Bivariate animal model estimates of genetic, phenotypic, and environmental correlations for production, reproduction, and somatic cells in Jerseys

Correlations were obtained between 18 response variables of a Jersey herd (Florida Agricultural Experiment Station, Gainesville) for 374 first lactations. Estimates were from the use of multivariate, derivative-free, restricted maximum likelihood procedures with the simplex method of partial maximization. Estimates agreed closely with those obtained previously by other methods in this and other dairy populations. All correlations between yields were high and positive; those between yields and days from parturition to first service were negative and near zero. Correlations between yields and somatic cell scores were moderate and negative; those between yields and constituent percentages in general were negative, except for the yield and percentage of the same constituent. Genetic correlations between chloride content and somatic cells and between measures of somatic cells were 1.0. Results suggest that single-trait selection for milk yield should result in correlated increases in constituent yields with slight decreases in percentage composition of constituents and somatic cell counts.     

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.     

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.     

Mastitis and the shape of the lactation curve in Norwegian dairy cows

An investigation of the shape of the lactation curve and the mastitis incidence was conducted to identify whether management interventions of the lactation curve constitute a potential for reducing incidence of mastitis at herd level. Lactation curves were estimated to describe the variation of daily milk yield during the 305-d lactation period in Norwegian Red cows. Associations between mastitis incidence at herd level and lactation curve characteristics such as production level at onset of lactation, magnitude and time of peak milk yield, and increase and decrease of milk yield rates were studied. Data from 250,303 lactations occurring during 2005 and 2006 from 14,766 herds were obtained from the Norwegian Dairy Herd Recording System. Besides veterinary treatments, the records included information on monthly test-day milk yields. The shapes of the lactation curves at herd level were parameterized using a modified Wilmink model in two separate mixed model analyses. In the first analysis a subset of lactations with no records of veterinary treatments was used. Lactation curves from herds with high (>0·31 cases/305-d lactation) and low (<0·07 cases/305-d lactation) herd mastitis incidence rate were parameterized and compared for three separate strata of parity. The result showed that high herd mastitis incidence rate was associated with a low intercept (P<0·05), a steep slope before peak milk yield (P<0·01) and a rapid decline after peak milk yield (P<0·01). In the second analysis a subset of high-yielding lactations with veterinary treatments of mastitis only and lactations with no records of veterinary treatment were compared. This was done to investigate whether the findings at herd level were also reflected at cow level. These results showed that lactation curves from lactations with mastitis cases were associated with a steep slope before peak milk yield (P<0·05) in second and later parities and a rapid decline after peak milk yield (P<0·01) in all three parity groups.     

Postpartum performance of dairy heifers freshening at young ages.

Records from Florida Agricultural Experiment Station dairy herd for 1144 heifers freshening from 1959 to 1979 were studied to evaluate effects of age and problems at parturition on subsequent yield and reproduction. Statistical analysis was by method of ordinary least squares analysis of variance; five measures of reproduction, survival to second lactation, and 15 measures of yield were studied. Mean first parturition age was 25.8 mo with 40% of individuals less than or equal to 23 mo; survival to second parturition was 67%. No effects of age at first parturition were detected on survival, postpartum reproductive performance, or milk composition other than lactose-mineral, chloride, and acidity percentages; effects on yield were similar to previous reports. Stillbirth did not affect subsequent reproductive performance but was associated with decreased milk yield: 181 kg or 5.2% of overall mean. Milk yield was depressed by 239 kg for retained fetal membrane, 173 kg for dystocia, and 98 kg for metritis; milk composition essentially was unaltered. Heritability of postpartum days to first estrus was .14; estimates were 0 for days to first service, days open, and calving interval. Additional research is needed on interrelationships of gestation length with subsequent yield and reproduction and in alleviating detrimental effects of problems at parturition.     

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 parameters for yield traits of cows treated or not treated with bovine somatotropin

The objective of this study was to estimate genetic correlations between yield traits of cows treated with bovine somatotropin (bST) and the same yield traits of untreated cows. Lactation records from registered Holstein cows were divided by parity into 3 data sets: 1, 2, and 3 through 5. Approximately 10% of the records in each data set were from cows treated with bST. The numbers of records of treated and untreated cows in the data sets were 4,337 and 48,765; 3,730 and 37,796; and 3,645 and 33,957. Two-trait animal models (records for cows treated or not treated) were used to estimate genetic parameters for milk production traits and somatic cell score (SCS). Estimates of heritability for milk yield for records of treated and untreated cows for the 3 data sets were 0.13, 0.16, and 0.09, and 0.18, 0.18, and 0.14, respectively, with estimates of repeatability of 0.50 and 0.41 for data set 3. Estimates of heritability for fat yield for records of treated and untreated cows were 0.31, 0.16, and 0.12, and 0.27, 0.21, and 0.16. Estimates of repeatability were 0.50 and 0.43 for data set 3. Heritability estimates for protein yield for records of treated and untreated cows were 0.13, 0.17, and 0.12, and 0.20, 0.23, and 0.16, with estimates of repeatability of 0.52 and 0.47. Estimates of heritability for SCS for treated and untreated cows were 0.08, 0.15, and 0.13, and 0.11, 0.13, and 0.13 with repeatability estimates of 0.52 and 0.45. Estimates of genetic correlations between milk yields with and without bST treatment in lactations 1, 2, and 3 to 5 were all 0.99. Estimates of genetic correlations for fat and protein yields were 0.96 for all data sets. Estimates for SCS were 0.99. Estimates of genetic correlations between records of treated and untreated cows were large enough to conclude that records of treated and untreated cows could be considered to be one trait, with treatment as a fixed effect to account for differences in means.     

Estimation of genetic parameters for milk yield across lactations in mixed-breed dairy goats

Currently, breeding values for dairy goats in the United Kingdom are not estimated and selection is based only on phenotypes. Several studies from other countries have applied various methodologies to estimate breeding values for milk yield in dairy goats. However, most of the previous analyses were based on relatively small data sets, which might have affected the accuracy of the parameter estimates. The objective of this study was to estimate genetic parameters for milk yield in crossbred dairy goats in lactations 1 to 4. The research was based on data provided by 2 commercial goat farms in the United Kingdom comprising 390,482 milk yield records on 13,591 dairy goats kidding between 1987 and 2012. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation, the best-performing animals were selected for breeding and, as a result, a synthetic breed was created. The pedigree file contained 28,184 individuals, of which 2,414 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. Covariance components were estimated with the average information REML algorithm in the ASReml package (VSN International Ltd., Hemel Hempstead, UK). A random regression animal model for milk yield with fixed effects of herd test day, year-season, and age at kidding was used. Heritability was the highest at 200 and 250 d in milk (DIM), reaching 0.45 in the first lactation and between 0.34 and 0.25 in subsequent lactations. After 300 DIM, the heritability started decreasing to 0.23 and 0.10 at 400 DIM in the first and subsequent lactations, respectively. Genetic correlation between milk yield in the first and subsequent lactations was between 0.16 and 0.88. This study found that milk yields in first and subsequent lactations are highly correlated, both at the genetic and phenotypic level. Estimates of heritability for milk yield were higher than most of the values reported in the literature, although they were in the range reported in this species. This should facilitate genetic improvement for the population studied as part of a broader multi-trait breeding program.     

Dry period length in US Jerseys: characterization and effects on performance

The objectives of this research were to characterize dry period lengths for US Jerseys, determine the effects of days dry (DD) on subsequent lactation actual milk, fat, and protein yields, fat and protein percentages, somatic cell score (SCS), and days open (DO), and to determine the dry period length that maximizes yield across lactations. Field data, collected through the Dairy Herd Improvement Association, on US Jersey cows first calving between January 1997 and November 2004 were used. Characterization of DD included a frequency distribution of dry period lengths as well as factors affecting US Jersey DD. Of the factors considered in this research, the primary ones affecting dry period length were DO, milk yield, and SCS. Cows with longer DO, lower milk yield, and higher SCS received longer dry periods. The model for analyses included herd-year of calving, year-state-month of calving, parity of calving, previous lactation record, age at calving, and DD as a categorical variable; records were preadjusted for cow effects. A total of 123,032 records from 73,797 cows in 808 herds were used for estimation of DD effects on subsequent lactation actual milk yield. Jersey milk, fat, and protein yields in the subsequent lactation were maximized with 61 to 65 DD. Dry periods of 30 d or fewer resulted in large reductions in subsequent lactation production. A short dry period was beneficial for fat and protein percentages in the subsequent lactation. Short dry periods also resulted in fewer DO in the subsequent lactation; however, this was entirely due to the lower milk yield associated with shortened dry periods. The biggest difference between Jerseys and Holsteins was a much larger detrimental effect on SCS in Jerseys for dry periods of 30 d or less. Jersey SCS increased 10%, relative to the overall mean, for dry periods of 20 d or less and 4.6% for DD between 21 and 30 d. Dry periods of 45 to 70 d maximized yields across adjacent lactations. A dry period length, after first lactation, of 45 to 70 d also maximized actual milk yield across lactations 1, 2, and 3. The final recommendation to Jersey producers is to avoid dry periods of <45 d. Long dry periods (>70 d) should also be avoided because these are even more costly to total yield than dry periods <30 d.     

Relationship of test-day somatic cell score with test-day and lactation milk yields

To determine the relationship of test-day (TD) somatic cell score (SCS) to TD and lactation milk yields, 1,320,590 records from Holstein first and second calvings from 1995 through 2002 were examined. All lactations had recorded yield and SCS for at least the first 4 TD. Least square analyses were conducted for yields on TD 2 through 10 within herd and cow. The model included regressions on current TD SCS and mean SCS of all previous TD with separate estimates by parity; effects for parity and calving year were included as well as regression on days in milk on TD 1. Corresponding analyses were conducted without regression on current SCS. An analysis of lactation yield was performed with a similar model and regression on all TD SCS. The SCS was highest most often on TD 1 for parity 1 (22.5%) and on TD 10 for parity 2 (18.5%). Regression of TD milk yield on mean of previous TD SCS was highest during the latter half of lactation (maximum of -0.346 kg/SCS unit on TD 9) for parity 1 and during TD through 7 (maximum of -0.366 kg/SCS unit on TD 4) for parity 2. Regression of TD yield on current TD SCS tended to be larger for later lactation. Regression of lactation yield on TD SCS was negative and important for TD 1 through 6 for parity 1 and for all TD for parity 2. To minimize milk loss, mastitis control is most important immediately pre- and postcalving for parity 1 and throughout lactation for parity 2.     

Estimating genetic values for milk production in the tropics

Variance components and predicted sire values were estimated using 305-d projected and unprojected milk records of varying lengths. Original data consisted of 15,512 lactation records of daughters of 138 Jamaica Hope sires that calved between 1969 and 1981 in 38 commercial dairy herds in Jamaica. Classification of records had little effect on components of variance. Herd-year-season variance decreased from 36% using all lactations to 28% with first lactations only. Sire variance was consistently about 10%. Cow component of variance accounted for 17% of the total variation using all lactations and 36% using all lactations of cows with recorded first lactations. Heritabilities for milk by Henderson's method 1 were five to six times larger than estimated from method 3 due to sire by herd confounding. Predicted sire values were between +400 kg and -400 kg. Rankings of sires with at least 5 progeny were considerably influenced by record classification, especially for sires with highest predicted values. There was less influence on rankings when at least 10 progeny per sire were used while the range in predicted sire values was larger using first lactation records only.     

Selection on yield and fitness traits when culling holsteins during the first three lactations

Emphasis by dairy producers on various yield and fitness traits when culling cows was documented for US Holstein calvings since 1982. Least squares differences between cows retained for additional parities and those culled were estimated for milk, fat, and protein yields; somatic cell score (SCS); days open (DO); dystocia score (DS), final score (FS), and 14 type traits. Compared with cows culled during first lactation, superiority for first-parity milk yield was 569 to 1,175 kg for cows with 2 lactations, 642 to 1,283 kg for cows with ≥2 lactations, 710 to 1,350 kg for cows with 3 lactations, and 663 to 1,331 kg for cows with ≥4 lactations. Cows retained for ≥2 lactations had first-parity SCS that were 0.34 to 0.62 lower (more favorable) than those of cows culled during first lactation; first-parity SCS for cows retained for 3 or ≥4 lactations were even more favorable than those of cows with 1 or 2 lactations. The negative genetic relationship between yield and fertility contributed to increased DO as selection for higher milk yield persisted across time despite considerable preference for early conception when culling cows. In 1982, cows retained in the herd for 2, 3, and ≥4 lactations conceived earlier during first lactation (19, 17, and 23 fewer DO, respectively) than those culled during first lactation; those differences had increased to 34, 41, and 52 fewer DO by 2000. Although DS has a negative relationship with survival, first-parity DS were only slightly lower (by 0.10 to 0.14) for survivors than for cows culled during first lactation. Cows retained for ≥2 lactations had greater first-parity FS by 1.4 to 1.9 points than those culled during first lactation. On a standardized basis, the most intense selection during first lactation was for milk and protein yields with less for fat (74 to 86% of that for milk), DO (18 to 74%), FS (22 to 38%), SCS (19 to 37%), and DS (7 to 15%). Producers continued to emphasize the same traits when culling during second and third lactations. Trait priority by producers during culling could aid in setting trait emphasis when selecting bulls for progeny test and could also be useful in developing software for index-based culling guides.     

Genetic (Co) Variances for Milk and Fat Yield in California,New York,and Wisconsin for an Animal Model by Restricted Maximum Likelihood

Two samples of data from approximately 4000 Holstein cows were analyzed by REML with a multivariate (milk and fat yields) animal model for first lactations started in 1970 through 1977 and in 1978 through 1985 and also for first lactation records started in low, middle, and high production herds in 1978 through 1985 separately for California, New York, and Wisconsin herds. Heritability estimates for milk yield (similar for fat yield) ignoring category of herd production were .29 for 1978 and later and .34 for 1977 and earlier. Estimates for low, middle, and high production herds were .23, .29, and .36. Estimates of genetic correlation between milk and fat averaged .62 for 1978 and later and .73 for 1977 and earlier; for 1978 and later these estimates were greater for California than for New York and Wisconsin, .70 vs. .58 overall. Phenotypic and environmental variances associated with low production herds were less than for middle and high production herds, but differences between middle and high herds varied by state and sample. The pattern of estimates of genetic and environmental parameters suggests that differences between California, New York, and Wisconsin are not very important for genetic evaluation procedures. Production of herds does seem important.     

Use of test-day records beyond three hundred five days for estimation of three hundred five-day breeding values for production traits and somatic cell score of Canadian Holsteins

The Canadian Test-Day Model includes test-day (TD) records from 5 to 305 d in milk (DIM). Because 60% of Canadian Holstein cows have at least one lactation longer than 305 d, a significant number of TD records beyond 305 DIM could be included in the genetic evaluation. The aim of this study was to investigate whether TD records beyond 305 DIM could be useful for estimation of 305-d estimated breeding value (EBV) for milk, fat, and protein yields and somatic cell score. Data were 48,638,184 TD milk, fat, and protein yields and somatic cell scores from the first 3 lactations of 2,826,456 Canadian Holstein cows. All production traits were preadjusted for the effect of pregnancy. Subsets of data were created for variance-component estimation by random sampling of 50 herds. Variance components were estimated using Gibbs sampling. Full data sets were used for estimation of breeding values. Three multiple-trait, multiple-lactation random regression models with TD records up to 305 DIM (M305), 335 DIM (M335), and 365 DIM (M365) were fitted. Two additional models (M305a and M305b) used TD records up to 305 DIM and variance components previously estimated by M335 and M365, respectively. The effects common to all models were fixed effects of herd × test-date and DIM class, fixed regression on DIM nested within region × age × season class, and random regressions for additive genetic and permanent environmental effects. Legendre polynomials of order 6 and 4 were fitted for fixed and random regressions, respectively. Rapid increase of additive genetic and permanent environmental variances at extremes of lactations was observed with all 3 models. The increase of additive genetic and permanent environmental variances was at earlier DIM with M305, resulting in greater variances at 305 DIM with M305 than with M335 and M365. Model M305 had the best ability to predict TD yields from 5 through 305 DIM and less error of prediction of 305-d EBV than M335 and M365. Model M335 had smaller change of 305-d EBV of bulls over the period of 7 yr than did M305 and M365. Model M305a had the least error of prediction and change of 305-d EBV from all models. Therefore, the use of TD records of Holstein cows from 5 through 305 DIM and variance components estimated using records up to 335 DIM is recommended for the Canadian Test-Day Model.     

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.     

Effects of mild inbreeding on productive and reproductive performance of Guernsey cattle

Production and reproduction records that spanned a 24-yr period were used to study the effects of low coefficients of inbreeding in two experiment station Guernsey herds. Inbreeding ranged from 0 to 25.3% and averaged 4.1%. Milk and fat yields were all first lactations standardized to a mature equivalent, twice daily milking, and 305 d. Intrasire regressions of production traits on percent inbreeding were -23.8 kg of milk, -1.25 kg of fat, and .002% for fat percentage. Estimates of the effect of inbreeding on reproductive traits had large standard errors but suggested that inbreeding depressed reproductive performance. Age at first calving decreased 3.7 d per 1% increase in inbreeding.     

Genetic (Co)Variances for Milk,Fat, and Protein Yield in Holsteins Using an Animal Model

First lactation milk, fat, and protein yields for first lactations of 8044 Holstein cows in New York from 24 herds were used to estimate genetic and phenotypic covariances with an animal model by restricted maximum likelihood. Numerator relationships within herd, including those from sires, were utilized, although relationships across herds were ignored. Each analysis was terminated after 300 rounds of iteration. Average milk production (twice daily milking, 305-d lactation, mature equivalent) was 8630 kg. Estimates were obtained for each individual herd and groups of 3, 6, and 12 herds. Average estimates from separate analyses of the 24 herds were nearly identical to those from combined analysis. Heritability estimates from combined analysis were .36, .35, and .33 for milk, fat, and protein yield with standard errors of approximately .03. Genetic correlations were .72 for milk and fat, .88 for milk and protein, and .77 for fat and protein. Phenotypic correlations were .81, .91, and .82. Heritability estimates for individual herds were quite variable with standard errors of about .15. The largest environmental standard deviation for a herd was about twice the smallest. Estimates from only one analysis failed to converge—a group of three herds. All single herd analyses reached convergence as did the other 7 trios of herds and all sets of 6 and 12 herds.     

Genetic parameters and trends of milk, fat, days open, and body weight after calving in North Carolina experimental herds

The main objective of this study was to estimate genetic trends for 3.7% FCM, fat yield, days open, and predicted body weight after calving in six experimental dairy herds owned by the State Farm Division of the North Carolina Department of Agriculture. Body weights were predicted from heart girths measured at or before the first test day after calving. Data analyzed were 23,052 records from 8575 cows, daughters of 681 bulls. Heritabilities and breeding values were estimated using the multiple-trait, derivative-free REML programs and a single-trait repeatability model. Breeding values of cows were averaged by and regressed on birth year to estimate genetic trends. Genetic correlations between traits were estimated by correlating breeding values. Estimates of heritability were 0.25 for 3.7% FCM, 0.28 for fat yield, 0.03 for days open, and 0.17 for predicted body weight. Unfavorable genetic relationships were found between yields and days open and between yields and body weight. Genetically, cows that were heavier after calving produced less milk and fat but conceived earlier than smaller cows. Genetic changes in yields and days open were greater for cows born after 1970, but the greatest genetic changes were after 1980 (FCM, 94.7 kg/yr; fat yield, 3.46 kg/yr; days open, 1.1 d/yr). Breeding values for body weight increased for cows born from 1950 to 1970, decreased until 1980, and increased for later parities. The results of our study suggest that AI organizations may need to include fertility traits in progeny testing and relax the emphasis on increased body weight.     

Preweaning milk replacer intake and effects on long-term productivity of dairy calves

The preweaning management of dairy calves over the last 30 yr has focused on mortality, early weaning, and rumen development. Recent studies suggest that nutrient intake from milk or milk replacer during the preweaning period alters the phenotypic expression for milk yield. The objective of this study was to investigate the relationship between nutrient intake from milk replacer and pre- and postweaning growth rate with lactation performance in the Cornell dairy herd and a commercial dairy farm. The analysis was conducted using traditional 305-d first-lactation milk yield and residual lactation yield estimates from a test-day model (TDM) to analyze the lactation records over multiple lactations. The overall objective of the calf nutrition program in both herds was to double the birth weight of calves by weaning through increased milk replacer and starter intake. First-lactation 305-d milk yield and residuals from the TDM were generated from 1,244 and 624 heifers from the Cornell herd and from the commercial farm, respectively. The TDM was used to generate lactation residuals after accounting for the effects of test day, calving season, days in milk, days pregnant, lactation number, and year. In addition, lactation residuals were generated for cattle with multiple lactations to determine if the effect of preweaning nutrition could be associated with lifetime milk yield. Factors such as preweaning average daily gain (ADG), energy intake from milk replacer as a multiple of maintenance, and other growth outcomes and management variables were regressed on TDM milk yield data. In the Cornell herd, preweaning ADG, ranged from 0.10 to 1.58 kg, and was significantly correlated with first-lactation yield; for every 1 kg of preweaning ADG, heifers, on average, produced 850 kg more milk during their first lactation and 235 kg more milk for every Mcal of metabolizable energy intake above maintenance. In the commercial herd, for every 1 kg of preweaning ADG, milk yield increased by 1,113 kg in the first lactation and further, every 1 kg of prepubertal ADG was associated with a 3,281 kg increase in first-lactation milk yield. Among the 2 herds, preweaning ADG accounted for 22% of the variation in first-lactation milk yield as analyzed with the TDM. These results indicate that increased growth rate before weaning results in some form of epigenetic programming that is yet to be understood, but has positive effects on lactation milk yield. This analysis identifies nutrition and management of the preweaned calf as major environmental factors influencing the expression of the genetic capacity of the animal for milk yield.     

Genetic evaluation of Holstein bulls for somatic cells in milk of daughters.

Lactational means of somatic cell score from sample days of primiparous DHI cows were analyzed to compare dairy records processing centers for data properties, to examine effects of age at calving and month of calving on somatic cell score, and to calculate preliminary PTA of sires for somatic cell scores. Five processing centers contributed data but differed substantially with respect to availability of records in progress, DIM on last sample day, and length of time that data were submitted. Highest lactational means of somatic cell score tended to be in short lactations for young cows but in long lactations for older cows. Regions of the country differed substantially for effect of month of calving on lactational means of somatic cell score, but lactational means of somatic cell scores increased with age at calving for all dairy records processing centers. Standardized yields of milk, fat, and protein were included as multiple traits with somatic cell score for analysis. Heritability of somatic cell score was .08 to .16 for individual processing centers and .10 across processing centers. Phenotypic correlations of somatic cell score with yield traits were negative, but genetic correlations were positive. Selection for decreased somatic cell score on a national basis should be possible and would seem advisable to decrease mastitis infections. Response may be slow, however, because of antagonistic genetic relationships with the yield traits, which have great economic importance.