Genetic Variation, Heritability, and Diversity Analysis of Upland Rice (<i>Oryza sativa</i>L.) Genotypes Based on Quantitative Traits

Tuhina-Khatun, M; Hanafi, Mohamed Musa; Rafii, Mohd Y.; Wong, Mui Yun; Salleh, Faezah Mohd; Ferdous, Jannatul

doi:10.1155/2015/290861

Cited by 92 publications

(66 citation statements)

References 13 publications

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“…Similar results were reported by Dutta et al, (2013);Singh et al, (2014) and Tuhina-Khatun et al, (2015) in rice. It is interesting to note that this difference was low for all the characters except panicle weight and stem weight, indicating that these characters were less influenced by environment.…”

Section: Discussionsupporting

confidence: 91%

“…In order to assess and quantify the genetic variability among the genotypes for the characters under study the variance components and values of heritability and genetic advance were estimated following the formula given by Burton and De Vane (1953);and Johnson et al (1955) and applied by Tuhina-Khatun et al (2015). Phenotypic and genotypic variances were estimated using the following formula: Both genotypic and phenotypic coefficients of variability were estimated using the formula below:…”

Section: Methodsmentioning

confidence: 99%

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Genetic variability and correlation analysis of rice (Oryza sativa L.) inbred lines based on agro-morphological traits

Konate¹,

Zongo²,

Kam³

et al. 2016

Afr. J. Agric. Res.

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In order to evaluate genetic variability of agro-morphological traits and also determine the correlation between grain yield with its components in rice lines, 17 recombinants inbred lines, their parents and a check variety were grown in research station of Africa rice center in Benin republic during two consecutive years 2013 and 2014. The experiments were laid out in a randomized complete block design with four replications. Phenotypic coefficients of variance were higher than genotypic coefficients of variance in all the characters across the two years. High heritability in broad sense (H 2 ) estimates were obtained for biomass (68.77%), date of 50% flowering (98.11%), plant height (81.94%), leaf area (82.90%), number of panicles (64.40%), leaf dry weight (72.91%), root weight (67.43%) and yield/plant (62.23%) suggesting that the traits were primarily under genetic control. A joint consideration of broad sense heritability (H 2 ) and genetic advance as per cent mean expected (GAM) revealed that leaves dries weight and roots weight combined high heritability and high GAM. Furthermore, high (H 2 ) and high GAM recorded in these characters could be explained by additive gene action. However, high estimates (H 2 ) combined with moderate GAM recorded for biomass, day to 50% flowering, leaf area, number of panicle and yield/plant could be due to non-additive gene effect. Grain yield/plant recorded positive and significant correlation with stem weight (r=0.5262) and biomass (r=0.9291). This result indicates that selection based on these two characters will be highly effective for yield improvement in rice.

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Section: Discussionsupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Genetic variability and correlation analysis of rice (Oryza sativa L.) inbred lines based on agro-morphological traits

Konate¹,

Zongo²,

Kam³

et al. 2016

Afr. J. Agric. Res.

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“…Similar results were reported by (Dutta et al, 2013;Singh et al, 2014;Tuhina-Khatun et al, 2015) in rice. The trait like yield panicle -1 which show higher difference between PCV and GCV indicated that environmental effect on the expression of those traits is higher.…”

Section: Estimate Of Genetic Parameterssupporting

confidence: 90%

Genetic variability analysis for various yield attributing traits in rice genotypes

Rashid

Nuruzzaman

Hassan

et al. 2017

J Bangladesh Agric Univ

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An experiment was conducted using a randomized complete block design to estimate genetic variability of ten rice genotypes. Analysis of variance for yield and yield contributing traits showed significant (p<0.01) variation among the genotypes. Results of genetic analyses showed a higher phenotypic coefficient of variation compared to their corresponding genotypic coefficient of variation for all the traits measured, which indicates that the traits were influenced by environment. The magnitude of difference between phenotypic coefficient of variance (PCV) and genotypic coefficient of variance (GCV) was less for the traits indicating little influence of environment. The higher estimates of PCV and GCV were observed for number of filled grains panicle -1 (27.53; 26.84), number of unfilled grains panicle -1 (26.76;25.28) and plant height (23.14; 23.00) indicates possibility of genetic improvement through direct selection for these traits, while days to 50% flowering, days to maturity, panicle length, number of effective tillers plant -1 , fertility (%), 1000 Seed weight and yield panicle -1 showed low PCV and GCV values indicating the need for creation of variability by hybridization or mutation followed by selection. High heritability values (>60%) along with high genetic advance and genetic advance as percentage of mean were found for all the traits indicating prevalence of additive gene action, which provides good scope for further improvement by selection.

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“…The exception was cycle 4 for GY, in which  h p 2 did not differ statistically from zero (α=0.05) due to the strong effect of residual variance (  σ 2 ) (Tables 2 and 3). The magnitude of the  h p 2 obtained in the present study for both traits (Table 3) is similar to those found in other works with upland rice crops (Colombari Filho et al, 2013;Ahmad et al, 2015;Tuhina-Khatun et al, 2015).…”

Section: Resultssupporting

confidence: 92%

“…Although several works have estimated the genetic parameters of autogamous species, such as rice (Bueno et al, 2012;Colombari Filho et al, 2013;Ahmad et al, 2015;Tuhina-Khatun et al, 2015), Falconer & Machay (1996) pointed out that the obtained results are only valid for the material of the researched population and for the environmental conditions in which the study was carried out. For this reason, the continuous study of the estimates of the variance components of a population is essential to guide genetic breeding in recurrent selection, in which the magnitude of genetic variability during the selection cycles may be affected by several different factors, such as, for example, the size of the sample for recombination, which, in turn, depends on the effective size of the recombination unit (Bernardo, 2010).…”

Section: Introductionmentioning

confidence: 99%

Genetic variability during four cycles of recurrent selection in rice

Júnior

Melo

Morais

et al. 2017

Pesq. agropec. bras.

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-The objective of this work was to estimate genetic and phenotypic parameters among progenies of the CNA6 population of upland rice (Oryza sativa) for grain yield and plant height in four cycles of recurrent selection, in order to evaluate the genetic variability and the genotype × location interaction. The experimental data were obtained from yield trials of S 0:2 progenies, which were carried out in the experimental design of Federer's augmented blocks, without replications for progenies within each location. The effect of S 0:2 progenies was significant in all cycles for grain yield and in the first three cycles for plant height, indicating the maintenance of the population's genetic potential to generate transgressive progenies. The participation of the component of the progeny × location interaction in phenotypic variance was of high magnitude. The genetic variability of the CNA6 population of upland rice is maintained for grain yield and plant height during the four cycles of recurrent selection.Index terms: Oryza sativa, genotype × environment interaction, population improvement, quantitative genetics, variance components. Variabilidade genética durante quatro ciclos de seleção recorrente em arrozResumo -O objetivo deste trabalho foi estimar parâmetros genéticos e fenotípicos entre progênies da população CNA6 de arroz (Oryza sativa) de terras altas para os caracteres produtividade de grãos e altura de plantas, em quatro ciclos de seleção recorrente, para análise da variabilidade genética e da interação genótipo × local. Os dados experimentais foram obtidos de ensaios de rendimentos de progênies S 0:2 , conduzidos em delineamento experimental de blocos aumentados de Federer, sem repetição para progênies por local. O efeito de progênies S 0:2 foi significativo em todos os ciclos para produtividade de grãos e nos três primeiros ciclos para altura de plantas, o que é indicativo da manutenção do potencial genético da população em gerar progênies transgressivas. A participação do componente da interação progênie × local na variância fenotípica foi de alta magnitude. A variabilidade genética da população CNA6 de arroz de terras altas quanto à produtividade de grãos e à altura de plantas é mantida durante os quatro ciclos de seleção recorrente.Termos para indexação: Oryza sativa, interação genótipo × ambiente, melhoramento populacional, genética quantitativa componentes de variância.

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Genetic Variation, Heritability, and Diversity Analysis of Upland Rice (Oryza sativaL.) Genotypes Based on Quantitative Traits

Cited by 92 publications

References 13 publications

Genetic variability and correlation analysis of rice (Oryza sativa L.) inbred lines based on agro-morphological traits

Genetic variability and correlation analysis of rice (Oryza sativa L.) inbred lines based on agro-morphological traits

Genetic variability analysis for various yield attributing traits in rice genotypes

Genetic variability during four cycles of recurrent selection in rice

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