scholarly journals Heritability, Genetic and Phenotypic Correlations, and Predicted Selection Response of Quantitative Traits in Peach: II. An Analysis of Several Fruit Traits

1998 ◽  
Vol 123 (4) ◽  
pp. 604-611 ◽  
Author(s):  
Valdomiro A.B. de Souza ◽  
David H. Byrne ◽  
Jeremy F. Taylor
Keyword(s):  
Fruit Development ◽  
Fixed Effects ◽  
Prunus Persica ◽  
Genetic Correlations ◽  
Soluble Solids ◽  
Direct Selection ◽  
Multiple Trait ◽  
Phenotypic Correlations ◽  
Development Period ◽  
Genetic And Phenotypic Correlations

Thirteen peach [Prunus persica (L.) Batsch] fruit characteristics were investigated for 3 years, 1993, 1994, and 1995, in College Station, Texas, to determine heritability, genetic and phenotypic correlations, and predicted response to selection. Seedlings of 108 families resulting from crosses among 42 peach cultivars and selections were used in the evaluations. A mixed linear model, with years treated as fixed and additive genotypes as random factors, was employed to analyze the data. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances between traits. Genetic and phenotypic correlations ≥0.65 and <0.30 were considered strong or very strong and weak, respectively. Date of ripening, fruit development period (FDP) and date of full bloom had the highest heritability (h2) estimates, 0.94, 0.91, and 0.78, respectively. Fruit cheek diameter and titratable acidity (h2 = 0.31) were the traits with the lowest estimates. Fruit development period, fruit blush, and date of ripening had the highest predicted selection responses, whereas fruit suture, fruit cheek, L/W12 (ratio fruit length to average fruit diameters), and fruit tip had the lowest values. Most genetic correlations were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. All four measures of fruit size were genetically and phenotypically very strongly correlated. Important genetic correlation estimates were also observed for date of ripening with FDP (ra = 0.93), date of ripening and FDP with fruit blush (ra = -0.77, ra = -0.72), SS (percent soluble solids) (ra = 0.63, ra = 0.62) and TA (ra = 0.55, ra = 0.64), and SS with TA (ra = -0.56). Direct selection practiced solely for early ripening and short FDP is expected to have a greater effect on correlated traits than direct selection for early bloom and large fruit mass.

scholarly journals Heritability, Genetic, and Phenotypic Correlations of Several Peach Traits

HortScience ◽  
1995 ◽  
Vol 30 (4) ◽  
pp. 763B-763
Author(s):  
Valdomiro A.B. de Souza ◽  
David H. Byrne ◽  
Jeremy F. Taylor
Keyword(s):  
Skin Color ◽  
Fixed Effects ◽  
Prunus Persica ◽  
Mixed Linear Model ◽  
Fruit Weight ◽  
Soluble Solids ◽  
Genetic Progress ◽  
Multiple Trait ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations

Heritability estimates are useful to predict genetic progress among offspring when the parents are selected on their performance, but they also provide information about major changes in the amount and nature of genetic variability through generations. Genetic and phenotypic correlations, on the other hand, are useful for better planning of selection programs. In this research, seedlings of 39 families resulting from crosses among 27 peach [Prunus persica (L.) Batsch] cultivars and selections were evaluated for date of full bloom (DFB), date of ripening (DR), fruit period development (FDP), flower density (FD), node density (ND), fruit density (FRD), fruit weight (WT), soluble solids content (SS), apical protuberance (TIP), red skin color (BLUSH), and shape (SH) in 1993 and 1994. The data were analyzed using the mixed linear model. The best linear unbiased prediction (BLUP) was used to estimate fixed effects and predict breeding values (BV). Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple-trait model to estimate genetic and phenotypic covariances between traits. The data indicates high heritability for DFB, DR, FDP, and BLUSH, intermediate heritability for WT, TIP, and SH, and low heritability for FD, ND, FRD, and SS. They also indicate year effect as a major environmental component affecting seedling performance. High correlation estimates were found between some traits, but further analysis is needed to determine their significance.

scholarly journals Heritability, Genetic and Phenotypic Correlations, and Predicted Selection Response of Quantitative Traits in Peach: I. An Analysis of Several Reproductive Traits

1998 ◽  
Vol 123 (4) ◽  
pp. 598-603 ◽  
Author(s):  
Valdomiro A.B. de Souza ◽  
David H. Byrne ◽  
Jeremy F. Taylor
Keyword(s):  
Fixed Effects ◽  
Prunus Persica ◽  
Fruit Set ◽  
Genetic Correlations ◽  
Selection Response ◽  
Direct Selection ◽  
Multiple Trait ◽  
Narrow Sense Heritability ◽  
Phenotypic Correlations ◽  
Flower Density

Seedlings of 108 families from crosses among 42 peach [Prunus persica (L.) Batsch] cultivars and selections were evaluated for six plant characteristics in 1993, 1994, and 1995. The data were analyzed by using a mixed linear model, with years treated as fixed and additive genotypes as random factors. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances among traits. The narrow-sense heritability estimates were 0.41, 0.29, 0.48, 0.47, 0.43, and 0.23 for flower density, flowers per node, node density, fruit density, fruit set, and blind node propensity, respectively. Most genetic correlations among pairs of traits were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. Flower density and flowers per node (ra = 0.95), fruit density and fruit set (ra = 0.84) and flower density and fruit density (ra = 0.71) were the combinations of traits that had the highest genetic correlation estimates. Direct selection practiced solely for flower density (either direction) is expected to have a greater effect on fruit density than direct selection for fruit density.

scholarly journals EFFECT OF FIXED FACTORS AND ESTIMATION OF GENETIC PARAMETERS OF GROWTH TRAITS FOR MOUNTAIN KIDS

2019 ◽  
Vol 50 (6) ◽  
Author(s):  
Hermiz & Baper
Keyword(s):  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Maximum Likelihood Method ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Likelihood Method ◽  
Phenotypic Correlations ◽  
Body Weights ◽  
Genetic And Phenotypic Correlations

Body weights at birth (469), weaning (394) and at six month of age (358) for kids utilized in this study were raised at private project in Duhok governorate, Iraq during two kidding season (2016-2017) and (2017-2018). GLM within SAS programme was used to analyze the data which include the fixed effects (age of doe, year and season of kidding, sex of kid and type of birth, regression on doe weight at kidding, and the regression of later weights of kids on earlier weights) influencing the studied traits. Restricted Maximum Likelihood Method was used to estimate repeatability, heritability, genetic and phenotypic correlations after adjusting the records for fixed effects. Variance components of random effects were tested for positive definite. Overall mean of weights at birth (BWT), weaning (WWT) and 6 month of age (WT6M) were 2.92, 15.32 and 24.45 kg, respectively. Differences among groups of age of doe in all studied traits were not significant, while year of kidding and sex of kid affect all traits significantly (p<0.01). Season of kidding affect BWT and WWT significantly (P<0.01). Single born kids were heavier (P<0.01) than twins in BWT only. Regression of BWT on doe weight at kidding (0.033 kg/kg) was significant (P<0.01), while the regressions of WWT and WT6M were not significant. The regression coefficients of WWT on BWT (1.906 kg/kg) and of WT6M on WWT (0.835 kg/kg) were highly significant (P<0.01). Repeatability estimates for BWT, WWT and WT6M were 0.47, 0.45 and 0.35, respectively; on the same order the estimates of heritability were 0.41, 0.61 and 0.79. Genetic correlations between BWT with each of WWT (0.45) and WT6M (0.55), and between WWT and WT6M (0.68) were highly significant. All phenotypic correlations between each pair of body weights were higher than genetic correlations and ranged between 0.48 and 0.73.

scholarly journals Genetic Parameters of Conformation Traits in Young Polish Holstein-Friesian Bulls

2014 ◽  
Vol 14 (4) ◽  
pp. 831-840
Author(s):  
Agnieszka Otwinowska-Mindur ◽  
Ewa Ptak ◽  
Wojciech Jagusiak ◽  
Andrzej Żarnecki
Keyword(s):  
Fixed Effects ◽  
Genetic Parameters ◽  
Dominant Role ◽  
Genetic Correlations ◽  
Progeny Testing ◽  
Multiple Trait ◽  
Holstein Friesian ◽  
Type Traits ◽  
Genetic And Phenotypic Correlations ◽  
Final Score

Abstract The objective of this study was to estimate the genetic parameters of conformation traits in Polish Holstein-Friesian bulls evaluated for registration in the herd book and for entry into progeny testing. Data were 8 linearly scored (1-9 scale) and 6 composite (scored from 50 to 100) conformation traits of 2,738 young bulls born between 2001 and 2011. The multiple-trait REML method was applied for (co)variance component estimation. The linear model included fixed linear regressions on age at evaluation (from 10 to 23 months), fixed effects of year of birth, fixed effects of herd-classifier, and random animal effect. Heritability estimates for all analysed traits were within the range of 0.04-0.37. Among the 6 composite type traits, heritability was highest for size and for overall conformation score. The lowest heritability was for feet and legs. Among the linearly scored traits, heritability was the lowest for rear legs - side view and foot angle, and the highest for rump angle and muscularity of front end. Composite traits showed the highest genetic correlations with muscularity and final score playing the dominant role. Genetic correlations among linear traits were low and moderate (0.02-0.53). The relatively low genetic and phenotypic correlations indicated that no conformation trait of bulls can be improved by indirect selection alone. More research is needed to establish relationship between bull conformation traits and the conformation of their progeny.

Genetic and phenotypic parameter estimates for growth traits of Hainan Black goat in southern China

2015 ◽  
Vol 55 (4) ◽  
pp. 447 ◽  
Author(s):  
Han-Lin Zhou ◽  
Li-Hong Gu ◽  
Yan-Yan Sun ◽  
Tie-Shan Xu ◽  
Guang Rong
Keyword(s):  
Fixed Effects ◽  
Environmental Effect ◽  
Growth Traits ◽  
Southern China ◽  
Genetic Correlations ◽  
Parameter Estimates ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Likelihood Ratio Testing ◽  
Black Goat

Genetic improvement of the growth of Hainan Black goats is a major concern as the breed is an important meat-type goat raised in southern China. To estimate genetic and phenotypic parameters for growth traits for this breed, a population of 1354 Hainan Black goats born and maintained at the Hainan Black Goat Breeding Farm from 2007 to 2011 was used. Heritabilities and phenotypic and genetic correlations for bodyweights (BWs) at birth and at 2, 4, 6, 8, 10 and 12 months of age (denoted as BW0, BW2, BW4, BW6, BW8, BW10 and BW12, respectively) and average daily weight gains (ADGs) from birth to 2 months, from 2 to 6 months, and from 6 to 12 months (denoted as ADG0–2, ADG2–6 and ADG6–12, respectively) were estimated using an animal model, with and without a permanent maternal environmental effect fitted as a random effect. Litter size, kidding year, birth season and sex, as well as their interactions, were investigated as fixed effects. Likelihood ratio testing indicated that the model with a permanent maternal environmental effect was better than that without a permanent maternal environmental effect for all traits. The direct additive heritability for BW and ADG ranged from 0.17 (ADG6–12) to 0.45 (BW0), indicating that growth traits of Hainan Black goats can be improved by phenotypic selection. Maternal permanent environmental variance was also estimated and varied from 0.08 (BW6) to 0.27 (BW10). The genetic and phenotypic correlations among ADG traits were positive and relatively low. However, the positive and relatively high genetic and phenotypic correlations among BW traits indicated that breeding programs are able to use selection at early ages to improve BW traits.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

Genetic parameters of Barki sheep raised under semi-arid conditions

1969 ◽  
Vol 11 (3) ◽  
pp. 361-367 ◽  
Author(s):  
M. H. Fahmy ◽  
E. Salah E. Galal ◽  
Y. S. Ghanem ◽  
S. S. Khishin
Keyword(s):  
Genetic Parameters ◽  
Genetic Correlations ◽  
Research Station ◽  
Phenotypic Correlations ◽  
Arid Conditions ◽  
Body Weights ◽  
Genetic And Phenotypic Correlations ◽  
Fleece Weight ◽  
Semi Arid ◽  
Desert Research

SUMMARYRecords on 695 lambs were collected over a period of 5 years from 1961/62 to 1965/66, at Ras El-Hekma Desert Research Station, 230 km west of Alexandria. The characters studied were birth, weaning and yearling body weights, pre- and post-weaning daily gains and greasy fleece weight.Birth, 120-day and 365-day body weights were 3·4, 18·2 and 33·4 kg respectively. Greasy fleece weight at 16 months of age was 3·29 kg. Heritability estimates of birth, weaning, yearling weights, pre- and post-weaning daily gains and greasy fleece weight were 0·22, 0·45, 0·41,0·45 and 0·29 respectively. Genetic and phenotypic correlations between birth, weaning and yearling weights were all positive and significant. Genetic correlations between fleece weight and body characteristics were negative and low.

scholarly journals Comparison of Genotypic and Phenotypic Correlations: Cheverud’s Conjecture in Humans

2018 ◽  
Author(s):  
Sebastian M. Sodini ◽  
Kathryn E. Kemper ◽  
Naomi R. Wray ◽  
Maciej Trzaskowski
Keyword(s):  
Evolutionary Biology ◽  
Genetic Correlations ◽  
Accurate Estimation ◽  
Human Populations ◽  
Phenotypic Correlations ◽  
Recent Developments ◽  
Genotypic And Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Selected Traits ◽  
The Uk

AbstractAccurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud’s conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. 17 traits were selected based on sample size, distribution and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or non-morphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.

Genetic parameter estimates (full sib and half sib analysis) of fertility and hatchability in two strains of Rhode Island chickens

2021 ◽  
Vol 38 (1) ◽  
pp. 14-22
Author(s):  
M. Orunmuyi ◽  
I. A. Adeyinka ◽  
O.O Oni
Keyword(s):  
Rhode Island ◽  
Additive Genetic Variance ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Parameter Estimates ◽  
Phenotypic Correlations ◽  
Poultry Breeding ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

A study was conducted to estimate the genetic parameters of fertility and hatchability in two strains of Rhode Island Red (RIR) Chickens denoted as Strain A and Strain B respectively using the full-sib (sire +dam variance) and maternal half-sib (dam variance) components. The birds were obtained from the selected populations of RIR Chickens kept at the poultry breeding programme of National Animal Production Research Institute, Shika, Zaria, Nigeria. Settable eggs were collected from mating 28 cocks to 252 hens in a ratio of 1cock:9 hens from each strain. Eggs were pedigreed according to sire and dam. Results showed that values obtained for number of egg set (EGGSET), number of fertile eggs (NFERT), number of hatched chicks (NHATCH), percentage of chicks hatched from total eggs set (PHATCH) and percentage of chicks hatched from fertile eggs (PHATCHBL) were all higher in strain A than strain B. Heritability estimates obtained from the full-sib and maternal half-sib analysis ranged from medium to high for the two strains (0.24-0.96). The maternal half sib estimates were higher (0.40-0.96) than the estimates obtained from full sibs (0.24- 0.48). Genetic and phenotypic correlations obtained for both strains were positive and similar regardless of method of estimation. Genetic correlations between EGGSET and PFERT were low in strain A using both full-sib and maternal half-sib analyses (0.09-0.14). Phenotypic correlations between EGGSET and PFERT, PHATCH and PHATCHBL were also low in both strains and regardless of method of analyses. Moderate to high heritability estimates suggest that genetic improvement can be obtained by selection of these reproductive traits. The full-sib analysis for estimating heritability will be preferred since it is assumed that only additive genetic variance contributes to the covariance between family members.

RELATIONSHIPS OF REPRODUCTION TRAITS, BODY WEIGHT AND MILK YIELD IN DAIRY CATTLE

1986 ◽  
Vol 66 (1) ◽  
pp. 53-65 ◽  
Author(s):  
T. R. BATRA ◽  
A. J. LEE ◽  
A. J. McALLISTER
Keyword(s):  
Body Weight ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Calving Interval ◽  
Phenotypic Correlations ◽  
Reproduction Traits ◽  
Heritability Estimates ◽  
National Cooperative

The relationships between reproduction traits, body weight and milk yield were investigated using data from 1611 heifers and 733 cows from two lines of the National Cooperative Dairy Cattle Breeding Project. The data were analyzed separately for heifers and cows within lines using a mixed linear model containing fixed effects for station, year of birth, season of birth and random effect of sires. Heritability estimates and genetic correlations were estimated by a paternal half-sib analysis. Heritability estimates for heifer and cow reproduction traits ranged between 0 and 26% while those of body weights at calving and 112 d postpartum and milk yield ranged from 24 to 43%. Heifers with difficult calving had a higher incidence of retained placenta than those with normal calving. Phenotypic correlations between heifer reproduction traits and milk yield during first lactation were small. High milk production in cows was associated with longer calving interval. Phenotypic correlations between heifer's and cow's reproduction traits were small. Difficult calving in heifers impairs reproductive performance after calving resulting in greater number of days from calving to first and last breeding and leading to a longer calving interval. Key words: Reproduction traits, heifers, cows, milk yield, dairy cattle

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