Genetic modelling of test day records in dairy sheep using orthogonal Legendre polynomials

Test day milk yields of three lactations in Sfakia sheep were analyzed fitting a random regression (RR) model, regressing on orthogonal polynomials of the stage of the lactation period, i.e. days in milk. Univariate (UV) and multivariate (MV) analyses were also performed for four stages of the lactation period, represented by average days in milk, i.e. 15, 45, 70 and 105 days, to compare estimates obtained from RR models with estimates from UV and MV analyses. The total number of test day records were 790, 1314 and 1041 obtained from 214, 342 and 303 ewes in the first, second and third lactation, respectively. Error variances and covariances between regression coefficients were estimated by restricted maximum likelihood. Models were compared using likelihood ratio tests (LRTs). Log likelihoods were not significantly reduced when the rank of the orthogonal Legendre polynomials (LPs) of lactation stage was reduced from 4 to 2 and homogenous variances for lactation stages within lactations were considered. Mean weighted heritability estimates with RR models were 0.19, 0.09 and 0.08 for first, second and third lactation, respectively. The respective estimates obtained from UV analyses were 0.14, 0.12 and 0.08, respectively. Mean permanent environmental variance, as a proportion of the total, was high at all stages and lactations ranging from 0.54 to 0.71. Within lactations, genetic and permanent environmental correlations between lactation stages were in the range from 0.36 to 0.99 and 0.76 to 0.99, respectively. Genetic parameters for additive genetic and permanent environmental effects obtained from RR models were different from those obtained from UV and MV analyses.     

Evaluation of reference lactation length in Chios dairy sheep

Definition and establishment of a fixed reference lactation length could provide useful tools for on-farm comparison of ewes and flock management as well as genetic evaluations for the breeding programme. The objectives of this study were to (i) evaluate different reference lactation lengths for the Chios dairy sheep and (ii) define the most suitable reference length for the breed. A total of 260 042 test-day milk records from 24 474 ewes in 130 flocks collected between 2003 and 2014 were used; 15 different lactation lengths were evaluated ranging from 120 to 260 days, defined at 10-day intervals as reference for the Chios sheep. The evaluation criteria included: (a) heritability and repeatability of milk yield in each reference lactation, (b) genetic correlation of reference lactation milk yield with actual lactation milk yield and yield at first test-day record and (c) correlated response in reference lactation milk yield from selection based on first test-day milk yield. The latter emulates genetic gains achieved for milk yield based on early lactation selection. Heritability and repeatability estimates of reference lactation milk yield and genetic correlation with actual lactation yield favoured long reference lactations (180 to 230 days). On the contrary, correlation with first test-day record milk yield was higher for short lactations (120 to 170 days). Moreover, selection on first test-day record milk yield would lead to a correlated response in reference yield in 220 days equal to 85% of the highest estimate achieved in the maximum reference length of 260 days (190 days when only considering first lactation milk yield). Based on the results of the present study, an overall reference lactation length for the Chios breed of 220 days post-lambing and a first lactation reference length of 190 days post-lambing are recommended.     

Relation of Milk Production Loss to Milk Somatic Cell Count

Milk production loss was studied in relation to increased somatic cell count (SCC). Available data were weekly test-day milk yields and SCC (in 1,000 cells/ml), and mastitis incidences. In total, 18,131 records from 274 cows were used. Production loss was determined for test-day kg milk, kg protein, and kg energy-corrected milk. Least-squares analysis of variance was used to estimate the direct effect of Log10(SCC) on production. The recorded measures of production were first corrected for fixed effects, with adjustment factors estimated from a healthy data-set. The average daily milk yield was 19.7 kg/day in first lactation and 22.0 in later lactations. The geometric mean of SCC was 63.1 in first lactation and 107.2 in later lactations. The incidence of clinical mastitis treated by a veterinarian was 19.8% of the lactations-at-risk. Linear relationships were found between the production parameters and Log10(SCC). Quadratic and cubic effects were evaluated, but were found to contribute little to the overall fit of the models. The individual milk yield loss was 1.29 kg/day for each unit increase in Log10(SCC) for cows in first lactation. Milk yield decreased by 2.04 kg/day per unit Log10(SCC) for older cows. Corresponding values for protein yield were 0.042 and 0.067 kg/day for first and later lactations, respectively.     

The Effect of Calf Gender on Milk Production in Seasonal Calving Cows and Its Impact on Genetic Evaluations

Gender of the calf whose birth initiates lactation could influence whole lactation milk yield of the dam due to hormonal influences on mammary gland development, or through calf gender effects on gestation length. Fetal gender could influence late lactation yields because cows become pregnant at peak lactation. The effects of calf gender sequences in parities 1–3 were assessed by separately fitting animal models to datasets from New Zealand comprising 274 000 Holstein Friesian and 85 000 Jersey cows, decreasing to 12 000 and 4 000 cows by parity 3. The lactation initiated by the birth of a female rather than a male calf was associated with a 0.33–1.1% (p≤0.05) higher milk yield. Female calf gender had carryover effects associated with higher milk yield in second lactations for Holstein Friesians (0.24%; p = 0.01) and third lactations for Jerseys (1.1%; p = 0.01). Cows giving birth to bull calves have 2 day longer gestations, which reduces lactation length in seasonal calving herds. Adding a covariate for lactation length to the animal model eroded some of these calf gender effects, such that calving a female led to higher milk yield only for second lactation Holstein Friesians (1.6%; p = 0.002). The interval centering method generates lower estimates of whole lactation yield when Wood’s lactation curves are shifted to the right by 2 days for male calves and this explained the higher yield in female calves when differences in lactation length were considered. Correlations of estimated breeding values between models including or excluding calf gender sequence were 1.00 for bulls or cows. Calf gender primarily influences milk yield through increased gestation length of male calves, and bias associated with the interval centering method used to estimate whole lactation milk yields. Including information on calf gender is unlikely to have an effect on selection response in New Zealand dairy cattle.     

Estimates of correlations among yield traits and somatic cell score with different models to adjust for bovine somatotropin effects on Holstein dairy cows

Records of Holstein cows from the Dairy Records Processing Center at Raleigh, NC were edited to obtain three data sets: 65,720 first, 50,694 second, and 65,445 later lactations. Correlations among yield traits and somatic cell score were estimated with three different models: 1) bovine somatotropin (bST) administration ignored, 2) bST administration as a fixed effect and 3) administration of bST as part of the contemporary group (herd-year-month-bST). Heritability estimates ranged from 0.13 to 0.17 for milk, 0.12 to 0.20 for fat, 0.14 to 0.16 for protein yields, and 0.08 to 0.09 for somatic cell score. Estimates were less for later than first lactations. Estimates of genetic correlations among yields ranged from 0.35 to 0.85 with no important differences between estimates with the 3 models. Estimates for lactation 2 agreed with estimates for lactation 1. Estimates of genetic correlations for later lactations were generally greater than for lactations 1 and 2 except between milk and protein yields. Estimates of genetic correlations between yields and somatic cell score were mostly negative or small (-0.45 to 0.11). Estimates of environmental correlations among yield traits were similar with all models (0.77 to 0.97). Estimates of environmental correlations between yields and somatic cell score were negative (-0.22 to -0.14). Estimates of phenotypic correlations among yield traits ranged from 0.70 to 0.95. Estimates of phenotypic correlations between yields and somatic cell score were small and negative. For all three data sets and all traits, no important differences in estimates of genetic parameters were found for the two models that adjusted for bST and the model that did not.     

Effects of stage of pregnancy on variance components,daily milk yields and 305-day milk yield in Holstein cows,as estimated by using a test-day model

Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (P<0.05) greater than that after the first calving. Therefore, we conclude that differences between the negative effects of early pregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open to maximize lifetime productivity in dairy cows.     

Milk yield and composition in mice: effects of litter size and lactation number

Milk yield was measured by a tritiated water dilution procedure during consecutive lactations in mice suckling four, 10 or 18 young. Analysis of variance revealed positive effects of lactation number and litter size on milk yield. There was a significant correlation between maternal body weight and parity; increased body weight accounted for some, but not all, of the parity-related increases in milk yield. Peak milk yield was reached between days 10 and 16 of lactation, but the efficiency with which the growing young utilized milk for weight gain was greatest before day 7. Milk composition varied significantly during the course of lactation.     

Genetic and phenotypic parameters of lactations longer than 305 days (extended lactations)

Test-day milk yield and somatic cell count data over extended lactation (lactation to 540-600 days) were analysed considering part lactations as different traits and fitting random regression (RR) models. Data on Australian Jersey and Holstein Friesian (HF) were used to demonstrate the shape of the lactation curve and data on HF were used for genetic study. Test-day data from about 100 000 cows that calved between 1998 and 2005 were used for this study. In all analyses, a sire model was used.When part lactations were considered as different traits, protein yield early in the lactation (e.g. first 2 months) had a genetic correlation of about 0.8 with protein yield produced after 300 days of lactation. Genetic correlations between lactation stages that are adjacent to each other were high (0.9 or more) within parity. Across parities, genetic correlations were high for both protein and milk yield if they are within the same stage of lactation. Phenotypic correlations were lower than genetic correlations. Heritability of milk-yield traits estimated from the RR model varied from 0.15 at the beginning of the lactation to as high as 0.37 by the 4th month of lactation. All genetic correlations between different days in milk were positive, with the highest correlations between adjacent days in milk and decreasing correlations with increasing time-span. The pattern of genetic correlations between milk yield in the second 300 days (301 to 600 days of lactation) do not markedly differ from the pattern in the first 300 days of lactation. The lowest estimated genetic correlation was 0.15 between milk yield on days 45 and 525 of lactation. The result from this study shows that progeny of bulls with high estimated breeding values for yield traits and those that produce at a relatively high level in the first few months are the most likely candidates for use in herds favouring extended lactations.     

Influence of the dam and sire on size at birth and subsequent growth, milk production and fertility in dairy heifers

Genetic selection has resulted in larger cows with high milk production potential but a tendency for poor fertility. In multiparous cows fetal development competes for nutrients with concurrent milk production. This study tested the hypotheses that (a) maternal age and milk yield during pregnancy alter calf birth size and (b) birth weight influences subsequent productivity and fertility. Concurrently born Holstein-Friesian heifers (n=65) with multiparous dams and three sires were monitored from birth to the end of their first lactation to assess effects of birth weight on growth, milk production and fertility. Calves were analyzed as three subgroups: low (L), average (A) and high (H) birth weight (BW) calves (n=21-22 per group). LBW calves were born 10 kg lighter than HBW calves and remained significantly lighter throughout the study. They were generally smaller in other measured indices (length, height, girth, ponderal index) between birth and 9 months and were more likely to have older dams (lactations 3-6) with higher peak yields (>42 kg/day). Milk production parameters were indistinguishable between the 3 birthweight groups and metabolic parameters (IGF-I, insulin, glucose) measured around first calving were unaffected. HBW offspring were more likely to have persistent corpora lutea following their first calving and other fertility parameters also tended to be worse. Sire influenced gestation length but not birth size. Sire heritability estimates showed that weight, IGF-I and insulin concentrations after first calving and fertility in the first lactation were all heritable. The results support the hypothesis that high milk production in the dam may predispose to birth of a smaller calf. Smaller birth size did not, however, have any subsequent adverse effects on productivity or fertility in the first lactation and sire was more influential at this stage.     

Changes in the yield, and carbohydrate, lipid and protein content of milk during lactation in the rat

The milk yield and composition was studied during the first three lactations of a group of rats. Milk yield increased steadily throughout the three lactations, but was somewhat lower during the first than subsequent lactations. Protein concentration was similar during all three lactations and varied little with stage of lactation. In contrast the lactose concentration, which was reasonably constant for the first 8 days post partum, increased thereafter two-fold by the end of the period studied in all three lactations. However, the N-acetyl-neuraminyl lactose concentration showed somewhat reciprocal changes. Considerable variations in the triacylglycerol concentration was found during the first lactation but few changes were observed during subsequent lactations. The free fatty acid concentration was at all times low and showed no significant changes during or between lactations. At most stages of lactation in raw milk, the major fatty acids are palmitate, oleate and linoleate. However, as lactation progresses there is an increase in the proportion of medium-chain saturated fatty acids and a corresponding decrease in the proportion of long chain unsaturated fatty acids in milk fat. Clearly the composition of milk is not invariable but changes both during and between lactations. Such changes may be expected to have some influence on the metabolism of the offspring.     

Relationships between conception rate in Holstein heifers and cows and milk yield at various stages of lactation

We investigated the relationships between conception rates (CRs) at first service in Japanese Holstein heifers (i.e. animals that had not yet had their first calf) and cows and their test-day (TD) milk yields. Data included records of artificial insemination (AI) for heifers and cows that had calved for the first time between 2000 and 2008 and their TD milk yields at 6 through 305 days in milk (DIM) from first through third lactations. CR was defined as a binary trait for which first AI was a failure or success. A threshold-linear animal model was applied to estimate genetic correlations between CRs of heifers or cows and TD milk yield at various lactation stages. Two-trait genetic analyses were performed for every combination of CR and TD milk yield by using the Bayesian method with Gibbs sampling. The posterior means of the heritabilities of CR were 0.031 for heifers, 0.034 for first-lactation cows and 0.028 for second-lactation cows. Heritabilities for TD milk yield increased from 0.324 to 0.433 with increasing DIM but decreased slightly after 210 DIM during first lactation. These heritabilities from the second and third lactations were higher during late stages of lactation than during early stages. Posterior means of the genetic correlations between heifer CR and all TD yields were positive (range, 0.082 to 0.287), but those between CR of cows and milk yields during first or second lactation were negative (range, −0.121 to −0.250). Therefore, during every stage of lactation, selection in the direction of increasing milk yield may reduce CR in cows. The genetic relationships between CR and lactation curve shape were quite weak, because the genetic correlations between CR and TD milk yield were constant during the lactation period.     

A note on the effect of variation of lactation length on the efficiency of tropical cattle selection for milk yield

Summary The effects of procedures generally used to reduce variation of lactation length on the efficiency of selection for milk yield are examined applying existing theory to a set of average literature estimates of heritabilities and correlations between lactation yield and length. Adjustment of milk yield for lactation length should be expected to remove more genetic than phenotypic variation, thus reducing selection efficiency in relation to unadjusted yield. Selecting individuals on an optimum index of lactation yield and length would be more efficient for improving yield than selecting on yield alone, while both criteria would have practically the same efficiency for selection on progeny test. This result could be applied to reduce milk recording frequency without losing selection accuracy. Culling on lactation length before selecting on yield would have little effect on individual selection efficiency. However, excluding short lactation records should be expected to reduce both selection accuracy of the progeny test and genetic variation in yield.     

Application of the covariance function approach with an iterative two-stage algorithm to the estimation of parameters of a random regression test day model for dairy production traits

The covariance function approach with an iterative two-stage algorithm of LIU et al. (2000) was applied to estimate parameters for the Polish Black-and-White dairy population based on a sample of 338 808 test day records for milk, fat, and protein yields. A multiple trait sire model was used to estimate covariances of lactation stages. A third-order Legendre polynomial was subsequently fitted to the estimated (co)variances to derive (co)variances of random regression coefficients for both additive genetic and permanent environment effects. Daily and 305-day heritability estimates obtained are consistent with several studies which used both fixed and random regression test day models. Genetic correlations between any two days in milk (DIM) of the same lactation as well as genetic correlations between the same DIM of two lactations were within a biologically acceptable range. It was shown that the applied estimation procedure can utilise very large data sets and give plausible estimates of (co)variance components.     

Genetic and phenotypic parameters for test day milk yield of Sahiwal cattle in the semi-arid tropics

A total of 19 376 test day (TD) milk yield records from the first three lactations of 1618 cows daughters of 162 sires were used to estimate genetic and phenotypic parameters and determine the relationship between daily milk yield and lactation milk yield in the Sahiwal cattle in Kenya. Variance components were estimated using animal models based on a derivative free restricted maximum likelihood procedure. Variance components were estimated using various univariate and multi-trait fixed regression test day models (TDM) that defined contemporary groups either based on the year-season of calving (YSCV) or on the year-season of TD milk sampling (YSTD). Variance components were influenced by CG which resulted in differences in heritability and repeatability estimates between TDM. Models considering YSTD resulted in higher additive genetic variances and lower residual variances compared with models in which YSCV was considered. Heritability estimates for daily yield ranged from 0.28 to 0.46, 0.38 to 0.52 and 0.33 to 0.52 in the first, second and third lactation, respectively. In the first and second lactation, the heritability estimates were highest between TD 2 and TD 4. Genetic correlations among daily milk yields ranged from 0.41 to 0.93, 0.50 to 0.83 and 0.43 to 86 in the first, second and third lactation, respectively. The phenotypic correlations were correspondingly lower. Genetic correlations were different from unit when fitting multi-trait TDM. Therefore, a multiple trait model would be more ideal in determining the genetic merit of dairy sires and bulls based on daily yield records. Genetic and phenotypic correlations between daily yield and lactation yields were high and positive. Genetic correlations ranged from 0.84 to 0.99, 0.94 to 1.00 and 0.94 to 0.97 in the first, second and third lactations, respectively. The corresponding phenotypic correlation estimates ranged from 0.50 to 0.85, 0.50 to 0.83 and 0.53 to 0.87. The high genetic correlation between daily yield and lactation yield imply that both traits are influenced by similar genes. Therefore daily yields records could be used in genetic evaluation in the Sahiwal cattle breeding programme.     

The effect of lactation length on greenhouse gas emissions from the national dairy herd

Many governments have signed up to greenhouse gas emission (GHGE) reduction programmes under their national climate change obligations. Recently, it has been suggested that the use of extended lactations in dairy herds could result in reduced GHGE. Dairy GHGE were modelled on a national basis and the model was used to compare emissions from lactations of three different lengths (305, 370 and 440 days), and a current ‘base’ scenario on the basis of maintaining current milk production levels. In addition to comparing GHGE from the average ‘National Herd’ under these scenarios, results were used to investigate how accounting for lactations of different lengths might alter the estimation of emissions calculated from the National Inventory methodology currently recommended by Intergovernmental Panel on Climate Change. Data for the three lactation length scenarios were derived from nationally recorded dairy performance information and used in the GHGE model. Long lactations required fewer milking cows and replacements to maintain current milk yield levels than short ones, but GHGEs were found to rise from 1214 t of CO₂ equivalent (CE)/farm per year for lactations of 305 days to 1371 t CE/farm per year for 440-day lactations. This apparent anomaly can be explained by the less efficient milk production (kg milk produced per kg cow weight) found in later lactation, a more pronounced effect in longer lactations. The sensitivity of the model to changes in replacement rate, persistency and level of milk yield was investigated. Changes in the replacement rate from 25% to 20% and in persistency by −10% to +20% resulted in very small changes in GHGE. Differences in GHGE due to the level of milk yield were much more dramatic with animals in the top 10% for yield, producing about 25% less GHGE/year than the average animal. National Inventory results were investigated using a more realistic spread of lactation lengths than recommended for such calculations using emissions calculated in the first part of the study. Current UK emission calculations based on the National Inventory were 329 Gg of methane per year from the dairy herd. Using the national distribution of lactation lengths, this was found to be an underestimate by about 10%. This work showed that the current rise in lactation length or a move towards calving every 18 months would increase GHGE by 7% to 14% compared with the current scenario, assuming the same milk yield in all models. Increased milk yield would have a much greater effect on reducing GHGE than changes to lactation length, replacement rate or persistency. National Inventory methodology appears to underestimate GHGE when the distribution of lactation lengths is considered and may need revising to provide more realistic figures.     

Genetic parameters for production,health, fertility and longevity traits in dairy cows

Milk production, fertility, longevity and health records, were extracted from databases of two milk recording organisations in the United Kingdom for the first three lactations of the Holstein–Friesian breed. These included data related to health events (mastitis and lameness), voluntarily recorded on a proportion of farms. The data were analysed to calculate disease incidence levels and to estimate genetic parameters for health traits and their relationships with production and other functional traits. The resulting dataset consisted of 124 793 lactations from 75 137 animals of 1586 sires, recorded in 2434 herds. Incidence of health events increased with parity. The overall incidence of mastitis (MAS) and lameness (LAM), defined as binary traits, were 17% and 16%, respectively. Heritability estimates for MAS and LAM were 0.04 and 0.02, respectively, obtained from repeatability linear sire models. Heritability estimates of mastitis and lameness as count traits were slightly higher, 0.05 and 0.03, respectively. Genetic correlations were obtained by bivariate analyses of all pair-wise combinations between milk 305-day yield (MY), protein 305-day yield (PY), fat 305-day yield (FY), lactation average log_e transformed lactation average somatic cell count (SCS), calving interval (CI), days to first service (DFS), non-return at 56 days (NR56), number of inseminations (NINS), mastitis (MAS), number of mastitis episodes (NMAS), lameness (LAM), number of lameness episodes (NLAM) and lifespan score (LS). As expected, MAS was correlated most strongly with SCS (0.69), which supports the use of SCS as an indicator trait for mastitis. Genetic correlations between MAS and yield and fertility traits were of similar magnitude ranging from 0.27 to 0.33. Genetic correlations between MAS with LAM and LS were 0.38 and −0.59, respectively. Not all genetic correlations between LAM and other traits were significant because of fewer numbers of lameness records. LAM had significant genetic correlations with MY (0.38), PY (0.28), CI (0.35), NINS (0.38) and LS (−0.53). The heritability estimates of mastitis and lameness were low; therefore, genetic gain through direct selection alone would be slow, yet still positive and cumulative. Direct selection against mastitis and lameness as additional traits should reduce incidence of both diseases, and simultaneously improve fertility and longevity. However, both health traits had antagonistic relationships with production traits, thus genetic gain in production would be slower.     

Genetic and phenotypic correlations among feed efficiency,production and selected conformation traits in dairy cows

The difficulties and costs of measuring individual feed intake in dairy cattle are the primary factors limiting the genetic study of feed intake and utilisation, and hence the potential of their subsequent industry-wide applications. However, indirect selection based on heritable, easily measurable, and genetically correlated traits, such as conformation traits, may be an alternative approach to improve feed efficiency. The aim of this study was to estimate genetic and phenotypic correlations among feed intake, production, and feed efficiency traits (particularly residual feed intake; RFI) with routinely recorded conformation traits. A total of 496 repeated records from 260 Holstein dairy cows in different lactations (260, 159 and 77 from first, second and third lactation, respectively) were considered in this study. Individual daily feed intake and monthly BW and body condition scores of these animals were recorded from 5 to 305 days in milk within each lactation from June 2007 to July 2013. Milk yield and composition data of all animals within each lactation were retrieved, and the first lactation conformation traits for primiparous animals were extracted from databases. Individual RFI over 301 days was estimated using linear regression of total 301 days actual energy intake on a total of 301 days estimated traits of metabolic BW, milk production energy requirement, and empty BW change. Pair-wise bivariate animal models were used to estimate genetic and phenotypic parameters among the studied traits. Estimated heritabilities of total intake and production traits ranged from 0.27±0.07 for lactation actual energy intake to 0.45±0.08 for average body condition score over 301 days of the lactation period. RFI showed a moderate heritability estimate (0.20±0.03) and non-significant phenotypic and genetic correlations with lactation 3.5 % fat-corrected milk and average BW over lactation. Among the conformation traits, dairy strength, stature, rear attachment width, chest width and pin width had significant (P<0.05) moderate to strong genetic correlations with RFI. Combinations of these conformation traits could be used as RFI indicators in the dairy genetic improvement programmes to increase the accuracy of the genetic evaluation of feed intake and utilisation included in the index.     

Data transformation for rank reduction in multi-trait MACE model for international bull comparison

Since many countries use multiple lactation random regression test day models in national evaluations for milk production traits, a random regression multiple across-country evaluation (MACE) model permitting a variable number of correlated traits per country should be used in international dairy evaluations. In order to reduce the number of within country traits for international comparison, three different MACE models were implemented based on German daughter yield deviation data and compared to the random regression MACE. The multiple lactation MACE model analysed daughter yield deviations on a lactation basis reducing the rank from nine random regression coefficients to three lactations. The lactation breeding values were very accurate for old bulls, but not for the youngest bulls with daughters with short lactations. The other two models applied principal component analysis as the dimension reduction technique: one based on eigenvalues of a genetic correlation matrix and the other on eigenvalues of a combined lactation matrix. The first one showed that German data can be transformed from nine traits to five eigenfunctions without losing much accuracy in any of the estimated random regression coefficients. The second one allowed performing rank reductions to three eigenfunctions without having the problem of young bulls with daughters with short lactations.     

Lamb and milk production of Awassi and East-Friesian sheep and their crosses under Mediterranean environment

Data on lambs born per ewe put to the ram (LB/EP), lambs born per ewe lambing (LB/EL), milk production through lactation and lactation length up to six lambings of 603 Awassi (A), East-Friesian (EF), A × EF (F1), F1 × F1 (F2), EF × F1 (1/4A), 1/4A × F1 (3/8A¹) and 3/8A¹ × 3/8A¹ (3/8A²) ewes bred in the same flock in the years 1956–1971 were analysed. The data were obtained from 2293 ewe-years, 1993 lambings and 1698 lactations. Genotype, age at lambing and sire within genotype had an (P < 0.05) effect on each trait. Effect of year of birth, genotype by age at lambing interaction and genotype by year of birth interaction were significant (P < 0.05) for milk production but not for lamb production. The effects of litter size on milk yield and lactation length were not significant. Least squares means (LSM) of LB/EP were highest in 3/8A² (1.48) and lowest in Awassi (0.98). LSMs of LB/EL were highest in EF (1.60), and lowest in Awassi (1.11). The LSMs of milk yield of A, F1, F2 and 3/8A² were similar, ranging from 223 to 248.1. The milk yield of EF was the lowest: only 161 1. The LSMs for lactation length were similar in all genotypes, about 198 days except for 1/4A and EF which had shorter (P < 0.05) lactations. The Awassi-transmitted effects were positive (P < 0.001) for lactation length and milk yield, and negative (P < 0.001) for LB/EL. Heterosis (P < 0.001) was found for LB/EL, milk yield and lactation length. Recombination effect was not significant for any trait.     

Analysis of lactation shapes in extended lactations

In order to describe the temporal evolution of milk yield (MY) and composition in extended lactations, 21 658 lactations of Italian Holstein cows were analyzed. Six empirical mathematical models currently used to fit 305 standard lactations (Wood, Wilmink, Legendre, Ali and Schaeffer, quadratic and cubic splines) and one function developed specifically for extended lactations (a modification of the Dijkstra model) were tested to identify a suitable function for describing patterns until 1000 days in milk (DIM). Comparison was performed on individual patterns and on average curves grouped according to parity (primiparous and multiparous) and lactation length (standard ⩽305 days, and extended from 600 to 1000 days). For average patterns, polynomial models showed better fitting performances when compared with the three or four parameters models. However, LEG and spline regression, showed poor prediction ability at the extremes of the lactation trajectory. The Ali and Schaeffer polynomial and Dijkstra function were effective in modelling average curves for MY and protein percentage, whereas a reduced fitting ability was observed for fat percentage and somatic cell score. When individual patterns were fitted, polynomial models outperformed nonlinear functions. No detectable differences were observed between standard and extended patterns in the initial phase of lactation, with similar values of peak production and time at peak. A considerable difference in persistency was observed between 200 and 305 DIM. Such a difference resulted in an estimated difference between standard and extended cycle of about 7 and 9 kg/day for daily yield at 305 DIM and of 463 and 677 kg of cumulated milk production at 305 DIM for the first- and second-parity groups, respectively. For first and later lactation animals, peak yield estimates were nearly 31 and 38 kg, respectively, and occurred at around 65 and 40 days. The asymptotic level of production was around 9 kg for multiparous cows, whereas the estimate was negative for first parity.