Genetic parameters for conjugated linoleic acid, selected milk fatty acids, and milk fatty acid unsaturation of Italian Holstein-Friesian cows

The objective of this study was to estimate genetic parameters for conjugated linoleic acid (CLA) and other selected milk fatty acid (FA) content and for unsaturation ratios in the Italian Holstein Friesian population. Furthermore, the relationship of milk FA with milk fat and protein content was considered. One morning milk sample was collected from 990 Italian Holstein Friesian cows randomly sampled from 54 half-sib families, located in 34 commercial herds in the North-eastern part of Italy. Each sample was analyzed for milk percentages of fat and protein, and for single FA percentages (computed as FA weight as a proportion of total fat weight). Heritabilities were moderate for unsaturated FA, ranging from 0.14 for C16:1 to 0.19 for C14:1. Less than 10% of heritability was estimated for each saturated FA content. Heritability for index of desaturation, monounsaturated FA and CLA/trans-11 18:1 ratio were 0.15, 0.14, and 0.15, respectively. Standard errors of the heritability values ranged from 0.02 to 0.06. Genetic correlations were high and negative between C16:0 and C18:0, as well as between C14:0 and C18:0. Genetic correlations of index of desaturation were high and negative with C14:0 and C16:0 (−0.70 and −0.72, respectively), and close to zero (0.03) with C18:0. The genetic correlation of C16:0 with fat percentage was positive (0.74), implying that selection for fat percentage should result in a correlated increase of C16:0, whereas trans-11 C18:1 and cis-9, trans-11 C18:2 contents decreased with increasing fat percentage (−0.69 and −0.55, respectively). Genetic correlations of fat percentage with 14:1/14 and 16:1/16 ratios were positive, whereas genetic correlations of fat percentage with 18:1/18 and CLA/trans-11 18:1 ratios were negative. These results suggest that it is possible to change the milk FA composition by genetic selection, which offers opportunities to meet consumer demands regarding health aspects of milk and dairy products.     

Genetic relationships between body condition score and reproduction traits in Canadian Holstein and Ayrshire first-parity cows

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and reproduction traits for first-parity Canadian Ayrshire and Holstein cows. Body condition scores were collected by field staff several times over the lactation in herds from Québec, and reproduction records (including both fertility and calving traits) were extracted from the official database used for the Canadian genetic evaluation of those herds. For each breed, six 2-trait animal models were run; they included random regressions that allowed the estimation of genetic correlations between BCS over the lactation and reproduction traits that are measured as a single lactation record. Analyses were undertaken on data from 108 Ayrshire herds and 342 Holstein herds. Average daily heritabilities of BCS were close to 0.13 for both breeds; these relatively low estimates might be explained by the high variability among herds and BCS evaluators. Genetic correlations between BCS and interval fertility traits (days from calving to first service, days from first service to conception, and days open) were negative and ranged between −0.77 and −0.58 for Ayrshire and between −0.31 and −0.03 for Holstein. Genetic correlations between BCS and 56-d nonreturn rate at first insemination were positive and moderate. The trends of these genetic correlations over the lactation suggest that a genetically low BCS in early lactation would increase the number of days that the primiparous cow was not pregnant and would decrease the chances of the primiparous cow to conceive at first service. Genetic correlations between BCS and calving traits were generally the strongest at calving and decreased with increasing days in milk. The correlation between BCS at calving and maternal calving ease was 0.21 for Holstein and 0.31 for Ayrshire and emphasized the relationship between fat cows around calving and dystocia. Genetic correlations between calving traits and BCS during the subsequent lactation were moderate and favorable, indicating that primiparous cows with a genetically high BCS over the lactation would have a greater chance of producing a calf that survived (maternal calf survival) and would transmit the genes that allowed the calf to be born more easily (maternal calving ease) and to survive (direct calving ease).     

Thin and fat cows,and the nonlinear genetic relationship between body condition score and fertility

Thin and fat cows are often credited for low fertility, but body condition score (BCS) has been traditionally treated as a linear trait when genetic correlations with reproductive performance have been estimated. The aims of this study were to assess genetic parameters for fertility, production, and body condition traits in the Brown Swiss population reared in the Alps (Bolzano-Bozen Province, Italy), and to investigate the possible nonlinearity among BCS and other traits by analyzing fat and thin cows. Records of BCS measured on a 5-point scale were preadjusted for year-season and days in milk at scoring, and were considered positive (1) for fat cows if they exceeded the value of 1 residual standard deviation or null (0) otherwise, whereas positive values for thin cows were imputed to records below −1 residual standard deviation. Fertility indicators measured on first- and second-parity cows were interval from parturition to first service, interval from first service to conception, interval from parturition to conception, number of inseminations to conception, conception at first service, and nonreturn rate at 56 d after first service. Production traits were peak milk yield, lactation milk yield, and lactation length. Data were from 1,413 herds and included 16,324 records of BCS, fertility, and production for first-parity, and 10,086 fertility records for second-parity cows. Animals calved from 2002 to 2007 and were progeny of 420 artificial insemination bulls. Genetic parameters for the aforementioned traits were obtained under univariate and bivariate threshold and censored linear sire models implemented in a Bayesian framework. Posterior means of heritabilities for BCS, fat cows, and thin cows were 0.141, 0.122, and 0.115, respectively. Genetic correlations of body condition traits with contemporary production were moderate to high and were between −0.556 and 0.623. Body condition score was moderately related to fertility in first (−0.280 to 0.497) and second (−0.392 to 0.248) lactation. The fat cow trait was scarcely related to fertility, particularly in first-parity cows (−0.203 to 0.281). Finally, the genetic relationships between thin cows and fertility were higher than those between BCS and fertility, both in first (−0.456 to 0.431) and second (−0.335 to 0.524) lactation. Body condition score can be considered a predictor of fertility, and it could be included in evaluation either as linear measure or as thin cow. In the second case, the genetic relationship with fertility was stronger, exacerbating the poorest body condition and considering the possible nonlinearity between fertility and energy reserves of the cow.     

Heritabilities and genetic correlations of body condition score and calving interval with yield, somatic cell score, and linear type traits in Brown Swiss cattle

This study aimed to estimate genetic parameters for body condition score (BCS), calving interval (CI), somatic cell score (SCS), yield, and linear type traits for the Italian Brown Swiss cattle population. A total of 32,359 records of first-parity lactating cows were collected from 2002 to 2004 in 4,885 dairy herds. The pedigree file included 96,661 animals. Multiple-trait animal models were analyzed using REML to estimate (co)variance components without repeated observations on traits. The estimated heritability was 0.15 for BCS, 0.05 for CI, and 0.06 for SCS, and ranged from 0.09 to 0.14 for test-day yield traits and from 0.07 to 0.32 for linear type traits. The genetic correlations of CI with yield and most linear type traits were positive, whereas the correlation between CI and BCS was negative (−0.35). For type traits, BCS showed, in general, a moderately negative genetic correlation except for strength, pastern, and heel height. The genetic correlation of CI or BCS with SCS was moderately low but favorable (0.19 and −0.26, respectively). The estimated correlations indicated that selection for greater yield and type traits can exert unfavorable effects on the reproductive ability of cows. To counterbalance these effects and to carry out early prediction of breeding values of bulls for fertility, inclusion of BCS in the breeding program is advisable.     

Genetics of body condition score in New Zealand dairy cows

Body condition score (BCS) data were collected on 169,661 first-parity cows from herds participating in progeny testing schemes and linear type assessment. Genetic and residual variances for BCS estimated across time using a quadratic random regression model were found to be largest at the start of lactation. Heritability estimates ranged from 0.32 to 0.23 from d 1 to 200 of lactation, with a mean of 0.26. Genetic correlations between BCS and other traits were estimated using 2 approaches: 1) a multivariate analysis that included BCS and live weight, both adjusted for stage of lactation; 270-d cumulative yields of milk, fat, and protein; average somatic cell score; and 2 measures of fertility; and 2) a bivariate random regression analysis in which BCS was considered to be a longitudinal trait across time, with the same measurements as in approach 1 for all other traits. Genetic correlations of BCS with the 2 fertility traits were 0.43 and 0.50 using the multivariate analysis; the corresponding random regression estimates between BCS as a longitudinal trait across time and 2 measures of fertility were 0.35 to 0.44 and 0.40 to 0.49, and tended to increase with stage of lactation. Genetic correlations estimated using the random regression model fluctuated around the multivariate estimates for live weight and somatic cell score, which were 0.50 and −0.12, respectively. Genetic correlations estimated using the multivariate analysis of BCS with fat and protein yields were close to zero. With the random regression model, genetic correlations between BCS and fat and protein yields were positive at d 1 of lactation (0.16 and 0.08, respectively) and were negative by d 200 of lactation (−0.25 and −0.20, respectively). In pastoral production systems, such as those typical in New Zealand, there appears to be an advantage in the total lactation yields of fat and protein for cows of higher BCS in early lactation, which is likely to be because these cows have body reserves that are available to be mobilized in later lactation, when feed resources are sometimes limited.     

Genetic analysis of skinfold thickness and its association with body condition score and milk production traits in Chinese Holstein population

The skin has many important roles in dairy cattle, and skinfold thickness could be used as an indicator of body fat deposition. The objectives of this study were to estimate genetic parameters of skinfold thickness and to explore its association with body condition score (BCS) and milk production traits in a Chinese Holstein population. Skinfold thicknesses over the neck (STN) and the last rib (STR), BCS, and test-day records of milk production traits were available for 6,416 lactating Holstein cows in the summers of 2015 and 2016 in Beijing, China. Multi-trait animal models were used to estimate variance and covariance components using the DMU software. The average STN was 7.15 ± 1.28 mm, and the average STR was 11.76 ± 1.95 mm (mean ± standard deviation). Estimated heritability was 0.13 ± 0.03 for STN and 0.26 ± 0.04 for STR. We detected a high genetic correlation (0.79 ± 0.08; heritability ± standard error) between STN and STR. Genetic correlations between skinfold thickness and BCS were low to moderate: 0.18 between STR and BCS, and 0.33 between STN and BCS. Genetic correlations between skinfold thickness and milk yield, milk fat percentage, and milk protein percentage were negligible, ranging from ?0.02 to 0.15. Collectively, skinfold thickness is characterized as a trait with moderate heritability. Skinfold thickness is sensitive to changes in body condition or fat deposition across parities and lactation stages in milking cows, and we confirmed the complementary nature of skinfold thickness and BCS genetically as well as phenotypically by comparing their changing trends throughout lactation and across lactations. The use of skinfold thickness, together with BCS, can assist in the monitoring of changes in body fat deposition to achieve higher management precision.     

Genetic parameters for female fertility, locomotion, body condition score, and linear type traits in Czech Holstein cattle

The aim of this study was to estimate genetic parameters for fertility traits and linear type traits in the Czech Holstein dairy cattle population. Phenotypic data regarding 12 linear type traits, measured in first lactation, and 3 fertility traits, measured in each of first and second lactation, were collected from 2005 to 2009 in the progeny testing program of the Czech-Moravian Breeders Corporation. The number of animals for each linear type trait was 59,467, except for locomotion, where 53,436 animals were recorded. The 3-generation pedigree file included 164,125 animals. (Co)variance components were estimated using AI-REML in a series of bivariate analyses, which were implemented via the DMU package. Fertility traits included days from calving to first service (CF1), days open (DO1), and days from first to last service (FL1) in first lactation, and days from calving to first service (CF2), days open (DO2), and days from first to last service (FL2) in second lactation. The number of animals with fertility data varied between traits and ranged from 18,915 to 58,686. All heritability estimates for reproduction traits were low, ranging from 0.02 to 0.04. Heritability estimates for linear type traits ranged from 0.03 for locomotion to 0.39 for stature. Estimated genetic correlations between fertility traits and linear type traits were generally neutral or positive, whereas genetic correlations between body condition score and CF1, DO1, FL1, CF2 and DO2 were mostly negative, with the greatest correlation between BCS and CF2 (−0.51). Genetic correlations with locomotion were greatest for CF1 and CF2 (−0.34 for both). Results of this study show that cows that are genetically extreme for angularity, stature, and body depth tend to perform poorly for fertility traits. At the same time, cows that are genetically predisposed for low body condition score or high locomotion score are generally inferior in fertility.     

Heritabilities and correlations among body condition score,dairy form and selected linear type traits

The objectives of this study were to estimate the heritability of body condition score (BCS) with data that could be used to generate genetic evaluations for BCS in the US, and to estimate the relationship among BCS, dairy form and selected type traits. Body condition score and linear type trait records were obtained from Holstein Association USA Inc. Because BCS was a new trait for classifiers, scoring distribution and accuracy was not normal. Records from 11 of 29 classifiers were eliminated to generate a data set that should represent BCS data recorded in the future. Edited data included 128,478 records for analysis of first lactation cows and 207,149 records for analysis of all cows. Heritabilities and correlations were estimated with ASREML using sire models. Models included age at calving nested within lactation, 5th order polynomials of DIM, fixed herd-classification visit effects and random sire and error. Genetic correlation estimates were generated between first lactation data that had records from 11 classifiers removed and data with no classifiers removed. Genetic correlation estimates were 0.995 and above between data with and without classifiers removed for scoring distributions, but heritability estimates were higher with the classifiers edited from the data. Heritability estimates for type traits and final score were similar to previously reported estimates. The heritability estimate for BCS was 0.19 for first lactation cows and 0.22 for all cows. The genetic correlation estimate for first lactation cows between BCS and dairy form was -0.73, whereas the genetic correlation estimate between BCS and strength was 0.72. Genetic correlation estimates were nearly identical when cows from all lactations were included in the analyses. Body condition score had a genetic correlation with final score closer to zero (0.08) than correlations of final score with dairy form, stature or strength.     

Heritability and correlations among body condition score loss,body condition score,production and reproductive performance

The objectives of this study were to estimate the heritability of body condition score loss (BCSL) in early lactation and estimate genetic and phenotypic correlations among BCSL, body condition score (BCS), production, and reproductive performance. Body condition scores at calving and postpartum, mature equivalents for milk, fat and protein yield, days to first service, and services per conception were obtained from Dairy Records Management Systems in Raleigh, NC. Body condition score loss was defined as BCS at calving minus postpartum BCS. Heritabilities and correlations were estimated with a series of bivariate animal models with average-information REML. Herd-year-season effects and age at calving were included in all models. The length of the prior calving interval was included for all second lactation traits, and all nonproduction traits were analyzed with and without mature equivalent milk as a covariable. Initial correlations between BCS and BCSL were obtained using BCSL and BCS observations from the same cows. Additional genetic correlation estimates were generated through relationships between a group of cows with BCSL observations and a separate group of cows with BCS observations. Heritability estimates for BCSL ranged from 0.01 to 0.07. Genetic correlation estimates between BCSL and BCS at calving ranged from -0.15 to -0.26 in first lactation and from -0.11 to -0.48 in second lactation. Genetic correlation estimates between BCSL and postpartum BCS ranged from -0.70 to -0.99 in first lactation and from -0.56 to -0.91 in second lactation. Phenotypic correlation estimates between BCSL and BCS at calving were near 0.54, whereas phenotypic correlation estimates between BCSL and postpartum BCS were near -0.65. Genetic correlations between BCSL and yield traits ranged from 0.17 to 0.50. Genetic correlations between BCSL and days to first service ranged from 0.29 to 0.68. Selection for yield appears to increase BCSL by lowering postpartum BCS. More loss in BCS was associated with an increase in days to first service.     

Genetic parameters for body condition score and its relationship with type and production traits in Swiss Holsteins

The objectives of this study were to estimate the genetic and environmental parameters between body condition score (BCS) and 27 conformation and 3 production traits in Swiss Holstein cattle. The dataset consisted of 31,500 first-lactation cows, which were daughters of 545 sires in 1867 herds. Bivariate sire models with relationships among sires were used to estimate parameters. Least squares means for BCS by lactation stage show that cows lose BCS up to 5 mo after calving and gain BCS prior to the next calving. Regression models showed that an increase in age and percentage of Holstein genes results in an increase and decrease in BCS, respectively. Heritability (h2) was 0.24 for BCS score, which indicates good potential for selection. Sire estimated breeding values for BCS ranged from -0.46 to +0.51 units. Heritabilities ranged from 0.08 (heel depth) to 0.46 (rump width) for type traits and 0.23 to 0.29 for yield traits. Genetic correlations of BCS with 8 conformation traits were significant; stature (0.28), heart girth (0.21), strength (0.17), loin (-0.39), body capacity (0.19), dairy character (-0.35), udder quality (-0.42), and teat position rear (-0.33). Milk production and body condition have an unfavorable genetic correlation (-0.12 to -0.17). These results show that selection for good body condition, body conformation, and optimal milk production is possible and their genetic associations reported here will be useful for designing Swiss breeding goals.     

Incorporating heifer feed efficiency in the Australian selection index using genomic selection

The economic benefit of expanding the Australian Profit Ranking (APR) index to include residual feed intake (RFI) was evaluated using a multitrait selection index. This required the estimation of genetic parameters for RFI and genetic correlations using single nucleotide polymorphism data (genomic) correlations with other traits. Heritabilities of RFI, dry matter intake (DMI), and all the traits in the APR (milk, fat, and protein yields; somatic cell count; fertility; survival; milking speed; and temperament), and genomic correlations between these traits were estimated using a Bayesian framework, using data from 843 growing Holstein heifers with phenotypes for DMI and RFI, and bulls with records for the other traits. Heritability estimates of DMI and RFI were 0.44 and 0.33, respectively, and the genomic correlation between them was 0.03 and nonsignificant. The genomic correlations between the feed-efficiency traits and milk yield traits were also close to zero, ranging between −0.11 and 0.10. Positive genomic correlations were found for DMI with stature (0.16) and with overall type (0.14), suggesting that taller cows eat more as heifers. One issue was that the genomic correlation estimates for RFI with calving interval (ClvI) and with body condition score were both unfavorable (−0.13 and 0.71 respectively), suggesting an antagonism between feed efficiency and fertility. However, because of the relatively small numbers of animals in this study, a large 95% probability interval existed for the genomic correlation between RFI and ClvI (−0.66, 0.36). Given these parameters, and a genetic correlation between heifer and lactating cow RFI of 0.67, inclusion of RFI in the APR index would reduce RFI by 1.76 kg/cow per year. Including RFI in the APR would result in the national Australian Holstein herd consuming 1.73 × 10⁶ kg less feed, which is worth 0.55 million Australian dollars (A$) per year and is 3% greater than is currently possible to achieve. Other traits contributing to profitability, such as milk production and fertility, will also improve through selection on this index; for example, ClvI would be reduced by 0.53d/cow per year, which is 96% of the gain for this trait that is achieved without RFI in the APR.     

Genetic evaluation and best prediction of lactation persistency

Cows with high persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction of persistency was calculated as a function of a trait-specific standard lactation curve and a linear regression of test-day deviations on days in milk. Regression coefficients were deviations from a balance point to make yield and persistency phenotypically uncorrelated. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of persistency of milk (PM), fat (PF), protein (PP), and SCS (PSCS) in Holstein cows. Data included 8,682,138 lactations from 4,375,938 cows calving since 1997, and 39,354 sires were evaluated. Sire estimated breeding values (EBV) for PM, PF, and PP were similar and ranged from −0.70 to 0.75 for PM; EBV for PSCS ranged from −0.37 to 0.28. Regressions of sire EBV on birth year were near zero (<0.003) but positive for PM, PF, and PP, and negative for PSCS. Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable, indicating that increasing SCS decreases yield traits, as expected. Genetic correlations among yield and persistency were low to moderate and ranged from −0.09 (PSCS) to 0.18 (PF). This definition of persistency may be more useful than those used in test-day models, which are often correlated with yield. Routine genetic evaluations for persistency are feasible and may allow for improved predictions of yield traits. As calving intervals increase, persistency may have greater value.     

Body and milk production traits as indicators of energy requirements and efficiency of purebred Holstein and 3-breed rotational crossbred cows from Viking Red,Montbéliarde,and Holstein sires

This study aimed to compare rotational 3-breed crossbred cows of Viking Red, Montbéliarde, and Holstein breeds with purebred Holstein cows for a range of body measurements, as well as different metrics of the cows' productivity and production efficiency. The study involved 791 cows (440 crossbreds and 351 purebreds), that were managed across 2 herds. Within each herd, crossbreds and purebreds were reared and milked together, fed the same diets, and managed as one group. The heart girth, height at withers, and body length were measured, and body condition score (BCS) was determined on all the cows on a single test day. The body weight (BW) of 225 cows were used to develop an equation to predict BW from body size traits, parity, and days in milk, which was then used to estimate the BW of all the cows. Equations from the literature were used to estimate body protein and lipid contents using the predicted BW and BCS. Evidence suggests that maintenance energy requirements may be closely related to body protein mass, and Holstein and crossbred cows may be different in body composition. Therefore, we computed the requirements of net energy for maintenance (NE_M) on the basis either of the metabolic weight (NE_M-MW: 0.418 MJ/kg of metabolic BW) or of the estimated body protein mass according to a coefficient (NE_M-PM: 0.631 MJ/kg body protein mass) computed on the subset comprising the purebred Holstein. On the same day when body measurements were collected, individual test-day milk yield and fat and protein contents were retrieved once from the official Italian milk recording system, and milk was sampled to determine fresh cheese yield. Measures of NE_M were used to scale the production traits. Statistical analyses of all variables included the fixed effects of herd, days in milk, parity, and genetic group (purebred Holstein and crossbred), and the herd × genetic group interaction. External validation of the equation predicting BW yielded a correlation coefficient of 0.94 and an average bias of −4.95 ± 36.81 kg. The crossbreds had similar predicted BW and NE_M-MW compared with the Holsteins. However, NE_M-PM of crossbreds was 3.8% lower than that of the Holsteins, due to their 11% greater BCS and different estimated body composition. The crossbred cows yielded 4.8% less milk and 3.4% less milk energy than the purebred Holsteins. However, the differences between genetic groups were no longer significant when the production traits were scaled on NE_M-PM, suggesting that the crossbreds and purebreds have the same productive ability and efficiency per unit of body protein mass. In conclusion, measures of productivity and efficiency that combine the cows' production capability with traits related to body composition and the energy cost of production seem to be more effective criteria for comparing crossbred and purebred Holstein cows than just milk, fat, and protein yields.     

Associations between ultrasound hepatic measurements,body measures,and milk production traits in Holstein cows

Ultrasound (US) imaging has been proposed as a noninvasive tool for monitoring liver dysfunction in dairy cows. This study, carried out on 306 clinically healthy Holstein cows in the first 120 d of lactation kept in 2 herds in northern Italy, aimed at investigating the association between US imaging-derived traits, namely predicted liver triacylglycerol content (pTAG, mg/g), liver depth (LD, mm), portal vein depth (PVD, mm) and area (PVA, mm²), and body size measurements, body condition score (BCS), and milk productivity indicators. Transcutaneous US examination, milk sampling, body size measurements (withers height and heart girth), and BCS were collected once from all cows in 10 sampling batches. The body weights (BW) of a subsample of 73 cows were recorded and used together with an existing data set of BW and measures of Holstein Friesian cows (n = 399) to develop a regression equation to predict BW, which was then used to compute productivity indicators by scaling the milk production traits to predicted BW. Body size measures, BCS, milk traits, and productivity indicators were classified (low, medium, and high) in 0.75 units of standard deviation of the residuals generated from a linear model that included the effects of parity, days in milk, and sampling batch. Liver pTAG, PVA, PVD, and LD were analyzed with a sequence of linear mixed models that included the fixed effects of days in milk and parity and the random effect of sampling batch as common terms, whereas the classes of body and milk traits and the productivity indicators were included one by one. The US-related traits were found to be associated with body size measurements and BCS. Specifically, pTAG was inversely related to BCS, whereas PVD and LD increased with increasing heart girth, BCS, and predicted BW. Generally, no relevant associations were observed between the US parameters and milk production traits, including when expressed in terms of productivity. In conclusion, this study suggests that US measures of liver dimensions of clinically healthy cows are related to their size, whereas pTAG concentrations reflect body condition status, with no particular implications for milk production and productivity. Moreover, healthy cows seemed able to counteract the metabolic stress of the first 120 d of the lactation period without straining liver functionality. Finally, US imaging proved to be a promising technique to assess liver metabolic conditions. However, further studies are needed to confirm its potential as a noninvasive tool for monitoring liver conditions in healthy cows.     

Evaluation of body condition score measured throughout lactation as an indicator of fertility in dairy cattle

Body condition score (BCS) records of primiparous Holstein cows were analyzed both as a single measure per animal and as repeated measures per sire of cow. The former resulted in a single, average, genetic evaluation for each sire, and the latter resulted in separate genetic evaluations per day of lactation. Repeated measure analysis yielded genetic correlations of less than unity between days of lactation, suggesting that BCS may not be the same trait across lactation. Differences between daily genetic evaluations on d 10 or 30 and subsequent daily evaluations were used to assess BCS change at different stages of lactation. Genetic evaluations for BCS level or change were used to estimate genetic correlations between BCS measures and fertility traits in order to assess the capacity of BCS to predict fertility. Genetic correlation estimates with calving interval and non-return rate were consistently higher for daily BCS than single measure BCS evaluations, but results were not always statistically different. Genetic correlations between BCS change and fertility traits were not significantly different from zero. The product of the accuracy of BCS evaluations with their genetic correlation with the UK fertility index, comprising calving interval and non-return rate, was consistently higher for daily than for single BCS evaluations, by 28 to 53%. This product is associated with the conceptual correlated response in fertility from BCS selection and was highest for early (d 10 to 75) evaluations.     

Genetic profile of body energy and blood metabolic traits across lactation in primiparous Holstein cows

The objectives of this study were to characterize the changes of body condition score (BCS), energy content (EC), cumulative effective energy balance (CEEB), and blood serum concentrations of glucose, β-hydroxybutyrate (BHBA), and nonesterified fatty acids (NEFA) across the first lactation of Holstein cows, and to estimate variance components for these traits. Four hundred ninety-seven cows kept on a commercial farm in Greece that had calved during 2005 and 2006 were used. Body condition score, estimated live weight, and blood metabolic traits were recorded weekly for the first 3 mo of lactation and monthly thereafter until the end of lactation. Body condition score and estimated live weight records were used to calculate EC and CEEB throughout the first lactation. Estimates of fixed curves and genetic parameters for each trait, by week of lactation, were obtained with the use of random regression models. The estimated fixed curves were indicative of changes in the metabolic process and energy balance of the cows. Significant genetic variance existed in all studied traits, and was particularly high during the first weeks of lactation (except for the genetic variance of CEEB, which was not significant at the beginning of lactation). Significant heritability estimates for BCS ranged from 0.34 to 0.79, for EC from 0.19 to 0.87, for CEEB from 0.58 to 0.93, for serum glucose from 0.12 to 0.39, for BHBA from 0.08 to 0.40, and for NEFA from 0.08 to 0.35. Genetic correlations between different weeks of lactation were near unity for adjacent weeks and decreased for weeks further apart, becoming practically zero for measurements taken more than 3 to 4 mo apart, especially with regard to blood metabolic traits. Significant heritability estimates were also obtained for BCS recorded before first calving. Results suggest that genetic evaluation and selection of dairy cows for early-lactation body energy and blood metabolic traits is possible.     

Short communication: genetic relationships among daily energy balance, feed intake, body condition score, and fat to protein ratio of milk in dairy cows

Postpartum energy status is critically important to health and fertility, and it remains a major task to find suitable indicator traits for energy balance. Therefore, genetic parameters for daily energy balance (EB) and dry matter intake (DMI), weekly milk fat to protein ratio (FPR), and monthly body condition score (BCS) were estimated using random regression on data collected from 682 Holstein-Friesian primiparous cows recorded between lactation d 11 to 180. Average energy-corrected milk (ECM), EB, DMI, BCS, and FPR were 32.0 kg, 9.6 MJ of NE_L, 20.3 kg, 2.95, and 1.12, respectively. Heritability estimates for EB, DMI, BCS, and FPR ranged from 0.03 to 0.13, 0.04 to 0.19, 0.34 to 0.59, and 0.20 to 0.54. Fat to protein ratio was a more valid measure for EB in early lactation than DMI, BCS, or single milk components. Correlations between FPR and EB were highest at the beginning of lactation [genetic correlation (r_g) = −0.62 at days in milk (DIM) 15] and decreased toward zero. Dry matter intake was the trait most closely correlated with EB in mid lactation (r_g = 0.73 at DIM 120 and 150). Energy balance in early lactation was negatively correlated to EB in mid lactation. The same applied to DMI. Genetic correlations between FPR across lactation stages were all positive; the lowest genetic correlation (0.55) was estimated between the beginning of lactation and early mid lactation. Hence, to improve EB at the beginning of lactation, EB and indicator traits need to be recorded in early lactation. We concluded that FPR is an adequate indicator for EB during the energy deficit phase. Genetic correlations of FPR with ECM, fat percentage, and protein percentage showed that a reduction of FPR in early lactation would have a slightly negative effect on ECM, whereas milk composition would change in a desirable manner.     

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; ?0.279 to ?0.343) and udder depth (?0.348 to ?0.419). Positive correlations were observed for production and body depth (0.138–0.228), dairy character (DCH) (0.334–0.422), and stature (STAT) (0.084–0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (?0.255 to ?0.470), positive correlations were found between disease traits and DCH (0.269–0.469) as well as STAT (0.172–0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.     

Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.     

Genetic relationship of body energy and blood metabolites with reproduction in holstein cows

Body condition score (BCS), energy content (EC), cumulative effective energy balance (CEEB), and blood serum concentrations of glucose, β-hydroxybutyrate (BHBA), and nonesterified fatty acids (NEFA) were measured throughout first lactation in 497 Holstein cows raised on a large commercial farm in northern Greece. All these traits are considered to be indicators of a cow's energy balance. An additional measure of BCS, EC, and blood serum glucose, BHBA, and NEFA concentrations were taken approximately 2 mo (61 ± 23 d) before first calving. During first lactation, first service conception rate, conception rate in the first 305 d of lactation, interval from calving to conception, number of inseminations per conception, incidence of metritis, and incidence of reproductive problems of these cows were recorded; interval between first and second calving, and second lactation first service conception rate were also recorded. Random regression models were used to calculate weekly animal breeding values for first lactation BCS, EC, CEEB, glucose, BHBA, and NEFA. Single trait animal models were used to calculate breeding values for these traits measured on pregnant heifers before calving. Reproductive records were then regressed on animal breeding values for these energy balance-related traits to derive estimates of their genetic correlations. Several significant estimates were obtained. In general, traits that are known to be positively correlated with energy balance (BCS, EC, CEEB, and glucose) were found to have a favorable genetic relationship with reproduction, meaning that increased levels of the former will lead to an enhancement of the latter. On the other hand, traits known to be negatively correlated with energy balance (BHBA and NEFA) were found to have an unfavorable genetic association with reproductive traits. Body condition score, BHBA, and NEFA recorded early in lactation, and glucose concentrations measured in pregnant heifers had the highest genetic correlation with future reproductive performance. Results suggest that genetic selection for body energy and blood metabolites could facilitate the genetic improvement of fertility and overall reproductive efficiency of dairy cows.