Economic value of female fertility and its relationship with profit in Spanish dairy cattle

Profitability Optimization of Dairy Farms: The Effect of Pregnancy Rate and Culling Decision

One of the most important decisions in dairy cattle production today is the correct choice of culling time for cows. In the culling decision process, the farmer has to take into account a number of factors, the complexity of which makes the decision-making task difficult. A crucial factor is the evolution of reproductive indicators. The aim of the research was to develop a microsimulation method that can be used to easily investigate the impact on profitability of increasing pregnancy rates and when the culling decision is made. In the microsimulation, the stock was examined without changing any other conditions. A microsimulation method has been developed to determine with high accuracy the effect of the pregnancy rate and the increase in culling days on the economic indicators of individual dairy farms. By microsimulation, the effect of changing these two parameters on the expected milk production of cows, the most important economic indicator for cattle farms, was investigated. The other parameters of economic importance were simulated using a cattle farm database. The purpose of microsimulation is to assist in producing certain managerial decisions in order to achieve better profitability and economic efficiency. In summary, the results showed that increasing the pregnancy rate can successfully reduce the length of the calving interval, but the improved pregnancy rate did not show a significant increase in milk production. In order to obtain results that can be used by farms, the authors intend to further develop the model in the future, adapting it to farms and taking into account their specificities.

Identification of candidate lethal haplotypes and genomic association with post-natal mortality and reproductive traits in Nellore cattle

The wide use of genomic information has enabled the identification of lethal recessive alleles that are the major genetic causes of reduced conception rates, longer calving intervals, or lower survival for live-born animals. This study was carried out to screen the Nellore cattle genome for lethal recessive haplotypes based on deviation from the expected population homozygosity, and to test SNP markers surrounding the lethal haplotypes region for association with heifer rebreeding (HR), post-natal mortality (PNM) and stayability (STAY). This approach requires genotypes only from apparently normal individuals and not from affected embryos. A total of 62,022 animals were genotyped and imputed to a high-density panel (777,962 SNP markers). Expected numbers of homozygous individuals were calculated, and the probabilities of observing 0 homozygotes was obtained. Deregressed genomic breeding values [(G)EBVs] were used in a GWAS to identify candidate genes and biological mechanisms affecting HR, STAY and PNM. In the functional analyses, genes within 100 kb down and upstream of each significant SNP marker, were researched. Thirty haplotypes had high expected frequency, while no homozygotes were observed. Most of the alleles present in these haplotypes had a negative mean effect for PNM, HR and STAY. The GWAS revealed significant SNP markers involved in different physiological mechanisms, leading to harmful effect on the three traits. The functional analysis revealed 26 genes enriched for 19 GO terms. Most of the GO terms found for biological processes, molecular functions and pathways were related to tissue development and the immune system. More phenotypes underlying these putative regions in this population could be the subject of future investigation. Tests to find putative lethal haplotype carriers could help breeders to eliminate them from the population or manage matings in order to avoid homozygous.

Success rate of artificial insemination, reproductive performance and economic impact of failure of first service insemination: a retrospective study

Background

A retrospective cohort study using a 10 year artificial insemination (AI) and cow reproductive performance data was conducted to study the success rate of AI; associations between effectiveness of AI and breed, AI season and, number of service per conception, and economic impact of failure of FSC in Dessie town, Dessie zuria and Kutaber districts. A total of 3480 dairy cows’ AI and reproductive performance records which were performed between 2003 and 2013 in the three selected districts of South Wollo were used. The economic losses and costs for cows that failed to conceive at their first AI associated with the larger number of days open were estimated.

Result

The prevalence of conception has a statistically significant difference between breeds of cows (P = 0.019). The non-return rate for first service was 58.54%. The median days to first service (DFS), inter-service interval (ISI) and gestation length (GL) were 126, 30 and 278 days respectively. Whereas, the mean + SD days open, calving interval (CI), number of inseminations (NOI) and number of services per conception (NSPC) were 147.2 ± 60.26, 424.5 ± 60.55, 1.14 ± 0.38 and 1.15 ± 0.39 respectively. Based on AI season there was a significant difference in conception between winter and spring (P = 0.021). There is a 45.04 days extension in the mean calving to conception interval in cows that did not conceive at their first AI but conceived by 2nd and 3rd AI than in cows that did conceive at their first AI. A total of 21,665.3 ETB extra costs was spent on reproductive treatment and other management for cows that failed to conceive at their first AI but conceived by second and third service. In cows that did not conceive totally the owner losses on average 473.7 ETB per cow per day extra costs until the cows will be culled.

Conclusion

Therefore to increase the conception rate and decrease the economic loss the owners of the dairy cows should supervise the cows regularly and should be trained on how to identify cows on estrous, the AI technicians should be trained to conduct the AI service accurately.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-022-03325-1.

The Occurrence of a Negative Energy Balance in Holstein-Friesian and Simmental Cows and Its Association with the Time of Resumption of Reproductive Activity

Intensive lactation (lactogenesis) in cows is conducive to a negative energy balance (NEB), so the search for traits associated with the physiological capacity to cope with its consequences is a current area of research. This is especially important because NEB overlaps with the resumption of the reproductive cycle, which determines the profitability of herds. This study analysed the relationship between NEB and the time of resumption of reproductive activity in cows with varying genetic potential (Simmental and Holstein-Friesian), fed a similar diet (TMR). The aim of the study was to analyse the dependencies between NEB markers and changes in progesterone levels between 25 and 31 days postpartum. A strong positive correlation was shown between daily milk production (DMP) and loss of body condition (LBCS; 0.772; p ≤ 0.05). These parameters were associated with the levels of NEB biomarkers. Higher values of NEB indicators (LBCS, C16:0, C18:1, NEFA, and BHBA) were usually noted during periods with higher DMP (II and III). The trends observed were confirmed by positive correlation coefficients (r), which ranged from 0.324 to 0.810 (p ≤ 0.05). The reverse trend was noted for glucose and leptin, which decreased as productivity increased, as confirmed by r values from -0.368 to -0.530 (p ≤ 0.05). In both breeds, the glucose and leptin levels decreased as DMP increased. Higher values for NEB indicators were shown to be negatively correlated with progesterone levels (r from -0.300 to -0.712; p ≤ 0.05), and a lower progesterone level was associated with a longer calving-to-first-service interval and calving-to-conception interval. The rate of postpartum triglyceride release depends on daily milk production, and therefore the adaptability of the liver should be considered an important element of mitigation of the consequences of NEB. This may have practical applications by extending productive life, which is often shortened due to deteriorating reproductive performance.

Breeding objectives for dairy cattle under low, medium and high production systems in the tropics

A deterministic bio-economic model was developed to estimate economic weights for genetic improvement of lactation milk yield, fat yield, age at first calving, calving interval, mature weight and survival under low, medium and high production systems in the Tropics. Input parameters were obtained from dairy production systems in Kenya which has a tropical environment. The highest proportion of revenue is from the sale of milk followed by sale of heifers, cull cows and sale of male calves under all production systems. On the other hand, feed cost is the most important production cost followed by labour, marketing, reproduction and health costs, respectively. Economic values for the six traits were derived from a profit equation using revenue and production costs per cow per year. The economic values were then discounted using diffusion coefficients which account for differences between traits in the time when the improvement is expressed. Economic weights were robust to changes in input and output prices, changes in feeding strategies, and changes in milk and surplus heifer marketing strategies. Genetic standard deviations were multiplied by economic values to standardise the economic value of traits and to compare their potential for economic response. When expressed as proportion of their sum, these relative economic weights under the low, medium and high production systems for lactation milk yield were 51.36, 59.79 and 63.98%; for fat yield 4.50, 10.69 and 9.05%; for age at first calving 3.16, 2.66 and 0.55%; for calving interval 33.59, 19.88 and 20.05%; for mature weight 1.55, 1.34 and 1.19% and for survival rate 5.84, 5.64 and 5.18%, respectively. The predicted responses followed the same pattern as the relative economic weights. This shows that milk yield and calving interval were most important in all production systems but the value of response for traits differed between production systems with more emphasis on milk yield and less on calving interval in the high production systems. Moderate correlations were estimated between the breeding objective for the low, medium and high production systems. To maximise response in the overall breeding objective, different selection criteria are required for the three production systems.

Factors affecting calving to conception interval (days open) in dairy cows located at Dessie and Kombolcha towns, Ethiopia

This study was aimed at determining the median days of calving to conception interval (days open) and identifying the major risk factors determining the days open in dairy cows. Both retrospective and longitudinal studies were conducted on dairy cows located in the Dessie and Kombolcha towns of South Wollo Zone, northeast Ethiopia from August 2019 to August 2020. The Kaplan-Meier model of survival analysis was used to determine the median days open and compare the survival distribution of each level of explanatory variables likely to influence the days open of dairy cows. Accordingly, the overall conception rate of dairy cows was 44.7%. The median days open in the study was 154 days. There is a 16% probability of surviving (i.e, the probability that the conception event has not yet occurred) at the end of 210 days postpartum period. The Cox proportional hazard model was used to quantify the effect of each of the explanatory variables on the days open in the first 210 days postpartum. Factors that had a significant effect (p<0.05) on the calving to conception interval were the season of insemination, breeding system, calving to insemination interval, and herd milk yield level. However, the peripartum, postpartum disorders, and the town of the farm are not significant (p>0.05). Accordingly, cows inseminated in the autumn season (HR = 4.45), cows less than or equal to 85 days calving to insemination interval (HR = 2.41), artificially inseminated cows (HR = 1.45), and high herd milk yield cow had a higher probability of becoming pregnant. In conclusion, the management practices and breeding decisions seem to be important determinants to improve the conception rate or decrease the days open in dairy cows.

Effects of dietary starch content and body condition score at calving on reproductive parameters in Holstein dairy cows

Nutritional modifications can potentially impact the reproductive performance and ultimately the economic results of dairy herds. The objectives were to investigate the effects of feeding a high starch (HS) diet and body condition score (BCS) at calving on reproductive responses and uterine health in Holstein dairy cows. One hundred seventy-four multiparous cows were randomly assigned to 1 of 2 experimental diets from 16 until 50 days in milk (DIM; n = 87 per group); normal starch (228 g/kg diet DM; NS) or high starch (270 g/kg diet DM; HS) diets. Each dietary treatment group was further subdivided based on BCS at calving as normal BCS (BCS ≤ 3.5; NBCS; n = 45) and high BCS (BCS ≥ 3.75; HBCS; n = 42). Transrectal ultrasonography was carried out at 10 DIM, and thereafter twice weekly until the onset of ovarian cyclicity or d 50 DIM. Feeding HS diet significantly affected the proportion of cows cycling by 30 and 40 DIM. Number of services per conception and calving interval (CI) were significantly improved in cows fed the HS compared to the NS diet (2.08 vs. 2.51 and 427.14 vs. 445.30 days for cows fed HS and NS diets, respectively). In summary, feeding higher starch diets from 16 till 50 DIM could be an effective strategy to improve the economic variables related to reproduction in dairy cows.

Economic impact of different strategies to use sex-sorted sperm for reproductive management in seasonal-calving, pasture-based dairy herds

To maximize efficiency, profitability, and societal acceptance of modern dairy production, it is important to minimize the production of male dairy calves with poor beef merit. One solution involves using sex-sorted sperm (SS) to generate dairy replacements and breeding all other cows to an easy-calving, short-gestation bull with good beef merit. We used the Pasture Based Herd Dynamic Milk Model to investigate the effect of herd fertility and use of SS on farm net profit in a herd of 100 cows. This was completed by simulating herds with differing fertility performance (good, average, poor), and differing farm reproductive management [conventional semen (CONV) or SS with varying pregnancy per artificial insemination (P/AI) relative to CONV (i.e., relative P/AI 100%, 85%, and 70%)]. As an additional consideration, the method of allocating SS to cows was also examined. The first option used SS on random heifers and cows (S). The second option used SS on heifers and targeted high-fertility cows (S_Sel). The final option was similar to S_Sel, but used a fixed-time artificial insemination (AI) protocol to facilitate AI on the farm mating start date (S_Sync). For CONV, dairy breed semen was used for AI until 50 animals were pregnant (50% chance of a female calf), whereas for S, S_Sel, or S_Sync the target number of animals successfully conceiving with SS was set at 28 (based on assumed 90% chance of a female calf from pregnancies derived from SS). Beef breed semen was used on all other dams. The results indicated that the biggest effect on farm net profit was not based on whether or not SS was used, but instead was most affected by the overall fertility performance of the herd. Total farm profit decreased by 10% between the good and average fertility herds, and decreased by a further 12% between the average and poor fertility herds. In almost all situations, when the relative P/AI with SS was ≥85%, use of SS led to an overall increase of the farm net profit. There was an economic benefit of using either S_Sel or S_Sync compared with S for the average and poor fertility herds but not for the good fertility herd, highlighting an interaction between SS P/AI and overall herd fertility as well as management practices. If the relative P/AI with SS was <70%, the use of SS led to a decrease in profitability in all simulations except for S_Sync, highlighting the importance of a good management strategy for use of SS. The findings in this study indicated that SS has significant potential to help facilitate greater integration between the dairy and beef production sectors, as well as increase farm profitability when used appropriately.

Risk Factors for the Efficiency of Artificial Insemination in Dairy Cows and Economic Impact of Failure of First Service Insemination in and around Haramaya Town, Oromia Region, Eastern Ethiopia

A cross-sectional study was conducted from November 2019 to May 2020 in and around Haramaya Town to study the risk factors of artificial insemination (AI) in dairy cattle and evaluate the economic impact of failure of first service AI. A questionnaire survey and field follow-up were employed for collecting data from cattle owners and artificial insemination technicians (AITs) who were selected purposively. Out of the 221 inseminated cows and heifers, the overall conception rate was 60.2% (n = 133). The conception rate was statistically different between breed (P=0.019) and insemination time (P=0.049). From a total of 133 conceived cows and heifers, the conception rate was 68 (53.54%) in local breeds and 65 (69.15%) in cross breeds. Parity, age of cows, inseminator experience, and body condition of cows did not create a significant difference in conception rate (P > 0.05). Failure to conceive at their first AI results in an extra cost of 440 ETB per day until conception. Therefore, to increase the conception rate, dairy cows should be inseminated early when they show signs of estrous; the owners of dairy cows should be trained on how to detect estrous signs in dairy cows and AI technicians should also take training in order to improve their skills.

Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models

Background

The effect of heat stress on livestock production is a worldwide issue. Animal performance is influenced by exposure to harsh environmental conditions potentially causing genotype-by-environment interactions (G × E), especially in highproducing animals. In this context, the main objectives of this study were to (1) detect the time periods in which heifer fertility traits are more sensitive to the exposure to high environmental temperature and/or humidity, (2) investigate G × E due to heat stress in heifer fertility traits, and, (3) identify genomic regions associated with heifer fertility and heat tolerance in Holstein cattle.

Results

Phenotypic records for three heifer fertility traits (i.e., age at first calving, interval from first to last service, and conception rate at the first service) were collected, from 2005 to 2018, for 56,998 Holstein heifers raised in 15 herds in the Beijing area (China). By integrating environmental data, including hourly air temperature and relative humidity, the critical periods in which the heifers are more sensitive to heat stress were located in more than 30 days before the first service for age at first calving and interval from first to last service, or 10 days before and less than 60 days after the first service for conception rate. Using reaction norm models, significant G × E was detected for all three traits regarding both environmental gradients, proportion of days exceeding heat threshold, and minimum temperature-humidity index. Through single-step genome-wide association studies, PLAG1, AMHR2, SP1, KRT8, KRT18, MLH1, and EOMES were suggested as candidate genes for heifer fertility. The genes HCRTR1, AGRP, PC, and GUCY1B1 are strong candidates for association with heat tolerance.

Conclusions

The critical periods in which the reproductive performance of heifers is more sensitive to heat stress are trait-dependent. Thus, detailed analysis should be conducted to determine this particular period for other fertility traits. The considerable magnitude of G × E and sire re-ranking indicates the necessity to consider G × E in dairy cattle breeding schemes. This will enable selection of more heat-tolerant animals with high reproductive efficiency under harsh climatic conditions. Lastly, the candidate genes identified to be linked with response to heat stress provide a better understanding of the underlying biological mechanisms of heat tolerance in dairy cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07496-3.

A large-scale study on the effect of age at first calving, dam parity, and birth and calving month on first-lactation milk yield in Holstein Friesian dairy cattle

Milk yield during first lactation is an important economical trait. Age at first calving (AFC) is considered an important predictor of subsequent milk yield. In addition, both season of birth, as well as season of calving, have been shown to influence milk production, with conflicting results. Finally, higher parity of the dam has been associated with a lower performance of the offspring. The aim of the present study was to assess the effect of the above-mentioned factors based on a large-scale study and to rank the most important determinants for first-lactation milk yield. Data on 3,810,678 Holstein Friesian heifers, born in Belgium and the Netherlands between 2000 and 2015, were provided by Cooperative CRV and CRV BV (Arnhem, the Netherlands) and consisted of birth dates, calving dates, and first-lactation productions. In addition, herd, sire, and dam information was provided. Linear regression models were built with herd-calving year and sire as random effects and 305-d energy-corrected milk (ECM) yield during first lactation as outcome variable. Birth month, calving month, parity of the dam, and AFC were included as fixed effects in the model and a dominance analysis was performed to rank the associated factors according to importance. Results revealed AFC to be the most important factor (R² = 0.047), with an increase in ECM up to an age of 33 mo. Calving month was a more important predictor than birth month (R² = 0.010 vs. R² = 0.002, respectively), with the highest first-lactation production in heifers calving in October to December, and the lowest in heifers calving in June and July. Birth month had a limited effect on first-lactation milk yield (R² = 0.002), potentially masked by rearing strategies during early life. Finally, parity of the dam ≥3 was associated with a reduced ECM of the offspring (R² = 0.002). In conclusion, our results show AFC to be an important determinant of milk yield during first lactation. In addition, seasonal patterns in milk production are seen, which should be further explored to identify the underlying mechanism.

Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems

High-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and management decisions in livestock operations. One of the most relevant tools used in the dairy and beef industry to predict complex traits is infrared spectrometry, which is based on the analysis of the interaction between electromagnetic radiation and matter. The infrared electromagnetic radiation spans an enormous range of wavelengths and frequencies known as the electromagnetic spectrum. The spectrum is divided into different regions, with near- and mid-infrared regions being the main spectral regions used in livestock applications. The advantage of using infrared spectrometry includes speed, non-destructive measurement, and great potential for on-line analysis. This paper aims to review the use of mid- and near-infrared spectrometry techniques as tools to predict complex dairy and beef phenotypes, such as milk composition, feed efficiency, methane emission, fertility, energy balance, health status, and meat quality traits. Although several research studies have used these technologies to predict a wide range of phenotypes, most of them are based on Partial Least Squares (PLS) and did not considered other machine learning (ML) techniques to improve prediction quality. Therefore, we will discuss the role of analytical methods employed on spectral data to improve the predictive ability for complex traits in livestock operations. Furthermore, we will discuss different approaches to reduce data dimensionality and the impact of validation strategies on predictive quality.

Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle

We investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model.

The Effect of Abnormal Reproductive Tract Discharge on the Calving to Conception Interval of Dairy Cows

Prolonged calving-to-conception interval (CCI) can increase economic loss in cattle. We investigated the effect of post-calving abnormal reproductive tract discharge (ARTD) on CCI in dairy cows and quantified the relationship of ARTD and associated risk factors with CCI. The source population was dairy cows that calved in the study period on three pasture-based, year-round calving farms in the Riverina, NSW, Australia. Farm records and records from veterinarians' visits were analyzed. ARTD was defined as the presence of reproductive tract discharge according to the following classification: per vaginum purulent discharge ≥21 days post-calving or mucopurulent discharge >26 days post-calving. The incidence of ARTD was calculated. A Kaplan-Meier survivor function was used to estimate median time to conception post-calving dependent on the presence or absence of ARTD. Mixed effects Cox-proportional hazard models were used to estimate the direct and indirect effects of ARTD, and other potential risk factors on CCI such as body condition score (BCS), ambient temperature, and milk yield. Model structures were guided by a directed acyclic graph of potential risk factors for ARTD. The incidence of ARTD in lactations was 16% (95% CI 13.8–18.5%) and did not differ significantly between the three farms (P > 0.05). The median CCI was 176 and 118 days for lactations with and without ARTD, respectively (P < 0.01). The rate of pregnancy following calving in cows with ARTD was significantly decreased relative to the rate of pregnancy in cows without (total effect hazard ratio = 0.62, se = 0.18, P = 0.01). High peak milk yield (>32 L) and parity >2 also significantly extended CCI. We did not observe an effect of BCS or ambient temperature on CCI. The incidence of ARTD in the current study was consistent with clinical endometritis (considered a major source of ARTD) reported in other studies. In contrast—and despite regular veterinary assessment and treatment of on the farms in this study—ARTD extended CCI. Evaluation of the economic impact of ARTD on dairy farms in this region is warranted, and methods to identify high risk cows and develop effective interventions are required.

Genotype by environment interaction for female fertility traits under conventional and organic production systems in Danish Holsteins

Conventional and organic production systems mainly differ in feeding strategies, outdoor and pasture access, and the use of antibiotic treatments. These environmental differences could lead to a genotype by environment interaction (G × E) and a requirement for including G × E in breeding decisions. The objectives of this study were to estimate variance components and heritabilities for conventional and organic production systems and investigate G × E under these 2 production systems for female fertility traits in Danish Holsteins. The analyzed traits included the interval from calving to first insemination (ICF), the interval from first to last insemination, number of inseminations per conception (NINS), and non-return rate within 56 d after the first insemination. Records of female fertility in heifers and the first 3 lactations in cows as well as grass ratio of feed at herd level were collected during the period from 2011 to 2016. The performances of a trait in heifers and cows (lactation 1 to 3) were considered as different traits. The (co)variance components and the resulting heritabilities and genetic correlations were estimated using 2 models. One was a bivariate model treating performances of a trait under organic and conventional production systems as 2 different traits using a reduced data set, and the other was a reaction norm model with random regression on the production system and the grass ratio of feed using a full data set. The full data set comprised records of 37,836 females from 112 organic herds and 513,599 females from 1,224 conventional herds, whereas the reduced data set comprised records from all these 112 organic herds and 92,696 females from 185 convention herds extracted from the full data set with grass ratio of feed lower than 0.20. All female fertility performances of the organic production system were superior to those of the conventional production system. Besides, heterogeneities in additive genetic variances and heritabilities were observed between conventional and organic production systems for all traits. Furthermore, genetic correlations between these 2 production systems ranged from 0.607 to 1.000 estimated from bivariate models and from 0.848 to 0.999 estimated from reaction norm models. Statistically significant G × E were observed for NINS in heifers, non-return rate within 56 d after the first insemination in heifers, and ICF from the bivariate model, and for ICF and NINS in cows from the reaction norm model.

Analysis of a large dataset reveals haplotypes carrying putatively recessive lethal and semi-lethal alleles with pleiotropic effects on economically important traits in beef cattle

BACKGROUND

In livestock, deleterious recessive alleles can result in reduced economic performance of homozygous individuals in multiple ways, e.g. early embryonic death, death soon after birth, or semi-lethality with incomplete penetrance causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced conception rates, longer calving intervals, or lower survival for live born animals.

METHODS

In this paper, we searched for haplotypes that carry putatively recessive lethal or semi-lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. Then, we associated the identified haplotypes with 44,351 insemination records that indicated early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on estimates of breeding value for 15 economically important traits in beef production.

RESULTS

We found support for one haplotype that carries a putatively recessive lethal (chromosome 16 in Simmental) and two haplotypes that carry semi-lethal alleles (chromosome 14 in Aberdeen Angus and chromosome 19 in Charolais), with population frequencies of 8.8, 15.2, and 14.4%, respectively. These three haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are €2.30, €3.42, and €1.47 for the terminal index and €1.03, - €3.11, and - €0.88 for the replacement index, where the standard deviations for the terminal index are €22.52, €18.65, and €22.70 and for the replacement index they are €31.35, €29.82, and €35.79. We identified ZFAT as the candidate gene for semi-lethality in Aberdeen Angus, several candidate genes for the lethal Simmental haplotype, and no candidate genes for the semi-lethal Charolais haplotype.

CONCLUSIONS

We analysed genotype, reproduction, survival, and production data to detect haplotypes that carry putatively recessive lethal or semi-lethal alleles in Irish beef cattle and identified one lethal and two semi-lethal haplotypes, which have pleiotropic effects on economically important traits in beef production.

Risk factors limiting first service conception rate in dairy cows and their economic impact

OBJECTIVE

We determined the risk factors limiting first service conception (FSC) rate in dairy cows and their economic impact.

METHODS

Data were collected from 790 lactations regarding cow parity, peri- and postpartum disorders, body condition score (BCS), reproductive performance, and expenses associated with reproductive management (treatment, culling, and others). Initially, we identified the risk factors limiting FSC rate in dairy cows. Various biological and environmental factors, such as herd, cow parity, BCS at 1 month postpartum and first artificial insemination (AI), resumption of cyclicity within 1 month of calving, year, AI season, insemination at detected estrus or timed AI, peri- and postpartum disorders, and calving to first AI interval, were evaluated. Next, we evaluated the economic impact of the success or failure of FSC by comparing the expense associated with reproductive management until conception between cows that did or did not conceive at their first service.

RESULTS

Cows with BCS <3.0 had a lower probability of conceiving at first insemination (odds ratio [OR] = 0.64, p<0.05) than cows with BCS ≥3.0. Cows inseminated during summer were less likely to conceive (OR = 0.44, p<0.001) than cows inseminated during spring. Cows with peri- or postpartum disorders were less likely to conceive (OR = 0.55, p<0.001) than cows without disorders. Survival curves generated using MedCalc showed an 81 day extension in the mean interval between calving and conception in cows that failed to conceive over those that did conceive at first insemination. Cows failing conceive required additional expenditure on reproductive treatment ($55.40) and other management ($567.00) than cows that conceived at first insemination.

CONCLUSION

Lower BCS, hot weather at first insemination, and peri- and postpartum disorders are risk factors limiting FSC, which result in an economic loss of $622.40 per dairy cow.

A cost-benefit analysis and the potential trade effects of the bovine viral diarrhoea eradication programme in Styria, Austria

This study evaluated the voluntary and compulsory implementation of a bovine viral diarrhoea virus (BVDV) eradication programme in the Austrian Federal State of Styria, Austria, from an economic point of view using ex-post assessment of costs and benefits (disease losses avoided). An economic net benefit (benefit:cost ratio, BCR=1.18) of the programme was demonstrated during the voluntary programme phase (January 1998-July 2004). The break-even point was reached in 2003. If investments in the compulsory programme (August 2004-December 2016) were taken into account, a net economic loss (BCR=0.16) was demonstrated. In contrast to on-going annual testing of all cattle herds, annual testing in accordance with a revised sampling scheme could reduce total surveillance costs by more than 77%. A Bayesian structural time series model was applied to analyse a hypothesised positive impact of the compulsory BVDV programme on the Styrian cattle export market. The average number of exported cows and bulls increased significantly by 42% (P=0.03) and 47% (P=0.01), respectively, and the producer price increased by 14% (P=0.00) and 5% (P=0.16), respectively, during the compulsory programme period compared with the period prior to intervention. This equates to an average revenue increase of €29,754 for cows and €137,563 for bulls per month. These results justify the implementation of eradication programmes, which initially may not appear to be economically viable, particularly if trade effects are not included in the calculations.

Joint estimation of (co) variance components and breeding values for mean and dispersion of days from calving to first service in Holstein cow

The present study explored the possibility of selection for uniformity of days from calving to first service (DFS) in dairy cattle. A double hierarchical generalised linear model with an iterative reweighted least-squares algorithm was used to estimate covariance components for the mean and dispersion of DFS. Data included the records of 27 113 Iranian Holstein cows (parity, 1–6) in 15 herds from 1981 to 2007. The estimated additive genetic variance for the mean and dispersion were 32.25 and 0.0139; both of these values had low standard errors. The genetic standard deviation for dispersion of DFS was 0.117, indicating that decreasing the estimated breeding value of dispersion by one genetic standard deviation can increase the uniformity by 12%. A strong positive genetic correlation (0.689) was obtained between the mean and dispersion of DFS. This genetic correlation is favourable since one of the aims of breeding is to simultaneously decrease the mean and increase the uniformity of DFS. The Spearman rank correlations between estimated breeding values in the mean and dispersion for sires with a different number of daughter observations were 0.907. In the studied population, the genetic trend in the mean of DFS was significant and favourable (–0.063 days/year), but the genetic trend in the dispersion of DFS was not significantly different from zero. The results obtained in the present study indicated that the mean and uniformity of DFS can simultaneously be improved in dairy cows.

Application of classification trees in determining the impact of phenotypic factors on conception to first service in Holstein cattle

The aim of the study was to evaluate the impact of phenotypic factors on the probability of conception to first service. The study analysed 49 317 lactation records gathered between 1995 and 2007 in Iran, detailing six consecutive lactations in 13 herds of Holstein cows. The impact of phenotypic factors on the conception to first service was evaluated using the classification tree technique. The CHAID algorithm with the Pearson Chi-squared test was used as the division criterion. The resulting tree was six levels deep and consisted of 22 leaves. The greatest divisions in the tree occurred based on the year of calving (five divisions), herd and parity (four divisions each), level of milk production and age at calving (three divisions each). Fewer divisions occurred based on the month when the first insemination was performed (two divisions). The tree structure obtained in the present study allowed identification of combinations of levels of factors associated with highest probabilities of conception. The highest rate of conception to first service was recorded for cows that: while calving were younger than 5 years old; were in herds 2, 4, 5, 7, 8, 12 and 14; and were inseminated in January, February, March, April, May and November. Those cows were at least in their third lactation.

Improving the reliability of female fertility breeding values using type and milk yield traits that predict energy status in Australian Holstein cattle

The objectives of this study were (1) to propose changing the selection criteria trait for evaluating fertility in Australia from calving interval to conception rate at d 42 after the beginning of the mating season and (2) to use type traits as early fertility predictors, to increase the reliability of estimated breeding values for fertility. The breeding goal in Australia is conception within 6 wk of the start of the mating season. Currently, the Australian model to predict fertility breeding values (expressed as a linear transformation of calving interval) is a multitrait model that includes calving interval (CVI), lactation length (LL), calving to first service (CFS), first nonreturn rate (FNRR), and conception rate. However, CVI has a lower genetic correlation with the breeding goal (conception within 6 wk of the start of the mating season) than conception rate. Milk yield, type, and fertility data from 164,318 cow sired by 4,766 bulls were used. Principal component analysis and genetic correlation estimates between type and fertility traits were used to select type traits that could subsequently be used in a multitrait analysis. Angularity, foot angle, and pin set were chosen as type traits to include in an index with the traits that are included in the multitrait fertility model: CVI, LL, CFS, FNRR, and conception rate at d 42 (CR42). An index with these 8 traits is expected to achieve an average bull first proof reliability of 0.60 on the breeding objective (conception within 6 wk of the start of the mating season) compared with reliabilities of 0.39 and 0.45 for CR42 only or the current 5-trait Australian model. Subsequently, we used the first eigenvector of a principal component analysis with udder texture, bone quality, angularity, and body condition score to calculate an energy status indicator trait. The inclusion of the energy status indicator trait composite in a multitrait index with CVI, LL, CFS, FNRR, and CR42 achieved a 12-point increase in fertility breeding value reliability (i.e., increased by 30%; up to 0.72 points of reliability), whereas a lower increase in reliability (4 points, i.e., increased by 10%) was obtained by including angularity, foot angle, and pin set in the index. In situations when a limited number of daughters have been phenotyped for CR42, including type data for sires increased reliabilities compared with when type data were omitted. However, sires with more than 80 daughters with CR42 records achieved reliability estimates close to 80% on average, and there did not appear to be a benefit from having daughters with type records. The cost of phenotyping to obtain such reliabilities (assuming a cost of AU$14 per cow with type data and AU$5 per cow with pregnancy diagnosed) is lower if more pregnancy data are collected in preference to type data. That is, efforts to increase the reliability of fertility EBV are most cost effective when directed at obtaining a larger number of pregnancy tests.

Estimation of genetic parameters of fertility traits in Chinese Holstein cattle

Guo, G., Guo, X., Wang, Y., Zhang, X., Zhang, S., Li, X., Liu, L., Shi, W., Usman, T., Wang, X., Du, L. and Zhang, Q. 2014. Estimation of genetic parameters of fertility traits in Chinese Holstein cattle. Can. J. Anim. Sci. 94: 281–285. The objective of this study was to estimate genetic parameters for fertility traits in Chinese Holstein heifers and cows. Data of 20169 animals with 42106 records over a period of 10 yr (2001–2010) were collected from Sanyuan Lvhe Dairy Cattle Center in Beijing, China. Traits included age at first service (AFS), number of services (NS), days from calving to first service (CTFS), days open (DO), and calving interval (CI). Genetic parameters were estimated with multiple-trait animal model using the DMU software. Heritability estimates for AFS, NS, CTFS, DO and CI were 0.100±0.012, 0.040±0.017, 0.034±0.011, 0.053±0.019 and 0.056±0.014, respectively. Genetic correlations between traits observed ranged from −0.13 to 0.99. Genetic correlations between AFS with NS, CTFS, DO and CI were −0.31, 0.15, −0.13 and −0.15, respectively. Calving interval was strongly correlated with NS, CTFS and DO (0.49–0.99), and DO showed strong correlation with NS and CTFS (0.49 and 0.58, respectively). The genetic correlation between CTFS and NS was negative moderate (−0.25). Results were in range with previous literature estimates and can be used in Chinese Holstein genetic evaluation for fertility traits.

Reaction norm of fertility traits adjusted for protein and fat production level across lactations in Holstein cattle

A total of 304,001 artificial insemination outcomes in up to 7 lactations from 142,389 Holstein cows, daughters of 5,349 sires and 101,433 dams, calving between January 1995 and December 2007 in 1,347 herds were studied by a reaction norm model. The (co)variance components for days to first service (DFS), days open, nonreturn rate in the first service (NRFS), and number of services per conception were estimated by 6 models: 3 Legendre polynomial degrees for the genetic effects and adjustment or not for the level of fat plus protein (FP) production recorded at day closest to DFS. For all traits and type of FP adjustment, a second degree polynomial showed the best fit. The use of the adjusted FP model did not increase the level of genetic (co)variance components except for DFS. The heritability for each of the traits was low in general (0.03-0.10) and increased from the first to fourth calving; nevertheless, very important variability was found for the estimated breeding value (EBV) of the sires. The genetic correlations (rg) were close to unity between adjacent calvings, but decreased for most distant parities, ranging from rg=0.36 (for DFS) to rg=0.63 (for NRFS), confirming the existence of heterogeneous genetic (co)variance components and EBV across lactations. The results of the eigen decomposition of rg shows that the first eigenvalue explained between 82 to 92% and the second between 8 to 14% of the genetic variance for all traits; therefore, a deformation of the overall mean trajectory for reproductive performance across the trajectory of the different calving could be expected if selection favored these eigenfunctions. The results of EBV for the 50 best sires showed a substantial reranking and variation in the shape of response across lactations. The more important aspect to highlight, however, is the difference between the EBV of the same sires in different calvings, a characteristic known as plasticity, which is particularly important for DFS and NRFS. This component of fertility adds another dimension to selection for fertility that can be used to change the negative genetic progress of reproductive performance presented in this population of Holstein cows. The use of a reaction norm model should allow producers to obtain more robust cows for maintenance of fertility levels along the whole productive life of the cows.

Trans-generational effect of maternal lactation during pregnancy: a Holstein cow model

Epigenetic regulation in mammals begins in the first stages of embryogenesis. This prenatal programming determines, in part, phenotype expression in adult life. Some species, particularly dairy cattle, are conceived during the maternal lactation, which is a period of large energy and nutrient needs. Under these circumstances, embryo and fetal development compete for nutrients with the mammary gland, which may affect prenatal programming and predetermine phenotype at adulthood. Data from a specialized dairy breed were used to determine the transgenerational effect when embryo development coincides with maternal lactation. Longitudinal phenotypic data for milk yield (kg), ratio of fat-protein content in milk during first lactation, and lifespan (d) from 40,065 cows were adjusted for environmental and genetic effects using a Bayesian framework. Then, the effect of different maternal circumstances was determined on the residuals. The maternal-related circumstances were 1) presence of lactation, 2) maternal milk yield level, and 3) occurrence of mastitis during embryogenesis. Females born to mothers that were lactating while pregnant produced 52 kg (MonteCarlo standard error; MCs.e. = 0.009) less milk, lived 16 d (MCs.e. = 0.002) shorter and were metabolically less efficient (+0.42% milk fat/protein ratio; MCs.e.<0.001) than females whose fetal life developed in the absence of maternal lactation. The greater the maternal milk yield during embryogenesis, the larger the negative effects of prenatal programming, precluding the offspring born to the most productive cows to fully express their potential additive genetic merit during their adult life. Our data provide substantial evidence of transgenerational effect when pregnancy and lactation coincide. Although this effect is relatively low, it should not be ignored when formulating rations for lactating and pregnant cows. Furthermore, breeding, replacement, and management strategies should also take into account whether the individuals were conceived during maternal lactation because, otherwise, their performance may deviate from what it could be expected.

Comparison of artificial insemination and natural service cost effectiveness in dairy cattle

Reproductive efficiency in the dairy herd is the most important factor for its economic success and a major concern for dairy farmers when using artificial insemination (AI) or natural service (NS). Our objectives were to estimate, compare and analyse the costs associated with breeding cattle by do-it-yourself (DIY) AI and NS and identify the factors that influence them, under typical dairy farming conditions in Greece. A simulation study was designed based on data from 120 dairy cattle farms that differed in size (range 40 to 285 cows) and milk production level (4000 to 9300 kg per cow per year). Different scenarios were employed to estimate costs associated directly with AI and NS as well as potentially extended calving intervals (ECI) due to AI. Results showed that bull maintenance costs for NS were €1440 to €1670 per year ($1,820 to $2,111). Direct AI costs were higher than those for NS for farms with more than 30 cows and ECI constituted a considerable additional burden. In fact, amongst the factors that affected the amount of milk needed to cover total extra AI costs, number of days open was the dominant one. Semen, feed and heifer prices had a very small effect. When, hypothetically, use of NS bulls results in a calving interval of 12 months, AI daughters with a calving interval of 13.5 months have to produce about 705 kg of additional milk in order to cover the extra cost. Their actual milk production, however, exceeds this limit by more than 25%. When real calving intervals are considered (13.0 v. 13.7 months for NS and AI, respectively) AI daughters turn out to produce more than twice the additional amount of milk needed. It was concluded that even under less than average management conditions, AI is more profitable than the best NS scenario. The efficient communication of this message should be a primary concern of the AI industry.

Association between age at first calving, year and season of first calving and milk production in Holstein cows

The effects of first calving (FC) in Holstein heifers on their first lactation, second lactation and lifetime milk production were examined from an initial database of 459 743 animals that first calved between 1 January 1990 and 31 July 2010 in Wallonia, Belgium. The FC age class (18 to 22, 22 to 26, 26 to 30, 30 to 34, 34 to 38 and 38 to 42 months), the FC season and FC year class (1990 to 1994, 1995 to 1999, 2000 to 2004 and 2005 to 2010) were considered when analysing the first and second lactation data. Lifetime data were similarly analysed, but did not include animals that calved after 2005 because many of them were still lactating. Only 24% of animals had their FC before 26 months of age. Animals that first calved between 22 and 26 months of age had more lactations and productive days during their life. They also had higher first and second lactation milk production and lifetime milk production. Summer or autumn FC improved first lactation, second lactation and lifetime milk production, as well as production per day of lactation, compared with winter or spring FC. Compared with animals that calved for the first time in 1990 to 1994, animals with a FC in 2000 to 2004 had a longer calving interval (0.5 months), fewer lactations per animal (-0.6) and fewer days in their lifetime lactation (a reduction of 144 days). As a result, the animals' lifetime production did not increase between 1990 to 1994 and 2000 to 2004, although milk production per day of lactation (22.85 v. 20.49 l/day) and per day of life (11.49 v. 10.78 l/day) improved. Milk fat content was lower in 2000 to 2004 than in 1990 to 1994, but protein content remained relatively constant, probably because of the cows' higher production level and increased dietary concentrate supplementation.

Trends in the reproductive performance of Holstein dairy cows in Iran

The study was undertaken to determine the trends in the reproductive performance of Holstein dairy cows in Iran during 1994 to 2008. Reproductive performance data for 528,034 lactations of 246,132 cows in 1,822 Holstein dairy herds of Iran were used. The potential effect of calving season, herd, parity, calving year, as well as herd size and 305-day milk production on reproductive performance traits was investigated using multiple regression models. The least squares means of age at first calving decreased by 3.1 (± 0.06) days per year from 806.5 (± 96.3) days in 1994 to 788 (± 89.9) days in 2008. The least squares means of calving interval increased 1.02 (± 0.03) days per year from 394.1 (± 65) days in 1994 to 413.2 (± 81) days in 2008. Greater 305-day milk production was associated with an average increase of 6.55 (± 0.08) days in calving interval per 1,000-kg increase in milk yield. Larger herd size was associated with an average decrease of 0.22 (± 0.02) days in calving interval per 50 cows per herd. The mean number of days dry was 88.6 (± 51.3) days and increased by 0.82 (± 0.02) days per year. In conclusion, reproductive performance in Holstein dairy herds has generally decreased, whereas herd size and milk production have increased over time. Producers may make significant improvements in herd reproduction by reviewing management strategies including the sire selection, reproductive management, inseminator training and techniques, and improved estrous detection. Moreover, it may be advisable for the fertility traits to be included in the genetic selection indices to reduce the rate of reproductive decline.

Analysis of lactation shapes in extended lactations

In order to describe the temporal evolution of milk yield (MY) and composition in extended lactations, 21 658 lactations of Italian Holstein cows were analyzed. Six empirical mathematical models currently used to fit 305 standard lactations (Wood, Wilmink, Legendre, Ali and Schaeffer, quadratic and cubic splines) and one function developed specifically for extended lactations (a modification of the Dijkstra model) were tested to identify a suitable function for describing patterns until 1000 days in milk (DIM). Comparison was performed on individual patterns and on average curves grouped according to parity (primiparous and multiparous) and lactation length (standard ≤305 days, and extended from 600 to 1000 days). For average patterns, polynomial models showed better fitting performances when compared with the three or four parameters models. However, LEG and spline regression, showed poor prediction ability at the extremes of the lactation trajectory. The Ali and Schaeffer polynomial and Dijkstra function were effective in modelling average curves for MY and protein percentage, whereas a reduced fitting ability was observed for fat percentage and somatic cell score. When individual patterns were fitted, polynomial models outperformed nonlinear functions. No detectable differences were observed between standard and extended patterns in the initial phase of lactation, with similar values of peak production and time at peak. A considerable difference in persistency was observed between 200 and 305 DIM. Such a difference resulted in an estimated difference between standard and extended cycle of about 7 and 9 kg/day for daily yield at 305 DIM and of 463 and 677 kg of cumulated milk production at 305 DIM for the first- and second-parity groups, respectively. For first and later lactation animals, peak yield estimates were nearly 31 and 38 kg, respectively, and occurred at around 65 and 40 days. The asymptotic level of production was around 9 kg for multiparous cows, whereas the estimate was negative for first parity.

Short communication: A comparison between purebred Holstein and Brown Swiss × Holstein cows for milk production, somatic cell score, milking speed, and udder measurements in the first 3 lactations

Brown Swiss × Holstein (BS × HO) crossbred cows (n = 55) and purebred Holstein (HO) cows (n = 50) were compared for milk yield, fat and protein production, somatic cell score, milking speed, and udder measurements for the first 3 lactations. Cows from a designed experiment were housed in a freestall barn at the experimental station of the federal state of Saxony-Anhalt, Germany, and calved from July 2005 to August 2008. Best prediction was used to determine actual production for 305-d lactations from test-day observations. For the first 3 lactations, BS × HO cows and HO cows were not significantly different for milk yield, fat and protein production, or SCS. Average milking time was significantly longer for BS × HO cows than for HO cows for first, second, and third lactations by 35, 51, and 30s, respectively. Average milking speed expressed as average yield per minute was significantly lower for BS × HO cows than for HO cows for the first 3 lactations by 0.19, 0.35, and 0.19 kg/min, respectively. Front and rear teats were significantly longer for BS × HO cows than for HO cows. Furthermore, front and rear udder clearance was significantly lower for BS × HO cows compared with HO cows in first and second lactations.

Genetic analysis of days from calving to first insemination and days open in Danish Holsteins using different models and censoring scenarios

The objectives of this study were to estimate genetic parameters and evaluate models for genetic evaluation of days from calving to first insemination (ICF) and days open (DO). Data including 509,512 first-parity records of Danish Holstein cows were analyzed using 5 alternative sire models that dealt with censored records in different ways: 1) a conventional linear model (LM) in which a penalty of 21 d was added to censored records; 2) a bivariate threshold-linear model (TLM), which included a threshold model for censoring status (0, 1) of the observations, and a linear model for ICF or DO without any penalty on censored records; 3) a right-censored linear model (CLM); 4) a Weibull proportional hazard model (SMW); and 5) a Cox proportional hazard model (SMC) constructed with piecewise constant baseline hazard function. The variance components for ICF and DO estimated from LM and TLM were similar, whereas CLM gave higher estimates of both additive genetic and residual components. Estimates of heritability from models LM, TLM, and CLM were very similar (0.102 to 0.108 for ICF, and 0.066 to 0.069 for DO). Heritabilities estimated using model SMW were 0.213 for ICF and 0.121 for DO in logarithmic scale. Using SMC, the estimates of heritability, defined as the log-hazard proportional factor for ICF and DO, were 0.013 and 0.009, respectively. Correlations between predicted transmitting ability from different models for sires with records from at least 20 daughters were far from unity, indicating that different models could lead to different rankings. The largest reranking was found between SMW and SMC, whereas negligible reranking was found among LM, TLM, and CLM. The 5 models were evaluated by comparing correlations between predicted transmitting ability from different data sets (the whole data set and 2 subsets, each containing half of the whole data set), for sires with records from at least 20 daughters, and chi(2) statistics based on predicted and observed daughter frequencies using a cross validation. The model comparisons showed that SMC had the best performance in predicting breeding values of the 2 traits. No significant difference was found among models LM, TLM, and CLM. The SMW model had a relatively poor performance, probably because the data are far from a Weibull distribution. The results from the present study suggest that SMC could be a good alternative for predicting breeding values of ICF and DO in the Danish Holstein population.

Trends in calving ages and calving intervals for Iranian Holsteins in Fars province, southern Iran

PURPOSE

To determine trends in calving ages and calving interval as measures of reproductive performance in Iranian Holsteins in Fars province, southern Iran during 2000-2005.

METHODS

Data about birth dates and previous calving dates for cows which calved between 21 March 2004 to 20 March 2005 were retrieved from the database of the Agricultural Jihad Organization of the province. Overall, calving records for 1134 cows from 12 herds during 2000-2005 were included in the statistical models.

RESULTS

Mean calving interval was 435 days in 2000 and declined significantly to 389 days during the study period (P < 0.001). Age at first calving decreased significantly from 30 months in 2000 to 26 months in 2005 (P < 0.001). The corresponding measures for age at second calving were 44 and 41 months, respectively (P = 0.003). Cows which calved during warm months had significantly (P < 0.001) higher calving interval (420 days) compared with calving in cold months (411 days). No significant effect for parity on calving interval was observed in this study.

CONCLUSIONS

Reproductive performance revealed relatively positive trend in the Iranian Holsteins in Fars province. This could be attributed to better management and nutrition practices during this period and also to the fact that large genetic trend for milk which has been observed in countries with decreasing reproductive performance has not occurred in these herds yet.

The association between reproductive performance and milk yield in Chilean Holstein cattle

The objective of this study was to evaluate the relationship between reproductive performance and milk yield in central-southern Chilean Holstein cattle that calved from 1990 to 2003. The analysis included 150,457 lactations obtained from a certified recording system. Reproductive indexes included in the study were calving interval (CI, d), calving to first service interval (CFSI, d), calving to conception interval (CCI, d), services per conception (SC), and conception rate at first service (CRFS). Survival analysis for the risk of pregnancy was also conducted. Models for reproductive indexes were significant and included, as independent variables, year and season of parturition, parity, length of dry period, milk and fat production standardized to 305 d, herd size, and herd. In 1990 and 2003, respectively, means +/- SEM for CI were 399 +/- 1.6 and 415 +/- 1.1 d; for CFSI were 85 +/- 0.6 and 97 +/- 0.6 d; for CCI were 124 +/- 1.3 d and 137 +/- 1 d; and for SC were 1.6 +/- 0.02 and 1.7 +/- 0.01. For every 100 kg of 305-d standardized milk yield, the CCI increased by 0.6 d and CRFS decreased by 0.9%. Association between milk yield and the risk of pregnancy was almost zero when a Cox proportional regression model was conducted (hazard ratio = 1.005; 95% confidence interval = 1.002 to 1.008). We conclude that CCI has increased over time and is related negatively to the increase in milk yield experienced by central-southern Chilean Holstein cattle during the last 15 yr. Nevertheless, risk of pregnancy was not explained by the individual level of standardized 305-d milk yield of cows studied.

Inbreeding depression on female fertility and calving ease in Spanish dairy cattle

Inbreeding depression on female fertility and calving ease in Spanish dairy cattle was studied by the traditional inbreeding coefficient (F) and an alternative measurement indicating the inbreeding rate (DeltaF) for each animal. Data included records from 49,497 and 62,134 cows for fertility and calving ease, respectively. Both inbreeding measurements were included separately in the routine genetic evaluation models for number of insemination to conception (sequential threshold animal model) and calving ease (sire-maternal grandsire threshold model). The F was included in the model as a categorical effect, whereas DeltaF was included as a linear covariate. Inbred cows showed impaired fertility and tended to have more difficult calvings than low or noninbred cows. Pregnancy rate decreased by 1.68% on average for cows with F from 6.25 to 12.5%. This amount of inbreeding, however, did not seem to increase dystocia incidence. Inbreeding depression was larger for F greater than 12.5%. Cows with F greater than 25% had lower pregnancy rate and higher dystocia rate (-6.37 and 1.67%, respectively) than low or noninbred cows. The DeltaF had a significant effect on female fertility. A DeltaF = 0.01, corresponding to an inbreeding coefficient of 5.62% for the average equivalent generations in the data used (5.68), lowered pregnancy rate by 1.5%. However, the posterior estimate for the effect of DeltaF on calving ease was not significantly different from zero. Although similar patterns were found with both F and DeltaF, the latter detected a lowered pregnancy rate at an equivalent F, probably because it may consider the known depth of the pedigree. The inbreeding rate might be an alternative choice to measure inbreeding depression.