Milk, fat, protein, somatic cell score, and days open among Holstein, Brown Swiss, and their crosses

The objectives of this study were to compare Holstein (HO), Brown Swiss (BS), and their crosses for milk, fat, and protein yields, somatic cell score (SCS), days open (DO), and age at first calving (AFC), and to estimate the effects of heterosis and recombination. First through fifth lactation records were obtained from 19 herds milking crosses among BS and HO. The edited data set included 6,534 lactation records from 3,473 cows of the following breed combinations: 2,125 pure HO, 926 pure BS, 256 BS sire × HO dam (SH), 105 backcrosses to BS (SX), 18 HO sire × BS dam, and 43 backcrosses to HO. Least squares means for daily milk, fat, and protein yields, mature-equivalent milk, fat, and protein yields, SCS, DO, and AFC were calculated for breed combinations with a model that included fixed effects of age within parity (except for AFC), days in milk for daily yield and SCS, herd-year-season of calving, and breed combination. Cow and error were random effects. Breed combination was replaced with regressions on coefficients for heterosis and recombination in a second analysis. Last, data were analyzed with a 5-trait animal model that included a single pedigree file for both breeds and coefficients for heterosis and recombination. The least squares means for fat production were 1.21, 1.15, 1.27, and 1.16 kg for HO, BS, SH, and SX, respectively, which corresponds to a heterosis estimate of 7.30% and a recombination estimate of −3.76%. Heterosis and recombination estimates for protein production were 5.63% and −3.31%, respectively. Heterosis estimates increased for fat yield (10.38%) and protein yield (7.07%) when maternal grandsire identification from a known artificial insemination sire was required. Regression coefficients indicated an 11.44-d reduction in DO due to heterosis. Heterosis estimates for SCS were inconsistent. Regression on heterosis for SCS was significant and favorable (−0.22) when the breed of sire was BS, but nonsignificant and unfavorable when sire breed was HO (0.43). Heterosis estimates were favorable for all traits, whereas recombination effects tended to be unfavorable for yield traits. Reduced performance of future generations did not appear to be the result of inseminating crossbred cows with inferior sires. Results indicated that first-generation crosses among BS and HO compared favorably with HO. Yield in subsequent generations was somewhat below expectations, perhaps due to recombination loss in HO.     

Fertility responses of Mexican Holstein cows to US sire selection

Genetic relationships between 2 fertility traits and milk production were investigated using mature-equivalent lactation records of 55,162 daughters of 1,339 Holstein sires in Mexico and 499,401 daughters of 663 Holstein sires in the northeastern United States. Data sets contained yields in first and second lactation, age at first calving (AFC), and calving interval (CI). There were 474 US sires in common between countries. A herd-year standard deviation criterion defined nonoverlapping low- (≤ 1,300 kg) and high- (≥ 1,600 kg) opportunity Mexican herd environments and a low-opportunity (≤ 1,024 kg) US environment. Genetic variances for the average Mexican herd (all data) for AFC and CI were 65 and 85% as large as those obtained from half-sisters in the average US herd. Genetic correlations for first-lactation milk in the average US herd and AFC and CI in the average Mexican environment were unfavorable (0.18 and 0.10). Regression coefficients of AFC in Mexican environments on US genetic gain in milk ranged from 2 to 7 d/1,000 kg. However, the favorable predicted response in AFC from genetic gain in milk in Mexican environments, like those in average US herds, ranged from − 4 to − 7 d/1,000 kg (r_g = − 0.20). This unequal AFC response may indicate genotype by environment interaction in fitness performance or differential breeding management of high and low yielding Mexican cows. The potential effects of age at first service of breeding females need to be disentangled to accurately assess genetic improvement needs for Mexican Holstein herds.     

Genetic analysis of Holstein cattle populations in Brazil and the United States

Genetic relationships between Brazilian and US Holstein cattle populations were studied using first-lactation records of 305-d mature equivalent (ME) yields of milk and fat of daughters of 705 sires in Brazil and 701 sires in the United States, 358 of which had progeny in both countries. Components of(co)variance and genetic parameters were estimated from all data and from within herd-year standard deviation for milk (HYSD) data files using bivariate and multivariate sire models and DFREML procedures distinguishing the two countries. Sire (residual) variances from all data for milk yield were 51 to 59% (58 to 101%) as large in Brazil as those obtained from half-sisters in the average US herd. Corresponding proportions of the US variance in fat yield that were found in Brazil were 30 to 41% for the sire component of variance and 48 to 80% for the residual. Heritabilities for milk and fat yields from multivariate analysis of all the data were 0.25 and 0.22 in Brazil, and 0.34 and 0.35 in the United States. Genetic correlations between milk and fat were 0.79 in Brazil and 0.62 in the United States. Genetic correlations between countries were 0.85 for milk, 0.88 for fat, 0.55 for milk in Brazil and fat in the US, and 0.67 for fat in Brazil and milk in the United States. Correlated responses in Brazil from sire selection based on the US information increased with average HYSD in Brazil. Largest daughter yield response was predicted from information from half-sisters in low HYSD US herds (0.75 kg/kg for milk; 0.63 kg/kg for fat), which was 14% to 17% greater than estimates from all US herds because the scaling effects were less severe from heterogeneous variances. Unequal daughter response from unequal genetic (co)variances under restrictive Brazilian conditions is evidence for the interaction of genotype and environment. The smaller and variable yield expectations of daughters of US sires in Brazilian environments suggest the need for specific genetic improvement strategies in Brazilian Holstein herds. A US data file restricting daughter information to low HYSD US environments would be a wise choice for across-country evaluation. Procedures to incorporate such foreign evaluations should be explored to improve the accuracy of genetic evaluations for the Brazilian Holstein population.     

Prenatal maternal effects on body condition score, female fertility, and milk yield of dairy cows

In this study, maternal effects were described as age of dam at first and second calving, first-lactation body condition score (BCS) of the dam during gestation, and milk yield of the dam. The impact of these effects on first-lactation daughter BCS, fertility, and test-day milk yield was assessed. The effect of milk yield of dam on daughter 305-d yield in the latter's first 3 lactations was also investigated. The proportion of total phenotypic variance in daughter traits accounted for by maternal effects was calculated. Dams calving early for the first time (18 to 23 mo of age) had daughters that produced 4.5% more first-lactation daily milk, had 7% higher BCS, and had their first service 3 d earlier than cows whose dams calved late (30 to 36 mo). However, daughters of dams that calved early had difficulties conceiving as they needed 7% more inseminations and had a 7.5% higher return rate. Cows from second calvings of relatively young (36 to 41 mo) dams produced 6% more first-lactation daily milk, had 2% higher BCS, and showed a significantly better fertility profile than cows whose dams calved at a late age (47 to 55 mo). High maternal BCS during gestation had a favorable effect on daughter BCS, nonreturn rate, and number of inseminations per conception. However, it was also associated with a small decrease in daughter daily milk yield. Changes in dam BCS during gestation did not affect daughter performance significantly. Maternal effects of milk yield of the dam, expressed as her permanent environment during lactation, adversely affected daughter 305-d milk, fat, and protein yield. However, although the effect was significant, it was practically negligible (<0.3% of the mean). Finally, overall maternal effects accounted for a significant proportion of the total phenotypic variance of calving interval (1.4 ± 0.6%) and nonreturn rate (1.1 ± 0.5%).     

Comparison of heritability estimates from daughter on dam regression with three models to account for production level of dam

Three models were used to estimate heritabilities for milk yields at different production levels and for different years as twice the regression of daughter residual effects on dam residual effects. The denominator is the residual mean square for dams. The numerator is the difference between the residual term for sum of dam's and daughter's records and sum of residual terms for records of dams and daughters. Model 1 included sire of daughter and herd-year-season of daughters only. Model 2 included sire of daughter, herd-year-season of dam, and herd-year-season of daughter. Model 3 included sire of daughter and herd-year-season of dam and herd-year-season of daughter combination. The weighted mean estimates for each method were, respectively, .35, .38, .38 for milk production and .61, .67, .67 for fat test. Yearly time trends in heritability were slightly positive for both milk production and fat test. Standard errors of heritability estimates from model 1 were 40 to 50% smaller than those from models 2 and 3 due to the smaller number of effects in the model. Estimates for model 2 from low to high production levels averaged .30, .38, .38, and .42 for milk yield and .64, .68, .67, and .71 for fat test.     

Identification of informative cooperator herds for progeny testing based on yield deviations

Several arguments exist for breeding organizations to focus on cooperative herds for progeny testing, but an efficient methodology addressing herd selection strategies is lacking. In this study, a new approach based on yield deviations (YD) to identify the most informative cooperator herds in terms of genetic differentiation was evaluated. Data comprised YD from 717,377 first-lactation cows from 2 regions in East and West Germany calving between January 2003 and January 2008. Daughters were ranked and classified within sire according to their YD for protein yield, fat yield, milk yield, and somatic cell score. Cows in created YD classes were merged with respective herd-calving year (HCY) characteristics. Cows of extreme YD classes (i.e., such classes including the most extreme daughter contributions), belonged to herds characterized by a high HCY production level, a low value for HCY somatic cell count, and a low HCY age at first calving (AFC). Cows with low extremes for YD in protein yield were associated with the lowest HCY production level, a high value for HCY somatic cell count, and a late HCY AFC. Ranks of HCY and ranks of herds considering HCY over the whole analyzed period were calculated by averaging YD percentages within HCY, and within herds, respectively. The YD percentages (in absolute values so that negative and positive daughter contributions were treated equally) were derived from the rank of the YD of a daughter within sire in relation to all daughters of a sire. A further partitioning of ranks of herds into quartiles revealed the following results: herds in the first quartile had the highest average protein yield, the highest intra-herd standard deviation for the national production index, and the lowest AFC. Correlations between herd rankings for different production traits ranged between 0.64 and 0.86, and were 0.65 for West Germany and 0.62 for East Germany between HCY 2006 and the average herd rank of all calving years. Correlations between daughter yield deviations for the highest and the lowest herd quartile of 0.87 for protein yield disproved concerns regarding genotype by environment interaction between test and production environment. The suggested methodology to identify informative cooperator herds is easy to implement, holds for regions with small herd sizes, and thus, may help in implementing sustainable and competitive dairy cattle breeding programs.     

Genotype by environment interaction for production traits while accounting for heteroscedasticity

Grazing (G) provides an alternative management system for dairy production. Heteroscedasticity (HV) of the data may bias estimates of genetic correlations of yield traits between environments, an indicator of genotype-by-environment interaction (G×E). The objective of this study was to investigate the effect of HV on estimates of heritabilities and genetic correlations for mature-equivalent milk, protein, and fat yield, and lactation-average somatic cell scores of daughters, and to determine if HV affects the ability of sire's predicted transmitting ability (PTA) to predict daughter production in G and confinement (C) herds. Data consisted of 72,489 records from 35,674 cows in 366 G herds from 11 states, and 117,629 records from 50,963 cows in 373 C herds from the same 11 states plus 1 geographically contiguous state. Herds were divided into variance quartiles (Q_V1-Q_V4) based on milk yield. A transformation was used to reduce HV by standardizing the within-herd standard deviation to the average across-herd standard deviation of a base year for each parity, and was similar to the method used in current USDA-DHIA genetic evaluations. Regression of daughter yield on sire PTA showed that PTA overestimated production of all traits in Q_V1-Q_V3 and of milk in Q_V4 of G herds. For C herds, yields of milk in Q_V1 and Q_V2, and of protein and fat in Q_V1 were overestimated, and protein was underestimated in Q_V4. Reducing HV had little effect on G herds, but for C herds, regression did not differ from unity for milk and protein in Q_V1 and Q_V2. For milk, protein, and fat in G, heritabilities were approximately 0.17, 0.17, and 0.19, respectively. The heritabilities for milk, protein, and fat in C herds were approximately 0.16, 0.17, and 0.21, respectively. Genetic correlations between C and G did not suggest a G×E in 3 upper quartiles, but a possible G×E (correlation = 0.21, estimated standard error = 0.22) for the lowest quartile. Reducing HV did not affect estimates of heritabilities or genetic correlations. Results indicated that modest evidence for existence of G×E did not arise solely from HV.     

Piecewise modeling of the associations between dry period length and milk,fat, and protein yield changes in the subsequent lactation

Our objective was to develop predictive models of 305-d mature-equivalent milk, fat, and protein yields in the subsequent lactation as continuous functions of the number of days dry (DD) in the current lactation. In this retrospective cohort study with field data, we obtained DHIA milk recording lactation records with the last DD in 2014 or 2015. Cows included had DD from 21 to 100 d. After editing, 1,030,141 records from cows in 7,044 herds remained. Three parity groups of adjacent (current, subsequent) lactations were constructed. We conducted all analyses by parity group and yield component. We first applied control models to pre-adjust the yields in the subsequent lactation for potentially confounding effects. Control models included the covariates mature-equivalent yield, days open, somatic cell score at 180 d pregnant, daily yield at 180 d pregnant, and a herd-season random effect, all observed in the current lactation. Days dry was not included. Second, we modeled residuals from control models with smooth piecewise regression models consisting of a simple linear, quadratic, and another simple linear equation depending on DD. Yield deviations were calculated as differences from predicted mature-equivalent yield at 50 DD. For validation, predictions of yield deviations from piecewise models by DD were compared with predictions from local regression for the DHIA field records and yield deviations reported in 38 experimental and field studies found in the literature. Control models reduced the average root mean squared prediction error by approximately 21%. Yield deviations were increasingly more negative for DD shorter than 50 d, indicating lower yields in the subsequent lactation. For short DD, the decrease in 305-d mature-equivalent milk yield ranged from 43 to 53 kg per DD. For mature-equivalent fat and protein yields, decreases were between 1.28 and 1.71 kg per DD, and 1.06 and 1.50 kg per DD, respectively. Yield deviations often were marginally positive and increasing for DD >50, so that the highest yield in the subsequent lactation was predicted for 100 DD. For long DD, the 305-d mature-equivalent milk yield increased at most 4.18 kg per DD. Patterns in deviations for fat and protein yield were similar to those for milk yield deviations. Predictions from piecewise models and local regressions were very similar, which supports the chosen functional form of the piecewise models. Yield deviations from field studies in the literature typically were decreasing when DD were longer, likely because of insufficient control for confounding effects. In conclusion, piecewise models of mature-equivalent milk, fat, and protein yield deviations as continuous functions of DD fit the observed data well and may be useful for decision support on the optimal dry period length for individual cows.     

Genotype x environment interaction for grazing vs. confinement. II. Health and reproduction traits

Continual selection for increased milk yield for more than 40 yr, combined with the antagonistic relationship between increasing yield, somatic cell count, and fertility, have resulted in sires that may not be optimal for producing daughters for grazing systems where seasonal calving is very important. The objective of this study was to investigate the possible existence of a genotype x environment interaction (G x E) in grazing vs. confinement herds within the United States for lactation average somatic cell score (LSCS), days open (DO), days to first service (DFS), and number of services per conception (SPC). Grazing herds were defined as those that utilized grazing for at least 6 mo each year and were enrolled in Dairy Herd Improvement (DHI). Control herds were confinement DHI herds of similar size in the same states. For LSCS, the performance of daughters in grazing and control herds was examined using linear regression of LSCS on the November 2000 USDA-DHIA sire predicted transmitting abilities (PTA) for SCS. Genetic parameters for all traits were estimated using REML in a bivariate animal model that treated the same trait in different environments as different traits. Rank correlations were calculated between sires' estimated breeding values for LSCS, calculated separately for sires in both environments. The coefficient of regression of daughter LSCS on sire PTA was less in grazing herds than in control herds. The coefficient of regression for control herds was closer to expectation. Estimates of heritability were approximately 0.12 for LSCS, and less than 0.05 for the reproduction traits. Heritabilities for DO, DFS, and SPC were slightly higher for control herds. Estimates of genetic correlation for each reproductive trait between the 2 environments were high and not significantly different from unity. Generally, these traits appear to be under similar genetic control, but a lower coefficient of regression of LSCS on sire PTA for SCS in grazing herds suggests differences in daughter performance in grazing herds may be overstated based on current PTA for SCS.     

Accuracy of foreign dairy bull evaluations in predicting United States evaluations for yield

Combining foreign daughter data with domestic information in dairy bull genetic evaluations has been shown to improve prediction of future domestic evaluations for US bulls. This study focused on the accuracy of Interbull evaluations of bulls with only foreign daughters, in predicting the latest domestic evaluations (based on US daughters). August 2003 USDA evaluations based only on US daughters were matched with the most recent February or August Interbull evaluations without US daughters. A minimum reliability of at least 80% for yield and 70% for somatic cell score (SCS) was required in both evaluations. This provided pairs of evaluations based on different daughters (foreign or US) for 286 bulls (60 bulls for SCS). Mean Interbull reliabilities on the US scale were 88% for yield and 84% for SCS, and the mean US reliability for the current evaluations was 91% for yield and 80% for SCS. Correlations between the Interbull and domestic evaluations were 0.90, 0.87, 0.90, and 0.87 for milk, fat, protein, and SCS respectively. Expected correlations were 0.89 for yield and 0.82 for SCS. Mean differences between the Interbull and current domestic evaluations were near zero. These foreign bulls had graduated from progeny test programs (selected for positive Mendelian sampling) before being marketed in the United States. Thus, parent average was a substantial underestimate of merit. The small average differences between evaluations from foreign and US daughters and high correlations indicate that Interbull evaluations based solely on foreign daughters are useful predictors of the US evaluations for yield and SCS, providing accuracy in agreement with reliabilities and much better estimates than the alternative, parent averages.     

Genetic Trends Among Artificially Bred Holsteins in Quebec

Mixed-model methods were used to evaluate 52 Holstein sires in artificial insemination for milk, fat, and protein yield and fat and protein percent. A total of 3288 305-day first lactations of Holstein on the Dairy Herd Analysis Service were studied. Sires were grouped by year of first service, and groups were used to measure trends in the average generic merit of sires sampled. Annual genetic trends among sires were 85, 1.4, and 1.0 kg for milk, fat, and protein yield and kg for milk, fat, and protein yield and ?.029 and ?.031% for fat and protein test. Genetic trends among their daughters were estimated for Quebec herds according to relative sire usage. Trends in yields were positive. Average yearly genetic gains for milk, fat, and protein yield were 46, 1.1 and .5 kg for all herds and 57, 1.9, and 1.1 kg for herds in Analysis Service. Trends for milk composition were negative. Annual genetic declines in fat and protein percent were ?.004 and ?.008% for the population and ?.003 and ?.014% for herds in Analysis Service.     

Accuracy of Cow Indexes According to Repeatability,Evaluation, Herd Yield,and Registry Status

Cow Indexes for over 2 million dams of Ayrshires, Brown Swiss, Guernseys, Holsteins, and Jerseys were matched with daughter Modified Contemporary Deviations. Correlations between dam Cow Index and daughter Deviation that were computed within sire and birth year of daughter increased with dam Repeatability and number of records for each daughter but were not as high as expected. Regressions of daughter Deviation on dam Cow Index were .84 to 1.08 across breeds and tended to increase with dam Repeatability. Correlations for registered Holstein pairs were about .03 higher than for grade pairs; regressions for the two groups were similar overall. Holstein pairs divided into 20 groups according to dam Cow Index showed that daughter Deviation, daughter sire merit and sire Repeatability, daughter birth year, and dam Repeatability all increased with dam Cow Index, whereas number of records for each daughter decreased. That decrease resulted from reduced opportunity because higher merit dams were younger and had younger daughters. Deviations for daughters of dams with extremely high Cow Indexes were higher than expected, which suggests preferential management of those daughters. Daughter Deviation in high yield herds was greater than expected from dam Cow Index.     

Heritability and impact of environmental effects during pregnancy on antral follicle count in cattle

Previous studies have documented that ovarian antral follicle count (AFC) is positively correlated with number of healthy follicles and oocytes in ovaries (ovarian reserve), as well as ovarian function and fertility in cattle. However, environmental factors (e.g., nutrition, steroids) during pregnancy in cattle and sheep can reduce AFC in offspring. The role that genetic and environmental factors play in influencing the variability in AFC and, correspondingly, the size of the ovarian reserve, ovarian function, and fertility, are, however, poorly understood. The present study tests the hypothesis that variability in AFC in offspring is influenced not only by genetic merit but also by the dam age and lactation status (lactating cows vs. nonlactating heifers) and milk production during pregnancy. Antral follicle count was assessed by ultrasonography in 445 Irish Holstein-Friesian dairy cows and 522 US Holstein-Friesian dairy heifers. Heritability estimates for AFC (± standard error) were 0.31 ± 0.14 and 0.25 ± 0.13 in dairy cows and heifers, respectively. Association analysis between both genotypic sire data and phenotypic dam data with AFC in their daughters was performed using regression and generalized linear models. Antral follicle count was negatively associated with genetic merit for milk fat concentration. Also, AFC was greater in offspring of dams that were lactating (n = 255) compared with nonlactating dams (n = 89) during pregnancy and was positively associated with dam milk fat concentration and milk fat-to-protein ratio. In conclusion, AFC in dairy cattle is a moderately heritable genetic trait affected by age or lactation status and milk quality but not by level of dam’s milk production during pregnancy.     

Models to predict milk fat concentration and yield of lactating dairy cows: A meta-analysis

Few models have attempted to predict total milk fat because of its high variation among and within herds. The objective of this meta-analysis was to develop models to predict milk fat concentration and yield of lactating dairy cows. Data from 158 studies consisting of 658 treatments from 2,843 animals were used. Data from several feed databases were used to calculate dietary nutrients when dietary nutrient composition was not reported. Digested intake (DI, g/d) of each fatty acid (FA; C12:0, C14:0, C16:0, C16:1, C18:0, C18:1 cis, C18:1 trans C18:2, C18:3) and absorbed amounts (g/d) of each AA (Arg, His, Ile, Leu, Lys, Met, Phe, Thr, Trp, Val) were calculated and used as candidate variables in the models. A multi-model inference method was used to fit a large set of mixed models with study as the random effect, and the best models were selected based on Akaike's information criterion corrected for sample size and evaluated further. Observed milk fat concentration (MFC) ranged from 2.26 to 4.78%, and milk fat yield (MFY) ranged from 0.488 to 1.787 kg/d among studies. Dietary levels of forage, starch, and total FA (dry matter basis) averaged 50.8 ± 10.3% (mean ± standard deviation), 27.5 ± 7.0%, and 3.4 ± 1.3%, respectively. The MFC was positively correlated with dietary forage (0.294) and negatively associated with dietary starch (?0.286). The DI of C18:2 (g/d) was more negatively correlated with MFC (?0.313) than that of the other FA. The best variables for predicting MFC were days in milk, FA-free dry matter intake, forage, starch, DI of C18:2, DI of C18:3, and absorbed Met, His, and Trp. The best predictor variables for MFY were FA-free dry matter intake, days in milk, absorbed Met and Ile, and intakes of digested C16:0 and C18:3. This model had a root mean square error of 14.1% and concordance correlation coefficient of 0.81. Surprisingly, DI of C18:3 was positively related to milk fat, and this relationship was consistently observed among models. The models developed can be used as a practical tool for predicting milk fat of dairy cows, while recognizing that additional factors are likely to also affect fat yield.     

Effect of prepubertal and postpubertal growth and age at first calving on production and reproduction traits during the first 3 lactations in Holstein dairy cattle

The objective of this study was to evaluate the effect of body condition score (BCS), body weight (BW), average daily weight gain (ADG), and age at first calving (AFC) of Holstein heifers on production and reproduction parameters in the 3 subsequent lactations. The data set consisted of 780 Holstein heifers calved at 2 dairy farms in the Czech Republic from 2007 to 2011. Their BW and BCS were measured at monthly intervals during the rearing period (5 to 18 mo of age), and the milk production and reproduction data of the first 3 lactations were collected over an 8-yr period (2005 to 2012). The highest milk yield in the first lactation was found in the group with medium ADG (5 to 14 mo of age; 0.949 to 0.850 kg of ADG). The highest average milk yield over lifetime performance was detected in heifers with the highest total ADG (≥0.950 kg/d). The difference in milk yield between the evaluated groups of highest ADG (in total and postpubertal growth ≥0.950 kg/d and in prepubertal growth ≥0.970 kg/d) and the lowest ADG (≤0.849 kg/d) was approximately 1,000 kg/305 d per cow. The highest milk yield in the first lactation was found in the group with the highest AFC ≥751 d, for which fat and protein content in the milk was not reduced. Postpubertal growth (11 to 14 mo of age) had the greatest effect on AFC. The group with lowest AFC ≤699 d showed a negative effect on milk yield but only in the first 100 d of the first parity. The highest ADG was detrimental to reproduction parameters in the first lactation. The highest BW at 14 mo (≥420 kg) led to lower AFC. Groups according to BCS at 14 mo showed no differences in AFC or milk yield in the first lactation or lifetime average production per lactation. We concluded that low AFC ≤699 d did not show a negative effect on subsequent production and reproduction parameters. Therefore, a shorter rearing period is recommended for dairy herds with suitable management.     

Short communication: variance estimates among herds stratified by individual herd heritability

The objectives of this study were to compare (co)variance parameter estimates among subsets of data that were pooled from herds with high, medium, or low individual herd heritability estimates and to compare individual herd heritability estimates to REML heritability estimates for pooled data sets. A regression model was applied to milk yield, fat yield, protein yield, and somatic cell score (SCS) records from 20,902 herds to generate individual-herd heritability estimates. Herds representing the 5th percentile or less (P5), 47th through the 53rd percentile (P50), and the 95th percentile or higher (P95) for herd heritability were randomly selected. Yield or SCS from the selected herds were pooled for each percentile group and treated as separate traits. Records from P5, P50, and P95 were then analyzed with a 3-trait animal model. Heritability estimates were 23, 31, 26, and 8% higher in P95 than in P5 for milk yield, fat yield, protein yield, and SCS, respectively. The regression techniques successfully stratified individual herds by heritability, and additive genetic variance increased progressively, whereas permanent environmental variance decreased progressively as herd heritability increased.     

Relationship between individual herd-heritability estimates and sire misidentification rate

The objectives of this study were to estimate heritabilities within herds participating in Dairy Herd Improvement and determine the relationship of the individual herd heritability with sire misidentification rate. Individual herd heritabilities for milk, fat, and protein yield and somatic cell score (SCS) were calculated with daughter-dam regression and daughter-sire predicted transmitting ability (PTA) regression using 4,712,166 records from 16,336 herds available for August 2000 evaluations and 7,084,953 records from 20,920 herds available for August 2006 evaluations. Herd heritabilities were estimated using regression models that included fixed breed, age within parity, herd-year-season of calving, dam records nested within state, sire PTA within state, and an interaction between sire PTA and herd variance; random regression coefficients were dam records within herd and sire PTA within herd. Average daughter-dam herd heritability estimates ranged from 0.21 (SCS in 2000) to 0.73 (protein percentage in 2006), whereas daughter-sire herd heritability ranged from 0.10 (SCS in 2000) to 0.42 (protein percentage in 2006). Verification of sire identification with DNA marker analysis was provided by Accelerated Genetics and Alta Genetics Inc. Daughter-sire herd heritability was more strongly correlated with sire misidentification rate than daughter-dam herd heritability. The correlation between the first principal component for all measures of herd heritability and sire misidentification rate was −0.38 (176 herds) and −0.50 (230 herds) in 2000 and 2006, respectively. Herd heritability can be estimated with simple regression techniques for several thousand herds simultaneously. The herd heritability estimates were correlated negatively with sire misidentification rates and could be used to identify herds that provide inaccurate data for progeny testing.     

Effect of Within-Herd Variance and Herd Mean Production on Response to Selection Within Herd

Lactation records of 1,032,438 Jersey and 1,490,909 Holstein cows on official DHI test from 20,380 and 33,858 herd-years, respectively, were used to compute herd-year means and within-herd-year standard deviations for mature equivalent fat percent, fat, and milk. Within-herd-year means and standard deviations were used to stratify records into five classes for each trait. Regressions of individual daughter's modified contemporary deviation on sire's PD were calculated for each of the 25 subclass combinations of within-herd-year mean and standard deviation. For milk and fat yield, low-low and high-high mean-variance subclasses contained more herd-years than low-high and high-low mean-variance subclasses. This was less evident for fat percent. Regression coefficients ranged from .66 to 1.41, .69 to 1.41, and .78 to 1.34 for fat percent, fat, and milk, respectively, for both breeds. Estimates of regressions indicated that coefficients increased with increases in within-herd-year variance but were nearly constant across herd-year means.     

Effect of dams’ parity and age on daughters’ milk yield in Norwegian Red cows

The effect of age and parity of dams on their daughters’ milk yield is not well known. Lactation data from 276,000 cows were extracted from the Norwegian Dairy Herd Recording System and analyzed using a linear animal model to estimate effects of parity and age within parity of dam. The 305-d milk yield of daughters decreased as parity of dam increased. Daughters of first-parity dams produced 149 kg more milk than did daughters of seventh-parity dams. We also observed an effect of age of dam within parity on 305-d milk yield of daughters in first lactation. Dams that were young at first calving gave birth to daughters with a higher milk yield compared with older dams within the same parity. The effect of age within parity of dam was highest for second-parity dams. Extensive use of heifers would have a systematic effect, and age and parity of dam should be included in the model when planning a future strategy.     

Estimates of genetic trend in an artificial insemination progeny test program and their association with herd characteristics.

Individual lactation records from Holstein cows in 3449 herds participating in an AI stud's young sire sampling program from 1971 to 1987 were used to characterize the sampling program and to estimate genetic merit and trend. Average genetic merit of cows in sampling program herds was consistently superior to the average genetic merit of cows in the US population. Genetic trend of sires of first-crop cows was 58 kg of milk and 1.5 kg of fat/yr from 1971 to 1978 and 176 kg of milk and 5.5 kg of fat/yr from 1979 to 1987. The average genetic merit of sires of first-crop cows born after 1983 was equivalent to or exceeded the genetic level of sires of other cows in the herd. Within-herd-year means and standard deviations of yield, genetic evaluation, and management traits (herd-year characteristics) were computed for a subset of 341 herds contributing first-crop daughters for at least 10 yr. The average of each herd-year characteristic during 10 or more years was used to predict within-herd genetic trend. Herd characteristics explained up to 51% of differences in within-herd genetic trends. Average sire genetic merit of daughters other than first-crop daughters accounted for up to 80% of the explained differences. Other herd characteristics suggested that herds with larger within-herd standard deviation milk yields, a larger number of young sires represented, younger cows, and greater percentage of cows sired by AI sires made greater genetic improvement. Results indicated that the average genetic merit of cows and the rate of within-herd genetic improvement are higher in herds that participate in a young sire sampling program.