Reproduction in dairy cattle: Effect of age,cow condition,production level,calving-to-first-service interval and the ‘male’

A study was conducted to determine the effect of various factors on the reproductive performance of approximately 1700 cows in 12 seasonally calving dairy herds in North Western Tasmania. Submission rate (percent of cows submitted for service for the first time in the first 24 days of the mating season) rose from 60% to 97% as cow condition score improved from 3 to 5.5. There was no effect on non-return rates (percent of cows submitted for service for the first time in the first 24 days of mating which did not return to service in the subsequent 21 days), provided condition score was 3.5 or over. Milk fat yield was positively correlated to both submission and non-return rate until milk fat yield exceeded 1.0 kg/day when both fell (from 79% to 71% and from 73% to 38%, respectively). Non-return rate was 46% when the calving-to-first-service interval was less than 40 days after which it rose to a more normal 65%. Submission rates were unaffected by calving-to-first-service interval. There was a significant positive correlation between age and non-return rate, but not between age and submission rate, although submission rate also tended to be higher in older cattle. The proportion of cows having short cycles (less than 18 days) was 18%. In contrast to reports in other species, the presence of the male did not improve oestrous detection or non-return rate of cows in the immediate post-partum period.     

Progesterone concentrations in milk fat at first insemination--effects on non-return and repeat-breeding

The relationship between milk fat progesterone concentration at first artificial insemination (AI) and reproductive performance of Norwegian Red Cattle dairy cows was investigated in a field study. Fifteen AI technicians collected milk samples from 2250 cows from 458 herds and progesterone was analysed in the milk fat portion of the samples. Logistic regression revealed decreased probability of non-return, and increased likelihood of repeat-breeding, with increasing progesterone concentrations at insemination. The odds ratio for non-return and for repeat-breeding between the minimum and maximum value for milk fat concentrations between 4 and 32.2ng/ml was 4.5 (P < 0.01) and 3.2 (P = 0.01), respectively. The variable 'Technician' did not significantly influence non-return rate or repeat-breeding. Progesterone concentration at AI was positively related to calving to last insemination interval, and to number of inseminations per cow (P < 0.05). The association between the progesterone concentration at insemination and calving interval was only marginally significant. Technician was significantly (P < 0.01) associated with interval from calving to first AI, interval from calving to last AI (P = 0.05), and number of AI per cow (P = 0.01). Technician was not significantly related to the calving interval.We conclude that increased suprabasal progesterone concentrations at the time of first insemination, and higher return rate at AI may, at least partly, be due to endocrinological asynchrony at AI, a condition which may lead to decreased fertility.     

Reproduction management of tethered cows on Norwegian dairy farms

Dairy farms in southern Norway were surveyed to obtain information regarding reproduction management in tied herds. A total of 1613 farms were included in the analyses. Reproductive performance during the main breeding period of the year (November 1 to February 28) was measured using the following dependent variables: calving to first service and last service interval, number of artificial inseminations per cow, non-return rate at 60 days, and calving interval. Culling for failure to conceive was found to be associated with longer calving to first service interval, more inseminations per cow and lower non-return rate. More inseminations per cow and lower non-return rate were also recorded in herds where breeding was close to calving. Oestrous checks late in the evening and frequent observations were associated with shorter calving to last service interval and shorter calving interval. Calving to last service interval was prolonged if the farmers were occupied with routine work while conducting oestrous checks. Manual rectal pregnancy testing was of little importance for reproductive efficiency in dairy herds with good breeding performance. More inseminations per cow occurred in herds where oestrous checks were conducted systematically 3 and 6 weeks after service. Calving to last service interval and calving interval were shorter when only one person was responsible for the herd breeding management.     

Effects of stage of pregnancy on variance components,daily milk yields and 305-day milk yield in Holstein cows,as estimated by using a test-day model

Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (P<0.05) greater than that after the first calving. Therefore, we conclude that differences between the negative effects of early pregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open to maximize lifetime productivity in dairy cows.     

Improvement of Prediction Ability for Genomic Selection of Dairy Cattle by Including Dominance Effects

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield.     

Multivariate analysis of factors associated with calving interval and calving rate in dairy cows

We collected data on reproductive events of cows (n = 2116) that included dates of calving, first service, last artificial insemination before pregnancy examination, pregnancy examination, abortion, diagnosis of cystic ovary, and treatment with prostaglandin. We used multivariate analysis to evaluate the relationship between the interval from insemination to pregnancy examination and the length of calving interval, adjusting for other factors affecting the calving interval. The effect of the interval from insemination to pregnancy examination on calving rate was estimated using logistic regression analysis. The calving interval was long for cows with a short interval from artificial insemination to first pregnancy examination, it was at a minimum at 55 d and increased thereafter. Other factors affecting the calving interval were cystic ovaries, prostaglandin treatment, abortion, number of artificial inseminations, and days to first service. The calving rate was low among cows with a short interval to pregnancy examination, reached a maximum at 48 d, and then declined. Other factors affecting the calving rate were abortion, number of artificial inseminations and whether the cow was bred by a clean-up bull.     

Single nucleotide polymorphisms in the growth hormone and insulin-like growth factor-1 genes are associated with milk production, body condition score and fertility traits in dairy cows

The somatotrophic axis (GH-IGF) is a key regulator of animal growth and development, affecting performance traits that include milk production, growth rate, body composition, and fertility. The aim of this study was to quantify the association of previously identified SNPs in bovine growth hormone (GH1) and insulin-like growth factor 1 (IGF-1) genes with direct performance trait measurements of lactation and fertility in Holstein-Friesian lactating dairy cows. Sixteen SNPs in both IGF-1 and GH1 were genotyped across 610 cows and association analyses were carried out with traits of economic importance including calving interval, pregnancy rate to first service and 305-day milk production, using animal linear mixed models accounting for additive genetic effects. Two IGF-1 SNPs, IGF1i1 and IGF1i2, were significantly associated with body condition score at calving, while a single IGF-1 SNP, IGF1i3, was significantly associated with milk production, including milk yield (means ± SEM; 751.3 ± 262.0 kg), fat yield (21.3 ± 10.2 kg) and protein yield (16.5 ± 8.0 kg) per lactation. Only one GH1 SNP, GH33, was significantly associated with milk protein yield in the second lactation (allele substitution effect of 9.8 ± 5.0 kg). Several GH1 SNPs were significantly associated with fertility, including GH32, GH35 and GH38 with calving to third parity (22.4 ± 11.3 days) (GH32 and GH38 only), pregnancy rate to first service (0.1%) and overall pregnancy rate (0.05%). The results of this study demonstrate the effects of variants of the somatotrophic axis on milk production and fertility traits in commercial dairy cattle.     

GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects

Background

Dominance effect may play an important role in genetic variation of complex traits. Full featured and easy-to-use computing tools for genomic prediction and variance component estimation of additive and dominance effects using genome-wide single nucleotide polymorphism (SNP) markers are necessary to understand dominance contribution to a complex trait and to utilize dominance for selecting individuals with favorable genetic potential.

Results

The GVCBLUP package is a shared memory parallel computing tool for genomic prediction and variance component estimation of additive and dominance effects using genome-wide SNP markers. This package currently has three main programs (GREML_CE, GREML_QM, and GCORRMX) and a graphical user interface (GUI) that integrates the three main programs with an existing program for the graphical viewing of SNP additive and dominance effects (GVCeasy). The GREML_CE and GREML_QM programs offer complementary computing advantages with identical results for genomic prediction of breeding values, dominance deviations and genotypic values, and for genomic estimation of additive and dominance variances and heritabilities using a combination of expectation-maximization (EM) algorithm and average information restricted maximum likelihood (AI-REML) algorithm. GREML_CE is designed for large numbers of SNP markers and GREML_QM for large numbers of individuals. Test results showed that GREML_CE could analyze 50,000 individuals with 400 K SNP markers and GREML_QM could analyze 100,000 individuals with 50K SNP markers. GCORRMX calculates genomic additive and dominance relationship matrices using SNP markers. GVCeasy is the GUI for GVCBLUP integrated with an existing software tool for the graphical viewing of SNP effects and a function for editing the parameter files for the three main programs.

Conclusion

The GVCBLUP package is a powerful and versatile computing tool for assessing the type and magnitude of genetic effects affecting a phenotype by estimating whole-genome additive and dominance heritabilities, for genomic prediction of breeding values, dominance deviations and genotypic values, for calculating genomic relationships, and for research and education in genomic prediction and estimation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-270) contains supplementary material, which is available to authorized users.     

Unraveling Additive from Nonadditive Effects Using Genomic Relationship Matrices

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies.     

Genetic merit for milk production and reproductive success in dairy cows

The effect of genetic merit for milk production traits - fat, protein and milk yield - in dairy cows on milk production, body condition, blood metabolites, reproductive hormones, feed intake and reproductive performance was studied over a period of 2 years. Cows were grouped into two categories, based on calculated pedigree indices using multiple-trait across country evaluation (MACE). Cows of high genetic merit (HGM, n = 48 in year 1 and n = 46 in year 2) had a mean predicted difference +/- standard deviation for milk production of 475 +/- 76kg. The cows of medium genetic merit (MGM, n = 48 in both years) had a mean predicted difference for milk production of 140 +/- 68kg.The cows calved between January and April, and were offered grass silage ad libitum plus 9kg concentrates per cow per day, irrespective genetic merit, from calving to turnout in March, when they were subjected to one of three grazing systems. Cows were available for rebreeding from late April until late July of each year.High genetic merit cows had higher milk production, incurred greater body condition loss between calving and first service and had lower plasma glucose and insulin-like growth factor-1 (IGF-1) concentrations than medium genetic merit cows. Furthermore, HGM cows had lower first and second service and overall conception rates, and required more services per conception than the MGM cows.Cows that did not conceive to first service were retrospectively compared to those that conceived to first service within each genetic merit group. There were no significant differences between the HGM cows that did not conceive to first service and those that conceived to this service in terms of milk production, body condition score change between calving and first service, feed intake at first service, or in plasma concentrations of glucose, non-esterified fatty acids (NEFA) or IGF-1. Medium genetic merit cows that did not conceive to first service lost more body condition between calving and first service than did those that conceived to this service.In the present study, HGM cows had higher milk production and reduced reproductive performance in comparison with MGM cows. However, reproductive performance was not associated with milk production, feed intake or plasma concentrations of glucose, NEFA or IGF-1 between calving and first service, since there were no significant differences in these variates between high or medium genetic merit cows that did not conceive to first service and those that conceived to this service. Therefore, these variates are unlikely to be useful predictors of reproductive performance, under the conditions of the present study.     

Estimates of genetic variance in an F2 maize population

Maize (Zea mays L.) breeders have used several genetic-statistical models to study the inheritance of quantitative traits. These models provide information on the importance of additive, dominance, and epistatic genetic variance for a quantitative trait. Estimates of genetic variances are useful in understanding heterosis and determining the response to selection. The objectives of this study were to estimate additive and dominance genetic variances and the average level of dominance for an F2 population derived from the B73 x Mo17 hybrid and use weighted least squares to determine the importance of digenic epistatic variances relative to additive and dominance variances. Genetic variances were estimated using Design III and weighted least squares analyses. Both analyses determined that dominance variance was more important than additive variance for grain yield. For other traits, additive genetic variance was more important than dominance variance. The average level of dominance suggests either overdominant gene effects were present for grain yield or pseudo-overdominance because of linkage disequilibrium in the F2 population. Epistatic variances generally were not significantly different from zero and therefore were relatively less important than additive and dominance variances. For several traits estimates of additive by additive epistatic variance decreased estimates of additive genetic variance, but generally the decrease in additive genetic variance was not significant.     

Effect of hyperketonaemia and feeding on fertility in dairy cows

Fertility in relation to acetone concentration in milk and level of nutrition was studied in 38,624 lactations from 474 herds over a 3-year period. Herd-related data on nutrition were collected once each year. Milk acetone concentrations higher than 0.40 mM were deemed to be hyperketonaemic. The interval from calving to first service was about 5 days longer in cows with acetone concentrations >2.00 mM, while the interval to the last service was shortest at 0.40 to 1.00 mM. The risk for cystic ovaries was severely increased in first calving heifers with acetone concentrations >2.00 mM (odds ratio; 8.7). In herds with a high frequency of hyperketonaemic cows, primiparous cows had a 6-day longer period from calving to the first service and a 12-day longer period from calving to the last service. Increased feeding frequency of concentrate (2 vs 4 times/day) was related to shorter intervals from calving to first service and from calving to last service of 5 and 6 days, respectively, in mature cows. Increased total intake of energy in early lactation was related to shorter intervals from calving to last service in both primiparous and multiparous cows, 0.3 and 0.1 days per megajoule metabolizable energy, respectively. However, increased amounts of concentrate at calving in multiparous cows, and 15 days after calving in primiparous cows, were related to longer intervals from calving to last service and from calving to first service, respectively. The negative effect on these intervals was estimated to be approximately 2 days per kilogram of concentrate.     

Novel Harmful Recessive Haplotypes Identified for Fertility Traits in Nordic Holstein Cattle

Using genomic data, lethal recessives may be discovered from haplotypes that are common in the population but never occur in the homozygote state in live animals. This approach only requires genotype data from phenotypically normal (i.e. live) individuals and not from the affected embryos that die. A total of 7,937 Nordic Holstein animals were genotyped with BovineSNP50 BeadChip and haplotypes including 25 consecutive markers were constructed and tested for absence of homozygotes states. We have identified 17 homozygote deficient haplotypes which could be loosely clustered into eight genomic regions harboring possible recessive lethal alleles. Effects of the identified haplotypes were estimated on two fertility traits: non-return rates and calving interval. Out of the eight identified genomic regions, six regions were confirmed as having an effect on fertility. The information can be used to avoid carrier-by-carrier mattings in practical animal breeding. Further, identification of causative genes/polymorphisms responsible for lethal effects will lead to accurate testing of the individuals carrying a lethal allele.     

Genomic analysis of dominance effects on milk production and conformation traits in Fleckvieh cattle

Background

Estimates of dominance variance in dairy cattle based on pedigree data vary considerably across traits and amount to up to 50% of the total genetic variance for conformation traits and up to 43% for milk production traits. Using bovine SNP (single nucleotide polymorphism) genotypes, dominance variance can be estimated both at the marker level and at the animal level using genomic dominance effect relationship matrices. Yield deviations of high-density genotyped Fleckvieh cows were used to assess cross-validation accuracy of genomic predictions with additive and dominance models. The potential use of dominance variance in planned matings was also investigated.

Results

Variance components of nine milk production and conformation traits were estimated with additive and dominance models using yield deviations of 1996 Fleckvieh cows and ranged from 3.3% to 50.5% of the total genetic variance. REML and Gibbs sampling estimates showed good concordance. Although standard errors of estimates of dominance variance were rather large, estimates of dominance variance for milk, fat and protein yields, somatic cell score and milkability were significantly different from 0. Cross-validation accuracy of predicted breeding values was higher with genomic models than with the pedigree model. Inclusion of dominance effects did not increase the accuracy of the predicted breeding and total genetic values. Additive and dominance SNP effects for milk yield and protein yield were estimated with a BLUP (best linear unbiased prediction) model and used to calculate expectations of breeding values and total genetic values for putative offspring. Selection on total genetic value instead of breeding value would result in a larger expected total genetic superiority in progeny, i.e. 14.8% for milk yield and 27.8% for protein yield and reduce the expected additive genetic gain only by 4.5% for milk yield and 2.6% for protein yield.

Conclusions

Estimated dominance variance was substantial for most of the analyzed traits. Due to small dominance effect relationships between cows, predictions of individual dominance deviations were very inaccurate and including dominance in the model did not improve prediction accuracy in the cross-validation study. Exploitation of dominance variance in assortative matings was promising and did not appear to severely compromise additive genetic gain.     

Reproductive performance and fatty liver in Guernsey cows

The relationship between fatty liver and reproductive performance was investigated in a commercial herd of Guernsey dairy cattle. Forty-two cows were sampled by liver biopsy at 1 week after calving, and divided into two groups, a fatty liver and a non-fatty liver group, on the basis of the level of liver fat. The cows in the fatty liver group had a milk yield of 5267 kg and a calving interval of 428 days compared with 4407 kg and 369 days for the cows in the non-fatty liver group. The reduced fertility was associated with an elongation in the interval from calving to first service of 20 days and with a reduced conception rate. The occurrence of fatty liver significantly impaired the reproductive performance of the cows.     

Seasonal effects of semen collection and artificial insemination on dairy cow conception

The effects of four seasons of semen collection and of artificial insemination on conception in dairy cows were studied. The solstices and equinoxes (December, March, June and September) defined the beginning and/or end of each season. Semen was collected from 973 progeny-test bulls over 8 years at the two Norwegian AI stations at 60.8 degrees N and 63.4 degrees N where artificial light was used to provide a minimum photoperiod of 10 h/day. The effect of using semen of elite bulls during progeny testing and after selection as elite sires also was investigated. Norwegian Red (NRF) cows were inseminated over a 7-year period using progeny test semen and over the last 4 years of the same period using the semen of the elite sires. The probability of conception to only first inseminations for cows up to, and including, the fifth lactation was assessed by 56-day non-return rate (56d NRR) and calving rate. Two data sets were analysed which excluded cows culled within 270 days of AI or included such cows as non-calving. The reasons for culling were categorised as those for fertility problems or all other reasons. Semen was used for AI irrespective of the season in which it had been collected. Season of semen collection did not affect 56d NRR but calving rate was significantly higher (by 0.5-0.8%, approximately; P < 0.01) for semen collected in the December-March period, when photoperiod was increasing, than at other times of the year. The season in which AI was performed showed a peak of 56d NRR in spring for heifers (P < 0.01) and in summer for parous animals (P < 0.01). For calving rate, however, no seasonal peak was found in heifers, whereas pluriparous cows had much higher calving rates in summer and autumn/early winter than late winter and spring (P < 0.01). Semen of elite sires resulted in higher calving rates by 0.5 (NS) to 1.9% (P < 0.01) when used after selection than when used during progeny testing. The difference between the calving rate achieved when the semen from elite sires was used during progeny testing and after selection indicates that farmers select different classes of cows for submission to AI by progeny test bulls and sires. The 56d NRR was not as good as calving rate for assessing seasonal and other effects on conception rates.     

Non-additive genetic effects in animal selection

Genetic evaluation of purebred farm animals has been carried out for about half a century, employing additive approximation to describe the genetic background. An evaluated animal has been attributed a single breeding value for each trait of the breeding goal. The predicted additive genetic value of an animal equals the average breeding value of its parents. Although the selection based on the additive approach has proved successful, there still is a possibility of increasing the reliability of the breeding value estimation by accounting for non-additive genetic effects of dominance and epistasis, disregarded in the additive model. In the non-additive model, the expected quality of the progeny equals the average of the parents plus an effect resulting from the interaction between the parents. In this case, the evaluated animal may have as many breeding values as there are possible candidates to mate to, for each trait. The dominance and epistatic effects have already been accounted for in selecting animals or populations for some crossbreeding plans (combining ability, heterosis, and recombination loss). Also, using crossbreds for the sake of the breeding value estimation of purebred animals requires removing the non-additive effects from the crossbred performance and distributing the additive component between the purebreds. Combining ability is more and more discussed as a factor for matings within breed to produce terminal progeny.     

海岛棉F1产量性状的条件遗传分析

调查了海岛棉5×4不完全双列杂交实验的3年产量性状资料,运用包括加性、显性、加性×环境互作、显性×环境互作的遗传模型进行条件和非条件的遗传分析.双列杂交的亲本具有不同果枝类型.非条件遗传方差结果表明,总皮棉产量没有检测到显著的非条件加性效应方差.但是铃重、霜前铃数、霜后铃数以及霜前皮棉产量的条件分析结果发现这些性状的加性效应均对总皮棉产量的加性效应有贡献.因此,可通过这些性状改良总皮棉产量的加性效应表现.当某材料产量构成因素的加性贡献率比较高时,选择该材料作为杂交亲本可望获得具有较好总皮棉产量表现的后代.各产量构成因素的显性效应对霜前皮棉产量和总皮棉产量的杂种优势具有较大的贡献率.产量构成因素之间又相互影响.那些能够检测到显著的正向贡献率的性状将为进一步改良目标性状提供可能.本研究结果显示运用条件分析方法不仅能分析原因性状对目标性状的贡献率,还可以分析特定亲本(或组合)的某一性状对该亲本或组合目标性状的作用大小和正负,据此就可以指导某一亲本后代或组合的目标性状的间接选择.这对实际育种中具体组合的选择具有重要的意义.     

Reproductive performance of Norwegian cattle from 1985 to 2005: trends and seasonality

Declining reproductive performance is a serious breeding concern in many countries. To reveal the situation in Norwegian cattle, trends in reproductive performance were studied using insemination reports from 1985 to 2005 and data based on herd recording files from 1989 to 2005. The total number of first services was 469.765 in 1985 declining to 335.712 in 2005. The number of recorded herds and animals declined from 21.588 to 14.718 and 360.289 to 309.452 from 1989 to 2005, respectively. Sixty days non-return rate after single inseminations (NR60) increased from 68.1 in 1985 to 72.7% in 2005 (p < 0.001) and the number of services per inseminated animal (NIA) decreased from 1.8 to 1.6 (p < 0.001) from 1985 to 2005. However, return rates 0–3 days post insemination (RR0-3) increased from 6 to 12% in the same period (p < 0.001). NR60 was higher and the RR0-3 was lower in the summer season compared to the winter season during the whole period. A fertility index (FS), has been calculated from the herd recording files each year from 1989 to 2005. The average FS-index did not show a significant trend and the calving interval was also fairly constant between 12.4 and 12.6 months during this period. The average interval from calving to first and last insemination, respectively, increased from a low of 79 and 102 days in 1990 to a high of 86 and 108 days in 2005. Both intervals were consistently longer for cows in first lactation than for cows in later lactations. The percentage of inseminated animals reported culled because of poor fertility decreased from 6.0% in 1989 to 4.6% in 1996 and thereafter again increased to 6% in 2005. In conclusion, most fertility measures, mainly comprising the Norwegian Red (NRF) breed, show a relatively high level of reproductive performance with a positive or a relatively constant trend during the last two decades.     

Effect of prepartum injection of vitamin E and selenium on postpartum reproductive function of dairy cattle

A total of 198 cows were randomly assigned to treatment with a single intramuscular injection of 10 ml of a preparation containing vitamin E and selenium or placebo 3 wk before expected parturition. Incidence of retained fetal membranes was 3.0% for the treated group and 10.1% for the control group (P=0.06). Administration of MU-SE also increased the percentage of cows pregnant to the first service (41.2 vs 25.3%; P=0.02), reduced the number of services per conception (2.3 vs 2.8; P=0.03), and reduced the interval from calving to conception (121 vs 141 days; P=0.06). The effect of MU-SE on fertility was apparent in cows with and without retained fetal membranes. There was no effect of MU-SE on the interval from calving to the first estrus. In conclusion, prepartum supplementation with vitamin E and selenium can decrease the incidence of retained fetal membranes, increase pregnancy rates and, thereby, reduce the interval from calving to conception in lactating dairy cows.