...5); font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-style: initial; text-decoration-color: initial;">The aim of the study was to compare different fitted models for show-jumping results of sporthorses and to estimate heritability and repeatability value. Show-jumping competition results collected between 1996 and 2011 were analyzed. The database contained 358 342 starts of 10 199 horses. Identity number, name and gender of the horse, rider, competition year, the level and location of the competition and placing were recorded in the database. To measure performance of horses, placing, number of starters and competition level were used. Competitions were categorized into five groups based on their difficulty level. The used repeatability animal model included fixed effects for age, gender, competition place, year of competition (and competition level in case of non-weighted measurement variables), and random effects for rider, animal and permanent environment effect. Variance components were estimated with VCE-6 software package. The goodness-of-fit of the models was low and moderate. Heritability and repeatability values were low for each measurement variables. The best goodness-of-fit model the weighted square root of placing resulted the highest heritability and repeatability value h2=0.074 and R=0.296.
The aim of the study was to estimate genetic parameters for show-jumping competition performance using random regression model. Show-jumping competition results collected between 1996 and 2009 were analyzed. The database contained 272 951 starts of 8020 horses. Identity number and gender of the horse, rider, competition date, the level of the c...ompetition and placing were recorded in the database. Competition levels were categorized into five groups. Weighted – competition level used – square root transformed placing was used to measure performance of horses. The random regression model included fixed effects for gender, year and place of competition, and random effects for rider, animal and permanent environment.
Later performance of show-jumping horses measured with weighted square root ranks is less influenced by rider and permanent environmental effects than performance at the beginning of a horse’s sporting career. Heritability increased continuously from 6.3 years of age (2296 age in days), values were in the range of 0.07 and 0.37. Higher heritability was found in later ages. Weak genetic and phenotypic correlation was found between the early 4–5–6 years of age and older (7, 8, 8+) age classes. From 8.5 years of age (3132 days old) there were strong genetic and phenotypic correlations between neighboring age groups. For the same age classes moderate and strong genetic and phenotypic correlation was found. Genetic correlation between 13.5 years of age and older horses was very strong.
One of the most important part of the genetic evaluation using a random regression model is the estimation of variance components. This is the topic of many papers because the large computational costs. We can use restricted maximum likelihood (REML), Gibbs sampling and ℜ method for the estimation of genetic parameters. The variance component...s are necessary to calculate the heritabilities and repeatabilities.
The aim of our paper is to estimate the variance components using a random regression repeatability model from test day data set of Hungarian Holstein-Friesian dairy cows and to analyse the change of additive genetic and permanent environmental variance, heritability and repeatability over lactation.
The authors made their analysis based on the body measurements of 3080 Hungarian Sport Horse mares listed in the Hungarian Sport Horse Studbook. Height at withers by stick, height at withers by tape, heart girth and cannon-bone circumference were measured in Hungarian Sport Horse mare performance tests.
Phenotypic correlations among height a
There were low phenotypic correlations between frame (as conformational trait) and height at the withers (measured by tape and stick) and heart girth.
The effectiveness of selection for improved drought tolerance and consumption quality in the progeny of crosses between pea cultivars with semi-leafless (afila) and normal leaves and different origins, respectively, were investigated. After single crosses, parent cultivars and F1, F2 and F3 generations were grown under non-irrigated conditions...in the same trials. We created a colour scale from 1 to 9 to measure statistically the shade of seed colour. The tolerance of genotypes against high temperature was measured by the number of pods per plant. The 3:1 segregation
observed in the F2 generation of crosses between semi-leafless and conventional cultivars indicated that the semi-leafless character is determined by a recessive gene. In contrast, the ratios of conventional (Af) and semi-leafless (af) genotypes were 7:1 and 9:1 ratio in the progenies of crosses of Af × af. The genetic progress was effective for improving the seed quality in F3 generation from crosses Af x af where we found that multiple
dominant alleles controlled the orange colour of cotyledons and its high heritability (h2 A=0,63). Selection is more effective in producing the genotypes with high yield and normal leaves if the crosses were made between the western European cultivars such as semi-leafless Profi and Delta used as maternal cultivars and conventional Auralia cultivars. In this case, there were decreases in the consumption quality, such as seed size and shade of colour. The selection based on the seed weight of single plants for increasing drought tolerance seemed to be more effective in F4
strains with normal leaves originated from Czechoslovakian maternal cultivar Y228; however, the genetic progress in the improvement of seed size and colour quality was slow.
The aim of this paper is to estimate heritabilities and to compare different fitted models for Hungarian Sporthorse showjumping results. Our analysis is based on the show-jumping results between 1996 and 2004. The repeatability animal model for the evaluation of the test results included the fixed effects of gender, breeder, rider, age, y...ear of competition, type of competition, height of fence and number of starters. Variance and covariance components were estimated with VCE-5 software package. Fitting of the models were evaluated with log-likelihood values and Akaike’s information criterion (AIC). Heritability was low in all cases.
The lowest goodness-of-fit model was height of fence-error score and the best-fitting genetic model based on AIC was model using cotangent transformation.
This paper gives a summary of the possibility for applying genomic information for breeding value estimation in beef cattle breeding. This process is called genomic prediction and is now widely used in dairy cattle globally as well as in some beef and sheep populations. The advantage of genomic prediction is a more accurate estimate of the gene...tic merit of an individual at a young age thereby facilitating greater annual genetic gain, predominantly through shorter generation intervals. Genomic predictions are more advantageous for sex-linked (e.g., milk yield), low heritability (e.g., fertility) and difficult-to-measure (e.g., feed intake) traits. The larger the reference population, on average, the more accurate the genomic predictions; additionally, the closer genetically the reference population is to the candidate population, the greater the accuracy of genomic predictions. Research is continuing on strategies to generate accurate genomic predictions using a reference population consisting of multiple breeds (and crossbred). Retrospective analysis of real-life data where genomic predictions have been operation for several years clearly shows a benefit of this technology.
Plant and ear height are very important characters not only for describing new varieties of maize (Zea mays L.), but for green and dry matter production, and even for grain yield. Significant positive correlations have been reported by various authors between plant height and stover yield, plant height and dry matter yield, and plant height and... grain yield. The height of the main ear is also correlated to plant height. It depends on the variety or the environment, but is likely to be the same height within a population. Many environmental and agronomical factors (e.g. plant density, fertilization, pests and diseases) influence the expression of these characters, which are not quality traits. Their expression is controlled by many genes and by the interactions between these genes. The heritability of these traits is high and they show significant genotypic variability and positive heterosis, as reported in many research publications.