Material and Methods The animal material consisted of 244 Thoroughbred horses of different ages that run in races in Hippodromes organized ...
Material and Methods The animal material consisted of 244 Thoroughbred horses of different ages that run in races in Hippodromes organized by the Jockey Club of Turkey. The animals were randomly selected from horses housed in Adana YeÅŸiloba Hippodrome, in Adana city, Turkey (37°0' N and 35°19' E), in 2013. Pedigree (stallion, birth date, age, gender, and mother age) and racing (running year, hippodrome, race distance, race duration, racetrack, and race type) information of the horses was obtained from the records of the Board of High Stewards,
Ministry of Food Agriculture and Livestock of Turkey, and the Jockey Club of Turkey. All morphometric measurements (Table 1) were taken from the right side with the horse standing in a normal position inside a fixed crush. Of the 244 investigated animals, 159 horses that had at least three paternal half-sibs and three official racing records were selected for the statistical analysis of race performance and effects of morphometric measurements on race performance. Race performance (m/sec) was calculated based on duration and distance for each race. The least squares mixed models including fixed effects of factors was used, as shown below: yijklm = μ + αi + βj + γk + δl + eijklm (for morphometric measurements), in which yijklm = dependent variable, µ = overall mean, αi = fixed effect of stallion, βj = the fixed effect of gender, γk = fixed effect of age, δl = fixed effect of mother age, and eijklm = random error. R. Bras. Zootec., 48:e20180030, 2019 Multivariate analysis of morphometry effect on race performance in Thoroughbred horses Paksoy and Ünal 3 yijklmnoprs = μ + αi + βj + γk + δl + ηm + κn + σo + τp + ωr + eijklmnoprs (for race performance), in which yijklmnoprs = dependent variable, µ = overall mean, αi = fixed effect of stallion, βj = fixed effect of gender, γk = fixed effect of age, δl = fixed effect of mother age, ηm = fixed effect of year, κn = fixed effect of hippodrome, σo = fixed effect of race distance, τp = fixed effect of racetrack, ωr = fixed effect of race type, and eijklmnoprs = random error. The meanings of the factors used in the mix models given above are explained below: Stallion: father of horses investigated.
Gender: male and female horses investigated. Age: ages of horses investigated = 2, 3, 4, 5, and 6+ years old. Mother age: mother ages of horses investigated = 2-5, 6, 7, 8, 9, 10, 11, 12, 13-15, and 16-19 years old. Year: the years of horse racing; 2001-2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, and 2013. Hippodrome: cities of hippodrome where horse races took place = Adana, Bursa, İstanbul, Ankara, İzmir, Diyarbakır, Şanlıurfa, and Elazığ. Race distance: between 800 and 2400 m, and run by the horses investigated from start to end points = 800-1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 2100, 2200, and 2400 m. Racetrack: ground composition of racetrack = dirt and turf. Race type: flat racing categories organized according to various characteristics. Maiden race: racing joined by horses that have never won. Handicap race: racing in which different weights are loaded on the horses, and these weights are determined by scores of official handicappers to equalize their chances of winning; handicap 13 (horses with a score between 1-50); handicap 14 (horses with a score between 1-65); handicap 15 (horses with a score between 1-75); handicap 16 (horses with a score between 30 and 85); and handicap 17 (horses with a score between 40 and 100). Condition race: racing where horses participated according to the total amount of lifetime earnings, and additional weights are loaded on horses according to the total amount of lifetime earnings. The more the number of condition race increases, the more total amount of lifetime earnings are needed to participate. Open class: racing with high-performance horses carrying the same weight.
Statistical significances among the subgroups were determined by Tukey’s test at 5% significance level. Pearson’s correlation coefficients were calculated among morphometric measurements. Table 1 - Descriptions of morphometric measurements examined in the research Morphometric measurement Definition WH - withers height Vertical distance from the highest point of the withers to the ground RH - rump height Vertical distance between the highest point of the sacrum and the ground CG - chest girth Circumference around the chest from behind the scapula CW - chest width Distance in the front side between the outer sides of the right and left articulatio humeri FCW - front chest width Distance in the front side between the inner sides of the right and left articulatio humeri CD - chest depth Vertical distance between the highest point of the withers and the sternum NL - neck length Distance from the angulus mandibula to the scapula SL - shoulder length Distance from the highest point of the withers to the caput humeri LWR - length of withers to rump Straight distance between the end of the withers and the beginning of the rump RL - rump length Distance from the tuber coxae to the tuber ischia BL - body length Horizontal distance from the caput humeri to the tuber ischia HW - head width Distance between the right and left processus lacrimalis rostralis HL - head length Distance from the crista occipitalis to the os incisivum CC - cannon circumference Circumference at the middle of the metacarpal bone R. Bras. Zootec., 48:e20180030, 2019 Multivariate analysis of morphometry effect on race performance in Thoroughbred horses Paksoy and Ãœnal 4 The Kolmogorov-Simirnov normality test for normal distribution fitness, the Kaiser-Meyer-Olkin test for sample size adequacy, and Bartlett’s sphericity test were applied in the morphometric measurement data.
Principal component analysis for morphometric measurements were performed, and then the factor loadings were rotated by the Varimax method. The significance of the rotated factor loadings was determined using the value of 0.45, which is the limit for n = 159. Factor eigenvalues greater than 1 were accepted (Alpar, 2013; Tabachnick and Fidell, 2014). For factor analysis, the basic factor analysis equation was used, as follows: Zp×1 = Æ›p×m Fm×1 + ep×1, in which Z = p×1 vector of variables, Æ› = p×m matrix of factor loadings, F = m×1 vector of factors, and e = p×1 vector of error factors. Multiple Linear Regression Analysis, using the model below, determined the importance of the effects of the obtained factors on race performance (RP): RP = a + b1 FS1 + b2 FS2 + b3 FS3 + b4 FS4 + e, in which a = regression constant value; FS = factor scores; b1 , b2 , b3 , and b4 = regression coefficients of factor scores; and e = error term. The t test was used for significance of the regression coefficients. The autocorrelation assumption was determined by the Durbin-Watson test. Statistical procedures were carried out using SPSS software (Statistical Package in Social Sciences for Windows, version 14.01). Results Least squares means (Table 2) were 169.34±0.52 cm for withers height, 187.66±1.12 cm for chest girth, and 168.52±0.75 cm for body length.
Table 2 - Descriptive statistics and P-values for the morphometric measurements of the horse Morphometric measurement Descriptive statistics of all horses (n = 244) P-value of the selected horses for race performance (n = 159) X±Sx (cm) Min (cm) Max (cm) CV (%) X±Sx (cm) Stallion Gender Age Mother age WH 169.15±0.23 157 178 2.11 169.34±0.52 <0.001 0.021 0.355 0.312 RH 167.46±0.23 155 177 2.16 167.65±0.54 <0.001 0.169 0.386 0.267 CG 187.22±0.46 162 204 3.86 187.66±1.12 0.032 0.390 0.555 0.852 CW 42.33±0.16 34 47 5.86 42.24±0.38 <0.001 0.469 0.227 0.356 FCW 20.34±0.10 16 24 8.01 20.10±0.25 0.038 0.606 0.552 0.769 CD 84.88±0.27 70 93 5.03 84.88±0.64 <0.001 0.302 0.282 0.524 NL 57.83±0.29 44 68 7.80 58.43±0.70 <0.001 0.158 0.600 0.671 SL 72.10±0.20 63 79 4.29 72.38±0.44 <0.001 0.211 0.171 0.741 LWR 62.50±0.26 54 72 6.45 62.43±0.56 <0.001 0.599 0.542 0.731 RL 37.57±0.17 31 43 7.13 37.22±0.36 <0.001 0.185 0.530 0.393 BL 168.17±0.33 154 178 3.04 168.52±0.75 <0.001 0.459 0.646 0.303 HW 23.88±0.05 21 25 3.02 24.00±0.13 0.116 0.029 0.381 0.552 HL 52.95±0.13 48 59 3.44 52.93±0.28 0.192 0.102 0.146 0.338 CC 20.46±0.05 19 22 3.52 20.48±0.11 0.040 0.038 0.326 0.453 WH - withers height; RH - rump height; CG - chest girth; CW - chest width; FCW - front chest width; CD - chest depth; NL - neck length; SL - shoulder length; LWR - length of withers to rump; RL - rump length; BL - body length; HW - head width; HL - head length; CC - cannon circumference; CV - coefficient of variation. Tukey’s test (P>0.05). R. Bras. Zootec., 48:e20180030, 2019 Multivariate analysis of morphometry effect on race performance in Thoroughbred horses Paksoy and Ãœnal 5 Age and mother age had no significant effects (P>0.05) on any of the investigated morphometric measurements, while gender was pronounced on withers height, cannon circumference, and head width (P<0.05). On the other hand, for stallion, a significant effect (P<0.05; P<0.001) occurred on all morphometric measurements except head length and width. Least squares means for race performance were 15.29±0.06 m/sec (Table 3). Race performance was significantly influenced by stallion (P<0.01), gender (P<0.01), age (P<0.05), year (P<0.05), hippodrome (P<0.001), race distance (P<0.001), racetrack (P<0.001), and race type (P<0.001), while mother age had no marked effect on this trait. In general, high and significant (P<0.05; P<0.01; P<0.001) correlation coefficients among morphometric measurements in positive direction were calculated, varying from 0.117 to 0.679 (Table 4). The 14 morphometric measurements examined showed fitness to normal distribution by the KolmogorovSmirnov test (P>0.05). Sample size adequacy by the Kaiser-Meyer-Olkin test was 0.849. The significance level of Bartlett’s sphericity test was P<0.001. Four factors (FI, FII, FIII, and FIV) with eigenvalues >1 were attained as a result of the analysis with PCA. The factors of FI (general size), FII (body thickness), FIII, and FIV explained 52.46, 15.50, 8.01, and 7.21% of the total variation of 83.19%, respectively. Ten loads in FI, five in FII, two in FIII, and two in FIV were statistically significant (Table 5). The regression coefficients obtained for the factors were not significant (P>0.05) (Table 6). The Durbin-Watson test for autocorrelation yielded a value of 1.377. Correlation coefficients between race performance and regression coefficients of FI, FII, FIII, and FIV were calculated as ‒0.012, ‒0.079, 0.022, and 0.050 (P>0.05), respectively. Discussion Size and morphometry are extremely important traits in nearly all horse breeds including Thoroughbred, and numerous breed registries select horses on functional criteria and support the breeding of horses with body types most convenient for those particular functions. Using many body measurements from the head, neck, trunk, and limbs in a great number of horse breeds such as Thoroughbred, Shire, and Friesian in USA showed that there was a high body size variation among the horse breeds (Brooks et al., 2010).
Coefficients of morphometric measurements covered in this study were low and less than 10%, which shows that the uniformity of morphological characteristics of the breed were rather high. These findings agreed with the report by Brooks et al. (2010) in which the lowest variation for body measurements among 65 horse breeds was observed in Thoroughbred horse breed. In terms of morphometric measurements examined, males showed higher values than females. However, the effect of gender on morphometric measurements was generally not very clear, given that gender effects were only important for withers height, cannon circumference, and head width. There was usually a slight increase in morphometric measurements as the animals grew older, but none of these increases was statistically significant. This shows that Thoroughbred horses generally complete their growth and development at the age of two, agreeing with the statement that Thoroughbred horses are early-maturing. In fact, Thoroughbred horses start their racing life one year earlier (two years old) than Arabian horses, the other breed used in flat racing in many countries. A research by Anderson and McIlwraith (2004) found that the various body measurements of Thoroughbred horses were similar at two and three years old
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