Analysis of Fertility and Dystocia in Holsteins Using Recursive Models to Handle Censored and Categorical Data

Roadmap to Dystocia Management-Guiding Obstetric Interventions in Cattle

Dystocia, or difficult labor, is a common complication during parturition in cattle that poses substantial risks to both dam and fetus. When the incidence is high on a farm level, it is a significant economic burden for dairy and beef enterprises. This review paper presents a comprehensive roadmap strategy to enhance decision-making in the management of dystocia in cows. The strategy encompasses early recognition and assessment, utilization of advanced diagnostic tools, and a range of medical and surgical interventions tailored to specific maternal and fetal causes of dystocia. The roadmap also integrates preventive measures to reduce the incidence of dystocia through genetic selection and optimized nutrition. By addressing the key challenges in dystocia management, such as resource constraints, timely intervention, and the need for continuous education, this strategy aims to improve health outcomes for cows and calves and reduce economic losses. Implementing this structured approach can facilitate better preparedness, efficient resource utilization, and improved overall livestock management, thereby promoting the sustainability and productivity of the cattle industry and addressing animal welfare aspects.

Inferring Causal Relationships for Lifetime Reproductive Traits and Modelling Latent Reproductive Performance Variable in Murciano-Granadina Goats

The current study investigated the application of structural equation models for genetic analysis of lifetime reproductive traits and latent variable modelling in the Murciano-Granadina goat breed. In the current investigation, data collected between 2016 and 2023 in a private dairy farm of the Murciano-Granadina goat breed in Ghale-Ganj city, located in the southern area of Kerman Iranian province were used. The investigated lifetime reproductive traits included overall litter size at birth (OLSB), overall litter size at weaning (OLSW), overall litter weight at birth (OLWB), and overall litter weight at weaning (OLWW). Four multivariate animal models, including standard (SMM), Inductive Causation algorithm-based structural equation (ICM), ICM with biological modification (ICM-BM), and fully recursive (FRM) models were fitted on the data and compared in terms of predictive ability measures including mean squared prediction error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y,y ̂ $$ \hat{\mathrm{y}} $$ )) of records. ICM-BM performed better than other models in terms of the lowest MSE and the highest r(y,y ̂ $$ \hat{\mathrm{y}} $$ ). Under ICM-BM, heritability estimates were low values of 0.08, 0.08, 0.11, and 0.10 for OLSB, OLSW, OLWB, and OLWW, respectively. Genetic correlations among lifetime reproductive traits were positive and varied from 0.72 (OLSB-OLWW) to 0.95 (OLSB-OLWB). The confirmatory factor analysis technique was used to construct a latent variable named reproductive performance (RP) from the investigated lifetime reproductive traits. The posterior mean for heritability of RP was estimated at 0.06. The genetic correlations between RP and the investigated lifetime reproductive traits were high and positive, ranging from 0.92 (RP-OLSB) to 0.99 (RP-OLSW). The corresponding phenotypic correlations were also high and positive, ranging from 0.81 (RP-OLWB) to 0.95 (RP-OLSW). Considering causal structure among the traits detected via ICM-BM had more advantages for genetic evaluation of the lifetime reproductive traits in the Murciano-Granadina goat compared with SMM. The low heritability estimates implied that the studied lifetime reproductive traits and RP were mainly controlled by non-additive genetic and environmental effects which limits the efficiency of direct genetic selection for improving these traits. Furthermore, positive genetic and phenotypic correlations favoured using RP latent variable for breeding purposes.

Commentary on the Adaptive Significance of Sociality Around Parturition Events, and Conspecific Support of Parturient Females in Some Social Mammals

In recent decades, it has become apparent that during parturition events in a number of social mammals, social support behaviours from group mates can be directed to parturient females (and their newborn neonates). Such behaviour has been documented in diverse taxa, across non-human primates, Elephantidae, Cetacea, and Chiroptera, living in a range of social group organisations, from matrilineal groups to cooperatively breeding groups and multi-male, multi-female groups. Since sociality, in association with parturition, has been demonstrated to confer several health benefits to human mothers and neonates, here, we also consider the potential adaptive significance of social support behaviours for other, non-human, social mammals. If appropriate social environments reduce a parturient female's dystocia risk and improve her responsiveness to her neonate following a successful birth, then the impacts of the peri-parturient social environment may ultimately have far-reaching impacts on the mother-neonate dyad's fitness. This seems a logical sequela since the health condition of a neonate at birth and the successful establishment of a strong maternal-neonate bond are often the most critical factors influencing mammalian offspring survival to independence. The principles of kin selection and alliance enhancement may serve to explain the fitness benefits to individuals who support group mates during their parturition and thus the selective advantage conferred to those exhibiting such behaviours. Older, multiparous females appear to hold a particularly important role in the assistance they can provide during the parturition of their group mates, given their greater level of experience of these events. Furthermore, a social birth may have an important influence on horizontal information transfer within a group. In particular, in long-lived, cognitively advanced social mammals (e.g., non-human primates, Elephantidae, Cetacea), witnessing birth events, early neonate responses, and maternal care, and engaging in allomaternal care with young neonates may be essential for nulliparous females' normal development. Such events may serve to prepare them for their own parturition and may improve their own parturition-related survivorship and that of their first-born offspring. Thus, it is vital that a better understanding is gained of the importance and salient features of social births in improving the health and survivorship outcomes for both the mother and her offspring in highly social species. The aim of this commentary is to assemble our current understanding of these highly interconnected themes. We suggest in the future, insights gained through observation of non-human social parturition in domestic and non-domestic species, by a wide and highly interdisciplinary range of stakeholders (including zookeepers, wildlife tourism guides, breeders of domestic animals, indigenous people, and ethologists), will be critical for enhancing our understanding of the influence of social environment on this rarely witnessed, yet highly important life event.

Equivalence of variance components between standard and recursive genetic models using LDL' transformations

BACKGROUND

Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nevertheless, in certain situations, the likelihood of recursive models and multiple trait models are equivalent. Consequently, the estimates of variance components derived from the multiple trait mixed model can be converted into estimates under several recursive models through LDL' or block-LDL' transformations.

RESULTS

The procedure was employed on a dataset comprising five traits (birth weight-BW, weight at 90 days-W90, weight at 210 days-W210, cold carcass weight-CCW and conformation-CON) from the Pirenaica beef cattle breed. These phenotypic records were unequally distributed among 149,029 individuals and had a high percentage of missing data. The pedigree used consisted of 343,753 individuals. A Bayesian approach involving a multiple-trait mixed model was applied using a Gibbs sampler. The variance components obtained at each iteration of the Gibbs sampler were subsequently used to estimate the variance components within three distinct recursive models.

CONCLUSIONS

The LDL' or block-LDL' transformations applied to the variance component estimates achieved from a multiple trait mixed model enabled inference across multiple sets of recursive models, with the sole prerequisite of being likelihood equivalent. Furthermore, the aforementioned transformations simplify the handling of missing data when conducting inference within the realm of recursive models.

Structural equation models to infer relationships between energy-related blood metabolites and milk daily energy output in Holstein cows

During lactation, high-yielding cows experience metabolic disturbances due to milk production. Metabolic monitoring offers valuable insights into how cows manage these challenges throughout the lactation period, making it a topic of considerable interest to breeders. In this study, we used Bayesian networks to uncover potential dependencies among various energy-related blood metabolites, i.e., glucose, urea, beta-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA), cholesterol (CHOL), and daily milk energy output (dMEO) in 1,254 Holstein cows. The inferred causal structure was then incorporated into structural equation models (SEM) to estimate heritabilities and additive genetic correlations among these phenotypes using both pedigree and genotypes from a 100k chip. Dependencies among traits were determined using the Hill-Climbing algorithm, implemented with the posterior distribution of the residuals obtained from the standard multiple-trait model. These identified relationships were then used to construct the SEM, considering both direct and indirect relationships. The relevant dependencies and path coefficients obtained, expressed in units of measurement variation of 1σ, were as follows: dMEO → CHOL (0.181), dMEO → BHB (-0.149), dMEO → urea (0.038), glucose → BHB (-0.55), glucose → urea (-0.194), CHOL → urea (0.175), BHB → urea (-0.049), and NEFA → urea (-0.097). Heritabilities for traits of concern obtained with SEM ranged from 0.09 to 0.2. Genetic correlations with a minimum 95% probability (P) of the posterior mean being >0 for positive means or <0 for negative means include those between dMEO and glucose (-0.583, P = 100), dMEO and BHB (0.349, P = 99), glucose and CHOL (0.325, P = 100), glucose and NEFA (-0.388, P = 100), and NEFA and BHB (0.759, P = 100). The results of this analysis revealed the existence of recursive relationships among the energy-related blood metabolites and dMEO. Understanding these connections is paramount for establishing effective genetic selection strategies, enhancing production and animal welfare.

Invited review: Recursive models in animal breeding: Interpretation, limitations, and extensions

Structural equation models allow causal effects between 2 or more variables to be considered and can postulate unidirectional (recursive models; RM) or bidirectional (simultaneous models) causality between variables. This review evaluated the properties of RM in animal breeding and how to interpret the genetic parameters and the corresponding estimated breeding values. In many cases, RM and mixed multitrait models (MTM) are statistically equivalent, although subject to the assumption of variance-covariance matrices and restrictions imposed for achieving model identification. Inference under RM requires imposing some restrictions on the (co)variance matrix or on the location parameters. The estimates of the variance components and the breeding values can be transformed from RM to MTM, although the biological interpretation differs. In the MTM, the breeding values predict the full influence of the additive genetic effects on the traits and should be used for breeding purposes. In contrast, the RM breeding values express the additive genetic effect while holding the causal traits constant. The differences between the additive genetic effect in RM and MTM can be used to identify the genomic regions that affect the additive genetic variation of traits directly or causally mediated for another trait or traits. Furthermore, we presented some extensions of the RM that are useful for modeling quantitative traits with alternative assumptions. The equivalence of RM and MTM can be used to infer causal effects on sequentially expressed traits by manipulating the residual (co)variance matrix under the MTM. Further, RM can be implemented to analyze causality between traits that might differ among subgroups or within the parametric space of the independent traits. In addition, RM can be expanded to create models that introduce some degree of regularization in the recursive structure that aims to estimate a large number of recursive parameters. Finally, RM can be used in some cases for operational reasons, although there is no causality between traits.

Genetical analysis of mastitis and reproductive traits in first-parity Holstein cows using standard and structural equation modelling

The present study aimed to investigate the causal relationships between clinical mastitis and some reproductive traits, including success at first insemination (SFI), the number of inseminations to pregnancy (INS), the interval from calving to first service (CTFS), first and last service interval (IFL), and open days (OD) in first-parity Holstein cows. For this purpose, the records of 58 281 first parity Holstein cows were analysed. These data sets were collected from 17 large dairy herds from 2008 to 2017. Recursive Mixed Models (RMMs) were applied and compared with the estimations under Standard Mixed Models. Then, one trivariate and three bivariate Gaussian-threshold models were used for the analyses. Recursive models were applied, considering that clinical mastitis can influence fertility traits. Mastitis is considered a covariate for the reproductive traits to determine their causal relationship. The results of this study indicated that causal effects of mastitis on SFI (on the observed scale, %), CTFS, IFL, OD, and INS were -5.7%, 3.3 days, 12.27 days, seven days, and 0.26 services, respectively. The estimated structural coefficients of the recursive models in the first parity imply that mastitis significantly lengthened the fertility interval and decreased the conception rate. In addition, genetic, residual, and phenotypic correlations between mastitis and the reproductive traits under both models were statistically significant. Results of genetic correlations between mastitis and fertility traits suggest that more incidence of mastitis during lactation is related to the delays in the heat show and pregnancy rate after insemination. In summary, considering the causal effects under RMMs may be advantageous to comprehend complicated relationships between complex traits better.

Pre-insemination prediction of dystocia in dairy cattle

Dystocia or difficult calving in cattle is detrimental to the health of the afflicted cows and has a negative economic impact on the dairy industry. The goal of this study was to create a data-driven tool for predicting the calving difficulty of non-heifer cows using input variables that are known prior to the moment of insemination. Compared to past studies, we excluded input variables that can only be known during or after insemination, such as birth weight and gestation length. This makes the model suitable for informing mating decisions that could reduce the incidence of difficult calvings or mitigate their consequences. We used a dataset consisting of 131,527 calving records of Holstein cattle, from which we derived a total of 274 phenotypic features and estimated breeding values. The distribution of classes in the dataset was 96.7 % normal calvings, and 3.3 % difficult calvings. We used a gradient boosted trees (XGBoost) as the learning model and a bagging ensemble approach to deal with the extreme class imbalance. The model achieved an average area under the ROC curve of 0.73 on unseen test data. Using feature importance analysis, we identified a number of features that have a high discriminatory value for calving difficulty, including maternal and paternal breeding values, and past phenotypic measurements of the cow.

Estimation of Genetic Parameters for Female Fertility Traits in the Polish Holstein-Friesian Population

Simple Summary

Female fertility is an important functional trait in dairy cattle. The aim of this study was to estimate genetic parameters for some fertility traits of Polish Holstein-Friesian cows. The results indicate that a few analyzed traits could be of use in genetic evaluation of Polish Holstein-Friesian cows.

Abstract

The objective of this study was to estimate genetic parameters for the analyzed fertility traits of Polish Holstein-Friesian primiparous and multiparous cows, as a step toward the incorporation of new traits into routine genetic evaluation. Lactation records of 116,836 Polish Holstein-Friesian cows were studied. The records cover the first three lactations of all cows. The cows, daughters of 2884 sires, were calved from 2006 to 2020. The conception rate for heifers (CRh) and for cows in the second (CR2) and third parity (CR3), the interval from first calving to first insemination (CTFI), the days open (DO), and the interval from first to successful insemination for heifers (FSh) and for cows in second (FS2) and third (FS3) parity were analyzed. The BLUPf90 package and a Bayesian method via Gibbs sampling were used to estimate (co)variance components. In general, all heritabilities were low and ranged from 0.013 (CTFI) to 0.038 (FS2). The heritability of conception rate and interval from first to successful insemination was slightly lower for heifers than for cows. Genetic correlations were moderate to high with two exceptions: correlation of CTFI with CRh (0.033) and with FSh (−0.051). The results indicate that a few analyzed traits could be used in genetic evaluation of Polish Holstein-Friesian cows. It is suggested to complement the selection index with traits for both heifers and cows, such as the interval from first to successful insemination (i.e., FSh, FS2 and FS3), in order to enable effective improvement of female fertility scores in the Polish Holstein-Friesian population.

Genetic correlations between fertility traits and milk composition and fatty acids in Holstein-Friesian, Brown Swiss, and Simmental cattle using recursive models

This study aimed to investigate the genetic and putative causal relationships between fertility traits [i.e., days open (DO) and calving rate (CR)] and milk quality, composition, and fatty acid contents (milk composition traits) in Holstein-Friesian, Brown Swiss, and Simmental cattle, using recursive models within a Bayesian framework. Trivariate animal models were run, each including one fertility trait, one milk composition trait, and, in all models, milk yield. The DO and CR data were merged with the test days closest to the insemination date for milk composition traits. After editing, 16,468 to 23,424 records for Holstein-Friesian, 23,424 to 46,660 for Brown Swiss, and 26,105 to 35,574 for Simmental were available for the analyses. Recursive animal models were applied to investigate the possible causal influences of milk composition traits on fertility and the genetic relationships among these traits. The results suggested a potential cause-and-effect relationship between milk composition traits and fertility traits, with the first trait influencing the latter. We also found greater recursive effects of milk composition traits on DO than on CR, the latter with some putative differences among breeds in terms of sensitivity. For instance, the putative causal effects of somatic cell score on CR (on the observed scale, %) varied from -0.96 to -1.39%, depending on the breed. Concerning fatty acids, we found relevant putative effects of C18:0 on CR, with estimates varying from -7.8 to -9.9%. Protein and casein percentages, and short-chain fatty acid showed larger recursive effects on CR, whereas fat, protein, and casein percentages, C16:0, C18:0, and long-chain fatty acid had larger effects on DO. The results obtained suggested that these milk traits could be considered as effective indicators of the effects of animal metabolic and physiological status on fertility.

Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep

Data collected on 2550 Kurdi lambs originated from 1505 dams and 149 sires during 1991 to 2015 in Hossein Abad Kurdi Sheep Breeding Station, located in Shirvan city, North Khorasan province, North-eastern area of Iran, were used for inferring causal relationship among the body weights at birth (BW), at weaning (WW), at six-month age (6MW), at nine-month age (9MW) and yearling age (YW). The inductive causation (IC) algorithm was employed to search for causal structure among these traits. This algorithm was applied to the posterior distribution of the residual (co)variance matrix of a standard multivariate model (SMM). The causal structure detected by the IC algorithm coupling with biological prior knowledge provides a temporal recursive causal network among the studied traits. The studied traits were analyzed under three multivariate models including SMM, fully recursive multivariate model (FRM) and IC-based multivariate model (ICM) via a Bayesian approach by 100,000 iterations, thinning interval of 10 and the first 10,000 iterations as burn-in. The three considered multivariate models (SMM, FRM and ICM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, )) of records. In general, structural equation based models (FRM and ICM) performed better than SMM in terms of lower DIC and MSE and also higher r(y, ). Among the tested models ICM had the lowest (36678.551) and SMM had the highest (36744.107)DIC values. In each case of the traits studied, the lowest MSE and the highest r(y, ) were obtained under ICM. The causal effects of BW on WW, WW on 6MW, 6MW on 9MW and 9MW on YW were statistically significant values of 1.478, 0.737, 0.776 and 0.929 kg, respectively (99% highest posterior density intervals did not include zero).

Twinning rate is not genetically correlated with production and reproduction traits in Iranian dairy cows

Context Any interruption to the reproductive system can negatively influence animal performance, and suitable animal-management practices should be adopted that will decrease the occurrence of reproductive problems such as may be the case with twinning. Aims The study was designed to estimate genetic parameters for twinning rate (TR) and to estimate genetic correlations between twinning rate and production and reproductive performances in the first lactation of Iranian Holstein cows. Methods The dataset used in this study was collected by the Animal Breeding Center of Iran during 1991–2013 and consisted of 273742 records of calving type (singleton or twin), 435742 records of 305-day milk yield, 424175 records of milk fat percentage, 253901 records of milk protein percentage, 251558 records of first calving interval, and 153632 records of number of days to first service. A single Gibbs sampling chain with 500000 rounds was generated to run linear and threshold animal models. Key results Posterior mean estimates of heritabilities for traits were: TR 0.0028, milk yield 0.28, milk fat percentage 0.33, milk protein percentage 0.38, first calving interval 0.064, and days to first service 0.061. Genetic correlations between TR and performance traits were negligible and varied from –0.08 (between TR and milk yield) to 0.04 (between TR and protein percentage). Conclusions Diminishing TR by genetic selection is a slow task owing to its low heritability. Negligible genetic correlation between TR and performance traits suggests that selection for decreased TR would not cause a significant decrease in milk production, nor is it likely to have a negative impact on the reproductive performance of dairy cows. Implications Dairy cattle breeders should follow genetic selection programs, especially for milk-production traits, without concern for an increase in twinning rate.

Symposium review: The choice and collection of new relevant phenotypes for fertility selection

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Bayesian estimates of genetic relationship between calving difficulty and productive and reproductive performance in Holstein cows

The objective of present study was to estimate genetic correlations between calving difficulty and productive and reproductive traits in Iranian Holsteins. Calving records from the Animal Breeding Center of Iran, collected from 1991 to 2011 and comprising 183 203 first-calving events of Holstein cows from 1470 herds were included in the dataset. Threshold animal models included direct genetic effect (Model 1) or direct and maternal genetic effects with covariance between them (Model 2) were fitted for the genetic analysis of calving difficulty. Also, linear animal models including direct genetic effect were fitted for the genetic analysis of productive and reproductive performance traits. A set of linear-threshold bivariate models was used for obtaining genetic correlation between calving difficulty and other traits. All analyses were implemented by Bayesian approach via Gibbs sampling methodology. A single Gibbs sampling chain with 300 000 rounds was generated by the TM program. Posterior mean estimates of direct heritabilities for calving difficulty were 0.056 and 0.066, obtained from different models. Also, posterior mean estimate of maternal heritability for this trait was 0.018. Estimate of correlation between direct and maternal genetic effects for calving difficulty was negative (–0.44). Posterior mean estimates of direct heritabilities for milk yield, fat yield, protein yield, days from calving to first service, days open and first calving interval were 0.257, 0.188, 0.235, 0.034, 0.042 and 0.050 respectively. The posterior means of direct genetic correlation between calving difficulty and milk yield, fat yield, protein yield, days from calving to first service, days open and first calving interval were low and equal to –0.135, 0.030, –0.067, –0.010, –0.075 and –0.074 respectively. The results of the current study indicated that exploitable genetic variation in calving difficulty, productive and reproductive traits could be applied in designing future genetic selection plans for Iranian Holsteins.

Effect of dystocia on subsequent reproductive performance and functional longevity in Holstein cows

The objective of this study was to evaluate the effect of dystocia on the reproductive performance and functional longevity in Iranian Holsteins. Data consisted of 1 467 064 lactation records of 581 421 Holstein cows from 3083 herds which were collected by the Animal Breeding Center of Iran from April 1987 to February 2014. Reproduction traits in this study included interval from first to second calving, days open and days from first calving to first service. The generalized linear model was used for the statistical analysis of reproductive traits. Survival analysis was performed using the Weibull proportional hazards models to analyse the impact of dystocia on functional longevity. The incidence of dystocia had an adverse effect on the reproductive performance of dairy cows. Therefore, reproductive traits deteriorated along with increase in dystocia score (p < 0.05). The culling risk was increased along with increase in the score of dystocia (p < 0.0001). The greatest culling risk was observed in primiparous cows, small herds and low-yielding cows (p < 0.0001). Also, the lowest culling risk was found for cows calving at the youngest age (<27 months), and cows with age at first calving >33 months had the greatest risk (p < 0.0001). The results of current study indicated that dystocia had important negative effects on the reproductive performance and functional longevity in dairy cows, and it should be avoided as much as possible to provide a good perspective in the scope of economic and animal welfare issues in dairy herds.

Comparison of breeding values among cows with exceptional longevity and their contemporary herdmates in German Holsteins

Abstract. The present analysis compares the estimated breeding values (EBVs), relative breeding values (RBVs), and daughter yield deviations (YDs) of cows with exceptional longevity with their contemporary herdmates. In addition, the relative breeding values of their sires were compared among these two daughter groups; the RBVs of the sires were also compared with the proportion of their daughters with exceptional longevity. Data included 5037 sires born between 1963 and 1996 with a total of 61 988 daughter; of these sires, 486 had sired daughters that completed more than nine lactations (exceptional cows) and 4957 sires had sired the contemporary herdmates. Exceptional cows had on average significantly lower EBVs for milk yield, fat and protein yield, and significantly lower YDs for milk and protein yield in the first three lactations, significantly lower RBVs for milk production and type but significantly higher RBVs for somatic cell score and functional longevity. The sires of exceptional cows had significantly higher RBVs for somatic cell count (RZS), functional longevity (RZN), and fitness (RZFit) in comparison to the sires of contemporary herdmates. Correlations among the proportion of exceptional cows per sire and RZN, RZS as well as RZFit were positive, whereas milk production (RZM) showed a negative correlation. An increase in the number of cows with exceptional longevity may be possible through a relative total breeding value with high positive weights for RZN, RZS, and RZFit but negative weights for RZM and type (RZE).

Alternative strategies for genetic analyses of milk flow in dairy cattle

Measurements for average milk flow (AMF) in kilograms of milk per minute of milking time from 629,161 Holstein cows from calving years 1990 to 2008 were used to estimate genetic covariance components using a variety of statistical models. For bivariate linear-threshold model applications, Gaussian-distributed AMF (linear sire model) was categorized into 2 distinct classes (threshold sire model) by setting arbitrary thresholds for extremely slow or extremely fast milking cows. In different bivariate runs with the 2 traits, Gaussian AMF and binary AMF, within a Bayesian framework, thresholds for the binary trait were 1.2, 1.6, 2.6, and 2.8 kg/min. Posterior heritabilities for AMF from the linear and the threshold models in all runs were in a narrow range and close to 0.26, and the posterior genetic correlation between AMF, defined as either a Gaussian or binary trait, was 0.99. A data subset was used to infer genetic and phenotypic relationships between AMF with test-day traits milk yield, fat percentage, protein percentage, somatic cell score (SCS), fat-to-protein ratio, and energy-corrected milk using recursive linear sire models, standard multiple trait linear sire models, and multiple trait linear sire models accounting for the effect of a trait 1 on a trait 2, and of trait 2 on trait 3, via linear regressions. The time-lagged 3-trait system focused on the first test-day trait after calving (trait 1), on AMF (trait 2), and on the test-day trait (trait 3) after the AMF measurement. Posterior means for heritabilities for AMF from linear and recursive linear models used for the reduced data set ranged between 0.29 and 0.38, and were slightly higher than heritabilities from the threshold models applied to the full data set. Genetic correlations from the recursive linear model and the linear model were similar for identical trait combinations including AMF and test-day traits 1 and 3. The largest difference was found for the genetic correlation between AMF and fat percentage from the first test day (i.e., -0.31 from the recursive linear model vs. -0.26 from the linear model). Genetic correlations from the linear model, including an additional regression coefficient, partly differed, especially when comparing correlations between AMF and SCS and between AMF and fat-to-protein ratio recorded after the AMF measurement data. Structural equation coefficients from the recursive linear model and corresponding regression coefficients from the linear model with additional regression, both depicting associations on the phenotypic scale, were quite similar. From a physiological perspective, all models confirmed the antagonistic relationship between SCS with AMF on genetic and phenotypic scales. A pronounced recursive relationship was also noted between productivity (milk yield and energy-corrected milk) and AMF, suggesting further research using physiological parameters as indicators for cow stress response (e.g., level of hormones) should be conducted.

Causal relationships between milk quality and coagulation properties in Italian Holstein-Friesian dairy cattle

Background

Recently, selection for milk technological traits was initiated in the Italian dairy cattle industry based on direct measures of milk coagulation properties (MCP) such as rennet coagulation time (RCT) and curd firmness 30 min after rennet addition (a₃₀) and on some traditional milk quality traits that are used as predictors, such as somatic cell score (SCS) and casein percentage (CAS). The aim of this study was to shed light on the causal relationships between traditional milk quality traits and MCP. Different structural equation models that included causal effects of SCS and CAS on RCT and a₃₀ and of RCT on a₃₀ were implemented in a Bayesian framework.

Results

Our results indicate a non-zero magnitude of the causal relationships between the traits studied. Causal effects of SCS and CAS on RCT and a₃₀ were observed, which suggests that the relationship between milk coagulation ability and traditional milk quality traits depends more on phenotypic causal pathways than directly on common genetic influence. While RCT does not seem to be largely controlled by SCS and CAS, some of the variation in a₃₀ depends on the phenotypes of these traits. However, a₃₀ depends heavily on coagulation time. Our results also indicate that, when direct effects of SCS, CAS and RCT are considered simultaneously, most of the overall genetic variability of a₃₀ is mediated by other traits.

Conclusions

This study suggests that selection for RCT and a₃₀ should not be performed on correlated traits such as SCS or CAS but on direct measures because the ability of milk to coagulate is improved through the causal effect that the former play on the latter, rather than from a common source of genetic variation. Breaking the causal link (e.g. standardizing SCS or CAS before the milk is processed into cheese) would reduce the impact of the improvement due to selective breeding. Since a₃₀ depends heavily on RCT, the relative emphasis that is put on this trait should be reconsidered and weighted for the fact that the pure measure of a₃₀ almost double-counts RCT.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0123-7) contains supplementary material, which is available to authorized users.

Factors associated with the differential in actual gestational age and gestational age predicted from transrectal ultrasonography in pregnant dairy cows

The objective of the study was to determine (1) how gestational age predicted using transrectal ultrasonography related to actual gestational age derived as the number of days from the most recent artificial insemination date, (2) what factors, if any, were associated with the differential between the two measures, and (3) the association between this differential in gestational age and the likelihood of subsequent pregnancy loss, stillbirth, or calving dystocia. The data set contained 7340 ultrasound records from 6805 Holstein Friesian dairy cows in 175 herds. Ultrasonography assessment underestimated gestational age relative to days since last service by 0.51 days (standard error [SE]: 0.040), although the differential was less during embryonic development phase (i.e., ≤42 days of gestation; mean overestimation of 0.31 days) versus fetal development phase (i.e., >42 days of gestation; mean underestimation of 0.81 days). Predicted calving date calculated from ultrasonography was 1.41 days (SE: 0.040) later than the actual subsequent calving date and was, on average, 0.52 days later than predicted calving date, assuming a gestation length of 282 days. Parity of the dam (P < 0.05), stage of pregnancy (P < 0.001), and sex of the calf born (P < 0.001) were all associated with the differential in gestational age based on ultrasonography versus days since last service. No obvious trend among parities was evident in the difference between the methods in predicting gestational age. Ultrasonography underestimated gestational age by 0.83 (SE: 0.15) days in parity 5+ cows and underestimated gestational age by 0.41 (SE: 0.14) days in the first-parity cows. Relative to gestational age predicted from the most recent service, ultrasonography underestimated gestational age by 0.75 (SE: 0.13) days for heifer fetuses and underestimated gestational age by 0.36 (SE: 0.13) days for bull fetuses. The heritability of the differential in gestational age between the methods of prediction was low 0.05 (SE: 0.022), corroborating heritability estimates for most cow reproductive traits. Overestimation of gestational age using ultrasonography was associated with an increased likelihood of pregnancy loss (P < 0.001). Gender of calf born (P < 0.001), sire breed of calf (P < 0.001), and parity (P < 0.001) were all associated with gestation length. Gestation length was 1.27 days longer (SE: 0.01) for bull calves compared to heifer calves. Calves from beef sires had a longer gestation length than calves from dairy sires, and older parity cows had a longer gestation length than younger cows. The results highlight factors associated with differences in gestational age obtained from ultrasonography and insemination data and illustrate the value of ultrasonography for the prediction of calving date and pregnancy loss.

Prevalence, risk factors and consequent effect of dystocia in holstein dairy cows in iran

The objective of this research was to determine the prevalence, risk factors and consequent effect of dystocia on lactation performance in Holstein dairy cows in Iran. The data set consisted of 55,577 calving records on 30,879 Holstein cows in 30 dairy herds for the period March 2000 to April 2009. Factors affecting dystocia were analyzed using multivariable logistic regression models through the maximum likelihood method in the GENMOD procedure. The effect of dystocia on lactation performance and factors affecting calf birth weight were analyzed using mixed linear model in the MIXED procedure. The average incidence of dystocia was 10.8% and the mean (SD) calf birth weight was 42.13 (5.42) kg. Primiparous cows had calves with lower body weight and were more likely to require assistance at parturition (p<0.05). Female calves had lower body weight, and had a lower odds ratio for dystocia than male calves (p<0.05). Twins had lower birth weight, and had a higher odds ratio for dystocia than singletons (p<0.05). Cows which gave birth to a calf with higher weight at birth experienced more calving difficulty (OR (95% CI) = 1.1(1.08–1.11). Total 305-d milk, fat and protein yield was 135 (23), 3.16 (0.80) and 6.52 (1.01) kg less, in cows that experienced dystocia at calving compared with those that did not (p<0.05).

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33,155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85,118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice.

Genetic and environmental analysis of dystocia and stillbirths in draft horses

Genetic parameters and environmental factors were estimated for foaling ease (FE) and stillbirths (SBs) in four breeds of draft horses based on 11 229, 38 877, 35 764 and 13 274 FE and SB scores recorded between 1998 and 2010 for Ardennais (A), Breton (B), Comtois (C) and Percheron (P), respectively. Incidences for the three FE categories were: easy or without help 91.0% (A) to 95.4% (B), difficult 3.4% (B) to 7.1% (A) and intervention of a veterinarian 1.1% (B) to 1.9% (A). The frequency of SB ranged between 5.4% (B) and 9.4% (A). A multiple-trait threshold animal model was used that included the effects of sex of foal, region, month, year of foaling, combined maternal age and parity, direct genetic, maternal genetic and permanent environments. Estimates were obtained using Markov Chain Monte Carlo Gibbs sampling. The most unfavourable effect was first parity, which decreased the probability of easy foaling to 78.6% for A and 88.3% for B. Interaction with age showed that the risk for first foaling for mares aged 3 years was higher than at 4 or 5 to 9 years. This was also observed for SB with an increased probability of SB at first foaling of 17.9% (A) or 9.6% (B). The most unfavourable month was found to be the most frequent month for foaling (April) and not the most demanding months weather-wise (winter). For FE, direct heritabilities were A 0.27 (0.06), B 0.14 (0.03), C 0.18 (0.03) and P 0.18 (0.04), and maternal heritabilities were A 0.25 (0.06), B 0.19 (0.04), C 0.12 (0.03) and P 0.21 (0.06). Genetic correlations between direct and maternal genetic effects were A −0.29 (0.14), B −0.39 (0.12), C −0.09 (0.14) and P −0.54 (0.17). For SB, direct heritabilities were A 0.52 (0.09), B 0.42 (0.04), C 0.28 (0.04) and P 0.39 (0.05), and maternal heritabilities were A 0.25 (0.05), B 0.10 (0.02), C 0.07 (0.02) and P 0.14 (0.02). Genetic correlations between direct and maternal genetic effects were A −0.85 (0.06), B −0.63 (0.06), C −0.64 (0.11) and P −0.69 (0.06). Direct genetic correlations between FE and SB traits were A 0.60 (0.10), B 0.58 (0.10), C 0.36 (0.10) and P 0.29 (0.15). Maternal genetic correlations between FE and SB traits were A 0.67 (0.10), B 0.47 (0.13), C 0.28 (0.15) and P 0.39 (0.15). These estimates are posterior means of the Gibbs samples and are within the upper limits of comparable results reported in cattle.

Importance of birthcoat for lamb survival and growth in the Romane sheep breed extensively managed on rangelands

The Romane sheep breed proved to be adapted to harsh conditions with high prolificacy and lamb survival in outdoor farming, even under bad climate conditions. This breed shows large variability in its fleece type at birth and it has been suggested that lamb survival could be related to birthcoat type. The aim of the present study was to: i) characterize the coat of the lamb at birth and quantify lamb survival in relation to the birthcoat type and its protective properties concerning heat loss in the Romane breed raised under permanent exposure outdoors from birth, and ii) estimate genetic parameters of birthcoat type in relation to lamb survival and live body weight. A total of 7,880 lambs from 104 sires and 1,664 dams were used in a 14-yr experiment. The pedigree file included 9,625 individuals over 15 generations. Birthcoat type, coat surface temperature, coat depth, lamb survival, and growth were measured from birth to weaning. Weather data (temperature, wind speed, relative humidity, and precipitation) were recorded daily during lambing time. Two types of coats were observed at birth: hairy coat (62.9% of lambs) with a long coat depth (average 23.3 mm) or woolly 1 (37.1% of lambs) with a short coat depth (average 8.3 mm). Birthcoat type was an important factor affecting lamb survival and growth from birth in the Romane breed. Total mortality rate was significantly less in hairy-bearing coat lambs than in short-woolly coat ones: 7.0% vs. 9.6%, 11.6 % vs. 14.8%, and 15.7 % vs. 20.1 % at 2, 10, and 50 d, respectively, and the relative risks of death increased by 37%, 67%, and 46 % at 2, 10, and 50 d of age, respectively, in short-woolly lambs. At birth, a significant lower coat surface temperature, indicating less heat loss, was observed in long-hairy coat lambs compared with others (21.1°C vs. 26.1°C). Heavier body weights and better growth performances up to the age of 50 d were observed in long-hairy-bearing coat lambs. Lamb survival was positively correlated to weather conditions at lambing time in short-woolly lambs, whereas no relation was observed in hairy-coat lambs. Heritability estimate of birthcoat type (hairy or woolly) is high (0.88). Genetic correlations between birthcoat type, lamb survival, and live body weight at birth were positive and moderate, suggesting that it would be beneficial to take birthcoat into account as an adaptive trait in any genetic strategies for sheep production in harsh conditions on rangelands.

Direct and maternal genetic relationships between calving ease, gestation length, milk production, fertility, type, and lifespan of Holstein-Friesian primiparous cows

As the emphasis in cattle breeding is shifting from traits that increase income toward traits that reduce costs, national breeding indices are expanding to include functional traits such as calving ease (CE). However, one issue is the lack of knowledge of genetic relationships between CE and other dairy traits. The same can be said about gestation length (GL), a potential novel selection trait with considerable heritabilities and possible genetic relationships with the calving process. This study aimed to estimate the genetic relationships between CE, GL, and other dairy traits of interest using a national data set of 31,053 primiparous cow performance records, as well as to separate direct and maternal genetic effects. Chosen dairy traits included fertility (calving interval, days to first service, nonreturn rate after 56 d, number of inseminations per conception), milk production (milk yield at d 110 in milk, accumulated 305-d milk yield, accumulated 305-d fat yield, accumulated 305-d protein yield), type (udder depth, chest width, rump width, rump angle, mammary composition, stature, body depth), and lifespan traits (functional days of productive life). To allow the separation of direct and maternal genetic effects, a random sire of the calf effect was included in the multi-trait linear trivariate sire models fitted using ASReml. Significant results showed that easily born individuals were genetically prone to high milk yield and reduced fertility in first lactation. Difficult calving primiparous cows were likely associated with being high-producing, wide and deep animals, with a reduced ability to subsequently conceive. Individuals that were born relatively early were associated with good genetic merit for milk production. Finally, individuals carrying their offspring longer were genetically associated with being wide and large animals that were themselves born relatively early. The study shows that it is feasible and valuable to separate direct and maternal effects when estimating genetic correlations between calving and other dairy traits. Furthermore, gestation length is best used as an indicator trait for lowly heritable calving traits, rather than as a novel selection trait. As estimated direct and maternal genetic correlations differ, we can conclude that genetic relationships between CE, GL, and traits of interest are present, but caution is required if these traits are implemented in national breeding indices.

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

Background

The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.

Methods

Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.

Results and discussion

On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.

Conclusions

For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.

Dystocia in Friesian cows and its effects on postpartum reproductive performance and milk production

A total of 1,243 records for 585 dairy Friesian cows from 1997–2004 were used to study the factors affecting dystocia and its effects on reproductive performance and milk production. The overall incidence of dystocia was 6.9%. The percentage of dystocia decreased with increasing live body weight, age, and parity of cows (P < 0.05); however, it increased with increasing birth weight of calves (P < 0.05). The highest percentage of dystocia was detected in winter season, but the least percentage was in summer season (P < 0.05). The percentage of incidence of dystocia was significantly (P < 0.05) higher with winter feeding compared to summer ration (8.2% vs. 5.1%). The percentage of incidence of dystocia was significantly (P < 0.05) higher with twinning than single calving (15.5% vs. 6.5%), while not significantly affected by the sex of born calves. Incidence of dystocia had adverse effects on reproductive performance and milk yield. The service interval, service period, days open, and calving interval were significantly (P < 0.05) longer in cows afflicted with dystocia compared to normal cows. The conception rate was lower (P < 0.05), but the number of service per conception was higher (P < 0.05) in cows afflicted with dystocia compared to normal cows (60.5% vs. 73.0% and 3.4 vs. 2.7, respectively). Average daily milk yield was lower (P < 0.05) by 1 kg for cows with incidence of dystocia compared to normal cows.

An application of change-point recursive models to the relationship between litter size and number of stillborns in pigs

We developed and implemented change-point recursive models and compared them with a linear recursive model and a standard mixed model (SMM), in the scope of the relationship between litter size (LS) and number of stillborns (NSB) in pigs. The proposed approach allows us to estimate the point of change in multiple-segment modeling of a nonlinear relationship between phenotypes. We applied the procedure to a data set provided by a commercial Large White selection nucleus. The data file consisted of LS and NSB records of 4,462 parities. The results of the analysis clearly identified the location of the change points between different structural regression coefficients. The magnitude of these coefficients increased with LS, indicating an increasing incidence of LS on the NSB ratio. However, posterior distributions of correlations were similar across subpopulations (defined by the change points on LS), except for those between residuals. The heritability estimates of NSB did not present differences between recursive models. Nevertheless, these heritabilities were greater than those obtained for SMM (0.05) with a posterior probability of 85%. These results suggest a nonlinear relationship between LS and NSB, which supports the adequacy of a change-point recursive model for its analysis. Furthermore, the results from model comparisons support the use of recursive models. However, the adequacy of the different recursive models depended on the criteria used: the linear recursive model was preferred on account of its smallest deviance value, whereas nonlinear recursive models provided a better fit and predictive ability based on the cross-validation approach.

Modeling relationships between calving traits: a comparison between standard and recursive mixed models

Background

The use of structural equation models for the analysis of recursive and simultaneous relationships between phenotypes has become more popular recently. The aim of this paper is to illustrate how these models can be applied in animal breeding to achieve parameterizations of different levels of complexity and, more specifically, to model phenotypic recursion between three calving traits: gestation length (GL), calving difficulty (CD) and stillbirth (SB). All recursive models considered here postulate heterogeneous recursive relationships between GL and liabilities to CD and SB, and between liability to CD and liability to SB, depending on categories of GL phenotype.

Methods

Four models were compared in terms of goodness of fit and predictive ability: 1) standard mixed model (SMM), a model with unstructured (co)variance matrices; 2) recursive mixed model 1 (RMM1), assuming that residual correlations are due to the recursive relationships between phenotypes; 3) RMM2, assuming that correlations between residuals and contemporary groups are due to recursive relationships between phenotypes; and 4) RMM3, postulating that the correlations between genetic effects, contemporary groups and residuals are due to recursive relationships between phenotypes.

Results

For all the RMM considered, the estimates of the structural coefficients were similar. Results revealed a nonlinear relationship between GL and the liabilities both to CD and to SB, and a linear relationship between the liabilities to CD and SB.

Differences in terms of goodness of fit and predictive ability of the models considered were negligible, suggesting that RMM3 is plausible.

Conclusions

The applications examined in this study suggest the plausibility of a nonlinear recursive effect from GL onto CD and SB. Also, the fact that the most restrictive model RMM3, which assumes that the only cause of correlation is phenotypic recursion, performs as well as the others indicates that the phenotypic recursion may be an important cause of the observed patterns of genetic and environmental correlations.

Predictive ability of models for calving difficulty in US Holsteins

The performance of alternative threshold models for analyzing calving difficulty (CD) in Holstein cows was evaluated in terms of predictive ability. Four models were considered, with CD classified into either three or four categories and analysed either as a single trait or jointly with gestation length (GL). The data contained GL and CD records from 90 393 primiparous cows, sired by 1122 bulls and distributed over 935 herd-calving year classes. Predictive ability of each model was evaluated using four criteria: mean squared error of the difference between observed and predicted CD scores; a Kullback-Leibler divergence measure between the observed and predicted distributions of CD scores; Pearson's correlation between observed and predicted CD scores and ability to correctly classify bulls as above or below average for incidence of CD. In general, the four models had similar predictive abilities. The joint analysis of CD with GL produced little, if any, improvement in predictive ability over univariate models. In light of the small difference in predictive ability between models treating CD with three or four categories and considering that a greater number of categories can provide more information, analysis of CD classified into four categories seems warranted.

Genetic improvement of dairy cow reproductive performance

The welfare of cow along with profitability in production are important issues in sustainable animal breeding programmes. Along with an intense/intensive selection for increased milk yield, reproductive performance has declined in many countries, in part due to an unfavourable genetic relationship. The largely unchanged genetic trend in female fertility and calving traits for Scandinavian Red breeds shows that it is possible to avoid deterioration in these traits if they are properly considered in the breeding programme. Today's breeding is international with a global selection and extensive use of the best bulls. The Nordic countries have traditionally recorded and performed genetic evaluation for a broad range of functional traits including reproduction. In recent years many other countries have also implemented genetic evaluation for these traits. Thus, the relative emphasis of dairy cattle breeding objectives has gradually shifted from production to functional traits such as reproduction. Improved ways of recording traits, e.g. physiological measures, early indicator traits, assisted reproductive techniques and increased knowledge of genes and their regulation may improve the genetic selection strategies and have large impact on present and future genetic evaluation programmes. Extensive data bases with phenotypic recordings of traits for individuals and their pedigree are a prerequisite. Quantitative trait loci have been associated to the reproductive complex. Most important traits, including reproduction traits are regulated by a multitude of genes and environmental factors in a complex relationship, however. Genomic selection might therefore be important in future breeding programmes. Information on single nucleotide polymorphism has already been introduced in the selection programmes of some countries.

Exploring biological relationships between calving traits in primiparous cattle with a Bayesian recursive model

Structural equation models (SEMs) of a recursive type with heterogeneous structural coefficients were used to explore biological relationships between gestation length (GL), calving difficulty (CD), and perinatal mortality, also known as stillbirth (SB), in cattle, with the last two traits having categorical expression. An acyclic model was assumed, where recursive effects existed from the GL phenotype to the liabilities (latent variables) to CD and SB and from the liability to CD to that of SB considering four periods regarding GL. The data contained GL, CD, and SB records from 90,393 primiparous cows, sired by 1122 bulls, distributed over 935 herd-calving year classes. Low genetic correlations between GL and the other calving traits were found, whereas the liabilities to CD and SB were high and positively correlated, genetically. The model indicated that gestations of approximately 274 days of length (3 days shorter than the average) would lead to the lowest CD and SB and confirmed the existence of an intermediate optimum of GL with respect to these traits.