to 30 d, 31 to 120 d, and 121 to 300 d after calving. Within each interval, absence or presence of CM was scored as "0" or "1" based on the CM episodes. A 12-variate (3 lactations x 4 intervals) threshold model was used, assuming that CM was a different trait in each interval. Residuals were assumed correlated within lactation but independent between lactations. The model for liability to CM had interval-specific effects of month-year of calving, age at calving (first lactation), or calving interval (second and third lactations), herd-5-yr-period, sire of the cow, plus a residual. Posterior mean of heritability of liability to CM was 0.09 and 0.05 in the first and last intervals, respectively, and between 0.06 and 0.07 for other intervals. Posterior means of genetic correlations of liability to CM between intervals ranged from 0.24 (between intervals 1 and 12) to 0.73 (between intervals 1 and 2), suggesting interval-specific genetic control of resistance to mastitis. Residual correlations ranged from 0.08 to 0.17 for adjacent intervals, and between -0.01 and 0.03 for nonadjacent intervals. Trends of mean sire posterior means by birth year of daughters were used to assess genetic change. The 12 traits showed similar trends, with little or no genetic change from 1976 to 1986, and genetic improvement in resistance to mastitis thereafter. Annual genetic change was larger for intervals in first lactation when compared with second or third lactation. Within lactation, genetic change was larger for intervals early in lactation, and more so in the first lactation. This reflects that selection against mastitis in NRF has emphasized mainly CM in early first lactation, with favorable correlated selection responses in second and third lactations suggested.