scholarly journals Genetic variability and heritability for quantitative traits in China aster (Callistephus chinensis (L.) Nees.)

2021 ◽  
Vol 12 (3) ◽  
Keyword(s):  
Genetic Variability ◽  
Quantitative Traits ◽  
China Aster

Assessment of Genetic Variability and Relationship between Different Quantitative Traits in Field Pea (Pisum sativum var. arvense) Germplasm

2021 ◽  
Author(s):  
Vijay Pratap ◽  
Vijay Sharma ◽  
Kamaluddin . ◽  
Gaurav Shukla
Keyword(s):  
Genetic Variability ◽  
Correlation Coefficient ◽  
Seed Yield ◽  
Harvest Index ◽  
Quantitative Traits ◽  
Field Pea ◽  
Path Coefficient ◽  
Genetic Advance ◽  
Path Coefficient Analysis ◽  
Biological Yield

Background: Assessment of genetic variability and inter-relationship between the characters can be used in the breeding programme to evolve new varieties with wide genetic diversity to maximize the yield potential in crop improvement programmes. Eighty-four field pea genotypes were evaluated in an augmented block design for thirteen quantitative traits to study variance components, heritability, genetic advance and inter-relationship between the yield and yield contributing traits. Methods: The extent of phenotypic and genotypic variation that exist in a character was calculated by the formula suggested by Burton and de Vane (1953). Heritability in broad sense and genetic advance as per cent of mean for each character was computed using the formula suggested by Hanson et al. (1956) and Johnson et al. (1955), respectively. Correlation coefficient was calculated by method suggested by Searle (1961) and path coefficient analysis done as per method of Wright (1921) and elaborated by Dewey and Lu (1959).Result: Significant differences observed among the genotypes tested for the yield characters indicated the presence of variability. High heritability coupled with high genetic advance as percent of mean was observed for the traits viz., plant height, effective pods plant-1, harvest index and seed yield plant-1 were governed by additive gene effects which will aid in effective selection. Correlation coefficient analysis revealed that seed yield plant-1 had highly significant and positive correlation with biological yield plant-1, effective pods plant-1, harvest index, seeds pods-1 and effective nodes plant-1, indicating that these traits are strongly associated with seed yield in field pea. Path coefficient analysis identified biological yield plant-1 followed by harvest index, seed pod-1, effective nodes plant-1, 100-seed weight and day to 50% flowering as highly desirable components with great direct effects on seed yield. 

scholarly journals Genetic variability in segregating generations of greengram (Vigna radiata L.Wilczek) for quantitative traits.

2019 ◽  
Vol 10 (1) ◽  
pp. 293
Author(s):  
I. Mariyammal ◽  
M. Pandiyan ◽  
C. Vanniarajan ◽  
J. S. Kennedy ◽  
N. Senthil
Keyword(s):  
Genetic Variability ◽  
Vigna Radiata ◽  
Quantitative Traits

scholarly journals Phenotypic and genetic variability, heritability and genetic advance for quantitative traits of two-rowed spring barley in Forest-steppe of Ukraine

2018 ◽  
Vol 0 (1) ◽  
pp. 81-86
Author(s):  
Володимир Миколайович Гудзенко ◽  
Олена Сергіївна Дем’янюк
Keyword(s):  
Genetic Variability ◽  
Quantitative Traits ◽  
Spring Barley ◽  
Forest Steppe ◽  
Genetic Advance

Dissection of additive genetic variability for quantitative traits in chickens using SNP markers

2014 ◽  
Vol 131 (3) ◽  
pp. 183-193 ◽  
Author(s):  
R. Abdollahi-Arpanahi ◽  
A. Pakdel ◽  
A. Nejati-Javaremi ◽  
M. Moradi Shahrbabak ◽  
G. Morota ◽  
...  
Keyword(s):  
Genetic Variability ◽  
Quantitative Traits ◽  
Snp Markers

scholarly journals Quantitative and molecular genetic variation in sympatric populations of Medicago laciniata and M. truncatula (Fabaceae): relationships with eco-geographical factors

2007 ◽  
Vol 89 (2) ◽  
pp. 107-122 ◽  
Author(s):  
MOUNAWER BADRI ◽  
HOUCINE ILAHI ◽  
THIERRY HUGUET ◽  
MOHAMED ELARBI AOUANI
Keyword(s):  
Genetic Variation ◽  
Genetic Variability ◽  
Local Adaptation ◽  
Quantitative Traits ◽  
Gene Diversity ◽  
Sympatric Populations ◽  
Widespread Species ◽  
Geographical Factors ◽  
Significant Difference ◽  
Selection For

SummaryMedicago laciniata is restricted to south of the Mediterranean basin and it extends in Tunisia from the inferior semi-arid to Saharan stages, whereas M. truncatula is a widespread species in such areas. The genetic variability in four Tunisian sympatric populations of M. laciniata and M. truncatula was analysed using 19 quantitative traits and 20 microsatellites. We investigated the amplification transferability of 52 microsatellites developed in M. truncatula to M. laciniata. Results indicate that about 78·85% of used markers are valuable genetic markers for M. laciniata. M. laciniata displayed significantly lower quantitative differentiation among populations (QST=0·12) than did M. truncatula (QST=0·45). However, high molecular differentiations, with no significant difference, were observed in M. laciniata (FST=0·48) and M. truncatula (FST=0·47). Several quantitative traits exhibited significantly smaller QST than FST for M. laciniata, consistent with constraining selection. For M. truncatula, the majority of traits displayed no statistical difference in the level of QST and FST. Furthermore, these traits are significantly associated with eco-geographical factors, consistent with selection for local adaptation rather than genetic drift. In both species, there was no significant correlation between genetic variation at quantitative traits and molecular markers. The site-of-origin explains about 5·85% and 11·27% of total quantitative genetic variability among populations of M. laciniata and M. truncatula, respectively. Established correlations between quantitative traits and eco-geographical factors were generally more moderate for M. laciniata than for M. truncatula, suggesting that the two species exhibit different genetic bases of local adaptation to varying environmental conditions. Nevertheless, no consistent patterns of associations were found between gene diversity (He) and environmental factors in either species.

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