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PubMed2004

Genotype x environment interaction for grazing vs. confinement. II. Health and reproduction traits.

Continual selection for increased milk yield for more than 40 yr, combined with the antagonistic relationship between increasing yield, somatic cell count, and fertility, have resulted in sires that may not be optimal for producing daughters for grazing systems where seasonal calving is very important. The objective of this study was to investigate the possible existence of a genotype x environment interaction (G x E) in grazing vs. confinement herds within the United States for lactation average somatic cell score (LSCS), days open (DO), days to first service (DFS), and number of services per conception (SPC). Grazing herds were defined as those that utilized grazing for at least 6 mo each year and were enrolled in Dairy Herd Improvement (DHI). Control herds were confinement DHI herds of similar size in the same states. For LSCS, the performance of daughters in grazing and control herds was examined using linear regression of LSCS on the November 2000 USDA-DHIA sire predicted transmitting abilities (PTA) for SCS. Genetic parameters for all traits were estimated using REML in a bivariate animal model that treated the same trait in different environments as different traits. Rank correlations were calculated between sires' estimated breeding values for LSCS, calculated separately for sires in both environments. The coefficient of regression of daughter LSCS on sire PTA was less in grazing herds than in control herds. The coefficient of regression for control herds was closer to expectation. Estimates of heritability were approximately 0.12 for LSCS, and less than 0.05 for the reproduction traits. Heritabilities for DO, DFS, and SPC were slightly higher for control herds. Estimates of genetic correlation for each reproductive trait between the 2 environments were high and not significantly different from unity. Generally, these traits appear to be under similar genetic control, but a lower coefficient of regression of LSCS on sire PTA for SCS in grazing herds suggests differences in daughter performance in grazing herds may be overstated based on current PTA for SCS.

Animals↗

PubMed1999

Comparison of methods for genetic evaluation of sires for survival of their daughters in the first three lactations.

Several approaches for analysis of survival in the first three lactations were compared using data from approximately 700,000 Canadian Holsteins. Two approaches (linear model and threshold model) were used to analyze a binary measure of survival. Other approaches were survival analyses to evaluate two measures of the number of days that cows were in milk during their first three lactations. One measure restricted days per lactation to < or = 305; the other was based on the actual number of days in milk without an upper limit on days per lactation. Variance components and breeding values (EBV) were estimated. Sire models were used almost exclusively, but one set of EBV was obtained using a linear animal model. Effects in the models were herd-year of calving, age at first calving, interaction of several factors related to herd, and production. Thus, all EBV were for functional herd life. Heritabilities were approximately 0.04, 0.07, and 0.10 from linear, threshold, and survival analyses, respectively. Correlations among sire EBV from all analyses using sire models were high, particularly for linear and threshold models (0.98). In contrast, correlations of EBV from sire models with EBV from the linear animal model were less than 0.90, regardless of the approach taken. In Canada, the current linear animal model remains in use for sire evaluation of herd life, but research with survival analyses will continue.

Animals↗

PubMed1979

Concentrations of progesterone in milk as a monitor of early pregnancy diagnosis in dairy cows.

The objectives of the experiment were to evaluate the efficacy of using progesterone concentrations in milk and palpation per rectum on days 21 or 22 postbreeding to estimate pregnancy and evaluate management practices; and to investigate physiological occurrences leading to incorrect diagnosis of pregnancy when serial samples of milk were collected. Of particular interest were indications of early embyronic death and insemination of cows not in estrus. Milk samples were collected at the afternoon milking of days 0 or 1 (day 0 = day of estrus), 9 or 10, 21 or 22 and 27 or 28 following breeding in 200 lactating dairy cows. Tentative diagnosis of pregnancy was made based on concentrations of progesterone in milk on days 21 and 22 alone and on days 21 or 22 and 27 or 28. In addition all cows were palpated per rectum on days 21 or 22 postbreeding and a tentative pregnancy diagnosis was made. Pregnancy was confirmed by examination of the genital tract per rectum between 35 and 50 days after breeding. Values of 4 ng/ml or greater and/or the presence of a mature corpus luteum were considered positive signs of pregnancy. Progesterone in milk ranged from 0.1 to 18 ng/ml. On days 0 or 1, 9 or 10, 21 or 22 and 27 or 28 concentrations of progesterone in milk averaged 1.5 +/- 0.3, 11.1 +/- 0.5, 12.0 +/- 0.4 12.5 +/- 0.5 ng/ml for pregnant cows. Corresponding samples from nonpregnant cows averaged 1.2 +/- 0.2, 10.3 +/- 0.4, 3.0 +/- 0.4, 6.8 +/- 0.6 ng/ml, respectively. Ninety-six and 104 cows were classified as pregnant and nonpregnant on days 21 or 22 as compared to 78 and 118 cows diagnosed as pregnant and nonpregnant on days 21 or 22 and 27 or 28 combined. Pregnancy detection by progesterone in milk on days 21 or 22 with pregnancy determined via rectal palpation 35 to 50 days postbreeding was 77 and 100% accurate for positive and negative diagnosis, respectively. The percent agreement using progesterone in milk on days 21 or 22 and 27 or 28 combined was 95 and 100%, respectively, for positive and negative diagnosis. Diagnosis based on rectal palpation 21 or 22 days postbreeding was 63 92 (69%) and 76 88 (87%) for pregnant and nonpregnant cows, respectively. Ten of the 200 cows had progesterone concentratins in milk of > 4 ng/ml at the time of breeding. Six of these cows were pregnant from a previous insemination. The other four cows were nonpregnant and were inseminated during the luteal phase of the cycle. In conclusion, measurement of progesterone in milk is a useful tool in early detection of pregnant and nonpregnant cows and may be useful in detecting reproductive problems in a dairy herd. It will probably be most useful when used in combination with later pregnancy diagnosis per rectum .

Journal Article↗

PubMed2001

Nocturnal melatonin and prolactin plasma concentrations in sheep selected for fertility in autumn lambing'.

Ewes selected for fertility in autumn lambing were used to evaluate correlated responses in nocturnal hormone levels. Four jugular blood samples were obtained during nighttime in August from each of 113 selected and 69 control ewes. Melatonin levels were lower for selected ewes (143 +/- 14 pg/mL) than for control ewes (184 +/- 13 pg/mL), and melatonin levels decreased with increases in estimated breeding values (EBV) for fertility (-2.23 +/- 0.79 pg mL(-1) x %(-1)). Prolactin levels were higher for selected ewes (90 +/- 7 ng/mL) than for control ewes (52 +/- 7 ng/mL), but significant line x ewe age interaction was also observed, with smaller differences in prolactin levels in 2-yr-old and older ewes (74 +/- 7 vs. 56 +/- 9 ng/mL for select and control ewes, respectively; P < 0.20 before and P = 0.05 after logarithmic transformation). Prolactin levels increased with both fertility EBV (1.23 +/- 0.53 ng mL(-1) x %(-1)) and maternal birth weight EBV (9.0 +/- 4.0 ng x ml(-1) kg(-1)). Heritability estimates were 0.43 (P < 0.02) for melatonin levels and 0.11 (P > 0.25) for prolactin levels. Thus, we conclude that selection for fertility in autumn lambing has affected patterns of melatonin and prolactin secretion during the dark phase.

Age Factors↗

PubMed2004

Genetic parameters for six measures of length of productive life and three measures of lifetime production by 6 yr after first calving for Hereford cows.

Genetic parameters for length of productive life given the opportunity (LPL/O), measured as days between first calving and disposal conditioned on one of six opportunity groups, L1 through L6 (e.g., L2 is length of productive life in days given the opportunity to live 2 yr after first calving), and lifetime production (LP), measured as the number of calves born (NB), number of calves weaned (NW), and cumulative weaning weight (CW) by 6 yr after first calving, were estimated using records of 1,886 Hereford cows from a selection experiment with three selected lines and a control line. Weaning weights were adjusted to 200 d of age and for sex and age of dam. Estimates of heritability and genetic and environmental correlations were obtained by restricted maximum likelihood with bivariate animal models, with year of birth of cow as a fixed effect and direct genetic and residual as random effects. Genetic trends were estimated by regressing means of estimated breeding values by year of birth and line on birth year. Estimates of heritability (SE) for LPL/O ranged from 0.05 (0.01) to 0.15 (0.03). Estimates of genetic correlations (SE) among LPL/O ranged from 0.74 (0.14) to 1.00 (0.00), and estimates of environmental correlations ranged from 0.67 (0.05) to 0.98 (0.01). Estimates of heritability (SE) for NB, NW, and CW were 0.17 (0.05), 0.21 (0.06), and 0.18 (0.01). Estimates of genetic correlations (SE) among NB, NW, and CW ranged from 0.96 (0.02) to 0.99 (0.01). Estimates of environmental correlations (SE) ranged from 0.93 (0.01) to 0.99 (0.01). Estimates of genetic correlations for L6 with NB, NW, and CW were near 1.00 (0.09). Estimates of environmental correlations (SE) ranged from 0.57 (0.03) to 0.60 (0.03). Estimates of genetic change per year (SE) for L6 were low for all lines and ranged from -3.53 (2.09) to 4.63 (2.11) d/yr. Genetic trends for NB and NW were negligible for all lines. Genetic trends for CW were low and ranged from -2.81 (1.67) to 3.29 (1.76) kg/yr. Differences in genetic trends between selected lines and control were not significant (P > 0.05). Estimates of environmental trends (SE) over all lines were -104.00 (25.48) d/yr, -0.26 (0.02) calves/yr, -0.25 (0.02) calves/yr, and -55.10 (15.63) kg/yr, for L6, NB, NW, and CW, respectively. Selection for LPLIO or LP could be successful in a breeding program, but may be relatively slow due to the low magnitude of heritability and extended generation interval.

Animals↗

PubMed1990

Laparoscopic artificial insemination in sheep.

The goal of any AI program is to create improved offspring, and the achievement of this objective will depend on the breeding value of the ram and ewe selected. Laparoscopic AI is being utilized in the sheep industry to extend the use of superior rams, and it offers the producer the opportunity to maximize the reproductive potential of superior sheep. Rapid genetic trait infusion of known superior stud rams into the flock is the primary economic benefit of laparoscopic AI. The success of laparoscopic AI depends on events and factors that interrelate in a complex way. Once the selection and preparation of the ewe have been accomplished, one of the more important steps in the program is the successful synchronization of the ewe to deliver the necessary ova to the site of fertilization at a specific time. One of the best methods of synchronization for laparoscopic AI is the use of a progesterone product for a controlled time period and the administration of PMSG upon its removal. Detecting the onset of estrus is critical, and the addition of sterile (e.g., vasectomized) males is helpful, even essential, to accurately determine when each ewe begins her estrus. The ram effect has been shown to stimulate ovulation and estrus. Ewes must be inseminated within a narrow window of time after the synchronization product is removed. Ewes should be inseminated in the order in which they begin to exhibit signs of behavioral estrus, but age, stage of lactation, duration of behavioral estrus, and breed must be taken into account when this order is established. Fresh-extended semen works well throughout this preferred time frame established for laparoscopic AI, but frozen semen gives best results when used near the end. Advancement in manufacturing technology today removes equipment as a variable factor. It is important, therefore, that the inseminator develop a level of expertise in laparoscopy to ensure maximum fertilization rates. If available, fresh-extended semen is preferred over frozen semen, using at least the minimal number of spermatozoa necessary for fertilization. Evaluation of the post-thaw frozen or fresh semen is necessary to determine motility, morphology, and concentration, all of which help determine the volume of the insemination dose. The minimum necessary for laparoscopic AI in fine-wooled breeds is 20 X 10(6) normal motile spermatozoa; however, the more seasonal and less fertile American sheep need approximately 40 to 50 X 10(6) normal motile sperm to achieve acceptable fertility rates.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed1997

Response to selection for fertility in a fall-lambing sheep flock.

Selection for fertility in a fall lambing system was applied for 5 yr (1.45 generations) in a crossbred sheep population. Three flocks were involved: a fall-lambing selected (S) flock of 125 ewes and 10 rams, a fall-lambing environmental control (EC) flock of 55 ewes and five rams, and a spring-lambing genetic control flock of 45 ewes and five rams used to produce replacements for EC. Estimated breeding values for fertility (ewes lambing per ewe exposed) were calculated for animals mated in each year of the study using a single-trait animal model and increased more rapidly in S (.0138/yr) than in EC (.0067/yr). After accounting for genetic drift, EBV of ewes mated in S in the final year of the study averaged .070 +/- .032 (P = .08). A correlated response of .0087 lambs/yr was observed in S for fall litter size Genetic trends in all body weights were positive in EC, likely because of supplemental selection on body size in ram lambs used in EC. Ninety-day weight, maternal effects on weaning weight, and 90-d scrotal circumference increased in S, but direct effects on birth and weaning weights declined. In order to focus on realized selection response in fertility, EBV for fertility of 330 replacement ewe lambs from S and EC were calculated using only data collected after their birth. These realized EBV were then regressed on pedigree EBV calculated at the time the ewe lambs were born. The regression was significant when all relationships were used to calculate both EBV (.20 +/- .08) but only approached significance (.13 +/- .07) when only records of the ewe lambs themselves, their descendants, and their paternal half-sibs were used to calculate realized EBV. Also, EBV for all ewes were calculated at the start of each breeding season and were higher (P < .01) for ewes that subsequently lambed than for open ewes. These results suggest that selection can be used to improve fertility in fall-lambing sheep flocks.

Animals↗

PubMed1999

The effect of using different culling regimens on genetic response with two-trait, two-stage selection in a nucleus broiler stock.

Stochastic simulation was used to study the effect on genetic response and inbreeding of various two-stage two-trait culling strategies. Four different parameter sets were considered for the two traits, BW and egg number. Selection of replacement animals was based on animal model best linear unbiased prediction (BLUP) to obtain estimated breeding values (EBV) at the second stage. Culling at Stage 1 was based on either animal model BLUP or phenotypes, and information from culled animals was either available or not available for calculation of second stage EBV. Besides founder individuals, six discrete generations were considered. Culling based on BLUP of two traits at Stage 1 produced higher response than culling on phenotypic evaluations. It was found that culling based on phenotypic evaluation and not carrying information to the second stage reduce rates of response by 9 to 17% and produced inbreeding higher than or close to that of BLUP selection. This study clearly shows that a double penalty of less response and higher inbreeding is generally paid for not using all information. Optimum selection schemes will depend on relative costs and benefits of collecting and processing the extra information required for full BLUP selection schemes.

Animals↗

PubMed2003

Estimation of environmental sensitivity of genetic merit for milk production traits using a random regression model.

The objective of this study was to estimate effects of environmental sensitivity of milk production traits for several environmental parameters and to investigate the impact of combining traits with different environmental sensitivity in an economic index. Variance components and breeding values were estimated for milk, fat, and protein yield, and fat and protein percentage by applying a random regression on values of an environmental parameter for each sire. Fourteen environmental parameters were defined and fitted to data consisting of 151,696 heifers in 6780 herds in The Netherlands with first-lactation records for milk production, somatic cell count, body condition score, and number of inseminations. Milk, fat, and protein yield showed environmental sensitivity in combination with 12 environmental parameters. Herd-year averages of protein, body condition score, age at calving, calving interval, and peak date of calving explained most genotype by environment interaction, mainly resulting from scaling effects. Almost all genetic correlations across environments were 0.99 or higher. Although heterogeneity of genetic variances was considerable, heterogeneity of heritabilities was limited. Scaling had a large effect on the weights of the economic index, but environmental sensitivities of milk, fat, and protein yields were approximately of equal magnitude. Consequently, very little reranking occurred based on the economic index.

Animals↗

PubMed2004

Development of an optimal index to improve lactation yield and persistency with the least selection intensity.

It is important to have improvement in both lactation milk yield and persistency. Modification of the lactation curve requires severe restrictions on selection criteria designed to simultaneously improve both milk yield and persistency. As a result, manipulating the lactation curve for improved persistency requires higher selection intensity than unrestricted selection based on 305-d estimated breeding value (EBV). Our study showed that for a given restriction imposed on both milk EBV and persistency, it is possible to derive different indexes to achieve this selection constraint with different degrees of selection intensity. Of the class of indexes that meets the same restriction, it is preferable to choose the index that requires the least selection intensity because it is easier to achieve the selection goal with the use of an index that requires a lower selection intensity than a higher selection intensity. An optimal index based on random regression (RR) coefficients was developed to achieve the prespecified stage genetic gains with the lowest selection intensity. A conversion equation was derived to convert the selection index based on RR coefficients to the selection index based on stage EBV with the lowest selection intensity. A numerical example is provided to demonstrate the procedures developed compared with conventional selection based on 305-d milk EBV.

Animals↗

PubMed1994

A simple procedure for obtaining approximate interim cow solutions from an animal model.

The computational costs required for solving the equations for an individual animal mixed model can be considerable. More frequent evaluations would benefit dairy producers, allowing them to make breeding and management decisions earlier. A procedure was developed to immediately obtain approximate estimates of cow breeding value as soon as new information becomes available. Only solutions for cows with records in progress are updated. The algorithm is based on solving a system of two equations and can be applied by producers. The method corrects for changes in estimated production of the current record of a cow but assumes that the effects of changes in evaluations of other animals related to this cow on the evaluation of the cow in question are negligible. Herd-year-season effects are not reestimated. The correlations between the updated cow evaluations based on animal model evaluations computed during May 1992, but using estimated production from November 1992, for records in progress and the animal model evaluations from November were .027 to .064 higher than the correlations between the May and November evaluations for production of milk, fat, and protein. Although gains are slight, the cost application of the algorithm is insignificant.

Algorithms↗

PubMed1997

Assessing the efficiency of multiplicative mixed model equations to account for heterogeneous variance across herds in carcass scan traits from beef cattle.

Data (n = 2,658) from live animal ultrasonic measures from 17 Angus herds were used to evaluate a multiplicative mixed model that incorporates scaling factors to correct for across-herd heterogeneity of variance. Traits included were ribeye muscle area (EMA), surface fat at the P8 site (P8), surface fat between the 12th and 13th ribs (RIB12), and weight at scanning (WEIGHT). Cattle ranged in age from 501 to 698 d and represented 291 contemporary groups. Data were initially analyzed using single-trait, animal model, Method R procedures to estimate variance components and heritabilities (h2). These estimates were incorporated into a multiplicative mixed model that simultaneously estimates breeding values (EBV) and heterogeneity factors. Re-estimation of h2 after scaling the data with the correction factors was explored to obtain a measure of the improvement in the genetic evaluation and to detect changes in ranking of individuals and herds. Initial h2 estimates for EMA, P8, RIB12, and WEIGHT were .36, .39, .29, and .48, respectively. Scaling factors ranged from .25 for P8 in a herd with eight records to 1.96 for RIB12 in a herd with 86 individuals. Re-estimates of h2 increased by an average of 4.2% for all the traits as a result of correcting for heterogeneity. Deviations of new scaling factors were within expectations. Correlations between EBV with and without heterogeneity correction were greater than .97 for all the traits. However, some substantial re-rankings of herds were observed for some traits in the smaller herds.

Analysis of Variance↗

PubMed2006

Genetic parameters for health traits and their relationship to different persistency traits in German Holstein dairy cattle.

Data from 3,200 Holstein cows from 3 commercial dairy farms in Germany were used to estimate heritabilities and breeding values for liability to udder diseases (UD), fertility diseases (FD), metabolic diseases (MD), and claw and leg diseases (CLD) using single-trait threshold sire models. A total of 92,722 medical treatments recorded from 1998 to 2003 were included in the analysis. Approximate genetic correlations between persistency of milk yield, fat yield, protein yield, and persistency of milk energy yield and liability to the health traits were calculated based on correlations between EBV. Posterior means of heritability of liability ranged from 0.05 to 0.08 for UD, from 0.04 to 0.07 for FD, from 0.08 to 0.12 for MD, and from 0.04 to 0.07 for CLD. Approximate genetic correlations of the disease traits with the persistency traits were favorable, except for MD in all lactations, which were unfavorable, and UD, which were around zero. Highest correlations in the range of 0.13 to 0.46 were found between the different persistency traits and CLD.

Animals↗

PubMedDate not supplied

Genetic parameters and responses of performance and body composition traits in pigs selected for high and low growth rate on a fixed ration over a set time.

Two lines of Large White pigs of common genetic origin were divergently selected over four years for high and low growth rate during a 6 week post-weaning test period in which all pigs were fed the same total amount of food (80% of estimated ad libitum intake). Genetic parameters and direct and correlated responses in performance and carcass traits were estimated on 2884 pigs with pedigrees comprising a total of 5324 animals, with restricted maximum likelihood and best linear unbiased prediction methods applied to a multi-trait animal model. Estimates of heritability (+/-SE) were 0.19 +/- 0.04 for lifetime daily gain (LDG), 0.16 +/- 0.03 for test daily gain (TDG), 0.25 +/- 0.04 for ultrasound P2 backfat (UBF) and 0.16 +/- 0.03 for food conversion ratio during test (TFC), and 0.15 +/- 0.04 for daily carcass weight gain (CDG), 0.43 +/- 0.06 for carcass backfat (CFT) and 0.40 +/- 0.06 for carcass lean percentage (LEAN). Common litter effects for TDG, UBF and TFC were less than 5% and for LDG, 17% of total phenotypic variance. Genetic correlations between performance and carcass traits were moderately to highly favourable. After four years of divergent selection for growth rate, the selection responses in estimated breeding value (EBV) for TDG were 40.14 and -41.11 g (SED 2.95) for the high and low growth lines, respectively. The regressions of EBV on year of birth, indicate that the annual genetic trend for TDG, was 8.73 g/yr in the high and -8.48 g/yr in the low lines (P <0.001). Correlated genetic responses in the high and low lines respectively were 5.28 g and -12.40 g (SED 2.09) in LDG, -0.35 mm and 0.56 mm (SED 0.009) in UBF, -0.145 units and 0.185 units (SED 0.012) in TFC, 3.17 g and -10.97 g (SED 1.53) in CDG, -1.13 mm and 1.01 mm (SED 0.155) in CFT and 1.24% and -1.27% (SED 0.150) in LEAN. It was concluded that selection for increased post-weaning daily gain on a ration of fixed amount reduces the age at slaughter and the level of backfat and increases the efficiency of food utilisation, weight and leanness of pig carcasses.

Animals↗

PubMed2006

Accounting for heterogeneous variances in multitrait evaluation of Jersey type traits.

The multitrait genetic evaluation system for type traits was modified to estimate adjustments for heterogeneous variance (HV) simultaneously with estimated breeding values (EBV) for final score and 14 linear traits. Each variance within herd, year, and parity was regressed toward a predicted variance, which was determined by fitting a model with fixed effects of the mean final score for herd, size of the contemporary group, appraisal month, and year-season and a random effect for herd-appraisal date. Herd-appraisal date was included as a random effect to regress the observed heterogeneity for a given herd-appraisal date toward the fixed effects. Method R was used to estimate variances for the heterogeneity model in each EBV iteration. To evaluate the effect of the adjustment, parent averages were calculated from evaluations with recent appraisals removed. The adjustment slightly improved correlations within birth year between those parent averages and EBV from current data on bulls for most traits, but did not improve correlations for final score, strength, dairy form, teat length, or foot angle. Annual trends for EBV were lower with HV adjustment than for unadjusted EBV for all traits except final score and rump angle for cows and rump width for bulls, which were essentially unchanged. Standard deviations of Mendelian sampling (evaluation minus mean of parent evaluations) declined less over time for HV-adjusted than for unadjusted evaluations. The slope at year 2000 of Mendelian-sampling standard deviations from HV-adjusted evaluations ranged from 10.0% for udder depth to 42.7% for teat length compared with the slope for unadjusted evaluations. This HV adjustment, which was implemented for USDA evaluations in May 2001 for Jerseys and in 2002 for other breeds, improves the accuracy of evaluations, particularly comparisons over time, by accounting for the change in variation.

Animals↗

PubMed2005

Studies on multiple trait and random regression models for genetic evaluation of beef cattle for growth.

A simulation study examined issues important for genetic evaluation of growth in beef cattle by random regression models with cubic Legendre polynomials (RRML) and linear splines with three knots (RRMS) compared with multiple-trait models (MTM). Parameters for RRML were obtained by conversion from covariance functions. Parameters for MTM and RRMS were extracted from RRML at 1, 205, and 365 d; parameters for RRMS were the same as MTM for all effects except the permanent environment and the residual. Four data sets were generated assuming RRML included records at 1, 205, and 365 d; at 1, 160 to 250, and 320 to 410 d; at 1, 100, 205, 300, and 365 d; and at 1, 55 to 145, 160 to 250, 275 to 325, and 320 to 410 d. Accuracies were computed as correlations between the true (simulated) and predicted breeding values. With the first data set, excellent agreement in accuracy was obtained for all models. With the second data set, the accuracy of MTM dropped by up to 1.5% compared with the first data set, but accuracy was unchanged for both RRML and RRMS. With the third (fourth) data set, accuracies of RRML were up to 2.4% (2.5%) higher than with the first (second) data set. Small differences in accuracy between RRML and RRMS were found with the third and fourth data sets, which were traced to inflated correlations especially between 1 and 205 d in RRMS; inflation could be decreased by adding one extra knot at 100 d to RRMS. Diagonalization of random coefficients was crucial for RRML but not for RRMS, resulting in approximately six (two) times faster convergence with RRML (RRMS). Reduction of dimensionality in RRML associated with small eigenvalues caused a less accurate evaluation for birth weight. Genetic evaluation of growth by RRM requires careful implementation. The RRMS is simpler to implement than the RRML.

Age Factors↗

PubMed2004

Random regression test-day models with residuals following a Student's-t distribution.

First-lactation milk yield test-day records of Canadian Holsteins were analyzed by single-trait random regression test-day models that assumed normal or Student's-t distribution for residuals. Objectives were to test the performance of the robust statistical models that use heavy-tailed distributions for the residual effect. Models fitted were: Gaussian, Student's-t, and Student's-t with fixed number of degrees of freedom (equal to 5, 15, 30, 100 or 1000) for the t distribution. Bayesian methods with Gibbs sampling were used to make inferences about overall model plausibility through Bayes factors, posterior means for covariance components, estimated breeding values for regression coefficients, solutions for permanent environmental regressions, and residuals of the models. Bayes factors favored Student's-t model with the posterior mean of degrees of freedom equal to 2.4 over all other models, indicating very strong departure from normality. Number of outliers in Student's-t model was reduced by 35% in comparison with the Gaussian model. Differences in covariance components for regression coefficients between models were small, and rankings of animals based on additive genetic merit for the first two regression coefficients (total yield and persistency) were similar. Results from the Gaussian and Student's-t models with fixed degrees of freedom become more alike (smaller departures from normality for Student's-t models) with increasing number of degrees of freedom for the t-distributions. For any pair of Student's-t models, the one with the smaller number of degrees of freedom for the t-distribution was shown to be superior. Similarly, number of outliers increased with increasing degrees of freedom for the t distribution.

Animals↗

PubMed2000

Experience with a test-day model.

The Canadian Test-Day Model is a 12-trait random regression animal model in which traits are milk, fat, and protein test-day yields, and somatic cell scores on test days within each of first three lactations. Test-day records from later lactations are not used. Random regressions (genetic and permanent environmental) were based on Wilmink's three parameter function that includes an intercept, regression on days in milk, and regression on an exponential function to the power -0.05 times days in milk. The model was applied to over 22 million test-day records of over 1.4 million cows in seven dairy breeds for cows first calving since 1988. A theoretical comparison of test-day model to 305-d complete lactation animal model is given. Each animal in an analysis receives 36 additive genetic solutions (12 traits by three regression coefficients), and these are combined to give one estimated breeding value (EBV) for each of milk, fat, and protein yields, average daily somatic cell score and milk yield persistency (for bulls only). Correlation of yield EBV with previous 305-d lactation model EBV for bulls was 0.97 and for cows was 0.93 (Holsteins). A question is whether EBV for yield traits for each lactation should be combined into one overall EBV, and if so, what method to combine them. Implementation required development of new methods for approximation of reliabilities of EBV, inclusion of cows without test day records in analysis, but which were still alive and had progeny with test-day records, adjustments for heterogeneous herd-test date variances, and international comparisons. Efforts to inform the dairy industry about changes in EBV due to the model and recovering information needed to explain changes in specific animals' EBV are significant challenges. The Canadian dairy industry will require a year or more to become comfortable with the test-day model and to realize the impact it could have on selection decisions.

Analysis of Variance↗