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.     

Genetic relationships between persistency and reproductive performance in first-lactation Canadian holsteins

The main objective of this study was to estimate genetic relationships between lactation persistency and reproductive performance in first lactation. Relationships with day in milk at peak milk yield and estimated 305-d milk yield were also investigated. The data set contained 33,312 first-lactation Canadian Holsteins with first-parity reproductive, persistency, and productive information. Reproductive performance traits included age at first insemination, nonreturn rate at 56 d after first insemination as a virgin heifer and as a first-lactation cow, calving difficulty at first calving and calving interval between first and second calving. Lactation persistency was defined as the Wilmink b parameter for milk yield and was calculated by fitting lactation curves to test day records using a multiple-trait prediction procedure. An 8-trait genetic analysis was performed using the Variance Component Estimation package (VCE 5) via Gibbs sampling to estimate genetic parameters for all traits. Heritabilities of persistency, day in milk at peak milk yield and estimated 305-d milk yield were 0.18, 0.09 and 0.45, respectively. Heritabilities of reproduction were low and ranged from 0.03 to 0.19. The highest heritability was for age at first insemination. Heifer reproductive traits were lowly genetically correlated, whereas cow reproductive traits were moderately correlated. Heifers younger than average when first inseminated and/or conceived successfully at first insemination tended to have a more persistent first lactation. First lactation was more persistent if heifers had difficulty calving (r(g) = 0.43), or conceived successfully at first insemination in first lactation (r(g) = 0.32) or had a longer interval between first and second calving (r(g) = 0.17). Estimates of genetic correlations of reproductive performance with estimated 305-d milk yield were different in magnitude, but similar in sign to those with persistency (0.02 to 0.51).     

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.     

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.     

Genetic parameters for fertility of dairy heifers and cows at different parities and relationships with production traits in first lactation

The objectives of this study were to estimate genetic parameters for fertility of Brown Swiss cattle, considering reproductive measures in different parities as different traits, and to estimate relationships between production traits of first lactation and fertility of heifers and first-parity and second-parity cows. Reproductive indicators were interval from parturition to first service, interval from first service to conception, interval from parturition to conception, number of inseminations to conception, conception rate at first service, and nonreturn rate at 56 d after first service. Production traits were peak milk yield (pMY), lactation milk yield, and lactation length (LL). Data included 37,546 records on heifers, and 24,098 and 15,653 records on first- and second-parity cows, respectively. Cows were reared in 2,035 herds, calved from 1999 to 2007, and were progeny of 527 AI bulls. Gibbs sampling was implemented to obtain (co)variance components using both univariate and bivariate threshold and censored linear sire models. Estimates of heritability for reproductive traits in heifers (0.016 to 0.026) were lower than those in first-parity (0.017 to 0.142) and second-parity (0.026 to 0.115) cows. Genetic correlations for fertility in first- and second-parity cows were very high (>0.920), whereas those between heifers and lactating cows were moderate (0.348 to 0.709). The latter result indicates that fertility in heifers is a different trait than fertility in lactating cows, and hence it cannot be used as robust indicator of cow fertility. Heifer fertility was not related to production traits in first lactation (genetic correlations between −0.215 and 0.251). Peak milk yield exerted a moderate and unfavorable effect on the interval from parturition to first service (genetic correlations of 0.414 and 0.353 after first and second calving, respectively), and a low and unfavorable effect on other fertility traits (genetic correlations between −0.281 and 0.295). Infertility after first calving caused a strong elongation of the lactation, and LL was negatively correlated with fertility of cows after second calving, so that LL can itself be regarded as a measure of fertility. Lactation milk yield depends on both pMY and LL, and, as such, is a cause and consequence of (in)fertility.     

Variance-covariance components associated with trimester yields of milk and fat and multiple trait sire evaluation for trimester yields

Genotypic and phenotypic variances and covariances for milk and fat yields of three equally-spaced intervals in first lactation, days 1 to 90, 91 to 180, and 181 to 270, were estimated from 26,523 records of initial progeny-test daughters of 2,086 Holstein sires. Henderson's method 3 was used with a model that included fixed herd-years, fixed age-month of freshening, and random sire and residual effects. Heritabilities for milk yields were .21, .21, and .13 for the first, second, and third 90 days in lactation and for fat yields were .19, .16, and .10. Heritabilities for milk and fat yields over the entire 270 days postpartum were .22 and .22. Genetic correlations among partial yields were high and ranged from .74 to .99 for milk and .86 to .99 for fat. Genotypic and phenotypic variances were used to predict breeding values for trimester milk yield by multiple trait, mixed model procedures for 3,797 Holstein artificial insemination sires from 283,900 first-lactation milk records of their daughters during the first 90, second 90, and third 90 days in lactation. Correlations among proofs for the three trimesters ranged from .85 to .94. Correlation between the sum of three trimester multiple trait proofs and proof for milk yield for 270 days of lactation from single trait analysis was .99. Correlations among proofs indicate sires may rank differently for milk yield in the three periods.     

Heritabilities and correlations among body condition scores, production traits, and reproductive performance

The objectives of this study were to estimate the heritability of body condition scores (BCS) from producer and consultant-recorded data and to describe the genetic and phenotypic relationships among BCS, production traits, and reproductive performance. Body condition scores were available at calving, postpartum, first service, pregnancy check, before dry off, and at dry off from the Dairy Records Management Systems in Raleigh, NC, through the PCDART program. Heritabilities, genetic correlations, and phenotypic correlations were estimated assuming an animal model using average information REML. Herd-year-season effects and age at calving were included in all models. Prior calving interval was included in models for second and third lactations. Analyses that included reproductive traits were conducted with and without mature equivalent milk as a covariable. Heritability estimates for BCS ranged from 0.09 at dry-off to 0.15 at postpartum in first lactation. Heritability estimates ranged from 0.07 before dry-off to 0.20 at pregnancy check in second lactation and from 0.08 before dry-off to 0.19 at first service in third lactation. Genetic correlations between adjacent BCS within first lactation were greater than 0.96 with the exception of calving and postpartum (0.74). In second lactation, adjacent genetic correlations were 1.0 with the exception of calving and postpartum (0.84). Genetic correlations across lactations were greater than 0.77. Phenotypic correlations between scoring periods were highest for adjacent scoring periods and when BCS was lowest. Phenotypic correlations were lower than genetic correlations, i.e., less than 0.70. Higher BCS during the lactation were negatively related to production, both genetically and phenotypically, but the relationship was moderate. Higher BCS were favorably related genetically to reproductive performance during the lactation.     

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.     

Age and Zebu-Holstein additive and heterotic effects on lactation performance and reproduction in Brazil

Data of 6482 lactations from 14 crossbred (Holstein x Zebu) herds in Brazil were used to study breed additive and heterosis effects for first, second, third, and first to fifth lactation milk yields, age at first calving, calving interval, and milk yield divided by calving interval, as well as the effect of age at calving on milk yield. Holstein additive expressed as deviation from Zebu and heterosis effects were highly significant for all traits. For each percentage of Holstein gene contribution an increase of 10.02, 12.02, 12.51, and 12.15 kg of milk were expected for first, second, third, and first to fifth lactation yields, respectively. Corresponding heterosis effects on those traits were 3.80, 3.39, 4.02, and 3.90 kg of milk for each percentage of heterozygosity. Replacement of pure Zebu genes by Holstein genes reduced age at first calving by 6 mo and shortened calving interval by 37 d. Holstein x Zebu heterotic effect decreased age at first calving by 2 mo and calving interval by 39 d. Holstein additive and heterosis effects for milk yield divided by calving interval were 3.4 and 1.3 kg of milk/d, respectively. Fitting breed additive and heterozygosity effects accounted for 99% of the genetic effects except for first to fifth lactation milk yield.     

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.     

Weight and age at calving and weight change related to first lactation milk yield

Daily milk yields from 400 first lactations collected from one herd over 16 yr were utilized to ascertain relations of weight and age at calving and change of body weight during first lactation on milk yield and calving interval. These relationships were evaluated for the complete lactation and for each of five 60-day segments of the lactation. The influence of sire on the interrelationship between body weight, age at calving, and milk yield also were measured in data from sires with 10 or more daughters. Average milk yield (300 day) and gain of body weight during first lactation for all records were 5544 and 56.2 kg. Both year and season of calving influenced weight at calving, milk yield, and the relationship between the two. Milk yield was the greatest and body weight gain the least for heifers calving in the fall. Analysis of all records revealed that calving weight but not calving age accounted for a significant portion of variation of milk yield during the first four 60-day periods. Both calving weight and age accounted for a significant amount of the variation of total milk yield. There was a significant effect of sire on calving weight and milk yield but not on total weight gain, age at calving, number of services, or calving interval. There was an increase of number of services and a trend toward a longer calving interval with increasing milk yield. Although age and weight at calving were nearly equal for explaining variation of total yield of milk of first lactation, age at calving was of little value in explaining variation of milk yield of the 60-day intervals. The relationship of these observations to the use of age correction factors for extended first lactation records is discussed.     

Genetic and phenotypic relationships among milk urea nitrogen, fertility, and milk yield in holstein cows

The aims of the study were to evaluate the relationships among milk urea nitrogen and nonreturn rates at the phenotypic scale, and to estimate genetic parameters among milk urea nitrogen, milk yield, and fertility traits in the early period of lactation. Milk yield, protein percentage, the interval from calving to first service, and 56- and 90-d nonreturn rates were available from 73,344 Holstein cows from 2,178 different herds located in a region in northwestern Germany. Generalized linear models with a logit link function were applied to assess the phenotypic relationships. Bivariate threshold-threshold, linear-threshold, and linear-linear models, fitted in a Bayesian framework, were used to estimate genetic correlations among traits. Milk yield, protein percentage, and milk urea nitrogen were means from test-day 1 (on average 20.8 d in milk) and test-day 2 (on average 53.1 d in milk) after calving. An increase in milk urea nitrogen was associated with decreasing 56-d nonreturn rates on the phenotypic scale. At fixed levels of milk urea nitrogen, greater values of protein percentage, indicating a surplus of energy in the feed, were positively associated with nonreturn rates. Heritabilities were 0.03 for 56- and 90-d nonreturn rates, 0.07 for interval from calving to first service, 0.13 for milk urea nitrogen, and 0.19 for milk yield. Service sire explained a negligible part (below 0.15%) of the total variance for nonreturn rates. Genetic correlations between the interval from calving to first service and nonreturn rates were close to zero. The genetic correlation between nonreturn rates was 0.94, suggesting that a change from nonreturn after 90 d to nonreturn after 56 d in the national genetic evaluation would not result in any loss of information. The genetic correlation between milk yield and nonreturn after 56 d was −0.31, and between milk yield and calving to first service was 0.14, both indicating an antagonistic relationship between production and reproduction. The genetic correlation between milk yield and milk urea nitrogen was 0.44, reflecting an energy deficiency in early lactation. The genetic correlations between milk urea nitrogen and nonreturn rates were too weak (−0.19 for 56-d nonreturn rate, and −0.23 for 90-d nonreturn rate) to justify the use of milk urea nitrogen as an additional trait in genetic selection for fertility, as demonstrated by selection index calculations.     

Genetic parameter estimates of portuguese dairy cows for milk, fat, and protein using a spline test-day model

A spline animal model was fitted to 152,103 test-day milk, fat, and protein yield records from 14,423 first-lactation cows. The models included age at calving and the herd-test-month as fixed effects. Model fitting was carried out using Restricted Maximum Likelihood with ASREML. For milk yield, the heritability at 18 d in milk was 0.19, which increased to the maximum estimated value of 0.23 at midlactation and then decreased. On average, milk, fat, and protein yield heritabilities were 0.22, 0.14, and 0.19, respectively.For milk yield, all correlations were positive and ranged from 0.54 to 0.99 for the genetic component and from 0.32 to 0.78 for the phenotypic component. Genetic correlations were higher than phenotypic ones. For fat and protein yields, all genetic correlations were positive, ranging from 0.43 to 0.99. The phenotypic correlations for fat yield had the lowest correlations of the 3 traits.Curves of estimated breeding values for milk, fat, and protein over lactation had positive deviations from mean curves for sires with high genetic merit, but there was considerable variability in the shapes of the curves for different sires. More research is needed to compare the spline function with other mathematical functions used as submodels of lactation curve.     

Genetic trends for milk yield of Jerseys and correlated changes in productive and reproductive performance

Estimates of genetic trends in 24 measures of milk and constituent yields, somatic cell counts, and reproduction were obtained from 935 records of 374 Jerseys in a single herd. Data were obtained from a designed project for single-trait selection from 1969 through 1987. One line was subjected to selection solely for milk yield and included 259 cows; an unselected control line included 115 cows. Estimates of trends were based on differences in linear phenotypic trends between lines for first lactations, all lactations, and for 305-d and total records. The genetic changes in milk yield for these four data sets were 1.22 to 1.48%/yr (36.8 to 41.0 kg per cow yr) and 0.54 to 1.64%/yr for five constituent yields. Except for the percentages of minerals plus lactose, all constituent percentages decreased by 0.05 to 0.60%/yr. The ratios of protein to fat and solids-not-fat to fat increased 0.30 to 0.54%/yr, respectively. The number of services required per conception increased (0.17%) in first parity records and in all data (0.69%). The intervals from parturition to first estrus and from parturition to first service decreased in first lactation (1.19 and 0.82%) annually but increased (1.25 and 0.01%) in all data. Age of heifers at first estrus decreased by 0.44% annually. Most of the five measures of somatic cells decreased in first lactations but increased for all data. Estimates of realized genetic correlations of 14 measures of constituent yield and composition (four correlations each) agreed well with values expected from the literature. The results quantified change in milk yield, constituent yields and percentages, reproductive performance, and somatic cell counts in a single herd and should prove useful in the development of selection programs for dairy cattle.     

Genetic parameters for first milk production and composition traits for Holsteins using multivariate restricted maximum likelihood

Heritabilities and genetic and phenotypic correlations among yields of milk, fat, protein, and percentages of fat and protein were estimated from 40,984 first lactation records of daughters of 488 young and 75 proven Holstein sires using multivariate REML and a sire model accounting for relationships and sire groups. Proven sires were treated as fixed effects. Heritabilities for yields of milk, fat, protein, and percentages of fat and protein were .29, .31, .25, .65, and .61, respectively. Genetic correlations of milk with yields of fat, protein, and percentages of fat and protein and correlations of fat yield with fat percentage were .45, .79, -.49, -.54 and .56, respectively. Genetic correlations among yields and among percentage of fat and protein were the same (.62). Genetic and phenotypic correlations of protein percentage with fat and protein yields and correlations of fat percentages with protein yield were small (-.13 to .11). Phenotypic correlations were .73 to .90 among yields of milk, fat, and protein; -.31 for milk and fat percentage; -.39 for milk and protein percentage; and .38 for fat yield and fat percentage. Estimates were consistent with an earlier study utilizing data from the same population and also with other reports.     

Lifetime profit as an individual trait and prediction of its breeding values in Spanish Holstein cows

Genetic parameters for lifetime profit and some productive traits were estimated from records of 42,401 Holstein cows with first calving before May 1996 from Navarra and Basque Autonomous Regions of Spain. Profit from the first, first two, and first three lactations were tested as early measures of profitability. Profit prediction was tested for another population of 2127 cows using selection indexes (Type-Production and economic indexes) and multitrait analysis for directly predicting profit from first-lactation records. High genetic correlations of actual profit with estimated profit from the first two or first three lactation records, (0.97 and 0.99, respectively) suggest that lifetime profit can be accurately estimated from data in second lactation. Profit was positively correlated to production traits (0.79 to 0.83), functional herd life (0.38), mature body weight (0.25), and days in milk (0.35), but genetic correlation was found to be close to zero with calving interval. Complicated relationships among profit and economic traits (i.e., calving interval, days in milk, and functional herd life) were found. Although the correlation between calving interval and profit was near zero, calving interval was the most important trait after production in prediction of sire profit by a stepwise regression analysis. Profit breeding values from multitrait analysis obtained higher correlation (0.48) with actual profit than Spanish official Type-Production index ICO (0.44) and economic index MEG (0.46). A correlation of 0.49 between profit breeding values and the economic index MEG2002, where stature and calving interval were included as new traits, was obtained.     

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 and additive genetic variation of productive and reproductive traits in Guernsey dairy cattle

Data were first lactation production and reproduction records initiated from 1958 to 1981 in two experiment station Guernsey herds. Heritability estimates using paternal half sib groups were .24 +/- .12 for milk yield, .27 +/- .12 for fat yield, and .77 +/- .15 for fat percentage. Heritability estimates for reproductive traits ranged from .01 to .04 for number of services, service period, conception rate, and days open, but were higher for days in milk at first breeding (.12) and age at first calving (.13). Except for age at first calving, coefficients of additive genetic variation were larger for reproductive traits than for productive traits. Genetic correlations between measures of production and reproduction were moderate to large and antagonistic, except that the relationship between production and age at first calving was favorable. Breeding value estimates for milk yield and reproduction were negatively correlated for sires with above average breeding values for milk yield. Huge phenotypic variances for reproductive traits masked substantial additive genetic variation for these traits. When all things are considered it seems unwise to ignore reproductive performance in selection programs for dairy cattle.     

Genetic components of heat stress for dairy cattle with multiple lactations

Data included 585,119 test-day records for milk, fat, and protein yields from the first, second, and third parities of 38,608 Holsteins in Georgia. Daily temperature-humidity indexes (THI) were available from public weather stations. Models included a repeatability test-day model with a random regression on a function of THI and a test-day random regression model using linear splines with knots at 5, 50, 200, and 305 d in milk and a function of THI. Random effects were additive genetic and permanent environmental in the repeatability model and additive genetic, permanent environmental, and herd year in the random regression model. Additionally, models included fixed effects for herd test day, calving age, milking frequency, and lactation stage. Phenotypic variance increased by 50 to 60% from the first to second parity for all yield traits with the repeatability model and by 12 to 15% from the second to third parity. General additive genetic variance increased by 25 to 35% from the first to second parity for all yield traits but decreased slightly from the second to third parity for milk and protein yields. Genetic variance for heat tolerance doubled from the first to second parity and increased by 20 to 100% from the second to third parity. Genetic correlations among general additive effects were lowest between the first and second parities (0.84 to 0.88) and were highest between the second and third parities (0.96 to 0.98). Genetic correlations among parities for the effect of heat tolerance ranged from 0.56 to 0.79. Genetic correlations between general and heat-tolerance effects across parities and yield traits ranged from −0.30 to −0.50. With the random regression model, genetic variance for heat tolerance for milk yield was approximately one-half that of the repeatability model. For milk yield, the most negative genetic correlation (approximately −0.45) between general and heat-tolerance effects was between 50 and 200 d in milk for the first parity and between 200 and 305 d in milk for the second and third parities. The genetic variance of heat tolerance increased substantially from the first to third parity. Genetic estimates of heat tolerance may be inflated with the repeatability model because of timing of lactations to avoid peak yield during hot seasons.     

Genetic analysis of milk urea nitrogen and relationships with yield and fertility across lactation

The aim of this project was to investigate the relationship of milk urea nitrogen (MUN) with 3 milk production traits [milk yield (MY), fat yield (FY), protein yield (PY)] and 6 fertility measures (number of inseminations, calving interval, interval from calving to first insemination, interval from calving to last insemination, interval from first to last insemination, and pregnancy at first insemination). Data consisted of 635,289 test-day records of MY, FY, PY, and MUN on 76,959 first-lactation Swedish Holstein cows calving from 2001 to 2003, and corresponding lactation records for the fertility traits. Yields and MUN were analyzed with a random regression model followed by a multi-trait model in which the lactation was broken into 10 monthly periods. Heritability for MUN was stable across lactation (between 0.16 and 0.18), whereas MY, FY, and PY had low heritability at the beginning of lactation, which increased with time and stabilized after 100 d in milk, at 0.47, 0.36, and 0.44, respectively. Fertility traits had low heritabilities (0.02 to 0.05). Phenotypic correlations of MUN and milk production traits were between 0.13 (beginning of lactation) and 0.00 (end of lactation). Genetic correlations of MUN and MY, FY, and PY followed similar trends and were positive (0.22) at the beginning and negative (−0.15) at the end of lactation. Phenotypic correlations of MUN and fertility were close to zero. A surprising result was that genetic correlations of MUN and fertility traits suggest a positive relationship between the 2 traits for most of the lactation, indicating that animals with breeding values for increased MUN also had breeding values for improved fertility. This result was obtained with a random regression model as well as with a multi-trait model. The analyzed group of cows had a moderate level of MUN concentration. In such a population MUN concentration may increase slightly due to selection for improved fertility. Conversely, selection for increased MUN concentration may improve fertility slightly.