Genetic Variability, Heritability and Genetic Advance for Yield and some Agronomic Traits in Digitaria exilis Accessions

2020 ◽  
Vol 8 (1) ◽  
pp. 1-5
Author(s):  
F. A. Umar ◽  
Keyword(s):  
Genetic Variability ◽  
Agronomic Traits ◽  
Genetic Advance ◽  
Digitaria Exilis

scholarly journals Genetic variability, heritability and genetic advance for growth, yield and yield related traits in maize genotypes

2021 ◽  
Vol 2 (2) ◽  
pp. 96-104
Author(s):  
Roshesh Rai ◽  
Prakash Khanal ◽  
Prabin Chaudhary ◽  
Rabin Dhital
Keyword(s):  
Genetic Variability ◽  
Grain Yield ◽  
Agronomic Traits ◽  
Block Design ◽  
Genetic Advance ◽  
Improvement Program ◽  
Positive Correlation ◽  
Maize Genotypes ◽  
High Heritability ◽  
Ear Height

Evaluation of the genetic variability, heritability and genetic advance of traits is an essential task in any plant improvement program. Twenty maize genotypes were replicated twice in a randomized complete block design on a research plot of Prithu Technical College, Deukhuri Dang of Nepal from June 2017 to September 2017 to determine genetic variability, heritability, and genetic advance for different agronomic traits. Analysis of variance showed significant differences in the traits tassel length, ear height, days to fifty percent tasseling, days to fifty percent silking, kernels’ rows ear-1, kernels row-1 and grain yield. The highest GCV (31.53%) and PCV (39.20%) were recorded on grain yield. Grain yield and ear height recorded high heritability along with high genetic advance as a percent of mean (GAM). Tassel length and kernels row-1 showed high heritability integrated with moderate GAM and moderate heritability integrated with moderate GAM respectively. Further, grain yield showed a significant and positive correlation with plant height, tassel length, ear height, cob length, cob diameter, kernels’ rows ear-1, and kernels row-1. Thus the selection of ear height, tassel length and kernels row-1 is suggested as they performed better in terms of both heritability and GAM than other traits and they also recorded a significant and positive correlation with yield.

scholarly journals Genetic variability and association pattern among quantitative nutritional traits in Swiss chard (Beta vulgaris subsp. L. var. cicla) accessions and its implication for breeding

Genetika ◽  
2014 ◽  
Vol 46 (2) ◽  
pp. 505-514
Author(s):  
Kadri Bozokalfa ◽  
Bülent Yağmur ◽  
Dursun Eşiyok ◽  
Aşçioğul Kaygisiz
Keyword(s):  
Genetic Variability ◽  
Agronomic Traits ◽  
Leafy Vegetables ◽  
Genetic Advance ◽  
Nutritional Elements ◽  
Coefficient Variation ◽  
Swiss Chard ◽  
Health Promoting ◽  
High Heritability ◽  
Mineral Concentrations

In addition to improving agronomic traits, enriched cultivar such as nutritional elements and health promoting compounds are new demands for today's and the future's perspectives of crop breeding. In this respect, among leafy vegetables Swiss chard is a good source of nutritional elements and supplies large amounts of health promoting compounds. The existing knowledge of genetic variability for mineral composition both at the phenotype and genotype level, heritability of characters and also relationships among investigated minerals is fundamental for variety selection in Swiss chard. This also applies for the assurance of desirable agronomic traits with optimum mineral concentrations. This research analysis of variance indicated highly significant differences among Swiss chard accessions for all investigated mineral concentrations and the accessions display higher phenotype coefficient variation than genotype coefficient variation for all traits. The results revealed that phosphorus, magnesium, sodium, iron, copper, zinc, manganese, nitrate and nitrite exhibited high genetic advance accompanied with high heritability (>60%). The remaining mineral content demonstrated high heritability with moderate genetic advance. Genotype correlations were higher than the phenotype correlation for significant mineral concentrations. Genotype and phenotype correlations followed similar trends in all significant cases indicating the high heritable nature of the characters and the results showed that Swiss chard accessions should allow for the selection of individuals for enriched mineral concentration in edible parts of the plant.

scholarly journals GENETIC VARIABILITY AND CHARACTER ASSOCIATION FOR AGRONOMIC TRAITS IN HYBRID RICE (Oryza Sativa L.)

2013 ◽  
Vol 24 (1) ◽  
pp. 45-51 ◽  
Author(s):  
M. J. Hasan ◽  
M. U. Kulsum ◽  
A. Akter ◽  
A. S. M. Masuduzzaman ◽  
M. S. Ramesha
Keyword(s):  
Genetic Variability ◽  
Hybrid Rice ◽  
Agronomic Traits ◽  
Oryza Sativa L ◽  
Genetic Advance ◽  
Thousand Grain Weight ◽  
Rice Varieties ◽  
Diverse Origin ◽  
Correlation And Path Analysis ◽  
Positive Effect

Twenty four hybrid rice varieties of diverse origin were studied for genetic variability, correlation and path analysis under medium high land of Gazipur. The PCV values were greater than GCV, revealing little influence of environment in character expression. High values of heritability along with moderate genetic advance were observed for panicle/m2, days to 50% flowering and plant height. Grain yield showed positive significant association with number of effective tillers/hill, panicle/m2, spikelet fertility and thousand grain weight at both genotypic and phenotypic levels. Same traits had highest significant positive effect on yield.DOI: http://dx.doi.org/10.3329/bjpbg.v24i1.16999

scholarly journals Genetic variability and association of yield and yield components among bread wheat genotypes under drought-stressed conditions

2021 ◽  
pp. 863-870
Author(s):  
Yared Semahegn ◽  
Hussein Shimelis ◽  
Mark Laing ◽  
Isack Mathew
Keyword(s):  
Genetic Variability ◽  
Grain Yield ◽  
Bread Wheat ◽  
Yield Components ◽  
Agronomic Traits ◽  
Genetic Advance ◽  
Wheat Cultivars ◽  
Wheat Genotypes ◽  
Lattice Design ◽  
Yield And Yield Components

Drought is one of the major constraints to wheat production and productivity globally. Developing drought-adapted wheat cultivars is paramount to increase wheat productivity under variable rainfall conditions. Understanding the genetic variability and trait association is key to the development of improved wheat cultivars. The objective of this study was to determine the extent of the genetic parameters and associations of yield and yield components of bread wheat genotypes, in order to design appropriate breeding strategies for yield improvement in wheat. One hundred and twenty genotypes were evaluated at five test sites in the 2018/19 cropping season using a 10 x 12 alpha lattice design with two replications. Different sowing dates were used to impose contrasting drought stress levels based on the onset of the main seasonal rains at each site. Data were recorded on agronomic traits such as days to heading (DH), days to maturity (DM), plant height (PH), spike length (SL), spikelet per spike (SS), kernel per spike (KS), 1000 kernel weight (TKW) and grain yield (GY). There was significant (p<0.01) genetic variation for all agronomic traits studied under both drought-stressed and non-stressed conditions. The highest estimates for genetic variance were obtained for DH (54.0%), followed by SL (38.3%). The high heritability estimated for DH (94.4%), SL (90.2%) and SS (85.2%), coupled with a high rate of genetic advance, suggest that direct selection for these traits would be effective under drought-stressed conditions. GY exhibited low genetic advance (9%) and heritability (41.5%) estimates, which were concomitant with its polygenic and complex inheritance pattern. Correlation and path analyses revealed that TKW was the most important contributing trait for improving grain yield under drought-stressed conditions

scholarly journals Genetic Variability, Heritability, Genetic advance and Divergence in Ethiopian Cowpea [Vigna unguiculata (L) Walp] Landraces

2020 ◽  
Author(s):  
Fantaye Belay ◽  
Kibrom Fischa
Keyword(s):  
Genetic Variability ◽  
Seed Yield ◽  
Coefficient Of Variation ◽  
Agronomic Traits ◽  
Agricultural Research ◽  
Crop Improvement ◽  
Grain Filling ◽  
Genetic Advance ◽  
Improvement Program ◽  
Cluster Distance

Abstract Information on genetic variability in cowpea germplasm is important for crop improvement and for efficient utilization of the existing genetic resources. Hence, the objectives of the present investigation were to estimate genetic variability, heritability, genetic advance and to identify divergent parents from distantly related clusters among Ethiopian cowpea accessions. The field experiment was carried out using 42 accessions at Abergelle Agricultural Research Center on station during the 2019 cropping season. Data were collected for 8 agronomic traits and analysis of variance revealed significant differences (p<0.01) among the accessions for the traits studied. Seed yield had higher genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) coupled with the highest genetic advance as percent of mean (100%). All the traits had moderate (68.01) to very high (99.98%) broad sense heritability. Further, high heritability coupled with high genetic advance as percent of mean was attained for days to flowering, grain filling period, plant height, pod length, seed yield and thousand seed weight reflecting the presence of additive gene action for the expression of these traits and improvement of these traits could be done through selection. The cluster analysis based on agronomic traits revealed four distinct groups at 90% similarity level. The highest inter cluster D2 was recorded between cluster III and cluster IV (D2=133.69 units). The range of inter cluster distance was 15.25 to 133.69 units, respectively. In conclusion, the high genetic distance revealed among clusters has to be exploited via crossing and selection of the most divergent parents for future cowpea improvement program.

Assessment of Genetic Variability, Diversity and Trait Correlation Analysis in Common Bean (Phaseolus vulgaris L.) Genotypes

2020 ◽  
Author(s):  
T. Basavaraja ◽  
L. Manjunatha ◽  
Rahul Chandora ◽  
S. Gurumurthy ◽  
N.P. Singh
Keyword(s):  
Genetic Variability ◽  
Seed Yield ◽  
Coefficient Of Variation ◽  
Agronomic Traits ◽  
Genetic Advance ◽  
High Heritability ◽  
Augmented Design ◽  
Pod Length ◽  
Trait Correlation ◽  
Number Of Branches

The present investigation was undertaken to study the genetic variability, diversity through cluster analysis and correlation among yield attributing traits. The experimental material is comprised of 63 diverse germplasm accessions including three check varieties were evaluated in augmented design during Rabi 2015-16 at IIPR, Kanpur. In this study, totally nine traits, namely, days to fifty per cent flowering (DF), days to maturity (DM), plant height (PH), number of branches per plant (NBP), number of pods per plant (NPP), pod length (PL), seeds per pod (SPP), 100 seeds wt (g) (HSW) and seed yield per plant (g) (SYP) were recorded. The results exhibited that the analysis of variance noticed significant differences among the genotypes for all characters studied. The genetic variability parameter showed that phenotypic coefficient of variation (PCV) were higher than those of genotypic coefficient of variation (GCV) for all the traits studied. Higher GCV coupled with heritability and genetic advance as % mean was recorded for PH, NPP, HSW and SYP. Likewise, high heritability coupled with high genetic advance as % mean was recorded in DF, PH, NPP, PL, HSW and SYP. Trait association study revealed that the seed yield per plant exhibited significant positive correlation with NBP, NPP, NSP and HSW. In the same pattern, Euclidian clustering analysis displays 63 genotypes were grouped to two major clusters. From this investigation, it was observed that all genotypes showed sufficient genetic variability for the traits studied. The genotype such as EC400414, EC400398, ET8415 and EC540173 were superior to check varieties in terms of morphological and other agronomic traits. These genotypes could be utilized in breeding programme for improvement of specific traits. 

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. 

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