Multivariate genetic analysis to account for preselection and disqualified races in the genetic evaluation of racing performances in German trotters

Abstract

The genetic associations between racing performance and preselection of horses considered as the binary trait racing status (trotters without or with at least one racing performance in life were classified as 0 and 1, respectively) as well as disqualified races (disqualified and non-disqualified trotters were classified as 1 and 0, respectively) were analysed in German trotters. Variance components for racing performance traits square root of rank at finish, racing time per km, and log of earnings with racing status were estimated based on an animal model using REML. Heritabilities of racing status, racing time and rank at finish were 0.30, 0.21, and 0.06, respectively. The genetic correlations between racing status and racing time or rank at finish were ?0.74 and ?0.32, indicating that horses started at least once showed a higher genetic potential in racing time or finishing ability than never started horses. This showed the high preselection of German trotters especially based on racing time. To account for this preselection, it was recommended for additional use of racing status in the German evaluation system. Breeding values of the three racing performance traits were estimated by two distinct models, in- or excluding racing status and compared by using three criteria. Racing time per km showed the highest correlation (r=0.98) between breeding values evaluated by these two distinct models. Therefore, incorrect selection rate of horses using breeding values from the model without racing status, was lowest for racing time per km (9.7%). Selection response increased about 1% for this trait after including racing status in the model. For the estimation of rank at finish, inclusion of racing status in the multiple trait model was much more important as indicated by a low correlation between breeding values (r=0.29) and high percentage of incorrectly selected stallions (97.5%). The trait disqualified races was first analysed using an univariate threshold model. Heritability of this trait was low (h ²=0.12) and repeatability (r=0.43) showed a moderate magnitude. Using a linear multiple trait animal model, disqualified races showed a low heritability (h ²=0.05) and a moderate favourable genetic correlation (r _g=0.43) with racing time per km. Consequently, selection on racing time per km is expected to improve indirectly the reliability of racing performance. Combined selection of reduction in disqualified races and racing time may even further improve the reliability of racing trotters.     

Genetic parameters for racing records in trotters using linear and generalized linear models

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.     

The use of foal and studbook traits in the breeding programmes of Finnhorse and Standardbred trotters

Genetic correlations for body measurements and subjectively scored traits between foals and studbook horses were estimated using bivariate linear mixed models. Observations for nine foal and eleven studbook traits in Finnhorses on 6529 foals and 6596 studbook horses and in Standardbred trotters on 3069 foals and 2112 studbook horses were available from the Finnish horse breeding shows. The number of sires with progeny in both foal and studbook data was 203 in Finnhorse and 145 in Standardbred trotters. Estimates of heritability for body measurements in foals and studbook horses using univariate models were high in both breeds (0.41-0.84). Heritability estimates for subjectively scored traits using univariate models were generally higher for foals (0.08-0.46) than for studbook horses (0.06-0.21) in both breeds. Genetic correlations between foals and studbook horses for body measurements were highly positive ranging from 0.74 to 0.96 in Finnhorses and from 0.79 to 0.99 in Standardbred trotters. Low to highly positive genetic correlations between foals and studbook horses for subjectively scored traits were obtained in Finnhorse trotters, whereas in Standardbred trotters genetic correlations for subjectively scored traits varied from moderately negative to highly positive. Higher estimates of heritability for foal traits and generally high genetic correlations between the foal and studbook traits indicate that an early selection for conformation traits would be efficient in the breeding programmes.     

Genetical-statistical analysis of traits in the German trotter

Data on 331 321 racing performances of all competing trotters in the Federal Republic of Germany have been filed since 1973. After adjusting to environmental factors, repeatabilities and heritabilities of the most important traits (racing time, money earnings and perfect gait) have been estimated. The highest degrees for repeatability (r_{between years} = 0.55?0.79) and heritability (h² = 0.21?0.49) are found in the average racing time per year. Therefore, this trait should be the main selection criterion in a practical breeding programme.     

Comparison of two different statistical models considering individual races or racetracks for evaluation of German trotters

Two different statistical models considering racetrack or individual race as fixed effect were compared, regarding genetic parameters and by using cross validation. Data for variance component estimation consisted of 48,942 performance observations from 4249 trotters. Variance components for the traits square root of rank at finish, racing time per km, and log of earnings per race were estimated by REML using two multiple trait animal models involving different racetracks or individual races. When including each individual race instead of racetracks in the statistical model, heritabilities increased from 0.05 to 0.07, 0.19 to 0.23, and 0.08 to 0.09 for square root of rank at finish, racing time per km, and log of earnings per race, respectively. Genetic and phenotypic correlations among traits increased also after consideration of individual races. Square root of rank at finish, as well as racing time per km and log of earnings per race, was highly genetically correlated with −0.99 and −0.88. The two statistical models were compared on the basis of their predictive ability by using cross validation. Data for these analyses consisted of 706,082 observations from 21,363 trotters. Randomly eliminated performance observations were predicted by cumulation of fixed and random effects obtained from estimation of breeding values for both models. Estimates for racing time showed lower bias and mean square error (MSE) when considering individual races instead of racetracks. Also, the correlation between predicted and true phenotypic value increased from 0.85 to 0.92. Estimates for square root of rank at finish were unbiased, but with a higher MSE when considering individual race effect. A similar high bias and MSE with both models were obtained for log of earnings. In order to avoid bias in estimation of genetic parameters and breeding values for racing time and square root of rank at finish, inclusion of each individual race in the statistical model was recommended.     

Genetic evaluation of Swedish standard-bred trotters for racing performance traits and racing status

The BLUP methodology has been applied to the genetic evaluation of Swedish standard-bred trotters for well over a decade. Initially a BLUP sire model was applied for evaluating breeding values of stallions on the basis of the racing performance of their offspring (Árnason et al. 1989). In 1992 an animal model (AM-) BLUP was introduced and official publication of index values were offered as an aid for effective selection of stallions and brood mares (Árnason 1992; Árnason and S vendsen 1991). The implementation of the BLUP animal model index has apparently caused profound enhancement in the selection intensity for both stallions and mares (Árnason 1997). The AM-BLUP evaluation has involved the following traits, which were all based on accumulated racing results as 3- to 5-year-olds: Number of races (starts); % of races ranked first to third at the finish (i.e. placed first to third); earnings per race; total earnings; best racing time per km; and racing (or start) status, which is denoted as one if the horse did race at least once as a 3- to 5-year-old and zero otherwise. The two traits: number of races and racing status were initially treated as single traits, in the AM-BLUP analyses, uncorrelated with the other racing performance traits. Those other traits are direct measures of racing performance for horses that have actually competed on the race track. They are highly intercorrelated and have been treated as a multivariate complex in the analyses. The computational load of general multivariate analyses has been considerably reduced by transformation of the records into uncorrelated canonical variates (e.g. Árnason 1982). In Sweden, about 40% of standard-bred trotters do not enter a race course and their racing performance variables have previously been treated as missing. Early analysis on the population of standard-bred trotters in Sweden did not show any correlation between racing status of brood mares and the racing performance of their offspring (M. B endroth , unpublished results). That gave justification for assuming that racing status had mainly environmental causes, and to be practically genetically uncorrelated with performance. The exclusion of nonracers (nonstarters) was therefore not expected to bias genetic evaluations for the performance traits. The expansion of the population during the 1980s and the early 1990s, and increase in the level of prize money, has probably invalidated the implication of these results and partly changed the racing status into a preselection criterion for racing performance. K lemetsdal (1992) has clearly illustrated that such a culling process can result in substantial bias in estimated breeding values. In 1995 a new enhanced procedure replaced the older version used for routine genetic evaluation of Swedish standard-bred trotters, with the aim of eliminating, or at least reducing, the selection bias and increasing the accuracy in the genetic evaluations. The main objective of this paper was to describe the enhanced procedure for genetic evaluation of Swedish standard-bred trotters where racing status and racing performance traits were treated in a complete multiple trait framework. The task was made computationally feasible by the application of a procedure which allows solution of multiple trait AM-BLUP with missing data on some traits using multiple step canonical transformation of records and solutions during the iterative solution phase (D ucrocq and B esbes 1993). The pertinence of the method for establishing a sound selection criterion was verified by stochastic simulations on simplified data structures. The second objective of this study was to evaluate the model and assess the set of genetic parameters used in the BLUP analysis, by linear regressions of the genetic predictions based on the most recent data on genetic predictions obtained in subsamples of the whole data set (method R, R everter et al. 1994a, b).     

Inheritance of racing performance of trotter horses: An overview

Harness racing is a form of horseracing in which the horses race in a specified gait (trot or pace). In contrast to the Thoroughbred, the trotter is not an international breed. In this type, the horses are raced with trotting or pacing gait. Breeds specialized for racing at trot or pace are indigenous to many countries. Separate breeds of light harness horses, generally designated as trotters have evolved for racing purposes in several countries. The important horse breeds used for harness racing in different parts of the world are the Standardbred, French Trotter, Swedish Trotter, Orlov Trotter, Russian Trotter, Finnhorse, Icelandic Toelter, Dole horse and North-Swedish cold-blooded horses. The trotter ranks worldwide second to the Thoroughbred in popularity as a racehorse. Racing performance in trotters, in contrast to Thoroughbred is characterized by qualifying tests before entering the races, inclusion of more than one breed in international races only and greater duration of racing career. An intensive selection of stallions on the basis of phenotypic racing performance has been practised in many trotter populations for quite a long time. Unlike Thoroughbreds, improvements have been observed in different trotter populations and this is attributed to both genetic and environmental changes. Environmental changes include enhanced training methods, as well as improved tracks, harness and sulkies. As a result of selection, racing time of trotters has been reduced over the years. The estimated annual genetic progress in racing performance traits of Swedish Standardbred horses corresponds to 5% of the phenotypic standard deviation, 3.6% in French Trotters and 5% in Dutch Trotters. According to the recent selection for speed in trot, this trait remains heritable and genetic improvement is observed in most countries. Correlations between earnings and times are negative and high, and hence favourable. As a result, selection based on times and earnings are quite effective. A multiple trait approach avoids potential biases of one particular measure, even if the objective of all traits is much the same. Since racing performance may be evaluated in both males and females and repeated observations can be obtained on the same animal, mass selection based on performance tests would be the selection procedure of choice. In the future, interest in the possible use of marker-assisted selection (MAS) for enhanced genetic improvement in horses is likely to increase. MAS is likely to be a valuable complement to selection of horses based on estimated breeding values (EBVs) obtained by the Best Linear Unbiased Prediction (BLUP) method, rather than as a replacement for EBVs.     

Genetic analysis of racing performance in Irish greyhounds

The aim of this study was to analyse racing performance data in Irish greyhounds with regard to genetic and environmental variation. Estimation of heritabilities for racing time (RT) and ranking, and the prediction of breeding values for all greyhounds in the investigated data were carried out. Data from 42,785 races in Ireland in the years 2000-2003 were available. These results were obtained from 42,880 greyhounds on 20 race tracks over a distance of 480 m. Three traits were analysed, RT, ranking and a scaled logarithmic function for RT (ART), which was used to adjust racing time to be normally distributed. The data were analysed with a bivariate animal model. The estimated heritabilities were moderate for RT (0.31) and ART (0.38), but very low for ranking (0.10). The repeatabilities were 0.56 (RT), 0.51 (ART) and 0.13 (ranking). The genetic correlations were very high, 0.99 (RT-ranking) and 0.96 (ART-ranking), while the phenotypic correlation was lower, 0.60 (RT-ranking) and 0.62 (ART-ranking). The genetic trend for the traits as well as the phenotypic change of the average RT was positive.     

Threshold-linear versus linear-linear analysis of birth weight and calving ease using an animal model: I. Variance component estimation.

Birth weight and calving difficulty were analyzed with Bayesian methodology using univariate linear models, a bivariate linear model, a threshold model for calving difficulty, and a joint threshold-linear model using a probit approach. Field data included 26,006 records of Gelbvieh cattle. Simulated populations were generated using parameters estimated from the field data. The Gibbs sampler was used to obtain estimates of the marginal posterior mean and standard deviation of the (co)variance components, heritabilities, and correlations. In the univariate analyses, the posterior mean of direct heritability for calving difficulty was .23 with the threshold model and .18 with the linear model. Maternal heritabilities were .10 and .08, respectively. In the bivariate analysis, posterior means of direct heritability for calving difficulty were .21 and .18 for the bivariate linear-threshold and linear-linear model, respectively. Maternal heritabilities were .09 and .06, respectively. Direct heritability for birth weight was .25 for the univariate model and .26 for bivariate models. Maternal heritability was .05 for the linear-threshold model and the univariate model and .06 for the bivariate linear model. Genetic correlation between direct genetic effects in both traits was .81 for the linear-threshold model and .79 for the bivariate linear. Residual correlation was .35 for the bivariate linear model and .50 for the bivariate linear-threshold. A simulation study confirmed that the posterior mean of the marginal distribution was suitable as a point estimate for univariate threshold and bivariate linear-threshold models.     

Genetic correlations for foal and studbook traits with racing traits and implications for selection strategies in the Finnhorse and Standardbred trotter

Genetic correlations for body measurements and conformation and functional traits in foals and studbook horses with racing traits were estimated in the Finnhorse and Standardbred. Genetic response and accuracy were estimated using records of animal, half‐sibs and parents in selection scenarios for racing traits, for foal and racing traits, for studbook and racing traits, and using records of animal, half‐sibs and parents for foal traits and racing traits of parents. Racing time and earnings were the breeding objective. Low‐to‐moderate genetic correlations for body measurements and racing traits indicated that selection favours bigger horses at all ages. Being mainly favourable for the breeding objective, genetic correlations for conformation and functional traits with racing traits were highest for the foal traits of type, trot and overall grade and for the studbook traits of character and movements. Genetic correlations for foal and studbook conformation with racing traits were low in the Finnhorse and moderate to high in the Standardbred. In foals, the highest genetic correlations were for trot with racing time (?0.54) and with earnings (0.52) in the Finnhorse, and for overall grade with racing time (?0.54) and with earnings (0.54) in the Standardbred. In studbook horses, genetic correlations were high for character with racing time and earnings in the Finnhorse (?0.68, 0.61) and in the Standardbred (?0.63, 0.70), and for movements with racing time and earnings in the Finnhorse (?0.70, 0.69) and in the Standardbred (?0.90, 0.88). To increase accuracy of conformation and functional traits, foal traits would be more useful in the index with racing traits, as being less preselected than studbook traits. The foal traits (type, trot, overall grade) having moderate heritability and genetic correlations with racing traits would be useful in multi‐trait index before a racing career, where the greatest gain is because of a shorter generation interval. It would be feasible to implement for AI stallions.     

Genetic parameters for direct and maternal calving ability over parities in Piedmontese cattle

Estimates of heritabilities and genetic correlations for calving ease over parities were obtained for the Italian Piedmontese population using animal models. Field data were calving records of 50,721 first- and 44,148 second-parity females and 142,869 records of 38,213 cows of second or later parity. Calving ability was scored in five categories and analyzed using either a univariate or a bivariate linear model, treating performance over parities as different traits. The bivariate model was used to investigate the genetic relationship between first- and second- or between first- and third-parity calving ability. All models included direct and maternal genetic effects, which were assumed to be mutually correlated. (Co)variance components were estimated using restricted maximum likelihood procedures. In the univariate analyses, the heritability for direct effects was .19 +/- .01, .10 +/- .01, and .08 +/- .004 for first, second, and second and later parities, respectively. The heritability for maternal effects was .09 +/- .01, .11 +/- .01, and .05 +/- .01, respectively. All genetic correlations between direct and maternal effects were negative, ranging from -.55 to -.43. Approximated standard errors of genetic correlations between direct and maternal effects ranged from .041 to .062. For multiparous cows, the fraction of total variance due to the permanent environment was greater than the maternal heritability. With bivariate models, direct heritability for first parity was smaller than the corresponding univariate estimate, ranging from .18 to .14. Maternal heritabilities were slightly higher than the corresponding univariate estimates. Genetic correlation between first and second parity was .998 +/- .00 for direct effects and .913 +/- .01 for maternal effects. When the bivariate model analyzed first- and third-parity calving ability, genetic correlation was .907 +/- .02 for direct effects and .979 +/- .01 for maternal effects. Residual correlations were low in all bivariate analyses, ranging from .13 for analysis of first and second parity to .07 for analysis of first and third parity. In conclusion, estimates of genetic correlations for calving ease in different parities obtained in this study were very high, but variance components and heritabilities were clearly heterogeneous over parities.     

The use of a random regression model to account for change in racing speed of German trotters with increasing age

In a genetic analysis of German trotters, the performance trait racing time per km was analysed by using a random regression model on six different age classes (2‐, 3‐, 4‐, 5‐ and 6‐year‐old and older trotters; the age class of 3‐year‐old trotters was additionally divided by birth months of horses into two seasons). The best‐fitting random regression model for the trait racing time per km on six age classes included as fixed effects sex, race track, condition of race track (fitted as second‐order polynomial on age), distance of race and each driver (fitted as first‐order polynomial on age) as well as the year‐season (fitted independent of age). The random additive genetic and permanent environmental effects were fitted as second‐order polynomials on age. Data consisted of 138 620 performance observations from 2373 trotters and the pedigree data contained 9952 horses from a four‐generation pedigree. Heritabilities for racing time per km increased from 0.01 to 0.18 at age classes from 2‐ to 4‐year‐old trotters, then slightly decreased for 5 year and substantially decreased for 6‐year‐old horses. Genetic correlations of racing time per km among the six age classes were very high (r_g = 0.82–0.99). Heritability was h² = 0.13 when using a repeatability animal model for racing time per km considering the six age classes as fixed effect. Breeding values using repeatability analysis over all and within age classes resulted in slightly different ranking of trotters than those using random regression analysis. When using random regression analysis almost no reranking of trotters over time took place. Generally, the analyses showed that using a random regression model improved the accuracy of selection of trotters over age classes.     

Genetic and phenotypic parameters and annual trends for milk production and fertility traits of the Sahiwal cattle in semi arid Kenya

Data comprising 7211 lactation records of 2894 cows were used to estimate genetic and phenotypic parameters for milk production (lactation milk yield, LMY and lactation length, LL) and fertility (calving interval, CI; number of services per conception, NSC and age at first calving, AFC) traits. Genetic, environmental and phenotypic trends were also estimated. Variance components were estimated using univariate, bivariate and trivariate animal models on based restricted maximum likelihood procedures. Univariate models were used for each trait, while bivariate models were used to estimate genetic and phenotypic correlations between milk production and fertility traits and between LMY, LL, CI and NSC within each lactation. Trivariate models were used in the analysis of LMY, LL, CI and NSC in the first three lactations. Heritability estimates from the univariate model were 0.16, 0.07, 0.03, 0.04 and 0.01 for LMY, LL, CI, AFC and NSC, respectively. The heritability estimates from trivariate analysis were higher for milk production traits than those from univariate analyses. Genetic correlations were high and undesirable between milk production and fertility traits, while phenotypic correlations were correspondingly low. Genetic trends were close to zero for all traits, while environmental and phenotypic trends fluctuated over the study period.     

Genetic evaluation of elbow scores and the relationship with hip scores in UK Labrador retrievers

A linear mixed model analysis of elbow and hip score data from UK Labrador retrievers was used to estimate the heritability of elbow score (0.16-0.19) and to determine a moderate and beneficial genetic correlation with hip score (0.40). A small improvement in the genetic trend of elbow score was observed during the years 2000-2008, equivalent to avoiding only the worst 3-4% of scored dogs for breeding, but close to what may have been anticipated if the current British Veterinary Association-approved guidelines were followed. Calculations suggested that a correlated response to indirect selection on hip score may elicit a greater response than direct selection on elbow score and that the genetic trend in elbow score may be explained as a consequence of the stronger selection pressure that has been placed on hip score. Increases in the accuracy of estimated breeding values for elbow score of 4-7% for dogs with elbow data only and 7-11% for dogs with both hip and elbow score were observed from bivariate analysis of elbow and hip data. A selection index confirmed the benefits of bivariate analysis of elbow and hip score data by identifying increases in accuracy (directly related to the response to selection) of 14% from the use of optimum coefficients compared to use of hip data only. The quantified genetic correlation means that hip score effectively acts as a 'secondary indicator' of elbow score in this breed and the preponderance of hip data means that it acts as a major source of information that may be used to improve the accuracy of estimates of genetic risk for elbow dysplasia.     

Direct and maternal genetic effects for preweaning growth in Retinta cattle estimated by a longitudinal approach throughout the calving trajectory of the cow

The direct and maternal genetic effects were estimated for the preweaning growth of Retinta calves with a multitrait model across parities, using a longitudinal approach with random regression models (RRM). The 120 (P120) and 180 days (P180) weights (5972 calves) were considered as different traits in each calving. The heritability of direct effect across parities was on average 0.37 for P120 and 0.58 for P180, slightly higher than the estimates by univariate (0.30 and 0.56) and bivariate models (0.30 and 0.51, respectively). The heritability for maternal effects was 0.16 for P120 and 0.26 for P180 and very similar by uni‐ (0.16 and 0.23) and multivariate model (0.16 and 0.22, respectively). The correlation between direct and maternal effects by RRM showed a pronounced antagonism ?0.64 for P120 and ?0.78 for P180), likewise uni‐ (?0.62 and ?0.72) and multivariate case (?0.64 and ?0.74, respectively). The preweaning weights should be considered as different traits across parities, because the genetic correlations were different from unity. The RRM also allowed us to estimate all the parameters throughout the calving trajectory of the cow. The use of multiple traits RRM across parities can provide very useful information for the breeding programmes.     

Genetic predictions of racing performance in quarter horses

Research on the racing performance of quarter horses has been used to develop genetic prediction summaries on all horses with at least one start on record at the American Quarter Horse Association. In the 1987 summary, records from a total of 212,065 horses were used to give genetic predictions on stallions, mares, geldings, fillies, and colts. A reduced animal model was used that incorporated the repeated records of individuals. The individual race was the contemporary group after the data were adjusted for distance, sex, and age. Estimates of heritability of .24 and repeatability of .32 suggest that increased racing performance can be achieved if the predictions are used by breeders. Continued research in variance component estimation includes the genetic covariances among the several distances, maternal influence, and genetic parameters for racing longevity.     

Heritability estimates for racing performance in Japanese Thoroughbred racehorses using linear and non-linear model analyses

This study evaluated the differences between linear and non‐linear modelled heritability estimates of racing performance based on lifetime earnings (LE) and lifetime ranking (LR) in Japanese Thoroughbred racehorses. The heritability estimate (h² = 0.25) obtained from a non‐linear model based on formal Japan Racing Association ranking was much higher than that obtained from a linear model based on the original trait phenotype (h² = 0.11). The linear models showed slightly higher heritability estimates under the trait categorizations than under the original phenotypes, while the non‐linear categorical trait models showed much higher heritability estimates than the linear models, especially for binary trait categorizations (h² = 0.34) with non‐winning and winning horses. The binary trait categorizations were consistent with the case and control classifications in the previous genome‐wide association study (GWAS), which identified possible sequence variants on ECA18 that affect racing performance in Japanese Thoroughbred racehorses. Those findings suggested that the different heritability estimates obtained from several trait categorizations would reflect the possible presence of susceptibility gene segregations in the analyzed population, indicating that heritability estimates from non‐linear models are useful for the selection of case and control populations in GWAS.     

Genetic parameters of racing performance traits of Quarter horses in Brazil

The data used in the present study were recorded at the Jockey Club of Sorocaba for 5094 racing performance of 1350 Quarter Horses at the Paulista Race Track of Sorocaba, state of São Paulo, Brazil, from 1991 to 1997. The considered traits were time and final rank. The model used in analysis included random animal and permanent environmental effects, and race, sex, age and origin as fixed effects. The variance and covariance components were estimated by the restricted maximum likelihood for an animal model, using the derivative-free process method and the MTDFREML software. For the time, heritability was 0.17 (0.05), while estimate of repeatability 0.55 (0.05). The lower heritability for the final rank, 0.13 (0.04), indicate that this trait is not the most appropriate one for inclusion in programs of Quarter horse selection in Sorocaba racetrack. The repeatability estimate for rank was 0.44 (0.04) and the genetic correlation between this trait and time was 0.99.     

Annual, career or single race records for breeding value estimation in race horses

The racing careers of 2, 3, 4, and 5-year-old Thoroughbreds and French trotters born in France between 1995 and 1999 were analysed. The horses were evaluated on a set of traits, with particular attention to annual or career earnings and number of starts.

As expected, the distributions of earnings corrected for year, age and sex are very skew and thus inappropriate for breeding value estimations. However, Log transformation results in near normal distributions more suitable for this purpose.

Another problem of annual or career earnings required a more complex approach. As most horses did not win any money in France (67% of the trotters and 41% of the Thoroughbreds), it is difficult to correctly evaluate these horses. On the other hand, a linear adjustment of the Log of earnings by the Log of the number of starts (exponential adjustment of the earning index) leads to regression coefficients close to 1. It justified the use of the Log of earnings per start and explained its higher heritability in literature. A quadratic adjustment of the Log of earnings by the Log of the number of starts (sigmoid adjustment of the earning index) improves the adjustment for the Thoroughbred only and should be implemented for these horses.

The probability of a horse to be placed according to the number of starts was also studied. It is shown that the observed percentage of non-placed horses p_s according to the number of starts, s, is in all cases inferior to the expected percentage (p_s < p₁^s). Therefore, races of the same horse cannot be considered as independent events. The percentage of horses placed and the mean earnings for each age can be combined in order to estimate the economical weights for each age class. Economical weights for the French trotter were 0.00, 0.21, 0.40, and 0.39 for 2, 3, 4, and 5-year olds respectively. They were 0.11, 0.45, 0.26 and 0.18 respectively for Thoroughbreds of the same age categories. The current tendency to move from annual or career criteria towards criteria at the race level is discussed. However, the question on how to evaluate the important proportion of horses born that never appeared in a race still remains open and should focus future research.