Showing 4 results for Heritability.
M. Modarresi, M. T. Assad, M. Kheradnam,
Volume 7, Issue 4 (1-2004)
Abstract
Yield is a quantitative trait and improving grain yield through direct selection is time-consuming. Indirect selection consisting of selection indices is more promising. A field experiment was conducted during 1999-2000 growing season in two experimental locations (Kooshkak and Badjgah) of College of Agriculture, Shiraz University, Shiraz. Thirteen corn hybrids were used in a randomized complete block design with three replications in each location. Thirty-five traits were measured in five developmental stages (stem elongation, tasseling, blister, hard dough and physiological maturity) and combined analysis of variance and covariance were conducted. Finally, 12 traits were selected for constructing selection indices via path analysis. Two optimum selection indices were used in this experiment. In both selection indices, different combinations of traits applied as linear function (multivariate linear model) and coefficients of traits in combinations were calculated. The coefficient of indices were obtained from: b=P-1Ga, where b is the vector of index coefficients, P-1 is the inverse of phenotypical variance and covariance matrix, G is the matrix of genotypical variance and covariance and a is the column vector of traits heritability. In the first index, heritability of traits with the same sign was used as economic values. Selection index including grain yield and net assimilation rate in the second stage (NAR2) was the best. In the second index, the sign of genotypic correlation with yield was given to economic values. Finally, selection index including grain yield and NAR2 was the best, too. In both selection indices, correlation of selection indices with genotypic value was equal to 1. This was 14% higher than the first index including yield alone. In both selection indices, physiological indices including net assimilation, crop growth, and relative growth rates were the most important traits comprising the best selection indices.
H. Farhangfar, H. Naeemipour Younesi,
Volume 11, Issue 1 (4-2007)
Abstract
A total of 25,471 Iranian Holstein heifers distributed in 523 herds of 20 provinces were used to estimate heritability, genetic and phenotypic associations between a number of traits related to the production and reproduction performance. The Animal Breeding Centre of Iran collected the records studied in this research between 1991 and 2001. The traits associated with production were 305-day, 2x adjusted milk, fat yields and fat percentage and the traits associated with reproduction were age at first calving, number of services per conception, gestation period, calving interval as well as dry days as a separate trait. The heritability estimates were 0.31, 0.23, 0.31, 0.14, 0.03, 0.05, 0.10 and 0.01 for 305-day, 2x milk, fat yields, fat percentage, age at first calving, dry days, calving interval, gestation period and the number of services per conception, respectively. Milk yield was genetically correlated with age at the first calving (-0.14), dry days
(-0.31), calving interval (0.54), gestation period (0.01) and the number of insemination per conception (0.38). Fat yield had negative genetic correlations with age at first calving (-0.16), dry days (-0.23) while it was positively correlated with calving interval (0.44), gestation period (0.11) and the number of insemination per conception (0.20). Age at the first calving, dry days and gestation period had a positive genetic correlation with fat percenateg (0.03, 0.15 and 0.09 respectively) while calving interval and the number of insemination per conception were negatively correlated with fat percentage (-0.21 and -0.25 respectively).
R. Honarnejad,
Volume 11, Issue 41 (10-2007)
Abstract
Six Iranian rice cultivars (Binam, Domsiyah, Shahpasand, Sepidrud, Khazar and Valed 46) were crossed in 1989 in the Iranian Rice Research Institute in Rasht, Iran in a full-diallel design. The F1 progenies together with parents were transplanted in a CRBD in the 5 x 0.75 m plots at plant density of 25 x 25 cm (60 plantlets per plot) in 3 replications. Part of this research was published in 1994 as a half-diallel design and the data of full-diallel, using Griffing approach, is subject of this paper. The analysis of variance showed significant differences among genotypes. The mean of six parents, 15 crosses and 15 reciprocal crosses were analyzed using the four diallel crossing systems of the Griffing approach. The SS of genotypes were separated into GCA for each parent and SCA for each cross using corresponding formula. The additive variance (VA) and dominance variance (VD) values were estimated using the table of variance analysis. The heritability (h2ns) was also estimated from VA and VD variances. The simple variance analysis of “grain yield per plant” and other agronomic traits using each of the 4 diallel crossing methods of Griffing showed significant differences (P < 1%) among genotypes, indicating a sufficient genetic potential of the investigated genotypes. The GCA variance analysis of the lines was significant for all the characteristics, indicating the importance of additive variance (VA) by inheritance of these traits. Using Griffing’s diallel methods 1 and 3, SCA variances for all investigated traits showed significance, whereas in the methods 2 and 4, traits “1000 grain weight” and “tiller per plant” were not significant according to SCA. This also indicates the importance of dominant variance (VD) in most of the traits, except for “1000 grain weight” and “tiller per plant”. The differences among the reciprocal crosses in diallel methods 1 and 3 were also examined where for all the characteristics (except for “deaf grains per panicle” and “length to breadth ratio of brown rice grain”) significant differences were observed, suggesting the possibility of cytoplasmic effect of mother line on the reciprocal crosses. The heritability (h2ns), which indicates the ratio of additive variance (VA) to phenotypic variance (VP), was estimated to be equal to zero due to the absence of additive variance for grain per panicle and the number of days from transplanting to full maturity of grain. The heritability for other characteristics was estimated high or low according to additive variance. For example in all 4 diallel methods the heritability estimation for length to breadth ratio of brown rice grain was relatively high (65 – 71%) whereas for “panicle length” and “grain yield per plant” was relatively low (13 – 48%). The correlation among genetic parameters (VA, VD, D, h2ns ) were generally high and significant.
F Ghafori, M Eskandari, H Mohamadi,
Volume 13, Issue 47 (4-2009)
Abstract
Variance components and genetic parameters of body weight of Mehraban sheep were estimated by univariate and random regression models. This was done by using body weight records of 2746 Mehraban lambs related to flocks under supervision of the Agriculture Organization of the Hamadan province, collected between 1990 and 2005. In both methods, variance components estimates were obtained by restricted maximum likelihood (REML) using DFUNI and DXMRR programs, respectively, via DFREML 3.1 software package. Results showed that variance components obtained from RR models (except for residual variance) in some ages were higher than those obtained from univariate models. Direct heritability (h2) estimates from univariate and RR models were approximately equal to weaning age but, overall, RR estimates were higher than those obtained from univariate analyses. Maternal heritability estimates (m2) from RR models were higher than univariate models’ estimates, and showed a different pattern of variation with age. Correlations between predicted breeding values from univariate and RR models for birth weight and weaning weight were 0.72 and 0.70, respectively. Results showed that estimates of variance components and genetic parameters by RR models were affected by data structure and in case of the need for genetic parameters, especially those related to body weight late in lambs’ life, estimates of univariate analyses should be preferred.
