Effects of persistency and production on the genetic parameters of milk and fat yield in Israeli-Holsteins

Herd-years of Israeli-Holsteins were stratified into three groups by two criteria: mean annualized milk yield [365 (total lactations yield/calving interval)] and mean persistency, estimated as the ratio of daily milk production at the 5th mo postpartum to daily production during the postpartum peak period. The latter was taken as an indication of the relative environmental stress on the cow. Primi- and multiparous cows were analyzed separately. Genetic parameters were estimated for annualized milk and fat production at each production and persistency group. Heritabilities increased with a rise in production for both primiparous and multiparous cows, but the effect was greater for multiparous cows. Even though persistency and production were correlated, no clear trends were evident for stratification by persistency; thus, a relationship between stress and heritability was not established. Genetic correlations among stratification groups were between .7 and .9 for persistency and between .6 and .86 for production; thus, sire x environmental interaction was greater for production than for persistency stratification. Production in a given year can be used as a criterion for selecting herds to test progeny of young sires in the following year.     

Genetic correlations among progeny groups for type traits, milk yield, yield persistency, and culling rates

Associations among six primipara type traits and first and second lactation milk yield, yield persistency, and culling rates were estimated by means of 100 progeny groups with first and 76 with second lactations. Correlations of second lactation culling rate with dairy character and with rear udder were approximately -.4. Persistency, measured in either first or second lactation, was negatively associated with all type traits.     

Genetic parameters for female fertility in Nordic Holstein and Red Cattle dairy breeds

Genetic evaluation of female fertility in Danish, Finnish, and Swedish dairy cows was updated in 2015 to multiple-trait animal model evaluation, where heifer and cow fertility up to third parity are considered as separate traits. A model for conception rate was also developed, which required variance component estimation for Nordic Holstein and Nordic Red Dairy Cattle. We used a multiple-trait multiple-lactation sire model to determine variance components for interval from calving to first insemination, length of service period, and conception rate. Monte Carlo Expectation Maximization REML allowed estimation of all 11 traits simultaneously. Study data were sampled from Swedish Holstein (n = 140,040) and Red Dairy Cattle (n = 101,315) heifers and cows. Conception rate observations are binomial observations with various numbers of failures preceding an observation of success. Using a simulation study, we confirmed that including a service number effect into the conception rate model allowed us to model the change in expectation of successful AI with increasing number of services. Heifers outperformed cows in all fertility traits according to the phenotypic means in the records. Heritabilities for the traits varied from 3 to 7% for interval from calving to first insemination, from 1 to 5% for length of service period, and from 1 to 3% for conception rate. Genetic correlations within traits (i.e., between parities) were favorable, ranging from moderate to high; genetic correlations between heifer and cow traits were lower than between cow traits in different parities. Lowest genetic correlations between traits were for interval from calving to first insemination and conception rate, intermediate for interval from calving to first insemination and length of service period, and highest for length of service period and conception rate. The variance components estimated in this study have been used in Nordic fertility breeding value evaluations since 2016.     

Consistency of maturity rate for milk yield across countries and generations

Differences among bulls in maturity rate of their daughters for milk yield were investigated. Milk records for US Holsteins with first-parity calving dates between 1960 and 1998 were used to calculate 3 evaluations for bulls based on daughter records from parity 1, parities 1 and 2, and parities 1, 2, and 3. The 3 evaluations were used to estimate parity-specific evaluations for parities 2 and 3. Maturity rate of Holstein bull daughters in Canada and the Netherlands was compared with that for daughters of the same bulls in the United States by using official November 2004 Canadian and August 2005 Dutch parity-specific evaluations. For bulls with ≥500 first-parity daughters, correlations among parity-specific evaluations within country and birth year of bull were 0.88 between parities 1 and 2, 0.84 between parities 1 and 3, and 0.96 between parities 2 and 3 for the United States; 0.90, 0.86, and 0.97, respectively, for Canada; and 0.92, 0.89, and 0.98, respectively, for the Netherlands. Correlations between Canada and the United States for within-country differences between evaluations for parities 1 and 2 were 0.72 for bulls with ≥50 first-parity daughters and 0.89 for bulls with ≥500 first-parity daughters; corresponding correlations between the Netherlands and the United States were 0.66 and 0.82. Correlations between countries for differences between evaluations for parities 1 and 3 were slightly less, and corresponding correlations between evaluations for parities 2 and 3 were still lower. To establish whether differences between parity-specific evaluations were genetic, comparisons were made across a generation. Coefficients for regression of son on sire within country and birth years of sire and son for parity-specific evaluations and differences between parity-specific evaluations ranged from 0.35 to 0.53, with standard errors of ≤0.04. Differences in maturity rate of bull daughters were quite consistent across country, and those differences were transmitted to the sons’ daughters. Modeling to account for maturity differences should increase the accuracy of US evaluations and reduce fluctuation between evaluations, especially for bulls with daughters that deviate substantially from the population mean for maturity rate for milk yield.     

Relationships between reproductive traits of heifers and cows and yield traits for Holsteins in Japan

The objective of this study was to investigate relationships between reproductive traits in heifers and cows and yield traits for Holsteins in Japan. Insemination and lactation records for cows calved between 1990 and 2003 in Hokkaido region were obtained. Age at first service, age at conception, and conception rate for first service were calculated for heifers. Days from calving to first service, days open, and conception rate for first service were calculated for first- and second-parity cows. The yield traits used were 305-d milk, fat, and protein yields. A threshold animal model was applied for the conception rate for first service, and a linear animal model was applied for the other traits. Single-trait and 2-trait genetic analyses were performed by the Bayesian method using Gibbs sampling. Heritability estimates ranged from 0.027 to 0.051 for conception rate for first service, and from 0.074 to 0.128 for the other reproductive traits. If the relationships of other traits were not considered, days from calving to first service was favorable to genetic selection for reproductive traits because of relatively high heritability and because it can be available earlier than the days open. Genetic correlations among reproductive traits were high, especially in cows. The genetic correlations between reproductive traits for heifers and those for cows were lower than the genetic correlations between reproductive traits for first parity and those of second parity, suggesting that reproductive traits for heifers should be evaluated separately from reproductive traits for cows. Genetic correlations between yield and reproductive traits in cows were antagonistic. In contrast, genetic correlations between reproductive traits for heifers and yield traits were slightly desirable. Depending on the reporting rate of insemination records for heifers and the results of investigations for relationships with productive maturity, selection by reproductive traits for heifers will enable the improvement of reproductive performance without a loss in genetic progress for yield traits.     

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).     

Genetic relationship between culling, milk production, fertility, and health traits in Norwegian red cows

First-lactation records on 836,452 daughters of 3,064 Norwegian Red sires were used to examine associations between culling in first lactation and 305-d protein yield, susceptibility to clinical mastitis, lactation mean somatic cell score (SCS), nonreturn rate within 56 d in heifers and primiparous cows, and interval from calving to first insemination. A Bayesian multivariate threshold-linear model was used for analysis. Posterior mean of heritability of liability to culling of primiparous cows was 0.04. The posterior means of the genetic correlations between culling and the other traits were −0.41 to 305-d protein yield, 0.20 to lactation mean SCS, 0.36 to clinical mastitis, 0.15 to interval from calving to first insemination, −0.11 to 56-d nonreturn as heifer, and −0.04 to 56-d nonreturn as primiparous cow. As much as 66% of the genetic variation in culling was explained by genetic variation in protein yield, clinical mastitis, interval of calving to first insemination, and 56-d nonreturn in heifers, whereas contribution from the SCS and 56-d nonreturn as primiparous cow was negligible, after taking the other traits into account. This implies that for breeds selected for a broad breeding goal, including functional traits such as health and fertility, most of the genetic variation in culling will probably be covered by other traits in the breeding goal. However, in populations where data on health and fertility is scarce or not available at all, selection against early culling may be useful in indirect selection for improved health and fertility. Regression of average sire posterior mean on birth-year of the sire indicate a genetic change equivalent to an annual decrease of the probability of culling in first-lactation Norwegian Red cattle by 0.2 percentage units. This genetic improvement is most likely a result of simultaneous selection for improved milk yield, health, and fertility over the last decades.     

Genetic correlation patterns between somatic cell score and protein yield in the Italian Holstein-Friesian population

Genetic parameters for somatic cell score (SCS) in the Italian Holstein-Friesian population were estimated addressing the pattern of genetic correlation with protein yield in different parities (first, second, and third) and on different days in milk within each parity. Three approaches for parameter estimation were applied using random samples of herds from the national database of the Italian Holstein Association. Genetic correlations for lactation measures (305-d protein yield and lactation SCS) were positive in the first parity (0.31) and close to zero in the second (0.01) and third (0.09) parities. These results indicated that larger values of SCS were genetically associated with increased production. The second and third sets of estimates were based on random regression test-day models, modeling the shape of lactation curve with the Wilmink function and fourth-order Legendre polynomials, respectively. Genetic correlations from both random regression models showed a specific pattern associated with days in milk within and across parities. Estimates varied from positive to negative in the first and second parity, and from null to negative in the third parity. Patterns were similar for both random regression models. The average overall correlation between SCS and protein yield was zero or slightly positive in the first lactation and ranged from zero to negative in later lactations. Correlation estimates differed by parity and stage of lactation. They also demonstrated the dubiousness of applying a single genetic correlation measure between SCS and protein in setting selection strategies. Differences in magnitude and the sign of genetic correlations between SCS and yields across and within parities should be accounted for in selection schemes.     

Effect of milk yield characteristics, breed, and parity on success of the first insemination in Dutch dairy cows

The objective of this study was to determine the contribution of cow factors to the probability of a successful first insemination (SFI). The investigation was performed with 51,791 lactations from 1,396 herds obtained from the Dutch dairy cow database of the Cattle Improvement Co-operative (CRV). Cows that had the first insemination (AI) between 40 and 150 d postpartum were selected. The first AI was classified as successful when cows were not reinseminated and either calved between 267 and 295 d later or were culled within 135 to 295 d after first AI. The lactation curve characteristics of individual lactations were estimated by Wilmink's curve using the test-day milk records from CRV. The lactation curve characteristics (peak milk yield, milk yield at the first-AI date, time of peak yield (PT), and milk persistency) were calculated. Breed, parity, interval from calving to first AI (CFI), lactation curve characteristics, milk production traits, moment of AI related to PT (before or after PT), calf status, month of AI, and month of calving were selected as independent variables for a model with SFI as a dependent variable. A multivariable logistic regression model was used with farm as a random effect. Overall SFI was 44%. The effect of parity on SFI depended on CFI. The first-parity cows had the greatest SFI (0.43) compared with other parities (0.32-0.39) at the same period of CFI before 60 d in milk (DIM), and cows in parity ≥5 had the least SFI (0.38-0.40) when AI was after 60 DIM. After 60 DIM, extending CFI did not improve SFI in the first-parity cows, but SFI was improved in multiparous cows. Holstein-Friesian cows had lesser SFI (0.37) compared with cross-breed cows (0.39-0.46). Twin and stillbirth calving reduced SFI (0.39) compared with a single female calf (0.45) or a male calf (0.43) calving. The SFI in different months of AI varied and depended on CFI. Cows that received AI before 60 DIM had a lesser SFI, especially in March, June, and July (0.18, 0.35, and 0.34, respectively). Artificial insemination before PT reduced SFI (0.39) in comparison with AI after PT (0.44). The effect of milk yield at the first-AI date on SFI varied depending on CFI. After 60 DIM at the same period of CFI, a high level of milk yield at the first-AI date reduced SFI. In conclusion, knowledge of the contribution of cow factors on SFI can be applied to support decision making on the moment of insemination of an individual cow in estrus.     

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.     

Influence of Production and Prices on Optimum Culling Rates and Annualized Net Revenue

Dynamic programming was used to make optimum insemination and culling decisions for a dairy enterprise. Monthly costs and revenues for cows were calculated from milk and fat yields, calf values, feed costs, veterinary costs, housing and equipment costs, and interest. Cows were described in the dynamic programming model by lactation number, month in lactation, milk production during the present and previous lactations, and time of conception. The model considered variation in milk yield, replacement heifer costs, carcass values, involuntary culling, genetic improvement, conception rates, semen costs, and interest. Prices and parameters were chosen to represent the Holstein population in the US. Optimum average yearly culling rate was about 25% (optimum average herd life was 47.8 mo) and the yearly annuity of net revenue for a replacement heifer over a 15-yr planning horizon was $443 in the base situation. Various average mature equivalent yields, replacement heifer prices, milk prices, and feed prices were used in a sensitivity analysis. The yearly annuity of net revenue was sensitive to changes in all these parameters. Milk yield, milk prices, and feed prices had major effects on yearly annuity. Optimum culling decisions were sensitive to changes in replacement heifer prices. Average mature equivalent milk yield, milk price, and feed price had small effects on culling.     

Fertility and milk production on commercial dairy farms with customized lactation lengths

Drying-off, calving, and start of lactation are critical transition events for a dairy cow. As a consequence, most animal health issues occur during these periods. By extending the voluntary waiting period for first insemination after calving, calving interval (CInt) can be extended, with possible positive effects for fertility and health. Some cows might be better suited for an extended CInt than others, due to differences in milk yield level, lactation persistency, or health status, which would justify a customized CInt based on individual cow characteristics. This study aims to investigate 13 farms with customized CInt, with respect to calving to first service interval (CFSI), accomplished CInt, services per conception (SC), conception rate at first artificial insemination (CR1AI), peak yield, lactation persistency, 305-d yield, and effective lactation yield. In total, 4,858 complete lactations of Holstein Friesian cows between 2014 and 2019 from the 13 farms were grouped by parity (1 or 2+) and CFSI (CFSI class; CFSI-1 < 84; 84 ≤ CFSI-2 < 140; 140 ≤ CFSI-3 < 196; 196 ≤ CFSI-4 < 252, CFSI-5 ≥ 252 d) or CInt (CInt class; CInt-1 < 364; 364 ≤ CInt-2 < 420; 420 ≤ CInt-3 < 476; 476 ≤ CInt-4 < 532, CInt-5 ≥ 532 d). Cow inseminations, available for 11 out of 13 farms (3,597 complete lactations), were grouped by parity (1 and 2+) and CFSI class or CInt class. The fertility and milk production characteristics were analyzed with generalized and general linear mixed models. The CFSI class was not associated with SC, but extended CInt class was associated with increased SC (CInt-1–5; 1.11–3.70 SC). More than 50% of cows in the CFSI class <84 d ended up in longer than expected CInt (>364 d), showing that these cows were not able to conceive for the desired CInt. More than 50% of cows in CInt classes 3 and higher (CInt ≥ 420 d) had an earlier first insemination before successful insemination (CFSI class 1; <196 d), showing that these extended CInt classes consisted of both cows with an extended waiting period for first insemination and cows that failed to conceive at earlier insemination(s). On most farms, lactation persistency was greatest in CInt class 1 (<364 d), probably related to the low peak yield in this class. When this shortest CInt class was excluded, persistency increased with extended CInt classes on most farms. Although at the majority of farms 305-d yield was greater in CInt ≥ 532 d, effective lactation yield at most farms was greatest in CInt from 364 to 531 d, especially for multiparous cows. Based on the results of this study, a CInt between 364 and 531 days seems most optimal for milk production, when high-yielding cows were selected.     

Genetic analysis of persistency in the israeli holstein population by the multitrait animal model

Persistency was defined as the predicted milk production 180 d after peak divided by peak production (in %). Heritability of persistency in a multitrait analysis including parities 1 through 5 increased from 0.16 to 0.27 from first through third parity, and then declined through fifth parity. Genetic correlations for persistency between consecutive parities were all > 0.8. First-parity genetic correlations of the traits included in the Israeli selection index with persistency were all < 0.1, except for fertility and herdlife, which were 0.20 and 0.25; whereas second-parity genetic correlations of persistency with the 3 milk production traits were all > 0.34, and the genetic correlation with fertility was only 0.10. The genetic correlation between second-parity persistency and herdlife was 0.58. Persistency in the Israeli Holstein population was analyzed by the multitrait animal model. The genetic trend since 1985 for the multiparity index was 0.22% persistency/yr, even though there was no direct selection on persistency.     

Estimation of regional genetic parameters for mortality and 305-d milk yield of US Holsteins in the first 3 parities

Several research reports have indicated increasing dairy cow mortality in recent years. The objectives of this research were to characterize the phenotypic differences in mortality in the first 3 parities across 3 regions of the United States to estimate the heritability of mortality of Holstein cows across regions and parities, and to estimate genetic and environmental correlations between milk yield and mortality across parities and regions. Dairy Herd Information (DHI) milk yield and mortality data were obtained from 3 different US regions: the Southeast (SE), Southwest (SW), and Northeast (NE). A total of 3,522,824 records for the first 3 parities were used: 732,009 (SE), 656,768 (SW), and 2,134,047 (NE) from 1999 to 2008. Cows that received a termination code of 6—“Cow died on the dairy; downer cows that were euthanized should be included here”—were given a mortality score of 2 (dead), whereas all other codes were assigned a mortality score of 1 (alive). Average annual mortalities in the first 3 parities across regions ranged from 2.2 to 7.2%, with mortality frequency increasing with increasing parity across all regions and with the SE having the highest mortality frequency. For genetic analysis, a 2-trait (305-d milk yield and mortality) linear-threshold animal model that fitted fixed effects of herd-year (for 305-d milk yield), cow age, days in milk (in month classes), month-of-termination, and random effects of herd-year (for mortality), animal, and residual was implemented. The model was used to estimate variance components separately for each region and parity. Heritability estimates for mortality were similar for all regions and parities, ranging from 0.04 to 0.07. Genetic correlations between mortality and 305-d milk yield across the first 3 parities were 0.14, 0.20, and 0.29 in SE; −0.01, 0.01, and 0.31 in SW; and 0.28, 0.33, and 0.19 in NE. We detected an adverse genetic relationship between milk production and mortality; however, the moderate magnitudes of the genetic correlations suggest that indices that include both milk yield and mortality could be effective in identifying sires that would provide opportunities for minimizing death loss even when selecting for increased milk yield.     

Exploiting genetic variability in the trajectory of lactation yield and somatic cell score with each progressing parity

The inclusion of reproductive performance in dairy cow breeding schemes has resulted in a cumulative improvement in genetic merit for reproductive performance; this improvement should manifest in longer productive lives through a reduced requirement for involuntary culling. Nonetheless, the average length of dairy cow productive life has not changed in most populations, suggesting that risk factors for culling, especially in older cows, are possibly more associated with lower yield or high somatic cell score (SCS) than compromised reproductive performance. The objective of the present study was to understand the dynamics of lactation yields and SCS in dairy cows across parities and, in doing so, quantify the potential to alter this trajectory through breeding. After edits, 3,470,520 305-d milk, fat, and protein yields, as well as milk fat and protein percentage and somatic cell count records from 1,162,473 dairy cows were available for analysis. Random regression animal models were used to identify the parity in which individual cows reached their maximum lactation yields, and highest average milk composition and SCS; also estimated from these models were the (co)variance components for yield, composition, and SCS per parity across parities. Estimated breeding values for all traits per parity were calculated for cows reaching ≥fifth parity. Of the cows included in the analyses, 91.0%, 92.2%, and 83.4% reached maximum milk, fat, and protein yield in fifth parity, respectively. Conversely, 95.9% of cows reached their highest average fat percentage in first parity and 62.9% of cows reached their highest average protein percentage in third parity. In contrast to both milk yield and composition traits, 98.4% of cows reached their highest average SCS in eighth parity. Individual parity estimates of heritability for milk yield traits, milk composition, and SCS ranged from 0.28 to 0.44, 0.47 to 0.69, and 0.13 to 0.23, respectively. The strength of the genetic correlations per trait among parities was inversely related to the interval between the parities compared; the weakest genetic correlation was 0.67 (standard error = 0.02) between milk yield in parities 1 and 8. Eigenvalues and eigenfunctions of the additive genetic covariance matrices for all investigated traits revealed potential to alter the trajectory of parity profiles for milk yield, milk composition, and SCS. This was further demonstrated when evaluating the trajectories of animal estimated breeding values per parity.     

Genotype x environment interaction for milk yield in Holsteins using Luxembourg and Tunisian populations

Test-day (TD) milk yield records of first-lactation Holstein cows in Luxembourg and Tunisia were analyzed using within-and between-country random regression TD models. Edited data used for within-country analysis included 661,453 and 281,913 TD records in Luxembourg and Tunisia, respectively. The joint data included 730,810 TD records of 87,734 cows and 231 common sires. Both data sets covered calving years 1995 to 2006. Fourth-order Legendre polynomials for random effects and a Gibbs sampling method were used to estimate variance components of lactation curve parameters in separate and joint analyses. Genetic variances of the first 3 coefficients from Luxembourg data were 46 to 69% larger than corresponding estimates from the Tunisian data. Inversely, the Tunisian permanent environment variances for the same coefficients were 52 to 65% larger than the Luxembourg ones. Posterior mean heritabilities of 305-d milk yield and persistency, defined as estimated breeding values (EBV) at 280 days in milk-EBV at 80 days in milk, from between-country analysis were 0.42 and 0.12 and 0.19 and 0.08 in Luxembourg and Tunisia, respectively. Heritability estimates for the same traits from within-country analyses, mainly from the Tunisian data, were lower than those from the joint analysis. Genetic correlations for 305-d milk yield and persistency between countries were 0.60 and 0.36. Product moment and rank correlations between EBV of common sires for 305-d milk yield and persistency from within-country analyses were 0.38 and 0.41 and 0.27 and 0.26, respectively. Differences between genetic variances found in both countries reflect different milk production levels. Moreover, low genetic and rank correlations suggest different ranking of sires in the 2 environments, which implies the existence of a genotype × environment interaction for milk yield in Holsteins.     

Influence of Involuntary Culling on Optimum Culling Rates and Annualized Net Revenue

Dynamic programming was used to make optimum insemination and culling decisions. Revenue depended on the sale of milk, calves, and cull cows. Costs were based on feed costs, health costs, replacement costs, housing costs, and interest. Conception probabilities, genetic improvement, variation in production, and repeatability of production and involuntary culling probabilities were considered when making the optimum decisions. Annualized net revenue, optimum culling rates, and the optimum average productive life were determined for various involuntary culling rates. Results indicated that involuntary culling probabilities have a large impact on annualized net revenue. Reducing involuntary culling rates by 2.9% (marginal involuntary culling rates by 20%) resulted in about $22 more net revenue per cow per year. Increasing average mature equivalent milk yield by 122 kg resulted in the same increase in net revenue. Value of lowering the overall rate of involuntary culling was not affected by assuming that higher yielding cows were more prone to culling for involuntary reasons; however, optimum voluntary culling patterns were altered. Less intense culling in young cows was optimum when compared with the situation where the probability of involuntary culling was independent of production. Management and breeding policies should be directed toward increasing milk yield and decreasing the causes of involuntary culling.     

Genetic analysis of fertility in the Italian Brown Swiss population using different models and trait definitions

The aim of this study was to estimate genetic parameters for fertility and production traits in the Brown Swiss population reared in the Alps (Bolzano-Bozen province, Italy). Fertility indicators were interval from parturition to first service, interval from first service to conception (iFC), and interval from parturition to conception, either expressed as days and as number of potential 21-d estrus cycles (cPF, cFC, and cPC, respectively); number of inseminations to conception; conception rate at first service; and non-return rate at 56 d post-first service. Production traits were peak milk yield, lactation milk yield, lactation length, average lactation protein percentage, and average lactation fat percentage. Data included 71,556 lactations (parities 1 to 9) from 29,582 cows reared in 1,835 herds. Animals calved from 1999 to 2007 and were progeny of 491 artificial insemination bulls. Gibbs sampling and Metropolis algorithms were implemented to obtain (co)variance components using both univariate and bivariate censored threshold and linear sire models. All of the analyses accounted for parity and year-month of calving as fixed effects, and herd, permanent environmental cow, additive genetic sire, and residual as random effects. Heritability estimates for fertility traits ranged from 0.030 (iFC) to 0.071 (cPC). Strong genetic correlations were estimated between interval from parturition to first service and cPF (0.97), and interval from parturition to conception and cPC (0.96). The estimate of heritability for cFC (0.055) was approximately double compared with iFC (0.030), suggesting that measuring the elapsed time between first service and conception in days or potential cycles is not equivalent; this was also confirmed by the genetic correlation between iFC and cFC, which was strong (0.85), but more distant from unity than the other 2 pairs of fertility traits. Genetic correlations between number of inseminations to conception, conception rate at first service, non-return rate at 56 d post-first service, cPF, cFC, and cPC ranged from 0.07 to 0.82 as absolute value. Fertility was unfavorably correlated with production; estimates ranged from −0.26 (cPC with protein percentage) to 0.76 (cPC with lactation length), confirming the genetic antagonism between reproductive efficiency and milk production. Although heritability for fertility is low, the contemporary inclusion of several reproductive traits in a merit index would help to improve performance of dairy cows.     

Effect of herd environment on the genetic and phenotypic relationships among milk yield, conception rate, and somatic cell score in Holstein cattle

A total of 248,230 primiparous records of Holstein cows calving from 1987 to 1994 (daughters of 588 sires in 3042 herds) was used to evaluate potential genotype by environment interactions among mature equivalent milk yield, lactation mean somatic cell score, and conception rate at first service. Herds were classified into low and high environmental groups using three different criteria: standard deviation of herd mature equivalent milk yield, a combination of herd mature equivalent milk yield mean and standard deviation, and the herd mean of body weight at first calving divided by age at first calving. Genetic parameters were modeled by using multiple-trait linear mixed models and were fitted using the multiple-trait derivative-free software. Heritabilities for mature equivalent milk yield, lactation mean somatic cell score, and conception rate at first service were 0.221, 0.106, and 0.015 in low environment herds and 0.300, 0.093, and 0.009 in high environment herds, respectively. Genetic (and phenotypic) correlations between mature equivalent milk yield and lactation mean somatic cell score, mature equivalent milk yield and conception rate at first service, and lactation mean somatic cell score and conception rate at first service were 0.277, -0.417, and -0.209, (-0.049, -0.180, and -0.040) and 0.173, -0.318, and -0.144, (-0.087, -0.166, and -0.035) in low and high environment herds, respectively. The genetic correlations between pairs of traits were consistently smaller in high environment herds, suggesting that differences in management between the two environment levels lessened the antagonistic genetic association between the traits studied. A long-range plan for low environment herds should focus on improving the level of management, which would greatly reduce the unfavorable correlated changes in lactation mean somatic cell score and conception rate at first service associated with the genetic improvement of mature equivalent milk yield.     

Comparison of ten Friesian strains in Poland for yield traits from first three parities

Milk yield, fat yield, and fat percentage for the first three parities were compared for crosses of Friesian strains from Canada, Denmark, Israel, The Netherlands, New Zealand, Sweden, the United Kingdom, the US, and West Germany with Polish black-and-white cattle. Mixed model multitrait BLUP solutions for milk yield ranked Holstein strains (US, Canada, and Israel) and New Zealand Friesians higher than European Friesian strains for all three parities. Largest difference for milk yield between highest ranking US strain and lowest ranking Polish strain was 1002 kg for first lactation. Rankings for fat yield were similar to those for milk yield. For all three parities, the New Zealand strain ranked highest for fat percentage and the US strain lowest. Although rankings were consistent across parities for all yield traits, differences between Holstein and Friesian strains decreased as parity increased. Holstein strains maintained their superiority for milk and fat yields for all three parities despite difficult environmental conditions and a feeding regimen worse than in their country of origin.