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Estimation of Genetic Variances and Stability Components of Yield-Related Traits of Green Super Rice at Multi-Environmental Conditions in Pakistan
by
Uzair, Muhammad
, Zaid, Imdad Ullah
, Habib, Madiha
, Naeem, Muhammad Kashif
, Asghar, Umair
, Zahra, Nageen
, Ali, Ghulam Muhammad
, Latif, Anila
, Khan, Muhammad Ramzan
, Rehman, Anum
in
Agricultural production
/ AMMI
/ Crop yield
/ Cultivars
/ Environmental conditions
/ Environmental factors
/ Exports
/ Fertilizers
/ Genetic diversity
/ Genetic variability
/ Genetic variance
/ Genomics
/ Genotype & phenotype
/ Genotypes
/ GGE biplot analysis
/ Grain
/ Heritability
/ Loam soils
/ Morphology
/ Multivariate analysis
/ Research centers
/ Rice
/ Seeds
/ Stability analysis
/ univariate stability analysis
/ variability
/ Variance analysis
2022
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Estimation of Genetic Variances and Stability Components of Yield-Related Traits of Green Super Rice at Multi-Environmental Conditions in Pakistan
by
Uzair, Muhammad
, Zaid, Imdad Ullah
, Habib, Madiha
, Naeem, Muhammad Kashif
, Asghar, Umair
, Zahra, Nageen
, Ali, Ghulam Muhammad
, Latif, Anila
, Khan, Muhammad Ramzan
, Rehman, Anum
in
Agricultural production
/ AMMI
/ Crop yield
/ Cultivars
/ Environmental conditions
/ Environmental factors
/ Exports
/ Fertilizers
/ Genetic diversity
/ Genetic variability
/ Genetic variance
/ Genomics
/ Genotype & phenotype
/ Genotypes
/ GGE biplot analysis
/ Grain
/ Heritability
/ Loam soils
/ Morphology
/ Multivariate analysis
/ Research centers
/ Rice
/ Seeds
/ Stability analysis
/ univariate stability analysis
/ variability
/ Variance analysis
2022
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Estimation of Genetic Variances and Stability Components of Yield-Related Traits of Green Super Rice at Multi-Environmental Conditions in Pakistan
by
Uzair, Muhammad
, Zaid, Imdad Ullah
, Habib, Madiha
, Naeem, Muhammad Kashif
, Asghar, Umair
, Zahra, Nageen
, Ali, Ghulam Muhammad
, Latif, Anila
, Khan, Muhammad Ramzan
, Rehman, Anum
in
Agricultural production
/ AMMI
/ Crop yield
/ Cultivars
/ Environmental conditions
/ Environmental factors
/ Exports
/ Fertilizers
/ Genetic diversity
/ Genetic variability
/ Genetic variance
/ Genomics
/ Genotype & phenotype
/ Genotypes
/ GGE biplot analysis
/ Grain
/ Heritability
/ Loam soils
/ Morphology
/ Multivariate analysis
/ Research centers
/ Rice
/ Seeds
/ Stability analysis
/ univariate stability analysis
/ variability
/ Variance analysis
2022
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Estimation of Genetic Variances and Stability Components of Yield-Related Traits of Green Super Rice at Multi-Environmental Conditions in Pakistan
Journal Article
Estimation of Genetic Variances and Stability Components of Yield-Related Traits of Green Super Rice at Multi-Environmental Conditions in Pakistan
2022
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Overview
Identifying adopted Green Super Rice (GSR) under different agro-ecological locations in Pakistan is crucial to sustaining the high productivity of rice. For this purpose, the multi-location trials of GSR were conducted to evaluate the magnitude of genetic variability, heritability, and stability in eight different locations in Pakistan. The experimental trial was laid out in a randomized complete block (RCB) design with three replications at each location. The combined analysis of variance (ANOVA) manifested significant variations for tested genotypes (g), locations (L), years (Y), genotype × year (GY), and genotype × location (GL) interactions revealing the influence of environmental factors (L and Y) on yield traits. High broad-sense heritability estimates were observed for all the studied traits representing low environmental influence over the expression of traits. Noticeably, GSR 48 showed maximum stability than all other lines in the univariate model across the two years for grain yield and related traits data. Multivariate stability analysis characterized GSR 305 and GSR 252 as the highest yielding with optimum stability across the eight tested locations. Overall, Narowal, Muzaffargarh, and Swat were the most stable locations for GSR cultivation in Pakistan. In conclusion, this study revealed that G×E interactions were an important source of rice yield variation, and its AMMI and biplots analysis are efficient tools for visualizing the response of genotypes to different locations.
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