Calving To First Insemination Research Articles

Estimation of genetic parameters for fertility traits in Chinese Holstein of south China.

Introduction: Chinese Holstein in South China suffer heat stress for a long period, which leads to evolutionary differences from Chinese Holstein in North China. The aim of this study was to estimate the genetic parameters of fertility traits for Chinese Holstein in South China. Methods: A total of 167,840 Chinese Holstein heifers and cows from Guangming Animal Husbandry Co., LTD farms were used in this study. The fertility traits analyzed were calving interval (CI), days open (DO), age of first service (AFS), age of first calving (AFC), calving to first insemination (CTFS), first insemination to conception (FSTC), gestation length (GL), non-return rate to 56days (NRR), and number of services (NS). Results: The descriptive statistics revealed that the same trait in heifers performed better than in cows, which was consistent with the other studies. The heritabilities of fertility traits in this study ranged from close to 0 (for NS of cows) to 0.2474 (for AFC of heifers). The genetic correlation of NRR between heifers and cows was 0.9993, which indicates that the NRR for heifers and cows could be treated as one trait in this population. Conclusion: The heritabilities of fertility traits in Chinese Holstein in south China were quite different from the heritabilities of fertility traits in North China. NRR56, NS, AFC, and CI were suggested to be included into the selection index to improve fertility performance of Chinsese Holstein of south China. The results of this study could provide genetic parameters for the animal breeding program of Chinese Holstein in the south of China.

Genomic prediction of fertility and calving traits in Holstein cattle based on models including epistatic genetic effects.

The goal of this study was to investigate whether the inclusion of genomic information and epistatic (additive by additive) genetic effects would increase the accuracy of predicting phenotypes adjusted for known environmental effects, reduce prediction bias and minimize the confounding between additive and additive by additive epistatic effects on fertility and calving traits in Holstein cattle. Phenotypic and genotypic records were available for 6090 cows. Eight cow traits were assessed including 56-day nonreturn rate (NRR), number of services (NS), calving to first insemination (CTFS), first insemination to conception (FSTC), gestation length (GL), calving ease (CE), stillbirth (SB) and calf size (CZ). Four scenarios were assessed for their ability to predict adjusted phenotypes, which included: (1) traditional pedigree-based Best Linear Unbiased Prediction (P-BLUP) for additive genetic effects (PA); (2) P-BLUP for additive and epistatic (additive by additive) genetic effects (PAE); (3) genomic BLUP (G-BLUP) for additive genetic effects (GA); and (4) G-BLUP for additive and epistatic genetic effects (GAEn, where n = 1-3 depending on the alternative ways to construct the epistatic genomic matrix used). Constructing epistatic relationship matrix as the Hadamard product of the additive genomic relationship matrix (GAE1), which is the usual method and implicitly assumes a model that fits all pairwise interactions between markers twice and includes the interactions of the markers with themselves (dominance). Two additional constructions of the epistatic genomic relationship matrix were compared to test whether removing the double counting of interactions and the interaction of the markers with themselves (GAE2), and removing double counting of interactions between markers, but including the interaction of the markers with themselves (GAE3) would had an impact on the prediction and estimation error correlation (i.e. confounding) between additive and epistatic genetic effects. Fitting epistatic genetic effects explained up to 5.7% of the variance for NRR (GAE3), 7.7% for NS (GAE1), 11.9% for CTFS (GAE3), 11.1% for FSTC (GAE2), 25.7% for GL (GAE1), 2.3% for CE (GAE1), 14.3% for SB (GAE3) and 15.2% for CZ (GAE1). Despite a substantial proportion of variance being explained by epistatic effects for some traits, the prediction accuracies were similar or lower for GAE models compared with pedigree models and genomic models without epistatic effects. Although the prediction accuracy of direct genomic values did not change significantly between the three variations of the epistatic genetic relationship matrix used, removing the interaction of the markers with themselves reduced the confounding between additive and additive by additive epistatic effects. These results suggest that epistatic genetic effects contribute to the variance of some fertility and calving traits in Holstein cattle. However, the inclusion of epistatic genetic effects in the genomic prediction of these traits is complex and warrant further investigation.

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

Simple SummaryFemale 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.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 parameters for endocrine and traditional fertility traits, hyperketonemia and milk yield in dairy cattle

High-yielding cows may suffer from negative energy balance during early lactation, which can lead to ketosis and delayed ability of returning to cyclicity after calving. Fast recovery after calving is essential when breeding for improved fertility. Traditionally used fertility traits, such as the interval from calving to first insemination (CFI), have low heritabilities and are highly influenced by management decisions. Herd Navigator™ management program samples and analyses milk progesterone and β-hydroxybutyrate (BHB) automatically during milking. In this study, the genetic parameters of endocrine fertility traits (measured from milk progesterone) and hyperketonemia (measured from milk BHB) in early lactation were evaluated and compared with traditional fertility traits (CFI, interval from calving to the last insemination and interval from first to last insemination) and the milk yield in red dairy cattle herds in Finland. Data included observations from 14 farms from 2014 to 2017. Data were analyzed with linear animal models using DMU software and analyses were done for first parity cows. Heritability estimates for traditional fertility traits were low and varied between 0.03 and 0.07. Estimated heritabilities for endocrine fertility traits (interval from calving to the first heat (CFH) and commencement of luteal activity (C-LA)) were higher than for traditional fertility traits (0.19 to 0.33). Five slightly different hyperketonemia traits divided into two or three classes were studied. Linear model heritability estimates for hyperketonemia traits were low, however, when the threshold model was used for binary traits the estimates became slightly higher (0.07 to 0.15). Genetic correlation between CFH and C-LA for first parity cows was high (0.97) as expected since traits are quite similar. Moderate genetic correlations (0.47 to 0.52) were found between the endocrine fertility traits and early lactation milk yield. Results suggest that the data on endocrine fertility traits measured by automatic systems is a promising tool for improving fertility, specifically when more data is available. For hyperketonemia traits, dividing values into three classes instead of two seemed to work better. Based on the current study and previous studies, where higher heritabilities have been found for milk BHB traits than for clinical ketosis, milk BHB traits are a promising indicator trait for resistance to ketosis and should be studied more. It is important that this kind of data from automatic devices is made available to recording and breeding organizations in the future.

Improving genetic evaluation using a multitrait single-step genomic model for ability to resume cycling after calving, measured by activity tags in Holstein cows

The objective of this study was to evaluate the improvement of the accuracy of estimated breeding values for ability to recycle after calving by using information of genomic markers and phenotypic information of correlated traits. The traits in this study were the interval from calving to first insemination (CFI), based on artificial insemination data, and the interval from calving to first high activity (CFHA), recorded from activity tags, which could better measure ability to recycle after caving. The phenotypic data set included 1,472,313 records from 820,218 cows for CFI, and 36,504 records from 25,733 cows for CFHA. The genomic information was available for 3,159 progeny-tested sires, which were genotyped using Illumina Bovine SNP50 BeadChip (Illumina, San Diego, CA). Heritability estimates were 0.06 for the interval from calving to first insemination and 0.14 for the interval from calving to first high activity, and the genetic correlation between both traits was strong (0.87). Breeding values were obtained using 4 models: conventional single-trait BLUP; conventional multitrait BLUP with pedigree-based relationship matrix; single-trait single-step genomic BLUP; and multitrait single-step genomic BLUP model with joint relationship matrix combining pedigree and genomic information. The results showed that reliabilities of estimated breeding values (EBV) from single-step genomic BLUP models were about 40% higher than those from conventional BLUP models for both traits. Furthermore, using a multitrait model doubled the reliability of breeding values for CFHA, whereas no gain was observed for CFI. The best model was the multitrait single-step genomic BLUP, which resulted in a reliability of EBV 0.19 for CFHA and 0.14 for CFI. The results indicate that even though a relatively small number of records for CFHA were available, with genomic information and using multitrait model, the reliability of EBV for CFHA is acceptable. Thus, it is feasible to include CFHA in Nordic Holstein breeding evaluations to improve fertility performance.

Genotype by environment interaction for the interval from calving to first insemination with regard to calving month and geographic location in Holstein cows in Denmark and Sweden

The objectives of this study were to investigate genotype by environment interaction effects, with environments defined as calving month and geographic location, on the interval from calving to first insemination (CFI) of Holstein cows in Denmark and Sweden. The data set included 811,285 records on CFI for first-parity cows from January 2010 to January 2014 housed in 7,458 herds. The longest mean CFI was 84.7 d for cows calving in April and the shortest was 76.3 d for cows calving in September. The longest mean CFI of 87.1 d was recorded at the northernmost location (LOC-8), whereas the shortest mean CFI of 73.5 d was recorded at the southernmost location (LOC-1). The multiple trait approach, in which CFI values in different calving months and different geographic locations were treated as different traits, was used to estimate the variance components and genetic correlations for CFI by using the average information (AI)-REML procedure in a bivariate sire model. Estimates of genetic variance and heritability were highest for January calvings and 3 times smaller for June calvings. Location 2 had the highest heritability and LOC-8 the lowest, with heritability estimates decreasing from LOC-2 to LOC-8. Genetic correlations of CFI between calving months were weakest between cold months (December and January) and warm months (June, August, and September); the lowest estimate was found between January and September calvings. Genetic correlations of CFI between the different geographic locations were generally strong, and the weakest correlation was between LOC-3 and LOC-8. These results indicate a genotype by environment interaction for CFI primarily regarding seasons described by calving months. The effect of geographic location was less important, mostly producing a scaling effect of CFI in different locations. We concluded that CFI is more sensitive to seasonal effects than geographic locations in Denmark and Sweden.

Estrus traits derived from activity measurements are heritable and closely related to the time from calving to first insemination

The aim of this study was to estimate genetic parameters for estrus-related traits that could improve selection for increased fertility due to improved ability of the cow to return to cycling and go into heat after calving. We compared the time from calving to first insemination (CFI) to 3 physical activity traits: the interval from calving to first high activity (CFHA), estrus duration (ED), and estrus strength (ES). We calculated CFI based on data from commercial Holstein herds that included the insemination dates for 11,363 cows. The CFHA, ED, and ES traits were derived from electronic activity tags for 3,533 Holstein cows. Estimates of heritability were 0.07 for CFI, 0.16 for CFHA, 0.02 for ED, and 0.05 for ES. We found a strong genetic correlation between CFI and CFHA (0.96). Genetic correlations between ED and CFI and CFHA were −0.37 and −0.68, respectively. Genetic correlations between ES and CFI and CFHA were −0.50 and −0.58, respectively. The heritability of CFHA and its strong genetic correlation with CFI suggest that including CFHA in the genetic evaluation of female cow fertility could improve the effectiveness of selection, because CFHA reflects the ability to return to cyclicity and go into heat after calving.

Non-genetic factors affecting fertility traits in South African Holstein cows

Profitable milk production and genetic improvement in dairy herds depend largely on fertile cows calving annually to initiate a new lactation period. Over the last 30 years, several studies have indicated a decline in the reproductive performance of dairy cows. From the perspectives of many farmers and veterinarians, the reproductive performance of cows is related to the calving interval (CI) and services per conception (SPC). Using these traits as cow fertility indicators is problematic as CI is dependent on subsequent calving dates, while SPC is strongly linked to inseminator proficiency. Cow fertility refers to the ability of cows to come into oestrus soon after calving, to conceive from a minimum number of services, and to stay pregnant until the next calving. In this paper, non-genetic factors affecting fertility traits other than CI in Holstein cows are discussed. Service records (n = 69 181) and pregnancy check results of 9 046 cows in 14 herds were available. Six fertility traits were derived. Means (± sd) for the interval traits, namely calving to first insemination (CFS) and the interval from calving to conception (days open (DO)) were 77 ± 30 and 134 ± 74 days, respectively, while the number of SPC was 2.55 ± 1.79. The proportion of first services occurring within 80 days post partum (FS80d) and the proportion of cows being confirmed pregnant within 100 days (PD100d) and 200 days post partum (PD200d) were 0.64 ± 0.48, 0.36 ± 0.48 and 0.71 ± 0.45, respectively. While lactation number, calving year and calving season affected reproduction traits significantly, herds (management) had the largest effect.Keywords: Dairy cows, days open, interval to first insemination, reproduction

Practical use of a uterine score system for predicting effects on interval from calving to first insemination and non-return rate 56 in Danish dairy herds

A detailed study of 398,237 lactations of Danish Holstein dairy cows was undertaken. The objective was to investigate the information gained by evaluating vaginal discharge in cows from 5 to 19days post-partum (p.p.) using an ordinal scale from 0 to 9. The study focused on the interval from calving to first insemination (CFI) and the non-return rate 56days after first insemination (NR56), adjusted for the confounders milk production and body condition score (BCS). For the analyses, BCS was evaluated on the same day that the uterine score was made. Milk production was defined as test-day milk yield in the first month p.p.The study showed that the evaluation of vaginal discharge according to this score system permitted ranking of cows according to CFI and NR56, i.e. an increasing uterine score was associated with a significantly longer time from calving to first insemination and significantly reduced the probability of success of the first insemination. Reproductive success was already affected if the uterine score had reached 4 (i.e. before the discharge smelled abnormally). The negative effect on CFI and NR56 increased as the uterine score increased, which suggested that the uterine scoring system was a useful guide to dairy producers.

Inferring relationships between clinical mastitis, productivity and fertility: A recursive model application including genetics, farm associated herd management, and cow-specific antibiotic treatments

A dataset of test-day records, fertility traits, and one health trait including 1275 Brown Swiss cows kept in 46 small-scale organic farms was used to infer relationships among these traits based on recursive Gaussian-threshold models. Test-day records included milk yield (MY), protein percentage (PROT-%), fat percentage (FAT-%), somatic cell score (SCS), the ratio of FAT-% to PROT-% (FPR), lactose percentage (LAC-%), and milk urea nitrogen (MUN). Female fertility traits were defined as the interval from calving to first insemination (CTFS) and success of a first insemination (SFI), and the health trait was clinical mastitis (CM). First, a tri-trait model was used which postulated the recursive effect of a test-day observation in the early period of lactation on liability to CM (LCM), and further the recursive effect of LCM on the following test-day observation. For CM and female fertility traits, a bi-trait recursive Gaussian-threshold model was employed to estimate the effects from CM to CTFS and from CM on SFI. The recursive effects from CTFS and SFI onto CM were not relevant, because CM was recorded prior to the measurements for CTFS and SFI. Results show that the posterior heritability for LCM was 0.05, and for all other traits, heritability estimates were in reasonable ranges, each with a small posterior SD. Lowest heritability estimates were obtained for female reproduction traits, i.e. h2=0.02 for SFI, and h2≈0 for CTFS. Posterior estimates of genetic correlations between LCM and production traits (MY and MUN), and between LCM and somatic cell score (SCS), were large and positive (0.56–0.68). Results confirm the genetic antagonism between MY and LCM, and the suitability of SCS as an indicator trait for CM. Structural equation coefficients describe the impact of one trait on a second trait on the phenotypic pathway. Higher values for FAT-% and FPR were associated with a higher LCM. The rate of change in FAT-% and in FPR in the ongoing lactation with respect to the previous LCM was close to zero. Estimated recursive effects between SCS and CM were positive, implying strong phenotypic impacts between both traits. Structural equation coefficients explained a detrimental impact of CM on female fertility traits CTFS and SFI. The cow-specific CM treatment had no significant impact on performance traits in the ongoing lactation. For most treatments, beta-lactam-antibiotics were used, but test-day SCS and production traits after the beta-lactam-treatment were comparable to those after other antibiotic as well as homeopathic treatments.

Relationship between hair fatty acid profile, reproduction, and milk performance in Holstein Friesian cows

The aim of this study was to analyze the relationship between the fatty acid profiles of hair of first parity cows and their reproduction and milk performance. Hair samples from 46 German Holstein cows, 50 to 62 d postpartum, were analyzed to assess the relationship. All cows were fed the same diet. The lipid composition of hair was determined by gas chromatography. The fat content in the hair was 0.86%. Hair lipids contributed 75.14% SFA, 15.81% MUFA, and 9.92% PUFA. Cows were classified into a high and a low performance group according to their a) length of the interval from calving to first insemination (CFI), b) 100-d protein yield (100-d PY), and c) length of the interval from calving to conception (CC) and 100-d PY. Cows with short CFI or high 100-d PY or short CC and high 100-d PY had significantly greater proportions of de novo synthesized C12:0 (P < 0.05) compared with the corresponding low performing groups. Increased proportions of C12:0 in the hair were associated with shorter CFI (r = -0.32, P = 0.033) and greater 100-d PY (r = 0.34, P = 0.021). Furthermore, a discriminant analysis with C12:0 as a variable best predicted short CC and high 100-d PY (error rate 33.5%). Greater proportions of de novo synthesized fatty acids in the hair, in particular C12:0, are likely to reflect a sufficient energy availability that is required for fatty acid synthesis in ruminants.

Short communication: Large-scale study on effects of metritis on reproduction in Danish Holstein cows

A total of 398,237 lactations of Danish Holstein dairy cows were studied with the main objective to investigate the effects of metritis on 2 fertility variables: interval from calving to first insemination (CFI) and nonreturn rate at 56d after first insemination (NR56), adjusting for milk production and body condition score as confounders. Metritis was defined as a score of at least 5 (indicating purulent vaginal discharge with abnormal smell) on the Danish uterine score scale (from 0 to 9, used to evaluate vaginal discharge in the first 19d postpartum on all fresh cows in herds participating in a national herd health program). Cows with metritis in early lactation presented a significant delay in first insemination (hazard ratio of 0.80) and a significantly reduced probability of success at first insemination. The effect of metritis was also present after adjusting for possible effects of body condition score, milk production in the first month of lactation, parity, herd, and year-season. Only a small part of the observed effect of metritis could be explained by variation in body condition score at calving and milk production in the first month after calving. The results from this large-scale study underscore the deleterious effects of metritis on the fertility variables CFI and NR56.

Genetic analysis of female fertility traits in Canadian Simmentals

Calving to first insemination (CFI) (probability that a cow will produce a calf from her first service) and days to calving (DC) (interval between the first exposure to the bull and calving) defined separately for heifers and multi-parity cows were analyzed with a 4-trait linear animal model. The data were 108,206 records on 56,879 Canadian Simmental females with artificial insemination (AI) and natural service (NS) breeding records from 1974 to 2010. The model included fixed effects of year-season of breeding, age of cow by season of breeding, and age of cow's dam. Random effects were: contemporary group defined as herd within breeding year-season by breeding status for the first insemination (AI or NS), service sire by year of breeding (for CFI only), animal genetic, and cow permanent environmental (PE) effects. Bayesian methods were used to estimate covariance components and genetic parameters. Three specific models with different levels of heterogeneity for covariances in NS and AI data were tested. Results are reported for the most plausible specification which was the model that assumed different residual covariances for NS and AI records. The data exhibited substantial heterogeneity of residual covariance components with respect to the type of first breeding, with AI records having larger residual variances for both traits. Pooled estimates (SD) of heritability ranged from 1.8% (0.33) for CFI in heifers to 3.5% (0.47) for DC in multi-parity cows. Interval trait (DC) had higher heritability compared with CFI; both traits expressed in older cows were more heritable than corresponding traits for heifers. Contemporary group contributed up to 58% (0.51) of the total variance for DC in heifers by NS breeding. Service sire and the PE were relatively larger (smaller) sources of variation compared with additive genetic (contemporary group) effects. All traits were highly genetically correlated: from 0.69 (0.06) for CFI in heifers and multi-parity cows to 0.92 (0.04) for DC in heifers and multi-parity cows. Environmental correlations ranged from −0.73 (0.01) between CFI in heifers and DC in older cows, to 0.91 (0.01) for DC in heifers and multi-parity cows. Results indicated that CFI and DC expressed different aspects of female fertility in beef cattle, and fertility of heifers and multi-parity cows seemed to be different traits genetically. All four traits could be used in a form of selection index in Canadian Simmentals to breed for better fertility. Genetic progress, however, would be challenging given low values of heritability.

Influence of different therapy approaches: With or without manual extraction - of retained placenta on reproductive performance in Simmental cows

The aim of the research was to determine the influence of different methods used in the therapy of retained placenta on conception rate and duration of days open in cows. Research was performed on 241 Simmental cows aged 2-8 years divided in three groups. The first group of cows (group A) (n=82) with retained placenta was treated with manual extraction of placenta 12-24 h after parturition combined with application of intrauterine antibiotics. The second group (group B) (n=79) with retained placenta was treated with intrauterine antibiotics only 12-24 h after parturition and repeated 2-3 times in 48 h intervals. The third group (group C) (n=80) was the control group and had physiological puerperium (without retained placenta). To assess the reproductive performance of Simmental cows, interval from calving to first insemination (days open to first service, DOFS), interval from calving to pregnancy (days open to pregnancy, DOP), relative pregnancy rate (%), first service conception rate (FSCR, %) and all service conception rate (ASCR, %) were measured. The estimate of hazard ratio for DOFS in group A relative to cows in group B was 2.20 (p<0.0001), implying that cows in group B had oestrus earlier and were open shorter until the first insemination, that is, the relative rate of first service decreased by 54.5% in the group A while holding all other variables constant. The variable that had a significant influence on DOFS was lactation (HR=0.99; p<0.0001). The estimate of hazard ratio for DOP in group A relative to cows in group B and C was 3.53 (p<0.0001) and 1.73 (p<0.0001), respectively, implying that cows in group B and C were open longer until pregnancy, that is, the relative rate of pregnancy in group A decreased by 71.6% and 42.2% in comparison with group B and C while holding all other variables constant. Variables that had a significant influence on DOP were lactation (HR=0.99; p<0.0001) and peripartal diseases (HR=0.48; p=0.02). The estimate of hazard ratio for DOFS and DOP between group B and C was not significant. Cows treated with intrauterine foaming tablets after RFM became pregnant earlier and had a better conception rate in contrast to cows treated with manual extraction of placentae.

Udder health and female fertility traits are favourably correlated and support each other in multi-trait evaluations

Genetic parameters were estimated for protein yield (PY), clinical mastitis (CM), somatic cell score, number of inseminations (NI) and days from calving to first insemination (CFI) in first-parity Swedish Red cows by series of tri-variate linear animal models. The heritability of PY was moderate (0.34 ± 0.004), and the heritabilities of the functional traits were all low (0.014 ± 0.001-0.14 ± 0.004). The genetic correlation between CM and CFI (0.38 ± 0.05) was stronger than the correlation between CM and NI (0.05 ± 0.06), perhaps because CM and CFI usually are observed in early lactation when the cow is likely to be in negative energy balance, whereas NI generally is recorded when the cow is not in negative energy balance any more. The genetic correlation between NI and CFI was very close to zero (-0.002 ± 0.05), indicating that these two fertility traits have different genetic backgrounds. All genetic correlations between PY and the functional traits were moderate and unfavourable, ranging from 0.22 ± 0.02 to 0.47 ± 0.03. In addition, the effect of including genetic and phenotypic correlations between the trait groups milk production, udder health and female fertility on the accuracy of the selection index was quantified for a heifer, a cow and a proven bull. The difference between the accuracy obtained by multi-trait and single-trait evaluations was largest for the cow (0.012) and small for the heifer and the bull (0.006 and 0.004) because the phenotype of the cow for one trait could assist in predicting the Mendelian sampling term for a correlated trait.

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

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

Inferring relationships between health and fertility in Norwegian Red cows using recursive models

Health and fertility are complex traits, and the phenotype for one trait may affect the phenotype of one or more other traits. For instance, disease in early lactation may impair a cow's ability to show estrus and to conceive after insemination. The objectives of the present study were to explore phenotypic and genetic relationships among health and fertility traits in Norwegian Red cows using a recursive effects model, which allows disentangling causal effects of phenotypes from the genetic and environmental correlations among traits. Records of interval from calving to first insemination (CFI), nonreturn rate within 56 d after first insemination (NR56), clinical mastitis (CM), ketosis (KET), and retained placenta from 55,568 first-lactation daughters of 1,577 Norwegian Red sires were analyzed. Trivariate recursive Gaussian-threshold models were used to analyze the 2 fertility traits (CFI and NR56) together with 1 disease trait in each analysis. The estimated structural coefficients of the recursive models imply that presence of KET or retained placenta lengthened CFI, whereas causal effects from CM to fertility were negligible. Recursive effects of disease on NR56, and of CFI on NR56, were all close to zero. Genetic correlations between health and fertility traits were low or moderate. The strongest genetic correlation was between KET and CFI (0.29), whereas genetic correlations between CM and NR56 and between CFI and NR56 were nil. In general, selection against disease is expected to slightly improve fertility (shorter CFI and higher NR56) as a correlated response and vice versa. The present results suggest that the use of structural-equation models, such as the one used here, may enhance our understanding of complex relationships among traits.

Comparison Between Bivariate Models for 56-Day Nonreturn and Interval from Calving to First Insemination in Norwegian Red

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

Threshold-linear analysis of measures of fertility in artificial insemination data and days to calving in beef cattle.

Mating and calving records for 47,533 first-calf heifers in Australian Angus herds were used to examine the relationship between days to calving (DC) and two measures of fertility in AI data: 1) calving to first insemination (CFI) and 2) calving success (CS). Calving to first insemination and calving success were defined as binary traits. A threshold-linear Bayesian model was employed for both analyses: 1) DC and CFI and 2) DC and CS. Posterior means (SD) of additive covariance and corresponding genetic correlation between the DC and CFI were -0.62 d (0.19 d) and -0.66 (0.12), respectively. The corresponding point estimates between the DC and CS were -0.70 d (0.14 d) and -0.73 (0.06), respectively. These genetic correlations indicate a strong, negative relationship between DC and both measures of fertility in AI data. Selecting for animals with shorter DC intervals genetically will lead to correlated increases in both CS and CFI. Posterior means (SD) for additive and residual variance and heritability for DC for the DC-CFI analysis were 23.5 d2 (4.1 d2), 363.2 d2 (4.8 d2), and 0.06 (0.01), respectively. The corresponding parameter estimates for the DC-CS analysis were very similar. Posterior means (SD) for additive, herd-year and service sire variance and heritability for CFI were 0.04 (0.01), 0.06 (0.06), 0.14 (0.16), and 0.03 (0.01), respectively. Posterior means (SD) for additive, herd-year, and service sire variance and heritability for CS were 0.04 (0.01), 0.07 (0.07), 0.14 (0.16), and 0.03 (0.01), respectively. The similarity of the parameter estimates for CFI and CS suggest that either trait could be used as a measure of fertility in AI data. However, the definition of CFI allows the identification of animals that not only record a calving event, but calve to their first insemination, and the value of this trait would be even greater in a more complete dataset than that used in this study. The magnitude of the correlations between DC and CS-CFI suggest that it may be possible to use a multitrait approach in the evaluation of AI and natural service data, and to report one genetic value that could be used for selection purposes.

Threshold-linear analysis of measures of fertility in artificial insemination data and days to calving in beef cattle1

Mating and calving records for 47,533 first-calf heifers in Australian Angus herds were used to examine the relationship between days to calving (DC) and two measures of fertility in AI data: 1) calving to first insemination (CFI) and 2) calving success (CS). Calving to first insemination and calving success were defined as binary traits. A threshold-linear Bayesian model was employed for both analyses: 1) DC and CFI and 2) DC and CS. Posterior means (SD) of additive covariance and corresponding genetic correlation between the DC and CFI were −0.62 d (0.19 d) and −0.66 (0.12), respectively. The corresponding point estimates between the DC and CS were −0.70 d (0.14 d) and −0.73 (0.06), respectively. These genetic correlations indicate a strong, negative relationship between DC and both measures of fertility in AI data. Selecting for animals with shorter DC intervals genetically will lead to correlated increases in both CS and CFI. Posterior means (SD) for additive and residual variance and heritability for DC for the DC-CFI analysis were 23.5 d2 (4.1 d2), 363.2 d2 (4.8 d2), and 0.06 (0.01), respectively. The corresponding parameter estimates for the DC-CS analysis were very similar. Posterior means (SD) for additive, herd-year and service sire variance and heritability for CFI were 0.04 (0.01), 0.06 (0.06), 0.14 (0.16), and 0.03 (0.01), respectively. Posterior means (SD) for additive, herd-year, and service sire variance and heritability for CS were 0.04 (0.01), 0.07 (0.07), 0.14 (0.16), and 0.03 (0.01), respectively. The similarity of the parameter estimates for CFI and CS suggest that either trait could be used as a measure of fertility in AI data. However, the definition of CFI allows the identification of animals that not only record a calving event, but calve to their first insemination, and the value of this trait would be even greater in a more complete dataset than that used in this study. The magnitude of the correlations between DC and CS-CFI suggest that it may be possible to use a multitrait approach in the evaluation of AI and natural service data, and to report one genetic value that could be used for selection purposes.