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.     

Body condition scores and dairy form evaluations as indicators of days open in US Holsteins

The objectives of this study were to estimate genetic correlations among body condition score (BCS), dairy form, milk yield, and days open in US Holsteins and investigate the potential of using BCS or dairy form evaluations as early indicators of days open. Dairy form and BCS obtained from the Holstein Association USA, Inc., were merged with mature equivalents (ME) for milk yields and days open data from AIPL-USDA. Cows were required to be classified between 24 and 60 mo of age, before 335 d in milk (DIM) and have ME milk of at least 4537 kg. A minimum of 20 daughters per sire and 10 cows per herd-classification visit (HV) or herd-year-season of calving (HYS) were required. The final data set included 159,700 records. Heritabilities and correlations among dairy form, BCS, milk yield, and days open were estimated with multiple trait sire models. Fixed effects included age at classification for dairy form and BCS, age at calving for milk yield, HV for dairy form and BCS, HYS for milk yield and days open, DIM within lactation group for dairy form and BCS and lactation group for milk yield and days open. Correlations among dairy form, BCS, and days open were generated with and without a ME milk covariable. Correlations between ME milk and days open were generated with and without covariables for dairy form or BCS. Random effects included sire and error. The genetic correlation estimates of days open with dairy form, BCS, and ME milk were 0.48, -0.30, and 0.38, respectively. The genetic correlation estimate between days open and dairy form was 0.38 after adjustment for ME milk, whereas the genetic correlation between days open and BCS was -0.24 after adjustment for ME milk. Combining dairy form evaluations with days open evaluations for 19 recently proven bulls resulted in an average increase of 0.06 for reliability of days open evaluations. The addition of BCS evaluations did not increase reliability when dairy form observations were available.     

Genetics of grass dry matter intake, energy balance, and digestibility in grazing irish dairy cows

The objective of this study was to estimate genetic parameters for grass dry matter intake (DMI), energy balance (EB), and cow internal digestibility (IDG) in grazing Holstein-Friesian dairy cows. Grass DMI was estimated up to 4 times per lactation on 1,588 lactations from 755 cows on 2 research farms in southern Ireland. Simultaneously measured milk production and BW records were used to calculate EB. Cow IDG, measured as the ratio of feed and fecal concentrations of the natural odd carbon-chain n-alkane pentatriacontane, was available on 583 lactations from 238 cows. Random regression and multitrait animal models were used to estimate residual, additive genetic and permanent environmental (co)variances across lactations. Results were similar for both models. Heritability for DMI, EB, and IDG across lactation varied from 0.10 [8 days in milk (DIM)] to 0.30 (169 DIM), from 0.06 (29 DIM) to 0.29 (305 DIM), and from 0.08 (50 DIM) to 0.45 (305 DIM), respectively, when estimated using the random regression model. Genetic correlations within each trait tended to decrease as the interval between periods compared increased for DMI and EB, whereas the correlations with IDG in early lactation were weakest when measured midlactation. The lowest correlation between any 2 periods was 0.10, −0.36, and −0.04 for DMI, EB, and IDG, respectively, suggesting the effect of different genes at different stages of lactations. Eigenvalues and associated eigenfunctions of the additive genetic covariance matrix revealed considerable genetic variation among animals in the shape of the lactation profiles for DMI, EB, and IDG. Genetic parameters presented are the first estimates from dairy cows fed predominantly grazed grass and imply that genetic improvement in DMI, EB, and IDG in Holstein-Friesian cows fed predominantly grazed grass is possible.     

Correlations among body condition scores from various sources, dairy form, and cow health from the United States and Denmark

The objectives of this study were to estimate genetic correlations among body condition scores (BCS) from various sources, dairy form, and measures of cow health. Body condition score and dairy form evaluated during routine type appraisal was obtained from the Holstein Association USA, Inc. A second set of BCS was obtained from Dairy Records Managements Systems (DRMS) and was recorded by producers that use PCDART dairy management software. Disease observations were obtained from recorded veterinarian treatments in several dairy herds in the United States. Estimated breeding values for diseases in Denmark were also obtained. Genetic correlations among BCS, dairy form, and cow health traits in the United States were generated with sire models. Models included fixed effects for age, DIM, and contemporary group. Random effects included sire, permanent environment, herd-year season for health traits, and error. Predicted transmitting abilities (PTA) for BCS and dairy form were correlated with estimated breeding values for disease in Denmark. The genetic correlation estimate between BCS from DRMS and BCS from the Holstein Association USA, Inc., was 0.85. The genetic correlation estimate between BCS and a composite of all diseases in the United States was -0.79, and PTA for BCS was favorably correlated with an index of resistance to disease other than mastitis in Denmark (0.27). Dairy form was positively correlated with a composite of all diseases in the United States (0.85) and was unfavorably correlated with an index for resistance to disease other than mastitis in Denmark (-0.29). Adjustment for protein yield PTA had a minimal affect on correlations between PTA for BCS or dairy form and disease in Denmark. Selection for higher body condition or lower dairy form with continued selection for yield may slow deterioration in cow health as a correlated response to selection for increased yield.     

Short communication: estimates of genetic parameters of body condition score in the first 3 lactations using a random regression animal model

The objective of this research was to estimate the genetic parameters of body condition score (BCS) in the first 3 lactations in Canadian Holstein dairy cattle using a multiple-lactation random regression animal model. Field staff from Valacta milk recording agency (Sainte-Anne-de-Bellevue, QC, Canada) collected BCS from Québec herds several times throughout each lactation. Approximately 32,000, 20,000, and 11,000 first-, second-, and third-parity BCS were analyzed, respectively, from a total of 75 herds. Body condition score was a moderately heritable trait over the lactation for parity 1, 2, and 3, with average daily heritabilities of 0.22, 0.26, and 0.30, respectively. Daily heritability ranged between 0.14 and 0.26, 0.19 and 0.28, and 0.24 and 0.33 for parity 1, 2, and 3, respectively. Genetic variance of BCS increased with days in milk within lactations. The low genetic variance in early lactation suggests that the evolution of the ability to mobilize tissue reserves in early lactation provided cattle with a major advantage, and is, therefore, somewhat conserved. The increasing genetic variance suggests that more genetic differences were related to how well cows recovered from the negative energy balance state. More specifically, increasing genetic variation as lactation progressed could be a reflection of genetic differences in the ability of cows to efficiently control the rate of mobilization of tissue reserves, which would not be crucial in early lactation. The shape of BCS curves was similar across parities. From first to third parity, differences included the progressively deeper nadir and faster rate of recovery of condition. Daily genetic correlations between parities were calculated from 5 to 305 DIM, and were summed and divided by 301 to obtain average daily genetic correlations. The average daily genetic correlations were 0.84 between parity 1 and 2, 0.83 between parity 1 and 3, and 0.86 between parity 2 and 3. Although not 1, these genetic correlations are still strong, so much of the variation observed in BCS was controlled by the same genes for each of the first 3 lactations. If a genetic evaluation for BCS is developed, regular collection of first-lactation BCS records should be sufficient for genetic evaluation.     

The genetic relationship between calving interval, body condition score and linear type and management traits in registered Holsteins

The trend to poorer fertility in dairy cattle with rising genetic merit for production over the last decade suggests that breeding goals need to be broadened to include fertility. This requires reliable estimates of genetic (co)variances for fertility and other traits of economic importance. In the United Kingdom at present, reliable information on calving dates and hence calving intervals are available for most dairy cows. Data in this study consisted of 44,672 records from first lactation heifers on condition score, linear type score, and management traits in addition to 19,042 calving interval records. Animal model REML was used to estimate (co)variance components. Genetic correlations of body condition score (BCS) and angularity with calving interval were -0.40 and 0.47, respectively, thus cows that are thinner and more angular have longer calving intervals. Genetic correlations between calving interval and milk, fat, and protein yields were between 0.56 and 0.61. Records of phenotypic calving interval were regressed on sire breeding values for BCS estimated from records taken at different months of lactation and breeding values for BCS change. Genetic correlations inferred from these regressions showed that BCS recorded 1 mo after calving had the largest genetic correlation with calving interval in first lactation cows. It may be possible to combine information on calving interval, BCS, and angularity into an index to predict genetic merit for fertility.     

Heritability of electronically recorded daily body weight and correlations with yield, dry matter intake, and body condition score

The objectives of this study were to estimate heritability for daily body weight (BW) and genetic correlations of daily BW with daily milk yield (MY), body condition score (BCS), dry matter intake, fat yield, and protein yield. The Afiweigh cow body weighing system records BW of every cow exiting the milking parlor. The Afiweigh system was installed at the Pennsylvania State University dairy herd in August 2001 and in July 2004 at the Virginia Tech dairy herd. The edited data included 202,143 daily BW and 290,930 daily MY observations from 575 Pennsylvania State University and 120 Virginia Tech Holstein cows. Data were initially analyzed with a series of 4-trait animal models, followed by random regression models. The models included fixed effects for age within lactation group, week of lactation, and herd-date. Random effects included animal, permanent environment, and error. The order of the polynomials for random animal and permanent environmental effects with the random regression model for daily BW was 4 and 6, respectively. Heritability estimates for daily BW ranged from 0.48 to 0.57 and were largest between 200 and 230 and smallest at 305 d of lactation. Genetic correlations were large between BW and BCS (0.60). The genetic correlation between daily BW and MY was −0.14 but was positive (0.24) after adjusting for BCS. Electronically recorded daily BW is highly heritable, and genetic evaluations of daily BW and BW change across the lactation could be used to select for less early lactation BW loss.     

Heritabilities and correlations among body condition scores, production traits, and reproductive performance

The objectives of this study were to estimate the heritability of body condition scores (BCS) from producer and consultant-recorded data and to describe the genetic and phenotypic relationships among BCS, production traits, and reproductive performance. Body condition scores were available at calving, postpartum, first service, pregnancy check, before dry off, and at dry off from the Dairy Records Management Systems in Raleigh, NC, through the PCDART program. Heritabilities, genetic correlations, and phenotypic correlations were estimated assuming an animal model using average information REML. Herd-year-season effects and age at calving were included in all models. Prior calving interval was included in models for second and third lactations. Analyses that included reproductive traits were conducted with and without mature equivalent milk as a covariable. Heritability estimates for BCS ranged from 0.09 at dry-off to 0.15 at postpartum in first lactation. Heritability estimates ranged from 0.07 before dry-off to 0.20 at pregnancy check in second lactation and from 0.08 before dry-off to 0.19 at first service in third lactation. Genetic correlations between adjacent BCS within first lactation were greater than 0.96 with the exception of calving and postpartum (0.74). In second lactation, adjacent genetic correlations were 1.0 with the exception of calving and postpartum (0.84). Genetic correlations across lactations were greater than 0.77. Phenotypic correlations between scoring periods were highest for adjacent scoring periods and when BCS was lowest. Phenotypic correlations were lower than genetic correlations, i.e., less than 0.70. Higher BCS during the lactation were negatively related to production, both genetically and phenotypically, but the relationship was moderate. Higher BCS were favorably related genetically to reproductive performance during the lactation.     

Durability of Traits: Nonlinear Association between Initial and Subsequent Measures

Subjective linearized scores were recorded for milking speed, fore udder smoothness, shoulder looseness, and udder depth on 7357 and 3730 Holstein cows during first and second lactations. Random sire effects in threshold models were estimated for each trait and lactation. There were 95 sires that had estimated effects for all the traits in both lactations. For each trait, sire effects for first and second lactations were used as independent and dependent variables, respectively, in quadratic regression. Sire effects corresponding to milking speed in second lactation had linear relationship to sire effects corresponding to milking speed in first lactation. Similar relationships for udder smoothness, shoulder looseness, and udder depth appeared nonlinear. The quadratic terms associated with prediction equations for shoulder looseness and udder depth were significant. Nonlinear associations between genetic evaluations in first and second lactations may have resulted from aging.     

The genetic relationship of body weight and early-lactation health disorders in two experimental herds

The objectives of this study were to estimate genetic parameters for body weight (BW) and BW change (BWC) and genetic correlations of BW and BWC with diseases and genomic predicted transmitting abilities (PTA) of productive and conformation traits of Holsteins during the first 120 DIM. Daily BW data were from the Afiweigh cow body weighing system (SAE Afikim, Kibbutz Afikim, Israel), which records BW as a cow exits the milking parlor. Disease categories included metabolic diseases, ketosis, infectious diseases, mastitis, reproductive diseases, and other diseases. Edited data included 68,914 and 11,615 daily BW observations from 441 Pennsylvania State University and 72 Virginia Tech Holstein cows, respectively. Two-trait random regression models were used to estimate relationships between BW, BWC, and diseases at 25, 38, and 58 mo of age at calving. Fixed effects for BW were age at calving nested within lactation group, week of lactation, and herd date; random effects for BW included animal, permanent environment, and error. Fixed effects for disease were herd-year-season of calving and age at calving nested within lactation group; random effects for disease were animal, permanent environment (for mastitis only), and error. Correlations of PTA for BW and BWC with genomic PTA for productive and type traits were also estimated with data from 117 cows. Heritability estimates for daily BW ranged from 0.34 to 0.63. Greater BW and less BWC were favorably correlated with ketosis, metabolic diseases, infectious diseases, and other diseases. The genetic correlation estimate between BW and ketosis was strongest at 60 DIM (−0.51), and genetic correlation estimates at 60 DIM with metabolic diseases (−0.52), infectious diseases (−0.81), and other diseases (−0.48) followed the same trend as ketosis. The genetic correlation estimate between BWC and ketosis was strongest for the change from 5 to 20 DIM (0.70) and was similar for metabolic diseases (0.37), infectious diseases (0.74), and other diseases (0.49). Correlations of BW and BWC with reproductive diseases tended to be in the reverse direction of those reported for ketosis. A larger PTA for BW was significantly correlated with smaller genomic PTA for milk yield, dairy form, rear udder height, and udder cleft. Predicted transmitting ability for BWC was negatively correlated with genomic PTA for protein percentage, strength, and hip width (ranging from −0.26 to −0.13 across lactation) and was positively correlated with dairy form, rear udder height, and udder cleft (ranging from 0.20 to 0.37 across lactation). Selection for reduced BW loss can be implemented with automated body weighing systems and may be successful in decreasing disease incidence in the early stages of lactation.     

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.     

Genetic relationship between first-lactation body energy and later-life udder health in dairy cattle

Weekly body condition score (BCS) and live weight records were used to calculate energy content (EC) and cumulative effective energy balance (CEEB) for 508 Holstein-Friesian cows in their first lactation. Cows were raised on an experimental farm and had calved between 1991 and 2000. Energy content was an estimate of the actual energy level of a cow at any given stage of lactation, whereas CEEB was associated with the total body energy content as defined by accumulated weekly energy balance changes since the onset of lactation. Genetic evaluations were computed for the 3 body energy traits (BCS, EC, and CEEB) for each week of first lactation. Random regression models were used to assess the association between first-lactation weekly genetic evaluations for body energy and monthly test-day log-transformed SCC, clinical mastitis, and other udder problems in the first 3 lactations. There was a significant effect of at least one body energy trait at any stage of first lactation past wk 3 on SCC in the first 3 lactations. Maximum genetic correlation estimates were −0.18 (±0.04) between wk-16 BCS and SCC in the first 2 lactations, −0.18 (±0.04) between wk-11 EC and SCC in the first 2 lactations, and −0.17 (±0.07) between wk-6 CEEB and SCC in the first 2 lactations. The effect of body energy traits on clinical mastitis was, in general, nonsignificant; nevertheless, moderate genetic correlations were estimated, ranging from −0.05 (±0.07) to −0.25 (±0.15). The effect of body energy traits on udder problems other than mastitis was negligible in all cases. Results suggest that, amongst the traits studied here, BCS, EC, and CEEB in the first 3 to 4 mo of lactation 1 had the greatest genetic association with SCC and mastitis in first, second, and, to a lesser extent, third lactations.     

Genetic analysis of body condition score of lactating Dutch Holstein and Red-and-White heifers

The aim of this study was to estimate phenotypic and genetic parameters for body condition scores (BCS) from the Dutch type classification system. Data included 108,809 Holstein (H) and 26,208 Red-and-White (R) heifers from 9701 herds that were scored once during lactation on a 1 to 9 scale (1 = emaciated and 9 = obese). Mean BCS for H and R data were 4.50 and 4.94, respectively. The BCS decreased as the percentage of Holstein genes increased. For both breeds, BCS after calving was about 5.6 and BCS was lowest around wk 11. For H heifers, mean BCS at drying off was about 0.8 lower than BCS at calving, whereas for R heifers BCS was at about the same level as at calving. Variance components were estimated using an animal model including the effects of herd x visit, classifier, age at calving, DIM, and genetic group. The random herd x visit effect explained about 10 to 15% of the phenotypic variation. Heritabilities ranged from 0.24 to 0.38, depending on breed and lactation period. Genetic correlations between BCS observations in bimonthly lactation periods were close to unity, especially for H. It was concluded that BCS data collected by type classifiers can well be used for genetic evaluation and that genetic variation between animals for BCS-change patterns is a small component of the overall variation in BCS.     

Genetic line comparisons and genetic parameters for endoparasite infections and test-day milk production traits

Keeping dairy cows in grassland systems relies on detailed analyses of genetic resistance against endoparasite infections, including between- and within-breed genetic evaluations. The objectives of this study were (1) to compare different Black and White dairy cattle selection lines for endoparasite infections and (2) the estimation of genetic (co)variance components for endoparasite and test-day milk production traits within the Black and White cattle population. A total of 2,006 fecal samples were taken during 2 farm visits in summer and autumn 2015 from 1,166 cows kept in 17 small- and medium-scale organic and conventional German grassland farms. Fecal egg counts were determined for gastrointestinal nematodes (FEC-GIN) and flukes (FEC-FLU), and fecal larvae counts for the bovine lungworm Dictyocaulus viviparus (FLC-DV). The lowest values for gastrointestinal nematode infections were identified for genetic lines adopted to pasture-based production systems, especially selection lines from New Zealand. Heritabilities were low for FEC-GIN (0.05–0.06 ± 0.04) and FLC-DV (0.05 ± 0.04), but moderate for FEC-FLU (0.33 ± 0.06). Almost identical heritabilities were estimated for different endoparasite trait transformations (log-transformation, square root). The genetic correlation between FEC-GIN and FLC-DV was 1.00 ± 0.60, slightly negative between FEC-GIN and FEC-FLU (?0.10 ± 0.27), and close to zero between FLC-DV and FEC-FLU (0.03 ± 0.30). Random regression test-day models on a continuous time scale [days in milk (DIM)] were applied to estimate genetic relationships between endoparasite and longitudinal test-day production traits. Genetic correlations were negative between FEC-GIN and milk yield (MY) until DIM 85, and between FEC-FLU and MY until DIM 215. Genetic correlations between FLC-DV and MY were negative throughout lactation, indicating improved disease resistance for high-productivity cows. Genetic relationships between FEC-GIN and FEC-FLU with milk protein content were negative for all DIM. Apart from the very early and very late lactation stage, genetic correlations between FEC-GIN and milk fat content were negative, whereas they were positive for FEC-FLU. Genetic correlations between FEC-GIN and somatic cell score were positive, indicating similar genetic mechanisms for susceptibility to udder and endoparasite infections. The moderate heritabilities for FEC-FLU suggest inclusion of FEC-FLU into overall organic dairy cattle breeding goals to achieve long-term selection response for disease resistance.     

Short communication: Modification of genetic evaluation of herd life from a three-trait to a five-trait model in Canadian dairy cattle

The national genetic evaluation of herd life for Canadian dairy breeds was modified from a 3-trait to a 5-trait animal model. The genetic evaluation incorporates information from daughter survival (direct herd life) and information from conformation, fertility, and udder health traits that are related to longevity (indirect herd life). Genetic evaluations for direct herd life were based on cows’ survival from first calving to 120 days in milk (DIM), from 120 to 240 DIM, from 240 DIM to second calving, survival to third calving, and survival to fourth calving, which were analyzed using a multiple-trait animal model. Sire evaluations obtained for each of the 5 survival traits were combined into an overall sire evaluation for direct herd life. Sire evaluations for indirect herd life were based on an index of sire evaluations for dairy strength, feet and legs, overall mammary, rump angle, somatic cell score, milking speed, nonreturn rate in cows, and interval from calving to first service. A multiple-trait sire model based on multiple-trait across-country evaluation methodology was used to combine direct and indirect genetic evaluations for herd life into an overall genetic evaluation for herd life. Sire evaluations for herd life were expressed as an estimated transmitting ability for the number of lactations. The transmitting ability represents expected differences among daughters for herd life; and the average herd life was set to 3 lactations.     

Clinical ketosis: phenotypic and genetic correlations between occurrences and with milk yield.

The repeatability and heritability of ketosis were estimated using data from 28,277 Finnish Ayrshire cows. A four-trait linear model including community-year, calving age and month, genetic group, and random sire effects was used to describe first and second lactation milk yields and veterinary diagnoses of ketosis. Variance components were estimated using REML. The disease traits were also analyzed with a categorical model including the same effects except that community and year were separate factors. Variance components were estimated with marginal maximum likelihood. Genetic relationships between 339 sires analyzed were included in models. The phenotypic correlation between the first and second lactation was defined as a repeatability of trait. The lactational incidence risk of ketosis was .05 in both the first and the second lactation. Average milk production was 4956 and 5547 kg in the first and second lactations, respectively. Estimates of heritabilities were .09 and .07 for ketosis and .23 and .19 for milk in the first and second lactations, respectively. Genetic correlations between first and second lactation recordings were .64 for ketosis and .93 for milk. Repeatabilities between subsequent lactations were .36 (.13 in linear analysis) for ketosis and .68 for milk. In the first lactation, genetic relationship between milk yield and ketosis was unfavorable, but in the second lactation ketosis and milk yield were genetically and phenotypically unrelated.     

Predictive abilities of different statistical models for analysis of survival data in dairy cattle

The objective of this study was to compare alternative trait definitions and statistical models for genetic evaluation of survival in dairy cattle. Data from the first 5 lactations of 808,750 first-crop daughters of 3,064 Norwegian Red sires were analyzed. Seven sire models were used for genetic analyses: linear and threshold cross-sectional models for binary survival scores from first lactation; a linear multi-trait model for survival scores from the first 3 lactations; linear and threshold repeatability models for survival scores from the first 5 lactations; a Weibull frailty model for herd life in first lactation; and a Weibull frailty model for herd life in the first 5 lactations. The models were compared to assess predictive ability of sire estimated breeding values with respect to average survival 365 d after first calving for second-crop daughters (not included in calculation of predicted transmitting abilities) of 375 elite sires. Generally, the linear multi-trait model analyzing survival in the first 3 lactations as correlated traits gave more-accurate predicted sire breeding values compared with both linear and Weibull frailty models using data from first lactation only, even when the latter models were extended to include data up to the sixth lactation. The Weibull frailty models did not improve predictive ability of sire estimated breeding values over what was obtained using a simple cross-sectional linear model for binary survival in first lactation.     

Dynamics of automatically generated body condition scores during early lactation and pregnancy at first artificial insemination of Holstein cows

The objective of this study was to characterize the association between body condition score (BCS) and BCS change (ΔBCS), determined by an automated camera system at multiple time points, and the subsequent pregnancy per first artificial insemination (P/AI1) of Holstein cows. A retrospective observational study was completed using data collected from 11,393 lactations in 7,928 Holstein cows calving between April 2019 and March 2021 in a commercial dairy operation located in Colorado. Cows were classified as primiparous or multiparous. Scores generated by BCS cameras at dry-off, calving, 21 days in milk (DIM), 56 DIM, and first artificial insemination were selected for the analyses and subsequently categorized as low (≤lower quartile), moderate (interquartile range), and high (≥upper quartile). Changes in BCS were calculated by periods of interest as change from dry-off to calving (multiparous cows); change from calving to 21 DIM; change from calving to 56 DIM; and change from calving to first artificial insemination and assigned into categories as large loss of BCS (top 25% of cows losing BCS); moderate loss (bottom 75% of cows losing BCS); no change (ΔBCS = 0); or gain of BCS (ΔBCS > 0). Data were examined in primiparous and multiparous cows separately using logistic regression and time-to-event analyses. Initial univariable models were followed by multivariable models that considered calving season, occurrence of disease, and milk yield up to 60 DIM as covariables. The logistic regression analyses indicated that in both parity groups the associations between BCS category and P/AI1 were more evident at 21 DIM, 56 DIM, and first artificial insemination, with lower odds of P/AI1 in cows in the low BCS category. Likewise, cows with large loss in BCS between calving and 21 DIM, calving and 56 DIM, and calving and first artificial insemination had lower odds of P/AI1 compared with other categories of ΔBCS within the same period of interest. Similarly, survival analyses evidenced that cows in the low BCS category required more time to get pregnant. In agreement, differences in the dynamics of the average daily BCS during the first 90 DIM were evident when cows were grouped by first AI outcome (pregnant vs. nonpregnant) and by their time to pregnancy category (<90 DIM; 91–150 DIM; or >150 DIM), with cows with reduced fertility showing lower BCS up to 90 DIM. Overall, low BCS and more pronounced reductions in BCS occurring closer to first artificial insemination resulted in lower odds of pregnancy per artificial insemination.     

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.     

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.