Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model

Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.     

Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models

Covariance components for test day milk yield using 263 390 first lactation records of 32 448 Holstein cows were estimated using random regression animal models by restricted maximum likelihood. Three functions were used to adjust the lactation curve: the five-parameter logarithmic Ali and Schaeffer function (AS), the three-parameter exponential Wilmink function in its standard form (W) and in a modified form (W*), by reducing the range of covariate, and the combination of Legendre polynomial and W (LEG+W). Heterogeneous residual variance (RV) for different classes (4 and 29) of days in milk was considered in adjusting the functions. Estimates of RV were quite similar, rating from 4.15 to 5.29 kg². Heritability estimates for AS (0.29 to 0.42), LEG+W (0.28 to 0.42) and W* (0.33 to 0.40) were similar, but heritability estimates used W (0.25 to 0.65) were highest than those estimated by the other functions, particularly at the end of lactation. Genetic correlations between milk yield on consecutive test days were close to unity, but decreased as the interval between test days increased. The AS function with homogeneous RV model had the best fit among those evaluated.     

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β(0) + β(1)X + e), quadratic regression, (y = β(0) + β(1)X + β(2)X(2) + e) cubic regression (y = β(0) + β(1)X + β(2)X(2) + β(3)X(3) +e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.     

Statistical analysis of test-day milk yields using random regression models for the comparison of feeding groups during the lactation period

Random regression models are widely used in the field of animal breeding for the genetic evaluation of daily milk yields from different test days. These models are capable of handling different environmental effects on the respective test day, and they describe the characteristics of the course of the lactation period by using suitable covariates with fixed and random regression coefficients. As the numerically expensive estimation of parameters is already part of advanced computer software, modifications of random regression models will considerably grow in importance for statistical evaluations of nutrition and behaviour experiments with animals. Random regression models belong to the large class of linear mixed models. Thus, when choosing a model, or more precisely, when selecting a suitable covariance structure of the random effects, the information criteria of Akaike and Schwarz can be used. In this study, the fitting of random regression models for a statistical analysis of a feeding experiment with dairy cows is illustrated under application of the program package SAS. For each of the feeding groups, lactation curves modelled by covariates with fixed regression coefficients are estimated simultaneously. With the help of the fixed regression coefficients, differences between the groups are estimated and then tested for significance. The covariance structure of the random and subject-specific effects and the serial correlation matrix are selected by using information criteria and by estimating correlations between repeated measurements. For the verification of the selected model and the alternative models, mean values and standard deviations estimated with ordinary least square residuals are used.     

Statistical analysis of test-day milk yields using random regression models for the comparison of feeding groups during the lactation period

Abstract

Random regression models are widely used in the field of animal breeding for the genetic evaluation of daily milk yields from different test days. These models are capable of handling different environmental effects on the respective test day, and they describe the characteristics of the course of the lactation period by using suitable covariates with fixed and random regression coefficients. As the numerically expensive estimation of parameters is already part of advanced computer software, modifications of random regression models will considerably grow in importance for statistical evaluations of nutrition and behaviour experiments with animals. Random regression models belong to the large class of linear mixed models. Thus, when choosing a model, or more precisely, when selecting a suitable covariance structure of the random effects, the information criteria of Akaike and Schwarz can be used. In this study, the fitting of random regression models for a statistical analysis of a feeding experiment with dairy cows is illustrated under application of the program package SAS. For each of the feeding groups, lactation curves modelled by covariates with fixed regression coefficients are estimated simultaneously. With the help of the fixed regression coefficients, differences between the groups are estimated and then tested for significance. The covariance structure of the random and subject-specific effects and the serial correlation matrix are selected by using information criteria and by estimating correlations between repeated measurements. For the verification of the selected model and the alternative models, mean values and standard deviations estimated with ordinary least square residuals are used.     

Bayesian inference of genetic parameters for test-day milk yield, milk quality traits, and somatic cell score in Burlina cows

The aim of the study was to infer (co)variance components for daily milk yield, fat and protein contents, and somatic cell score (SCS) in Burlina cattle (a local breed in northeast Italy). Data consisted of 13576 monthly test-day records of 666 cows (parities 1 to 8) collected in 10 herds between 1999 and 2009. Repeatability animal models were implemented using Bayesian methods. Flat priors were assumed for systematic effects of herd test date, days in milk, and parity, as well as for permanent environmental, genetic, and residual effects. On average, Burlina cows produced 17.0 kg of milk per day, with 3.66 and 3.33% of fat and protein, respectively, and 358000 cells per mL of milk. Marginal posterior medians (highest posterior density of 95%) of heritability were 0.18 (0.09–0.28), 0.28 (0.21–0.36), 0.35 (0.25–0.49), and 0.05 (0.01–0.11) for milk yield, fat content, protein content, and SCS, respectively. Marginal posterior medians of genetic correlations between the traits were low and a 95% Bayesian confidence region included zero, with the exception of the genetic correlation between fat and protein contents. Despite the low number of animals in the population, results suggest that genetic variance for production and quality traits exists in Burlina 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.     

Lucerne silage in high yielding dairy cows: effect of parity and analysis of reasons in mixed-parity group housing using random regression test-day models

A study with high-yielding dairy cows was re-analysed in order to test the suitability of lucerne silage separately for primi- and multiparous cows as an alternative to grass silage in maize-based total mixed rations (TMR). Lactation curves were fitted using random regression test-day models for energy corrected milk (ECM) and dry matter intake (DMI) as well as for number and duration of feeder visits (NFV and DFV, respectively). Existing models for ECM and DMI were extended by animal-specific random effects, which were formulated in their dependency on days in milk. For NFV and DFV random regression models were applied for the very first time. The chosen approach of statistical analysis permitted comparisons of the lactation curves as well as of least square means for sub-periods to answer nutritional questions. Whilst primiparous cows had generally lower DMI and ECM as compared to multiparous cows, only in primiparous cows a negative effect of lucerne TMR on ECM was observed, especially in early lactation. Nutritional factors should be rejected because of very similar ECM between the various TMR in multiparous cows. Traits of feeding behaviour indicated that particle size could contribute to the decreased ECM. Even more impact on the lower ECM should be addressed to domination behaviour of multiparous cows. The resulting restlessness of primiparous cows caused a reduced intake per minute spent at the feeder. Further studies should focus on optimising the proportion and chopping length of lucerne in the diet and to improve flock management to maximise feed intake of primiparous cows. Generally, statistical analysis of lactation data became a very complex issue. It seems inevitable that nutritionists and statisticians team up to address this problem.     

Milk yield, residual milk, oxytocin and cortisol release during machine milking in Gir, Gir x Holstein and Holstein cows

This study evaluated the effect of exclusive machine milking on oxytocin (OT) and cortisol (CORT) release, and on milk yield and residual milk in Gir (group Gir), Holstein (group Hol) and crossbred animals (group GirHol). Six animals from each group were submitted to experimental milkings. As expected, milk yield was significantly higher in the Hol group than in the groups GirHol and Gir, and group GirHol produced more milk than the Gir group. In contrast, all groups exhibited significant but similar levels of OT, although OT increased more rapidly during milking for the groups Hol and GirHol than for the Gir group. In addition, CORT levels measured during and after milking were significantly influenced by the group. The Gir group showed higher levels of CORT than the groups GirHol and Hol. The lower performances of the Gir breed can not be explained by a less efficient milk ejection reflex because all cows studied released enough OT and had an effective milk ejection.     

Random regression analyses using B-splines to model growth of Australian Angus cattle

Regression on the basis function of B-splines has been advocated as an alternative to orthogonal polynomials in random regression analyses. Basic theory of splines in mixed model analyses is reviewed, and estimates from analyses of weights of Australian Angus cattle from birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 animals in 43 herds, with a high proportion of animals with 4 or more weights recorded. Changes in weights with age were modelled through B-splines of age at recording. A total of thirteen analyses, considering different combinations of linear, quadratic and cubic B-splines and up to six knots, were carried out. Results showed good agreement for all ages with many records, but fluctuated where data were sparse. On the whole, analyses using B-splines appeared more robust against "end-of-range" problems and yielded more consistent and accurate estimates of the first eigenfunctions than previous, polynomial analyses. A model fitting quadratic B-splines, with knots at 0, 200, 400, 600 and 821 days and a total of 91 covariance components, appeared to be a good compromise between detailedness of the model, number of parameters to be estimated, plausibility of results, and fit, measured as residual mean square error.     

Milk yield persistency in Brazilian Gyr cattle based on a random regression model

With the objective of evaluating measures of milk yield persistency, 27,000 test-day milk yield records from 3362 first lactations of Brazilian Gyr cows that calved between 1990 and 2007 were analyzed with a random regression model. Random, additive genetic and permanent environmental effects were modeled using Legendre polynomials of order 4 and 5, respectively. Residual variance was modeled using five classes. The average lactation curve was modeled using a fourth-order Legendre polynomial. Heritability estimates for measures of persistency ranged from 0.10 to 0.25. Genetic correlations between measures of persistency and 305-day milk yield (Y305) ranged from -0.52 to 0.03. At high selection intensities for persistency measures and Y305, few animals were selected in common. As the selection intensity for the two traits decreased, a higher percentage of animals were selected in common. The average predicted breeding values for Y305 according to year of birth of the cows had a substantial annual genetic gain. In contrast, no improvement in the average persistency breeding value was observed. We conclude that selection for total milk yield during lactation does not identify bulls or cows that are genetically superior in terms of milk yield persistency. A measure of persistency represented by the sum of deviations of estimated breeding value for days 31 to 280 in relation to estimated breeding value for day 30 should be preferred in genetic evaluations of this trait in the Gyr breed, since this measure showed a medium heritability and a genetic correlation with 305-day milk yield close to zero. In addition, this measure is more adequate at the time of peak lactation, which occurs between days 25 and 30 after calving in this breed.     

温热因子和小麦产量的最优回归模型探讨

通过温热因子和小麦产量的相关分析及最优回归模型的建立,结果表明在降水较少的地区,温热增产作用未能正常发挥;在降水较多的地区,温热增产作用则得到一定程度的发挥;并针对不同地区分别提出了相应的小麦增产措施。     

Identification and bioinformatics analysis of differentially expressed milk exosomal microRNAs in milk exosomes of heat-stressed Holstein cows

Functional & Integrative Genomics - In summer, heat stress is one of the primary reasons for the compromised health and low milk productivity of dairy cows. Hyperthermia affects milk synthesis...     

Impact of three THI levels on somatic cell count,milk yield and composition of multiparous Holstein cows in a subtropical region

In Egypt, cow's milk represents 52.11% of the total milk production. Climatic condition is mainly expected to impact the welfare and productive performance of livestock animals. Thus, we aimed to explore the impact of temperature-humidity index (THI) on somatic cell count (SCC), milk production and composition on daily milk test records (33600) of Holstein cows under subtropical Egyptian conditions with different levels of THI. Our results revealed that daily milk yield and composition (fat%, protein %, yielded fat, yielded protein and the percentage of lactose) were higher in low THI (31.91 kg, 3.91%, 3.22%, 418 kg, 349 kg and 4.20%, respectively) when compared with high THI. SCC significantly increased 36% from low to high THI. In addition to, it was increased with advanced parities 231.11% from 2nd to 7th parities. At high THI level, SCC was negatively correlated with total MY (r=−0.12 P<0.05), 305 MY (r=−0.16 P<0.05), protein % (r=−0.15 P<0.01), fat% (r=−0.14 P<0.01) and lactose % (r=−0.26 P<0.01). The current study concluded that dairy cows performance was better in most of the investigated parameters at low THI than those in high THI. Thus, indicating a detrimental effect of THI on both welfare and economic return.     

Effect of calf suckling on oxytocin,prolactin, growth hormone and milk yield in crossbred Gir x Holstein cows during milking

This study evaluated the effect of different milking managements on oxytocin, prolactin and growth hormone release in Gir x Holstein cows. Six cows were suckled by their calves, before and after milking (SM group); another six cows were submitted to exclusive milking (M group). High OT levels were observed during suckling of the SM group, however both groups had similar levels of OT during milking. The SM group presented PRL levels significantly higher than the M group, however only during suckling. For GH levels, the SM group showed higher levels than the M group, however this difference was significant only during the first suckling, cleaning of the teats and at the beginning of machine milking. Despite these results, SM cows produced more milk (milking plus suckling) than M cows, however milk obtained by milking was similar for both groups.     

Proliferation and apoptosis in subcutaneous adipose tissue of lactating cows with different genetic merit for milk yield

The aim of this study was to investigate the adipocyte size and fate in subcutaneous fat (scAT) of cows diverging for genetic merit at mid lactation stage, when anabolic activity increases and animals are in a state of positive energy balance. Twenty mid lactation cows (180 ± 20 days in milk) grouped according to the Estimated Breeding Values (EBV) for milk yield in plus (EBVp) and minus (EBVm) variants were selected. Average of adipocytes area, proliferation and apoptotic labelling index as well as DLK-1 expression, a marker of pre-adipocytes, were immunohistochemically evaluated in scAT biopsies. In EBVp cows, the BCS was lower (P < 0.01) whereas milk yield, protein, fat yield (P < 0.001) and plasma free fatty acid concentration (P < 0.05) were higher. The scAT of EBVp cows showed a significantly (P < 0.001) higher frequency between 500 and 3000 μm² classes in comparison to EBVm cows, that showed a significantly (P < 0.01) higher apoptotic labeling index. The immunohistochemical reaction showed DLK-1 positivity in scAT of EBVp cows. Taking together, the data indicate a link between milk yield genetic merit of cows, scAT morphology and function, suggesting greater dynamics and metabolic flexibility in EBVp cows.     

The effect of a monensin controlled-release capsule on the incidence of retained fetal membranes, milk yield and reproductive responses in Holstein cows

The objective of this study was to determine the effect of a monensin controlled-release capsule on the incidence of retained fetal membranes (RFM), milk yield and conception rate at first service (CRFS). The study was conducted during May to August 2004 in a large dairy herd in Chihuahua, Mexico. Cows (n = 2,025) from 20 to 30 d before expected parturition were randomly assigned to either a treatment or a control group. The treated group (n = 1,010) received orally a capsule of monensin that released 335 mg/d for 95 d. Control cows (no capsule, n = 1,015) were randomly assigned and matched by parity. Outcome variables were the incidence of RFM, first three test day milk and CRFS. Monensin decreased the incidence of RFM by 3.9% only in multiparous cows. Therefore, multiparous cows treated with monensin were 0.78 times (95% C.I. = 0.71-0.86) as likely as control multiparous cows to develop RFM. Overall, milk yield was negatively affected by the RFM condition, but it was improved by monensin only in multiparous cows with RFM at test day 1. Conception rate at first service was depressed by 10.6% in multiparous cows with RFM. However, in RFM cows treated with monensin, CRFS improved to the level of treated cows without RFM.     

Diurnal variation of milk fatty acids in early-lactation Holstein cows with and without hyperketonemia

Estimates of milk constituents by Fourier-transform mid-infrared (FTIR) analysis have been shown to be a useful tool in monitoring energy deficit in early-lactation dairy cows. Our objectives were to describe the diurnal variation in milk fatty acids (FAs) and estimate the association of hyperketonemia with concentrations and diurnal patterns of FTIR estimates of milk FA. Blood samples were collected via jugular catheters bihourly for 5 d from multiparous Holstein cows (n = 28) enrolled between 3 and 9 days in milk. Milk samples were collected thrice daily at 0600, 1400, and 2200 h for d 2, 3, and 4 of the study period. Cows were retrospectively classified as hyperketonemic (HYK; n = 13) or non-HYK (n = 15) based on blood beta-hydroxybutyrate (bBHB) concentrations analyzed during the study period. Cows were classified as HYK if bBHB was ≥ 1.2 mmol/l for ≥ 50% (22/44) of bihourly timepoints; cows were classified as non-HYK if bBHB was ≥ 1.2 mmol/l for < 50% of bihourly timepoints. The HYK cows had bBHB ≥ 1.2 mmol/l for 31.4 ± 6.8 timepoints while the non-HYK cows had bBHB ≥ 1.2 mmol/l for 8.0 ± 3.9 timepoints. We used generalized linear mixed models to analyze concentrations of milk FA over time and differences between HYK groups. The relative percentage of de novo, mixed, and preformed FAs all followed diurnal patterns, however only the yield of preformed FA diurnally cycled, reaching a nadir at 0600 h and peaking at 1400 h. The yield per milking of preformed FA was also greater in the HYK cows than in the non-HYK cows. Oleic acid in milk followed a similar diurnal pattern to the yield of preformed FA, likely driving the cyclical nature of preformed FA. Finally, stearic acid was greater in HYK cows. Our results suggest that FTIR estimates of milk FA offer the potential to provide insight on the energy status of early-lactation cows, and when interested in understanding the absolute concentrations and yields of milk FA, diurnal variation should be considered.