Estimates of Genetic Variability, Heritability and Genetic Advance for Blast Resistance Gene Introgressed Segregating Population in Rice

Govintharaj, Ponnaiah; Tannidi, Shalini; Manonmani, S.; Robin, S.

doi:10.20546/ijcmas.2016.512.075

Cited by 9 publications

(4 citation statements)

References 4 publications

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“…This finding was line up with (Ameenal et al, 2016;Ponnaiah Govintharaj et al, 2016). Negative skewness was noticed only in panicle length and it explained that duplicate gene interaction plays major role (Lestari et al, 2015).…”

Section: Tnau Cms 2b × Zenithsupporting

confidence: 79%

Genetic Variability for Yield and Yield Components Characters in Bacterial Blight and Blast Resistance Genes Introgressed Backcross Populations in Rice

Govintharaj¹,

Tannidi²,

Manonmani³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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Section: Tnau Cms 2b × Zenithsupporting

confidence: 79%

Genetic Variability for Yield and Yield Components Characters in Bacterial Blight and Blast Resistance Genes Introgressed Backcross Populations in Rice

Govintharaj¹,

Tannidi²,

Manonmani³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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“…Wider variability, low to high heritability and genetic advance as percent of mean, skewness and kurtosis was found among these crosses for all the traits were reported earlier by PONNAIAH GOVINTHARAJ et al (2016 and.…”

Section: Resultssupporting

confidence: 57%

Character association and path analysis in bacterial blight resistance genes pyramided segregating populations of rice (Oryza sativa L.)

2018

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An exploratory research work was conducted to study the character association and their direct and indirect effects on grain yield in three bacterial blight resistance genes introgressed segregating populations (F2) in rice. Data for yield and five other traits which were component of yield were recorded in 449 F2 individuals in all three crosses. Thousand grain weight was highly correlated with single plant yield in (r=0.95**, p<0.01) CB 174 R × IRBB 60> (r=0.48**, p<0.01) CB 87 R × IRBB 60> (r=0.44**, p<0.01) TNAU CMS 2B × IRBB 60. Thousand grain weight was exhibited important yield determining component for CB 174 R × IRBB 60 (0.92) and CB 87 R × IRBB 60 (0.45), and panicle length for (0.39) TNAU CMS 2B × IRBB 60 by direct effect. The genetic information derived from our study could be useful to select potential segregating individual among the F2 population for future rice breeding program.

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“…In contrast, Immanuel et al [59] found high heritability value of more than 90% and high GA for most traits except for days to maturity and panicle length which had a moderate genetic advance. Work of Govintharaj et al [60] also observed high and moderate heritability for several traits in the segregating population of blast introgressed lines.…”

Section: Discussionmentioning

confidence: 86%

Assessment of Agro-Morphologic Performance, Genetic Parameters and Clustering Pattern of Newly Developed Blast Resistant Rice Lines Tested in Four Environments

et al. 2020

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Multi-environmental yield trial is very vital in assessing newly developed rice lines for its adaptability and stability across environments especially prior to release of the newly developed variety for commercial cultivation. The growth performance and phenotypic variability of these genotypes are the combination of environment, genotype and genotype by environment (G×E) interaction factors. Thus, evaluation creates an opportunity for effective selection of superior genotypes. The objectives of this study were to evaluate the newly developed blast resistant rice lines in varied environmental conditions, precisely measure the response of the advanced lines in multiple environments and classify the genotypes into groups that could serve as varieties for commercial cultivation. Genetic materials included 18 improved blast resistant rice lines and the recipient parent MR219. The total of 19 newly developed genotypes was evaluated under four varied environments in Peninsular Malaysia. The experiments were carried out using randomized complete block design (RCBD) with three replications at each environment. Data were collected on the vegetative, yield and yield component traits. Descriptive statistics (mean performance) and analysis of variance were conducted using SAS Software version 9.4. Genotypic and phenotypic coefficients, phenotypic variance component, heritability and genetic advance were also determined. Analysis of variance revealed that all traits were significantly different for genotypes except days to maturity, number of filled grains and total number of grains. Meanwhile, all the traits differed significantly for genotype × environment (G×E) except number of tillers per hill and number of panicles per hill. Low heritability (<30%) was found for all the traits. Similarly, low genetic advance was also observed for all the traits except for number of tillers per hill and number of panicles per hill. yield per hectare had significant and positive correlation with most evaluated traits except for days to flowering, days to maturity, plant height and number of unfilled grains. Cluster analysis classified the 19 evaluated genotypes into six groups. Therefore, the six clusters/groups of genotypes were recommended as varieties for commercial cultivation in Malaysia and other rice growing regions.

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Estimates of Genetic Variability, Heritability and Genetic Advance for Blast Resistance Gene Introgressed Segregating Population in Rice

Cited by 9 publications

References 4 publications

Genetic Variability for Yield and Yield Components Characters in Bacterial Blight and Blast Resistance Genes Introgressed Backcross Populations in Rice

Genetic Variability for Yield and Yield Components Characters in Bacterial Blight and Blast Resistance Genes Introgressed Backcross Populations in Rice

Character association and path analysis in bacterial blight resistance genes pyramided segregating populations of rice (Oryza sativa L.)

Assessment of Agro-Morphologic Performance, Genetic Parameters and Clustering Pattern of Newly Developed Blast Resistant Rice Lines Tested in Four Environments

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