Breed differences over time and heritability estimates for production and reproduction traits of dairy goats in the United States

To aid in improvement of breeding programs for production and reproduction traits of US dairy goats, breed differences over time were documented and genetic parameters were estimated. Data were from herds with ≥2 breeds (Alpine, LaMancha, Nubian, Oberhasli, Saanen, or Toggenburg), but only purebred data were analyzed. Three kidding periods were examined: 1976 through 1984, 1985 through 1994, and 1995 through 2005. Univariate repeatability mixed models were used to estimate least squares means by kidding period-breed and genetic parameters for milk, fat, and protein yields, combined fat and protein yield, fat and protein percentages, protein:fat ratio, age at first kidding, and kidding interval. Trends across kidding periods were favorable for most yield traits for all breeds but generally unfavorable for reproduction traits. Saanens had the highest milk (1,063 to 1,125 kg) and protein yields (31 to 33 kg). Nubians had the highest fat yields (37 to 40 kg) and lowest milk yields (791 to 851 kg). Oberhaslis had the lowest fat (31 to 33 kg) and protein (23 to 27 kg) yields. Alpines had the largest increase in milk yield (7.4%); Oberhaslis had the largest increase in protein (17.4%) and combined fat and protein (13.2%) yields. Combined fat and protein yield was higher for Nubians, Saanens, and Alpines (65 to 72 kg) than for LaManchas, Toggenburgs, and Oberhaslis (53 to 67 kg). Nubians had the highest fat (4.7 to 4.8%) and protein (3.6 to 3.8%) percentages. Only Nubians increased in fat percentage (2.1%); protein percentage increased most for Toggenburgs (7.4%) and Alpines (7.1%). Protein:fat ratio was highest for Toggenburgs (0.84 to 0.89) and lowest for Nubians (0.76 to 0.81), but Nubians had the largest increase in protein:fat ratio (6.6%). Saanens were oldest at first kidding (509 to 589 d), and Toggenburgs and LaManchas generally were youngest (435 to 545 d); age at first kidding increased most for Alpines (21.8%) and LaManchas (21.6%). Kidding intervals generally were shorter for Oberhaslis, LaManchas, and Nubians (350 to 377 d) than for Toggenburgs, Alpines, and Saanens (373 to 387 d). Kidding interval increased most for Nubians (3.9%) and Saanens (3.8%) and decreased only for Oberhaslis (5.4%). Heritability estimates across breeds were 0.35 for milk and fat yields, 0.37 for protein yield and protein:fat ratio, 0.36 for combined fat and protein yield, 0.52 for fat percentage, 0.54 for protein percentage, 0.23 for age at first kidding, and 0.05 for kidding interval. Genetic selection within breed is feasible for production and reproduction traits of US dairy goats.     

Genetic and environmental parameters for milk production, udder health, and fertility traits in Mexican Holstein cows

Genetic and phenotypic parameters for Mexican Holstein cows were estimated for first- to third-parity cows with records from 1998 to 2003 (n = 2,971-15,927) for 305-d mature equivalent milk production (MEM), fat production (MEF), and protein production (MEP), somatic cell score (SCS), subsequent calving interval (CAI), and age at first calving (AFC). Genetic parameters were obtained by average information matrix-REML methodology using 6-trait (first-parity data) and 5-trait (second- and third-parity data) animal models. Heritability estimates for production traits were between 0.17 ± 0.02 and 0.23 ± 0.02 for first- and second-parity cows and between 0.12 ± 0.03 and 0.13 ± 0.03 for third-parity cows. Heritability estimates for SCS were similar for all parities (0.10 ± 0.02 to 0.11 ± 0.03). For CAI, estimates of heritability were 0.01 ± 0.05 for third-parity cows and 0.02 ± 0.02 for second-parity cows. The heritability for AFC was moderate (0.28 ± 0.03). No unfavorable estimates of correlations were found among MEM, MEF, MEP, CAI, and SCS. Estimates of environmental and phenotypic correlations were large and positive among production traits; favorable between SCS and CAI; slightly favorable between MEM, MEF, and MEP and SCS, between AFC and SCS, and between SCS and CAI; and small but unfavorable between production traits and CAI. Estimates of genetic variation and heritability indicate that selection would result in genetic improvement of production traits, AFC, and SCS. Estimates of both heritability and genetic variation for CAI were small, which indicates that genetic improvement would be difficult.     

Estimation of genetic parameters for milk yield across lactations in mixed-breed dairy goats

Currently, breeding values for dairy goats in the United Kingdom are not estimated and selection is based only on phenotypes. Several studies from other countries have applied various methodologies to estimate breeding values for milk yield in dairy goats. However, most of the previous analyses were based on relatively small data sets, which might have affected the accuracy of the parameter estimates. The objective of this study was to estimate genetic parameters for milk yield in crossbred dairy goats in lactations 1 to 4. The research was based on data provided by 2 commercial goat farms in the United Kingdom comprising 390,482 milk yield records on 13,591 dairy goats kidding between 1987 and 2012. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation, the best-performing animals were selected for breeding and, as a result, a synthetic breed was created. The pedigree file contained 28,184 individuals, of which 2,414 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. Covariance components were estimated with the average information REML algorithm in the ASReml package (VSN International Ltd., Hemel Hempstead, UK). A random regression animal model for milk yield with fixed effects of herd test day, year-season, and age at kidding was used. Heritability was the highest at 200 and 250 d in milk (DIM), reaching 0.45 in the first lactation and between 0.34 and 0.25 in subsequent lactations. After 300 DIM, the heritability started decreasing to 0.23 and 0.10 at 400 DIM in the first and subsequent lactations, respectively. Genetic correlation between milk yield in the first and subsequent lactations was between 0.16 and 0.88. This study found that milk yields in first and subsequent lactations are highly correlated, both at the genetic and phenotypic level. Estimates of heritability for milk yield were higher than most of the values reported in the literature, although they were in the range reported in this species. This should facilitate genetic improvement for the population studied as part of a broader multi-trait breeding program.     

Genetic heterogeneity of feed intake,energy-corrected milk,and body weight across lactation in primiparous Holstein,Nordic Red,and Jersey cows

In this study, we aimed to estimate and compare the genetic parameters of dry matter intake (DMI), energy-corrected milk (ECM), and body weight (BW) as 3 feed efficiency–related traits across lactation in 3 dairy cattle breeds (Holstein, Nordic Red, and Jersey). The analyses were based on weekly records of DMI, ECM, and BW per cow across lactation for 842 primiparous Holstein cows, 746 primiparous Nordic Red cows, and 378 primiparous Jersey cows. A random regression model was applied to estimate variance components and genetic parameters for DMI, ECM, and BW in each lactation week within each breed. Phenotypic means of DMI, ECM, and BW observations across lactation showed to be in very similar patterns between breeds, whereas breed differences lay in the average level of DMI, ECM, and BW. Generally, for all studied breeds, the heritability for DMI ranged from 0.2 to 0.4 across lactation and was in a range similar to the heritability for ECM. The heritability for BW ranged from 0.4 to 0.6 across lactation, higher than the heritability for DMI or ECM. Among the studied breeds, the heritability estimates for DMI shared a very similar range between breeds, whereas the heritability estimates for ECM tended to be different between breeds. For BW, the heritability estimates also tended to follow a similar range between breeds. Among the studied traits, the genetic variance and heritability for DMI varied across lactation, and the genetic correlations between DMI at different lactation stages were less than unity, indicating a genetic heterogeneity of feed intake across lactation in dairy cattle. In contrast, BW was the most genetically consistent trait across lactation, where BW among all lactation weeks was highly correlated. Genetic correlations between DMI, ECM, and BW changed across lactation, especially in early lactation. Energy-corrected milk had a low genetic correlation with both DMI and BW at the beginning of lactation, whereas ECM was highly correlated with DMI in mid and late lactation. Based on our results, genetic heterogeneity of DMI, ECM, and BW across lactation generally was observed in all studied dairy breeds, especially for DMI, which should be carefully considered for the recording strategy of these traits. The genetic correlations between DMI, ECM, and BW changed across lactation and followed similar patterns between breeds.     

Genetic parameters for fertility of dairy heifers and cows at different parities and relationships with production traits in first lactation

The objectives of this study were to estimate genetic parameters for fertility of Brown Swiss cattle, considering reproductive measures in different parities as different traits, and to estimate relationships between production traits of first lactation and fertility of heifers and first-parity and second-parity cows. Reproductive indicators were interval from parturition to first service, interval from first service to conception, interval from parturition to conception, number of inseminations to conception, conception rate at first service, and nonreturn rate at 56 d after first service. Production traits were peak milk yield (pMY), lactation milk yield, and lactation length (LL). Data included 37,546 records on heifers, and 24,098 and 15,653 records on first- and second-parity cows, respectively. Cows were reared in 2,035 herds, calved from 1999 to 2007, and were progeny of 527 AI bulls. Gibbs sampling was implemented to obtain (co)variance components using both univariate and bivariate threshold and censored linear sire models. Estimates of heritability for reproductive traits in heifers (0.016 to 0.026) were lower than those in first-parity (0.017 to 0.142) and second-parity (0.026 to 0.115) cows. Genetic correlations for fertility in first- and second-parity cows were very high (>0.920), whereas those between heifers and lactating cows were moderate (0.348 to 0.709). The latter result indicates that fertility in heifers is a different trait than fertility in lactating cows, and hence it cannot be used as robust indicator of cow fertility. Heifer fertility was not related to production traits in first lactation (genetic correlations between −0.215 and 0.251). Peak milk yield exerted a moderate and unfavorable effect on the interval from parturition to first service (genetic correlations of 0.414 and 0.353 after first and second calving, respectively), and a low and unfavorable effect on other fertility traits (genetic correlations between −0.281 and 0.295). Infertility after first calving caused a strong elongation of the lactation, and LL was negatively correlated with fertility of cows after second calving, so that LL can itself be regarded as a measure of fertility. Lactation milk yield depends on both pMY and LL, and, as such, is a cause and consequence of (in)fertility.     

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated.     

Genetic parameters of coagulation properties, milk yield, quality, and acidity estimated using coagulating and noncoagulating milk information in Brown Swiss and Holstein-Friesian cows

The aim of this study was to estimate heritabilities of rennet coagulation time (RCT) and curd firmness (a₃₀) and their genetic correlations with test-day milk yield, composition (fat, protein, and casein content), somatic cell score, and acidity (pH and titratable acidity) using coagulating and noncoagulating (NC) milk information. Data were from 1,025 Holstein-Friesian (HF) and 1,234 Brown Swiss (BS) cows, which were progeny of 54 HF and 58 BS artificial insemination sires, respectively. Milk coagulation properties (MCP) of each cow were measured once using a computerized renneting meter and samples not exhibiting coagulation within 31 min after rennet addition were classified as NC milk. For NC samples, RCT was unobserved. Multivariate analyses, using Bayesian methodology, were performed to estimate the genetic relationships of RCT or a₃₀ with the other traits and statistical inference was based on the marginal posterior distributions of parameters of concern. For analyses involving RCT, a right-censored Gaussian linear model was used and records of NC milk samples, being censored records, were included as unknown parameters in the model implementing a data augmentation procedure. Rennet coagulation time was more heritable [heritability (h²) = 0.240 and h² = 0.210 for HF and BS, respectively] than a₃₀ (h² = 0.148 and h² = 0.168 for HF and BS, respectively). Milk coagulation properties were more heritable than a single test-day milk yield (h² = 0.103 and h² = 0.097 for HF and BS, respectively) and less heritable than milk composition traits whose heritability ranged from 0.275 to 0.275, with the only exception of fat content of BS milk (h² = 0.108). A negative genetic correlation, lower than −0.85, was estimated between RCT and a₃₀ for both breeds. Genetic relationships of MCP with yield and composition were low or moderate and favorable. The genetic correlation of somatic cell score with RCT in BS cows was large and positive and even more positive were those of RCT with pH and titratable acidity in both breeds, ranging from 0.80 to 0.94. Including NC milk information in the data affected the estimated correlations and decreased the uncertainty associated with the estimation process. On the basis of the estimated heritabilities and genetic correlations, enhancement of MCP through selective breeding with no detrimental effects on yield and composition seems feasible in both breeds. Milk acidity may play a role as an indicator trait for indirect enhancement of MCP.     

Estimation of heritabilities and correlations associated with milk color traits

The objective of this study was to estimate the genetic parameters associated with milk color traits of dairy cattle. The data consisted of test day records of 9516 first lactation dairy cows and the records of 6358 of these cows that went on to produce a second lactation. Friesians, Jerseys, and crossbred cows were included in the data. Test day records included measures of milk, fat, and protein as well as milk color measured as absorbance at 450 nm. From these measurements, fat color and beta-carotene yield were calculated. Analyses were performed both within and across breeds. Jerseys produced more beta-carotene than did Friesians, and milk and fat from Jerseys had more intense color. Lactation model estimates for the heritabilities of milk color traits ranged from 0.33 to 0.44 (across breed), 0.40 to 0.49 (Friesians), and 0.17 to 0.31 (Jerseys). In all analyses, the heritability estimates associated with beta-carotene yield were lower than the estimates associated with the color of milk or fat. Genetic correlations between beta-carotene yield and the production traits were positive, but genetic correlations between fat color and production traits were generally negative. Genetic correlations between milk color and milk and protein yields were negative, and the correlations with fat yield were close to zero.     

Genetic analysis of atypical progesterone profiles in Holstein-Friesian cows from experimental research herds

The objective of this study was to quantify the genetic variation in normal and atypical progesterone profiles and investigate if this information could be useful in an improved genetic evaluation for fertility for dairy cows. The phenotypes derived from normal profiles included cycle length traits, including commencement of luteal activity (C-LA), interluteal interval, luteal phase length. and interovulatory interval. In total, 44,977 progesterone test-day records were available from 1,612 lactations on 1,122 primiparous and multiparous Holstein-Friesian cows from Ireland, the Netherlands, Sweden, and the United Kingdom. The atypical progesterone profiles studied were delayed cyclicity, prolonged luteal phase, and cessation of cyclicity. Variance components for the atypical progesterone profiles were estimated using a sire linear mixed model, whereas an animal linear mixed model was used to estimate variance components for the cycle length traits. Heritability was moderate for delayed cyclicity (0.24 ± 0.05) and C-LA (0.18 ± 0.04) but low for prolonged luteal phase (0.02 ± 0.04), luteal phase length (0.08 ± 0.05), interluteal interval (0.08 ± 0.14), and interovulatory interval (0.03 ± 0.04). No genetic variation was detected for cessation of cyclicity. Commencement of luteal activity, luteal phase length, and interovulatory interval were moderately to strongly genetically correlated with days from calving to first service (0.35 ± 0.12, 0.25 ± 0.14, and 0.76 ± 0.24, respectively). Delayed cyclicity and C-LA are traits that can be important in both genetic evaluations and management of fertility to detect (earlier) cows at risk of compromised fertility. Delayed cyclicity and C-LA were both strongly genetically correlated with milk yield in early lactation (0.57 ± 0.14 and 0.45 ± 0.09, respectively), which may imply deterioration in these traits with selection for greater milk yield without cognizance of other traits.     

Milk, fat, protein, somatic cell score, and days open among Holstein, Brown Swiss, and their crosses

The objectives of this study were to compare Holstein (HO), Brown Swiss (BS), and their crosses for milk, fat, and protein yields, somatic cell score (SCS), days open (DO), and age at first calving (AFC), and to estimate the effects of heterosis and recombination. First through fifth lactation records were obtained from 19 herds milking crosses among BS and HO. The edited data set included 6,534 lactation records from 3,473 cows of the following breed combinations: 2,125 pure HO, 926 pure BS, 256 BS sire × HO dam (SH), 105 backcrosses to BS (SX), 18 HO sire × BS dam, and 43 backcrosses to HO. Least squares means for daily milk, fat, and protein yields, mature-equivalent milk, fat, and protein yields, SCS, DO, and AFC were calculated for breed combinations with a model that included fixed effects of age within parity (except for AFC), days in milk for daily yield and SCS, herd-year-season of calving, and breed combination. Cow and error were random effects. Breed combination was replaced with regressions on coefficients for heterosis and recombination in a second analysis. Last, data were analyzed with a 5-trait animal model that included a single pedigree file for both breeds and coefficients for heterosis and recombination. The least squares means for fat production were 1.21, 1.15, 1.27, and 1.16 kg for HO, BS, SH, and SX, respectively, which corresponds to a heterosis estimate of 7.30% and a recombination estimate of −3.76%. Heterosis and recombination estimates for protein production were 5.63% and −3.31%, respectively. Heterosis estimates increased for fat yield (10.38%) and protein yield (7.07%) when maternal grandsire identification from a known artificial insemination sire was required. Regression coefficients indicated an 11.44-d reduction in DO due to heterosis. Heterosis estimates for SCS were inconsistent. Regression on heterosis for SCS was significant and favorable (−0.22) when the breed of sire was BS, but nonsignificant and unfavorable when sire breed was HO (0.43). Heterosis estimates were favorable for all traits, whereas recombination effects tended to be unfavorable for yield traits. Reduced performance of future generations did not appear to be the result of inseminating crossbred cows with inferior sires. Results indicated that first-generation crosses among BS and HO compared favorably with HO. Yield in subsequent generations was somewhat below expectations, perhaps due to recombination loss in HO.     

Voluntary waiting period management practices in dairy herds participating in a progeny test program

A survey was mailed to approximately 4,000 herds participating in a young sire progeny test program to estimate the percentage of herds that selectively alter the voluntary waiting period (VWP) for individual cows or groups of cows. Responses were received from 673 herds (17%; 583 Holsteins, 55 Jerseys, 35 other dairy breeds). The mean VWP cited by respondents was 56 ± 0.6 d (range = 30 to 90 d) and did not differ by breed. Among responding herds, 64% (432/673) indicated the VWP was selectively altered for one or more reasons. The most frequently cited reasons for altering the VWP were postpartum health (50%), season (18%), milk yield (18%), parity (14%), and other reasons (14%). In Holstein herds that altered the VWP based on milk yield, the highest production group averaged 14 more days to first service than the lowest production group (≥40 vs. <20 kg of energy-corrected milk, respectively). In contrast, days to first service were nearly identical for all production groups in Holstein herds that did not vary the VWP based on milk yield. In conclusion, management decisions to selectively alter the VWP led to differences in days to first service and may have a confounding effect on genetic estimates of daughter fertility. Opportunities to improve the accuracy of daughter pregnancy rate estimates may reside in models that adjust for VWP management decisions on a within-herd basis.     

Factors affecting the plasmin-plasminogen system in milk obtained from three Greek dairy sheep breeds with major differences in milk production capacity

The purpose of this study was to evaluate the effect of breed, stage of lactation, and health status of the udder on the plasmin-plasminogen system in ovine milk. A total of 38 ewes were used from 3 breeds [Boutsiko (n = 12), Chios (n = 12), and a synthetic breed (50% Boutsiko, 25% Arta, and 25% Chios, n = 14)] with major differences in their genetic potential with respect to milk yield. Milk samples were collected every 2 wk throughout the lactation period and were analyzed for fat, protein, lactose, and somatic cell count (SCC). In addition, milk plasmin (PL), plasminogen (PG), and plasminogen activator (PA) activities were determined. The Chios breed had the greatest average daily milk yield, the synthetic breed had an intermediate milk yield, and ewes of the Boutsiko breed had the lowest milk yield. Milk samples obtained from the Boutsiko breed had similar PL and PA activities, compared with those obtained from the other 2 breeds. The ratio of PG:PL was less in milk samples from the Boutsiko breed compared with the other 2 breeds, indicative of an increased rate of conversion of PG to PL for this breed. There was no correlation between PL activity and daily milk yield in ewes from all 3 breeds. Activities of PL, PG, and PA were greater in ovine milk with elevated SCC (>300,000/mL) compared with activities in milk with low SCC (<300,000/mL). The ratio of PG:PL was less in the high-SCC group compared with the low-SCC group, which indicates an increased rate of conversion of PG to PL for the high-SCC group. There was a decrease in PG and PA activities as well as in the PG:PL ratio in late lactation milk (mo 5 to 6) when compared with early or mid lactation milk (mo 1 to 4). Thus, the PL-PG system is affected by breed, stage of lactation, and the health status of the udder. No relationship was found between PL activity and daily milk yield in the 3 Greek dairy sheep breeds. Plasmin is not a marker for gradual involution in the Greek sheep breeds studied.     

Environmental sensitivity of milk production in extensive environments: a comparison of Simmental, Brown Swiss, and Tyrol Grey using random regression models

A total of 25,160 milk test-day records from 2,516 cows in first lactation of 3 dairy cattle breeds [Simmental (n = 1,900), Brown Swiss (n = 444), and Tyrol Grey (n = 172)] in Kosovo were analyzed using nested repeatability and random regression test-day models with varying (co)variance structures. The different models were compared based on likelihood-based criteria. The best model was a second-order random regression model, with heterogeneous cow variance per breed and heterogeneous residual variance per lactation month and breed, which was used for further analysis. The highest milk production was found in Brown Swiss, followed by Simmental and Tyrol Grey. Substantial breed differences were found for the trajectories of cow and residual variances by month of lactation, with the highest variances found for Brown Swiss, followed by Simmental and Tyrol Grey. High cow and residual variances indicated a high degree of environmental sensitivity on the macro- and microenvironmental levels, respectively. Thus, these results indicate increased environmental sensitivity for breeds with higher genetic potential for milk production. These results support the conclusion that dairy cattle production under the current environmental conditions of Kosovo should be based on a breed with moderate production that is robust to the diet offered (e.g., Tyrol Grey).     

A comparison between Holstein-Friesian and Jersey dairy cows and their F1 hybrid on milk fatty acid composition under grazing conditions

The objective of this study was to investigate the effect of 2 breeds, Holstein and Jersey, and their F₁ hybrid (Jersey × Holstein) on milk fatty acid (FA) concentrations under grazing conditions, especially conjugated linoleic acid (CLA) and n-3 polyunsaturated fatty acids because of their importance to human health. Eighty-one cows (27 per breed grouping) were allocated a predominantly perennial ryegrass pasture. Samples were collected over 2 periods (June and July). Breed affected dry matter intake and milk production and composition. Holstein cows had the highest dry matter intake (18.4 ± 0.40 kg of DM/d) and milk production (21.1 ± 0.53 kg of DM/d). Holstein and Jersey × Holstein cows had similar 4% fat corrected milk, fat yield, and protein yield; with the exception of fat yield, these were all higher than for Jersey cows. Milk fat concentration was highest for Jersey cows and lowest for Holstein cows, with the hybrid cows intermediate. Total FA and linolenic acid intake (1.09 ± 0.023 and 0.58 ± 0.012 kg/d, respectively) were highest for Holstein cows. In terms of milk FA, Holstein cows had higher contents of C14:1, cis-9 C18:1 and linoleic acid. In turn, Jersey and Jersey × Holstein cows had higher content of C16:0. Milk concentrations of neither the cis-9,trans-11 isomer of CLA nor its precursor, vaccenic acid, were affected by breed. Nevertheless, large variation between individual animals within breed grouping was observed for CLA and estimated Δ⁹-desaturase activity. There was some evidence for a negative heterotic effect on milk concentration of CLA, with the F₁ hybrid cows having lower concentrations compared with the mid parent average. Plasma FA profile did not accurately reflect differences in milk FA composition. In conclusion, there was little evidence for either breed or beneficial heterotic effects on milk FA content with human health-promoting potential, though significant within-breed, interanimal variation was observed.     

Short communication: Effect of environment on the expression of breed and heterosis effects for production traits

Character states of New Zealand herds were formed within the environmental ranges of herd average total lactation yield of fat plus protein (MS), which is a proxy for feeding level, summer heat load index (HLI), herd size, and altitude. A univariate multibreed sire model was applied to first-lactation (2 yr old) records of milk, fat, and protein within each environmental character state to estimate breed and heterosis effects. A scaling effect was observed for MS yield between overseas Holstein-Friesian (OHF) and New Zealand Jersey (NZJ) animals when comparing breed performance in extreme MS character states. For example, differences for milk, fat, and protein yield between these breeds were 561, 1.3, and 9.3 kg, respectively, in the character state averaging 227 kg of MS/cow, much smaller than the differences of 1,151, 3.1, and 23.0 in the character state averaging 376 kg of MS/cow. Heterosis levels for milk, fat, and protein yields were highest for OHF × NZJ, followed by New Zealand Friesian (NZF) × NZJ and OHF × NZF with average heterosis for all traits of 7.3, 5.7, and 2.7%, respectively. Heterosis levels for OHF × NZF were suppressed in very low MS yield environments and in many cases were not significantly different from zero. Heterosis was suppressed in crosses with OHF in the high HLI environment. Crossbred animals (OHF × NZJ, NZF × NZJ, and OHF × NZF) generally achieved higher fat yields than any of the straight-bred animals.     

Genetic effects of heat stress on milk yield of Thai Holstein crossbreds

The threshold for heat stress on milk yield of Holstein crossbreds under climatic conditions in Thailand was investigated, and genetic effects of heat stress on milk yield were estimated. Data included 400,738 test-day milk yield records for the first 3 parities from 25,609 Thai crossbred Holsteins between 1990 and 2008. Mean test-day milk yield ranged from 12.6 kg for cows with <87.5% Holstein genetics to 14.4 kg for cows with ≥93.7% Holstein genetics. Daily temperature and humidity data from 26 provincial weather stations were used to calculate a temperature-humidity index (THI). Test-day milk yield varied little with THI for first parity except above a THI of 82 for cows with ≥93.7% Holstein genetics. For third parity, test-day milk yield started to decline after a THI of 74 for cows with ≥87.5% Holstein genetics and declined more rapidly after a THI of 82. A repeatability test-day model with parities as correlated traits was used to estimate heat stress parameters; fixed effects included herd-test month-test year and breed groups, days in milk, calving age, and parity; random effects included 2 additive genetic effects, regular and heat stress, and 2 permanent environment, regular and heat stress. The threshold for effect of heat stress on test-day milk yield was set to a THI of 80. All variance component estimates increased with parity; the largest increases were found for effects associated with heat stress. In particular, genetic variance associated with heat stress quadrupled from first to third parity, whereas permanent environmental variance only doubled. However, permanent environmental variance for heat stress was at least 10 times larger than genetic variance. Genetic correlations among parities for additive effects without heat stress considered ranged from 0.88 to 0.96. Genetic correlations among parities for additive effects of heat stress ranged from 0.08 to 0.22, and genetic correlations between effects regular and heat stress effects ranged from −0.21 to −0.33 for individual parities. Effect of heat stress on Thai Holstein crossbreds increased greatly with parity and was especially large after a THI of 80 for cows with a high percentage of Holstein genetics (≥93.7%). Individual sensitivity to heat stress was more environmental than genetic for Thai Holstein crossbreds.     

A model for the genetic evaluation of number of clinical mastitis cases per lactation in Czech Holstein cows

Cases of mastitis from 9,550 lactations of 6,242 cows were recorded on 5 farms in the Czech Republic from 1996 to 2008. The number of clinical mastitis (CM) cases per cow adjusted to a lactation length of 305 d was analyzed with 4 linear single-trait animal models and one 3-trait model, which also included lactation mean somatic cell score (SCS) and 305-d milk yield. Factors included in the model of choice were parity, combined effect of herd and a 2-yr calving period, calving season, permanent environmental effect of the cow, and additive genetic effect of the cow. From both the single-trait and multiple-trait models, estimated heritability of number of CM cases was 0.11 (±0.015 for the multiple-trait model). Permanent environmental effects accounted for approximately one-third of the phenotypic variance. Heritability estimates for lactation mean SCS and 305-d milk yield were 0.17 ± 0.019 and 0.25 ± 0.011, respectively, and genetic correlations of these traits with number of CM cases were 0.80 ± 0.059 and 0.34 ± 0.079, respectively. Genetic evaluation of the number of CM cases in Czech Holsteins could be carried out including data from all parities using a 3-trait animal model with SCS and milk yield as additional traits.     

Genetic relationships between persistency and reproductive performance in first-lactation Canadian holsteins

The main objective of this study was to estimate genetic relationships between lactation persistency and reproductive performance in first lactation. Relationships with day in milk at peak milk yield and estimated 305-d milk yield were also investigated. The data set contained 33,312 first-lactation Canadian Holsteins with first-parity reproductive, persistency, and productive information. Reproductive performance traits included age at first insemination, nonreturn rate at 56 d after first insemination as a virgin heifer and as a first-lactation cow, calving difficulty at first calving and calving interval between first and second calving. Lactation persistency was defined as the Wilmink b parameter for milk yield and was calculated by fitting lactation curves to test day records using a multiple-trait prediction procedure. An 8-trait genetic analysis was performed using the Variance Component Estimation package (VCE 5) via Gibbs sampling to estimate genetic parameters for all traits. Heritabilities of persistency, day in milk at peak milk yield and estimated 305-d milk yield were 0.18, 0.09 and 0.45, respectively. Heritabilities of reproduction were low and ranged from 0.03 to 0.19. The highest heritability was for age at first insemination. Heifer reproductive traits were lowly genetically correlated, whereas cow reproductive traits were moderately correlated. Heifers younger than average when first inseminated and/or conceived successfully at first insemination tended to have a more persistent first lactation. First lactation was more persistent if heifers had difficulty calving (r(g) = 0.43), or conceived successfully at first insemination in first lactation (r(g) = 0.32) or had a longer interval between first and second calving (r(g) = 0.17). Estimates of genetic correlations of reproductive performance with estimated 305-d milk yield were different in magnitude, but similar in sign to those with persistency (0.02 to 0.51).     

Method R estimates of heritability for milk, fat, and protein yields of United States dairy cattle.

Heritabilities for milk, fat, and protein yields were estimated from first lactation data used for USDA-Dairy Herd Improvement Association (DHIA) genetic evaluations. Contemporary group assignments and standard deviations within herd-year were determined with the procedure used for national evaluations. Pedigree data were included for animals born since 1970; yield data were included for cows born since 1980. Lactation records were divided into four mutually exclusive data sets based on standard deviations. Ranges for standard deviations were chosen so that data sets were approximately equal in size. Method R was used to estimate heritability with 25 different random samples of half of the data for each data set. Because of the large number of Holstein observations, estimates of heritability for Holsteins were based on random subsets of the complete data file; each subset included approximately 5% of the data. Mean heritability estimates increased with standard deviations, and estimates ranged from 0.18 to 0.51 across breeds. Repeatability estimates for milk yield of Holsteins were approximately 0.50 and did not change with standard deviation. These heritability estimates were higher than those previously used in the USDA-DHIA genetic evaluation. Heritability used in the USDA-DHIA genetic evaluation have been increased based on these results.     

Selection on yield and fitness traits when culling holsteins during the first three lactations

Emphasis by dairy producers on various yield and fitness traits when culling cows was documented for US Holstein calvings since 1982. Least squares differences between cows retained for additional parities and those culled were estimated for milk, fat, and protein yields; somatic cell score (SCS); days open (DO); dystocia score (DS), final score (FS), and 14 type traits. Compared with cows culled during first lactation, superiority for first-parity milk yield was 569 to 1,175 kg for cows with 2 lactations, 642 to 1,283 kg for cows with ≥2 lactations, 710 to 1,350 kg for cows with 3 lactations, and 663 to 1,331 kg for cows with ≥4 lactations. Cows retained for ≥2 lactations had first-parity SCS that were 0.34 to 0.62 lower (more favorable) than those of cows culled during first lactation; first-parity SCS for cows retained for 3 or ≥4 lactations were even more favorable than those of cows with 1 or 2 lactations. The negative genetic relationship between yield and fertility contributed to increased DO as selection for higher milk yield persisted across time despite considerable preference for early conception when culling cows. In 1982, cows retained in the herd for 2, 3, and ≥4 lactations conceived earlier during first lactation (19, 17, and 23 fewer DO, respectively) than those culled during first lactation; those differences had increased to 34, 41, and 52 fewer DO by 2000. Although DS has a negative relationship with survival, first-parity DS were only slightly lower (by 0.10 to 0.14) for survivors than for cows culled during first lactation. Cows retained for ≥2 lactations had greater first-parity FS by 1.4 to 1.9 points than those culled during first lactation. On a standardized basis, the most intense selection during first lactation was for milk and protein yields with less for fat (74 to 86% of that for milk), DO (18 to 74%), FS (22 to 38%), SCS (19 to 37%), and DS (7 to 15%). Producers continued to emphasize the same traits when culling during second and third lactations. Trait priority by producers during culling could aid in setting trait emphasis when selecting bulls for progeny test and could also be useful in developing software for index-based culling guides.