Short communication: Genetic analysis of nonreturn rate and mastitis in first-lactation Norwegian Red cows

Associations between clinical mastitis (CM) and nonreturn rate within 56 d after first insemination (NR56) were examined in Norwegian Red (NRF) cows. Records on absence or presence of CM within each of the intervals, −30 to 30, 31 to 150, and 151 to 300 d after first calving, and records on NR56 for 620,492 first-lactation daughters of 3,064 NRF sires were analyzed with a Bayesian multivariate threshold liability model. Point estimates of genetic correlations between NR56 and the 3 CM traits were between −0.05 and −0.02. Residual correlations were close to zero, and correlations between herd-5-yr effects on NR56 and CM in the 3 lactation intervals ranged from −0.15 to −0.17. It appears that CM and NR56 in first lactation are independent traits.     

Correlated selection responses for female fertility after selection for high protein yield or low mastitis frequency in Norwegian Red cows

Correlated selection responses in female fertility were estimated from a selection experiment with 2 groups of Norwegian Red cows selected for high protein yield (HPY) and low mastitis frequency (LCM), respectively. Genetic trends were calculated for nonreturn rate within 56 d after first insemination (NR56) for heifers, first-lactation cows, and second- and third-lactation cows, calving interval between first and second calving (CIN), and interval from calving to first insemination (CFI) for first-lactation cows and for second- and third-lactation cows. A total of 5,001 cows from the selection experiment had estimated breeding values for fertility, of which 2,806 were HPY and 2,195 were LCM cows. Permutation tests showed significant genetic differences between LCM and HPY for all fertility traits except CFI for second- and third-lactation cows. Observed differences between mean EBV in HPY and in LCM were, with few exceptions, far outside the range of the permutation test (i.e., significantly different from zero). LCM cows were, in general, genetically more fertile than HPY cows, with higher NR56 in heifers and cows, shorter CIN, and shorter CFI in first lactation. Genetic differences between HPY and LCM after 6 cow-generations were 2.5 percentage units NR56 in heifers, 2 percentage units NR56 in cows, and 4 d for CIN. No difference was found for CFI in second and third lactation. This is the first report of genetic change in female fertility as a correlated response after selection against mastitis.     

Heritabilities, genetic correlations, and genetic change for female fertility and protein yield in Norwegian Dairy Cattle

Data from 1,815,581 first insemination records from daughters of 2697 Norwegian Dairy Cattle (NRF) sires were analyzed. A multitrait model was used to estimate genetic parameters and genetic change for 56-d nonreturn rate in virgin heifers (NR56D0), for 56-d nonreturn rate in first lactation cows (NR56D1L), for interval from calving to first insemination (CFI1L), and for protein yield (PY(305)1L). The heritabilities for NR56D0, NR56D1L, CFI1L, and PY(305)1L were 1.08, 0.99, 3.01, and 20.80%, respectively. Genetic correlation between heifer and cow fertility was high and favorable between NR56D0 and NR56D1L (0.54) and moderate and unfavorable between NR56D0 and CFI1L (0.24). The genetic correlations between NR56D1L and CFI1L and between NR56D0 and PY(305)1L were 0.08 and 0.04, respectively. A small, unfavorable genetic correlation between NR56D1L and PY(305)1L (-0.18) was found, while the genetic correlation between PY(305)1L and CFI1L was strongly unfavorable (0.47). Since 1972, NRF sires have been selected for NR56D0 using breeding values estimated from large progeny groups and with considerable weight in the total merit index. A linear regression analysis of sire PTA on year of first insemination of daughters showed an annual genetic change of 0.14% units for NR56D0. Selection was able to stabilize the genetic change of NR56D1L (0.03%/yr) but an undesirable change for CFI1L (0.11 d/yr) was found. The change of sire PTA for PY(305)1L was 0.63 kg/yr.     

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

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

Comparison between bivariate models for 56-day nonreturn and interval from calving to first insemination in Norwegian red

A bivariate threshold-linear (TL) and a bivariate linear-linear (LL) model were assessed for the genetic analysis of 56-d nonreturn (NR56) and interval from calving to first insemination (CFI) in first-lactation Norwegian Red (former Norwegian Dairy Cattle) (NRF). Three different datasets were used to infer genetic parameters and to predict transmitting abilities for NRF sires. Mean progeny group sizes were 147.8, 102.7, and 56.5 daughters, and the corresponding number of sires were 746, 743, and 742 in the 3 datasets. Otherwise, the structures of the 3 datasets were similar. When the TL model was used, heritability of liability to NR56 was 2.8% in the 2 larger datasets and 3.8% in the smallest dataset. In the LL model, the heritability of NR56 in the largest dataset and in the 2 smaller datasets was 1.2 and 0.9%, respectively. For CFI, the heritability was similar in TL and LL models, ranging from 2.4 to 2.7%. The small heritability of the 2 reproductive traits implies that most of the variation is environmental and that large progeny groups are required to get accurate sire PTA. The point estimates of the genetic correlation between NR56 and CFI were near zero in both models. The 2 bivariate models were compared in terms of predictive ability using logistic regression and a χ² statistic based on differences between observed and predicted outcomes for NR56 in a separate dataset. Comparison was also with respect to ranking of sires and correlations between sire posterior means (TL model) and PTA (LL model). We found very small differences in ability to predict NR56 between the 2 bivariate models, regardless of the dataset used. Correlations between sire posterior means (TL) and sire PTA (LL) and rank correlations between sire evaluations were all >0.98 in the 3 datasets. At present, the LL model is preferred for sire evaluations of NR56 and CFI in NRF. This is because the LL model is less computationally demanding and more robust with respect to the structure of the data than TL.     

Selection responses for disease resistance in two selection experiments with Norwegian red cows

Genetic trends for clinical mastitis (CM), ketosis (KET), retained placenta (RP), and 305-d protein yield (PY305) were calculated for 2 Norwegian dairy cattle selection experiments. The first experiment, accomplished from 1978 to 1989, included groups selected for high (HMP) and low milk production (LMP). The second experiment started in 1989 and included selection for high protein yield (HPY) and low mastitis frequency (LCM). In both experiments proven sires from the active breeding program of Norwegian Red were used as sires. To take into account that selection of sires was external to the experiment, all available data from the Norwegian Red population, including disease records for 2.7 million first-lactation cows, were analyzed with a multivariate animal model. Estimated breeding values for cows in the experiments were extracted from this analysis to calculate genetic trends in the selection groups. Genetic trends for PY305 were, as expected, positive for the HMP and HPY groups, and negative for LMP and LCM. The HMP group showed increasing genetic trends for all 3 diseases, arguably a correlated response after selection for increased milk production, whereas the LCM group showed decreasing genetic trends for CM, KET, and RP. The genetic trends for KET and RP in the LCM group are most likely correlated responses after selection against CM. After 5 cow-generations the genetic difference between HPY and LCM was 10 percentage units CM, 1.5 percentage units KET, and 0.5 percentage units RP.     

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.     

Selection of bull dams for production and functional traits in an open nucleus herd

The aim of this study was to compare different scenarios for bull dam selection in a nucleus herd. A deterministic simulation study using selection index methodology was undertaken. In the scenarios studied, differing amounts of information on functional traits were available when bull dams were selected, and the resulting genetic responses in these traits were compared. Field-recorded fertility traits used in the scenarios were available as progeny test results of artificial insemination bulls: these included pregnant at first insemination (PFI), interval between calving and first insemination (CFI), and cases of reproductive disorders (RD). Similarly, field-recorded cases of clinical mastitis (CM), lactation somatic cell score (LSCS), and protein yield (PY) were included for pedigree selection. In the scenarios, heat intensity score and progesterone levels were treated as new indicator traits of fertility recorded in the nucleus herd. Traits CFI and LSCS were assumed to be better recorded with higher heritability in the nucleus herd than in ordinary herds. Economic weights currently used in Nordic Cattle Genetic Evaluation (NAV) were adapted and used in the scenarios. The results showed that these weights, if used in multiple trait genetic evaluation, would lead to undesirable genetic changes in functional traits for the bull dam selection path in a nucleus environment. More frequent recording of additional traits failed to improve selection for functional traits, as did more frequent recording of ordinary traits. Restriction index methodology was used to derive the bull dam total weights that gave no unfavorable response (i.e., zero genetic change) in traits PFI, CFI, and CM. When summarized over lactations, the new bull dam total weights, when additional records from nucleus were used, had to be 12 to 23 times higher for fertility, and 3 times higher for mastitis, than the presently used NAV weights, if these traits were to remain unchanged through the bull dam selection path. Thus, nucleus herd selection of bull dams is questionable for low heritability traits that are already recorded in the field.     

Genetic analysis of pathogen-specific clinical mastitis in Norwegian Red cows

The objective of this study was to estimate heritabilities and genetic correlations for pathogen-specific clinical mastitis (CM) in Norwegian Red cows. In Norway, breeding values for mastitis are predicted based on records of veterinary treatments of clinical mastitis. Bacteriological milk sample results from the mastitis laboratories have been recorded routinely into the Norwegian Dairy Herd Recording System since 2000, but have so far not been used in genetic analyses. This additional source of data may provide valuable information on pathogen-specific CM. Records from 234,088 first-lactation Norwegian Red cows, daughters of 1,656 sires, were used for genetic analyses of unspecific, Staphylococcus aureus, Streptococcus dysgalactiae, and Escherichia coli CM. The 4 CM traits were defined as binary and scored as 1 if the cow had at least 1 case of the CM in question and 0 otherwise. A Bayesian approach using Gibbs sampling was applied, and a multivariate threshold liability model was used for the analyses. The posterior mean (SD ≤ 0.01) of the heritabilities were 0.06 for liability of unspecific CM, 0.04 for Staph. aureus CM, 0.02 for Strep. dysgalactiae CM, and 0.03 for E. coli CM. The posterior mean (SD) of the genetic correlations were all high, ranging from 0.75 (0.14) to 0.87 (0.07). The highest genetic correlation was found between unspecific CM and Strep. dysgalactiae CM, whereas the lowest was found for E. coli CM and Staph. aureus CM. Genetic correlations lower than 1 indicate that mastitis caused by different pathogens can be considered as partly different traits. In spite of high rank correlations (0.95-0.98), some re-ranking of sires was observed.     

Analysis of fertility and dystocia in Holsteins using recursive models to handle censored and categorical data

A method based on the analysis of recursive multiple-trait models was used to 1) estimate genetic and phenotypic relationships of calving ease (CE) with fertility traits and 2) analyze whether dystocia negatively affects reproductive performance in the next reproductive cycle. Data were collected from 1995 through 2002, and contained 33,532 records of CE and reproductive data of 17,558 Holstein cows distributed across 560 herds in official milk recording from the Basque Country Autonomous Community (Spain). The following fertility traits were considered: days open (DO), days to first service, number of services per pregnancy (NINS), and outcome of first insemination (OFI). Four bivariate sire and sire-maternal grandsire models were used for the analyses. Censoring existed in DO (26.49% of the data) and NINS (12.22% of the data) because of cows having been sold or culled before reaching the next parturition. To avoid bias, a data augmentation technique was applied to censored data. Threshold models were used for CE and OFI. To consider that CE affects fertility and the genetic determination of CE and fertility traits, recursive models were applied, which simultaneously considered CE as a fixed effect on fertility performance and the existence of a genetic correlation between CE and fertility traits. The effects of CE score 3 (difficult birth) with respect to score 1 (no problem) for days to first service, DO, NINS, and OFI were 8 d, 31 d, 0.5 services, and - 12% success at first insemination, respectively. These results showed poorer fertility after dystocia. Genetic correlations between genetic effects of fertility traits and CE were close to zero, except for the genetic correlations between direct effects of DO and CE, which were positive, moderate, and statistically different from 0 (0.47 ± 0.24), showing that genes associated with difficult births also reduce reproductive success.     

Genetic evaluation of fertility using direct and correlated traits

Poor fertility has become a major reason for involuntary culling of dairy cows in the United Kingdom. Calving interval (CI) and body condition score (BCS) are recorded, heritable, genetically correlated with each other, and could be used to extend the scope of dairy indices to include fertility traits. The use of U.K. insemination information for the evaluation of fertility has not been examined previously. Fertility and correlated traits were examined using nationally recorded milk (MILK = daily milk yield at test nearest d 110), BSC, and fertility traits (CI and the insemination traits of nonreturn rate after 56 d, NR56; days to first service, DFS; and number of inseminations per conception, INS). Genetic parameters for the traits were estimated simultaneously with a multitrait sire maternal grandsire (MGS) model and a multitrait BLUP sire MGS model was used to predict sire predicted transmitting abilities for each trait. The relationship between the fertility traits and other predicted transmitting abilities calculated in the United Kingdom was then examined. Heritabilities for the fertility traits were CI = 0.033 +/- 0.01, DFS = 0.037 +/- 0.01, NR56 = 0.018 +/- 0.001, and INS = 0.020 +/- 0.001, with a genetic correlation of 0.671 +/- 0.063 between CI and DFS and -0.939 +/- 0.031 between NR56 and INS. There was an unfavorable genetic correlation between the fertility traits and milk yield and BCS. Predicted transmitting abilities produced are similar in size and range to those produced in other studies and genetic trends are as expected. Results to date are encouraging and suggest that the planned program of work will lead to a fertility index that, when used by breeding companies, will lead to improvements in national dairy cow fertility.     

Genetic analysis of reproductive disorders and their relationship to fertility and milk yield in Austrian Fleckvieh dual-purpose cows

The objective of this study was to estimate genetic parameters for various reproductive disorders based on veterinary diagnoses for Austrian Fleckvieh (Simmental) dual-purpose cattle. The health traits analyzed included retained placenta, puerperal diseases, metritis, silent heat and anestrus, and cystic ovaries. Three composite traits were also evaluated: early reproductive disorders, late reproductive disorders, and all reproductive disorders. Heritabilities were estimated with logit threshold sire, linear sire, and linear animal models. The threshold model estimates for heritability ranged from 0.01 to 0.14, whereas the linear model estimates were lower, ranging from 0.005 to 0.04. Rank correlations among random effects of sires from linear and threshold sire models were high (>0.99), whereas correlations between any sire model (linear, threshold) and the linear animal model were lower (0.88-0.92). Genetic correlations among reproductive disorders, fertility traits, and milk yield were estimated with bivariate linear animal models. Fertility traits included interval from calving to first insemination, nonreturn rate at 56 d, and interval between first and last insemination. Milk yield was calculated as the mean from test-day 1 and test-day 2 after calving. Estimated genetic correlations were 1 among metritis, retained placenta, and puerperal diseases and 0.85 between silent heat-anestrus and cystic ovaries. Low to moderate correlations (−0.01 to 0.68) were obtained among the other disorders. Genetic correlations between reproductive disorders and fertility traits were favorable, whereas antagonistic relationships were observed between milk yield in early lactation and reproductive disorders. Pearson correlations between estimated breeding values for reproductive disorders and other routinely evaluated traits were computed, which revealed noticeable favorable relationships to longevity, calving ease maternal, and stillbirth maternal. The results showed that data from the Austrian health monitoring project can be used for genetic selection against reproductive disorders in Fleckvieh cattle.     

Genetic parameters for female fertility traits and a fertility index in Spanish dairy cattle

Genetic correlations among female fertility traits (linear and binary) were estimated using 225,085 artificial insemination records from 120,713 lactations on 63,160 Holstein cows. Fertility traits were: calving interval, days open, a linear transformation of days open, days to first insemination, interval between first and last insemination, number of inseminations per service period, pregnancy within 56 and 90 d after first insemination, and success in first insemination. A bivariate animal model was implemented using Bayesian methods in the case of binary traits. Low heritabilities (0.02 to 0.06) were estimated for these fertility traits. Strong genetic correlations (0.89 to 0.99) were found among traits, except for days to first service, where the genetic correlation with other fertility traits ranged from −0.52 to −0.18 for binary traits, and from 0.50 to 0.82 for days to first service, calving interval, and days open. Four fertility indices were proposed utilizing information from insemination records; these indices combined one indicator of the beginning of the service period and one indicator of conception rate. Two additional indices used information from the milk-recording scheme, including calving interval and a linear transformation of days open. The fertility index composed of days to first service and pregnancy within 56 d achieved the highest genetic gain for reducing fertility cost, reducing days to first service, and reducing the number of inseminations per lactation ($8.60, −1.31 d, and −0.03 AI, respectively). This index achieved at least 15% higher genetic gain than obtained from indices with information from the milk recording scheme only (calving interval and days open).     

Genetic evaluation of fertility traits of dairy cattle using a multiple-trait animal model

A genetic evaluation system was developed for 5 fertility traits of dairy cattle: interval from first to successful insemination and nonreturn rate to 56 d of heifers, and interval from calving to first insemination, nonreturn rate to 56 d, and interval first to successful insemination of cows. Using the 2 interval traits of cows as components, breeding values for days open were derived. A multiple-trait animal model was applied to evaluate these fertility traits. Fertility traits of later lactations of cows were treated as repeated measurements. Genetic parameters were estimated by REML. Mixed model equations of the genetic evaluation model were solved with preconditioned conjugate gradients or the Gauss-Seidel algorithm and iteration on data techniques. Reliabilities of estimated breeding values were approximated with a multi-trait effective daughter contribution method. Daughter yield deviations and associated effective daughter contributions were calculated with a multiple trait approach. The genetic evaluation software was applied to the insemination data of dairy cattle breeds in Germany, Austria, and Luxembourg, and it was validated with various statistical methods. Genetic trends were validated. Small heritability estimates were obtained for all the fertility traits, ranging from 1% for nonreturn rate of heifers to 4% for interval calving to first insemination. Genetic and environmental correlations were low to moderate among the traits. Notably, unfavorable genetic trends were obtained in all the fertility traits. Moderate to high correlations were found between daughter yield-deviations and estimated breeding values (EBV) for Holstein bulls. Because of much lower heritabilities of the fertility traits, the correlations of daughter yield deviations with EBV were significantly lower than those from production traits and lower than the correlations from type traits and longevity. Fertility EBV were correlated unfavorably with EBV of milk production traits but favorably with udder health and longevity. Integrating fertility traits into a total merit selection index can halt or reverse the decline of fertility and improve the longevity of dairy cattle.     

Genetic and phenotypic relationships among endocrine and traditional fertility traits and production traits in Holstein-Friesian dairy cows

The objective of this study was to estimate the heritability of a number of traditional and endocrine fertility traits in addition to d-56 predicted milk yield (MY56), and the genetic and phenotypic correlations between these traits. Various fixed effects such as season, year, herd, lactation number, diet, percentage Holstein (PCH) of the cow, and occurrence of uterine infection (UI), dystocia (DYS), and retained placenta (RP) were also investigated. Data collected for 1212 lactations of 1080 postpartum (PP) Holstein-Friesian dairy cows in eight commercial farms between 1996 and 1999 included thrice weekly milk progesterone samples, calving and insemination dates, various reproductive health records, monthly/bimonthly production records, three-generation pedigrees, and PCH information. Genetic models were fitted to the data to obtain heritabilitites and correlations using ASREML. Estimates of heritability for interval to commencement of luteal activity PP (lnCLA), length of the first luteal phase PP (lnLutI) and occurrence of persistent CL type I (PCLI) were 0.16, 0.17, and 0.13, respectively. Heritabilities for pregnancy to first service (PFS), interval to first service (IFS), and MY56 were 0.14, 0.13, and 0.50, respectively. Genetic regressions of lnCLA and lnLutI on PTA of the sire for milk, fat, and protein yields, and PIN95 were investigated. Regressions of lnCLA were positive and significant on fat yield, while regressions of lnLutI on both protein yield and PIN95 were negative and significant. Genetic correlations of endocrine fertility traits (lnCLA, lnLutI, and PCLI) with MY56 were high (0.36, P < 0.05; -0.51, P < 0.05; and -0.31, P < 0.1, respectively). Percentage Holstein of the cows had no significant effect on any of the fertility parameters monitored. This work emphasizes the strong genetic correlation of fertility with production traits and, therefore, highlights the urgent requirement for selective breeding for fertility in the United Kingdom. The high heritability of endocrine fertility traits stress their potential value for inclusion in a selection index to improve fertility.     

Calving traits,milk production,body condition,fertility, and survival of Holstein-Friesian and Norwegian Red dairy cattle on commercial dairy farms over 5 lactations

The objective of this study was to compare calving traits, BCS, milk production, fertility, and survival of Holstein-Friesian (HF) and Norwegian Red (NR) dairy cattle in moderate-concentrate input systems. The experiment was conducted on 19 commercial Northern Ireland dairy farms, and involved 221 HF cows and 221 NR cows. Cows completed 5 lactations during the experiment, unless they died or were culled or sold. Norwegian Red cows had a lower calving difficulty score than HF cows when calving for the first and second time, but not for the third and fourth time. At first calving, the incidence of stillbirths for NR cows was 4%, compared with 13% for HF cows, whereas no difference existed between breeds in the proportion of calves born alive when calving for the second time. When calving for the first time, NR cows had a poorer milking temperament than HF cows, whereas milking temperament was unaffected by breed following the second calving. Holstein-Friesian cows had a higher full-lactation milk yield than NR cows, whereas NR cows produced milk with a higher milk fat and protein content. Full-lactation fat + protein yield was unaffected by genotype. Norwegian Red cows had a lower somatic cell score than HF cows during all lactations. Although NR cattle had a higher BCS than the HF cows during lactations 1 and 2, no evidence existed that the 2 genotypes either lost or gained body condition at different rates. Conception rates to first artificial insemination were higher with the NR cows during lactations 1 to 4 (57.8 vs. 40.9%, respectively), with 28.5% of HF cows and 11.8% of NR cows culled as infertile before lactation 6. A greater percentage of NR cows calved for a sixth time compared with HF cows (27.2 vs. 16.3%, respectively). In general, NR cows outperformed HF cows in traits that have been historically included in the NR breeding program.     

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.     

Genetic parameters of blood β-hydroxybutyrate predicted from milk infrared spectra and clinical ketosis,and their associations with milk production traits in Norwegian Red cows

The aim of this study was to estimate genetic parameters for blood β-hydroxybutyrate (BHB) predicted from milk spectra and for clinical ketosis (KET), and to examine genetic association of blood BHB with KET and milk production traits (milk, fat, protein, and lactose yields, and milk fat, protein, and lactose contents). Data on milk traits, KET, and milk spectra were obtained from the Norwegian Dairy Herd Recording System with legal permission from TINE SA (Ås, Norway), the Norwegian Dairy Association that manages the central database. Data recorded up to 120 d after calving were considered. Blood BHB was predicted from milk spectra using a calibration model developed based on milk spectra and blood BHB measured in Polish dairy cows. The predicted blood BHB was grouped based on days in milk into 4 groups and each group was considered as a trait. The milk components for test-day milk samples were obtained by Fourier transform mid-infrared spectrometer with previously developed calibration equations from Foss (Hillerød, Denmark). Veterinarian-recorded KET data within 15 d before calving to 120 d after calving were used. Data were analyzed using univariate or bivariate linear animal models. Heritability estimates for predicted blood BHB at different stages of lactation were moderate, ranging from 0.250 to 0.365. Heritability estimate for KET from univariate analysis was 0.078, and the corresponding average estimate from bivariate analysis with BHB or milk production traits was 0.002. Genetic correlations between BHB traits were higher for adjacent lactation intervals and decreased as intervals were further apart. Predicted blood BHB at first test day was moderately genetically correlated with KET (0.469) and milk traits (ranged from ?0.367 with protein content to 0.277 with milk yield), except for milk fat content from across lactation stages that had near zero genetic correlation with BHB (0.033). These genetic correlations indicate that a lower BHB is genetically associated with higher milk protein and lactose contents, but with lower yields of milk, fat, protein, and lactose, and with lower frequency of KET. Estimates of genetic correlation of KET with milk production traits were from ?0.333 (with protein content) to 0.178 (with milk yield). Blood BHB can routinely be predicted from milk spectra analyzed from test-day milk samples, and thereby provides a practical alternative for selecting cows with lower susceptibility to ketosis, even though the correlations are moderate.     

Estimates of genetic parameters for Canadian Holstein female reproduction traits

Age at first insemination, days from calving to first insemination, number of services, first-service nonreturn rate to 56 d, days from first service to conception, calving ease, stillbirth, gestation length, and calf size of Canadian Holstein cows were jointly analyzed in a linear multiple-trait model. Traits covered a wide spectrum of aspects related to reproductive performance of dairy cows. Other frequently used fertility characteristics, like days open or calving intervals, could easily be derived from the analyzed traits. Data included 94,250 records in parities 1 to 6 on 53,158 cows from Ontario and Quebec, born in the years 1997 to 2002. Reproductive characteristics of heifers and cows were treated as different but genetically correlated traits that gave 16 total traits in the analysis. Repeated records for later parities were modeled with permanent environmental effects. Direct and maternal genetic effects were included in linear models for traits related to calving performance. Bayesian methods with Gibbs sampling were used to estimate covariance components of the model and respective genetic parameters. Estimates of heritabilities for fertility traits were low, from 3% for nonreturn rate in heifers to 13% for age at first service. Interval traits had higher heritabilities than binary or categorical traits. Service sire, sire of calf, and artificial insemination technician were important (relative to additive genetic) sources of variation for nonreturn rate and traits related to calving performance. Fertility traits in heifers and older cows were not the same genetically (genetic correlations in general were smaller than 0.9). Genetic correlations (both direct and maternal) among traits indicated that different traits measured different aspects of reproductive performance of a dairy cow. These traits could be used jointly in a fertility index to allow for selection for better fertility of dairy cattle.     

Genetic analysis of fertility-related diseases and disorders in Norwegian Red cows

Heritability of and genetic correlations among silent heat (SH), cystic ovaries (CO), metritis (MET), and retained placenta (RP) were inferred. These traits were chosen because they are the 4 most frequent fertility-related diseases and disorders among first-lactation cows in Norway. Records of 503,683 first-lactation daughters of 1,058 Norwegian Red sires with first calving from 2000 through 2006 were analyzed with a 4-variate threshold sire model. Presence or absence of each of the 4 diseases was scored as 1 or 0 based on whether or not the cow had at least 1 veterinary treatment for the disease. The mean frequency was 3.1% for SH, 0.9% for MET, 0.5% for CO, and 1.5% for RP. The model for liability had effects of age at calving and of month-year of calving, herd, sire of the cow, and a residual. Posterior mean (SD) of heritability of liability was 0.06 (0.01) for SH, 0.03 (0.01) for MET, 0.07 (0.01) for CO, and 0.06 (0.01) for RP. The genetic correlation between MET and RP was strong, with posterior mean (SD) 0.64 (0.10). A negative genetic correlation (−0.26) was found between RP and CO. The posterior distributions of the other genetic correlations included zero with high density, and could not be considered different from zero. The frequency of fertility-related diseases and disorders is very low in the Norwegian Red population at present, so there is limited scope for genetic improvement. However, this study indicates that reasonably precise genetic evaluation of sires is feasible for these traits given information from large daughter groups.