Genotype × Environment Interaction and Yield Stability Analysis in Hybrid Rice (Oryza sativa L.) By AMMI Biplot

Akter, A; Hasan, MJ; Kulsum, MU; Rahman, Md. Mosaddequr; Paul, Anu; Lipi, LF; Akter, Salma

doi:10.3329/brj.v19i2.28168

Cited by 29 publications

(19 citation statements)

References 16 publications

(18 reference statements)

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“…The differences of mean square due to (environments + (Genotypes X Environments) were highly significant for all traits studied which exhibited that considerable interaction of all entries under different environmental conditions of years, locations and treatments in different years. The variances due to entries were showed to be highly significant for all the traits studied against pooled deviation which means the presence of sufficient genetic variability between the genotypes, Gill and Kumar (1989), Popovic et al, (2013), Selvi et al, (2015), Hamawaki et al, (2015), Akter et al, (2015)and Silva et al, (2016).…”

Section: Variation and Interactionmentioning

confidence: 87%

Molecular Characterization and Stability Analysis for Yield and its Components Traits in Soybean (Glycine max L.)

Mouhamady¹,

Rahman²,

Elewa³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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Seven soybean entries namely;(Crawford, Giza 21, Giza 22, Giza 35, Giza 82, Giza 83 and Giza 111) with different reaction for highly yielding, tolerance for salinity, water deficit conditions and resistance for diseases were evaluated under twelve environments through two years (2015, 2016 seasons), three locations (the farm of agricultural research in Mansoura city, Dakahlia Governorate, the farm of agriculture research center, Sakha station Kafr El-Sheikh governorate and the farm of national research Centre in Nubaria, Beheira Governorate, Egypt) in addition two planting dates (the first planting date was 15 may, while the second date was 1 June) to study the range of genetic stability, the behavior responsible for the persistence cultivar, the interactions between these cultivars and all different environments and their effect on some yield components, respectively. Stability analysis was done using data calculated obtained from plant height, first pod height, number of pods/plant, 1000-grain weight, number of grains/plant, grain weight/plant and grain yield/plant traits beside (Random amplified polymorphic DNA (RAPD) through using four primers for the previous seven cultivars. The final results revealed that mean square variances of (Genotypes x Environments), (Environments+(Genotypes x Environments), the linear components of (Environments) and (Genotypes x Environments) and pooled deviation were highly significant and detected that the genotypes; (Crawford, Giza 21, Giza 22, Giza 35, Giza 83, Giza 111) were the most genetic stability entries according to the results of stability analysis specially (bi, S 2 di, R 2 ) and recommended for using it under different environments, while the cultivar (Giza 82) coming in the second rank. Heritability in broad sense was high in plant height, number of pods/plant and grain yield/plant traits which indicated that the environment effect on these traits through using the previous entries was very low with intension the genetic stability unlike the rest of traits studied. DNA Fingerprinting analysis was conducted to compare between the seven soybean entries using four primers namely; (OPC10, OPF-4, OPA-17, and OPG-5). The four primers recorded 12 amplicons, where 8 of them were polymorphic with 66.67% polymorphism, while 4 fragments were monomorphic. Cluster analysis divided the seven genotypes into two main clusters, where the first one contained the genotypes (2, 4), while the second cluster involved the rest of genotypes, respectively.

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Section: Variation and Interactionmentioning

confidence: 87%

Molecular Characterization and Stability Analysis for Yield and its Components Traits in Soybean (Glycine max L.)

Mouhamady¹,

Rahman²,

Elewa³

et al. 2017

Int.J.Curr.Microbiol.App.Sci

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“…Previously, studies comparing transgenic cultivars and non-transgenic recurrent parents have shown a significant difference between these cultivars in yield and quality traits [24,41,57]. Studies of hybrids of rice [16,58] and maize [59,60] have concluded that hybrid genotypes are not only high-yielding but also show stable performance in different environments. The ultimate objective of the current study was to compare the performance and stability of hybrids and inbred lines of cotton in different environments.…”

Section: Discussionmentioning

confidence: 99%

“…Many studies have reported that GEI has significant effects on yield and quality traits in various crops [13][14][15][16]. Similarly, GEI research has long been of major interest to cotton breeders.…”

Section: Introductionmentioning

confidence: 99%

“…Many parametric and non-parametric models have been developed for plant breeding to analyze the responses of genotypes to different environments [26][27][28]. Several researchers have reported that the additive main effects and multiplicative interaction (AMMI) model is effective for investigating GEIs in agronomic crops, e.g., rice [16,29], wheat [13,30], and maize [31]. The AMMI model uses regression analysis, which depends on G and E scores derived from principal component analysis of the GEI matrix to identify covariates of genotypes and environments [32].…”

Section: Introductionmentioning

confidence: 99%

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Adaptability and Stability Comparisons of Inbred and Hybrid Cotton in Yield and Fiber Quality Traits

Shahzad

Guo

et al. 2019

Agronomy

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Cotton (Gossypium hirsutum L.) is the most important fiber crop worldwide. Characterizing genotype by environment interaction (GEI) is helpful to identify stable genotypes across diverse environments. This study was conducted in six environments to compare the performance and stability of 11 inbred lines and 30 intraspecific hybrids of cotton. Analysis of variance using the additive main effects and multiplicative interaction model revealed that genotype (G), environment (E), and GEI had highly significant effects on yield and fiber quality traits. Mean comparisons among genotypes showed that most hybrids had higher means for yield and fiber quality traits than inbred genotypes. Additionally, a larger portion of the total variability in yield traits was explained by E than G and GEI. However, G and GEI combined contributed more to the total variance in fiber traits than E. The first three interaction principal components explained the majority of GEI in all traits under study. For most traits, the environments were not clustered together, implying contrasting interaction with genotypes. Stability measurements indicated that most hybrids showed more stable performance than inbred lines for all traits. The hybrids SJ48-1 × Z98-15 and L28-2 × A2-10 displayed both better performance and stability in yield and fiber quality traits. Our results show the importance of hybridization for improving cotton yield and fiber quality in a wide range of environments.

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“…The performance of a crop is the result of the cultivar's genotype (G), the environment in which it grows (E), and the interaction between G and E (GEI) (Akter et al, 2015). Interaction between these two explanatory variables gives an insight towards the identification of the genotype suitable for specific environments, which may constitute good opportunities (Bornhofen et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis for genotype stability and adaptability in maize yield based on environment and genotype interaction models

Machado

Neto

Hongyu

2019

CeN

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Current analysis investigates genotype x environment interaction and stability performance of grain yield with nine maize genotypes in seven environments. ANOVA revealed highly significant (p-value<0.001) data for genotypes, environments and their interactions. Only PC1 (45.4%) and PC2 (35%) were significant (p ≤ 0.05). Genotype G7 had a specific adaptation to environment E7, whereas genotypes G2 and G3 were adapted to environment E1, and genotypes G8 and G9 to environment E5. Dataset was divided into group A, composed of E5 and E7, and group B composed of E1, E2, E3 and E6. Genotypes G1, G2, G3 and G6, belonging to group B, were the most productive. Further, no environment fell into the G4, G5, G7, G8 and G9 sectors, denoting these genotypes as the poorest ones across environments. GGE biplot indicated that genotype G4 was highly unstable, whereas G3 very stable. In addition, G2 was more desirable due to its small contribution to both G and GE. On the other hand, G4 and G9 were more undesirable due to large contribution to either G or GE. Finally, genotypes G2 and G9 were very different. Their dissimilarity may be due to difference in mean yield and/or in GEI.

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Genotype × Environment Interaction and Yield Stability Analysis in Hybrid Rice (Oryza sativa L.) By AMMI Biplot

Cited by 29 publications

References 16 publications

Molecular Characterization and Stability Analysis for Yield and its Components Traits in Soybean (Glycine max L.)

Molecular Characterization and Stability Analysis for Yield and its Components Traits in Soybean (Glycine max L.)

Adaptability and Stability Comparisons of Inbred and Hybrid Cotton in Yield and Fiber Quality Traits

Statistical analysis for genotype stability and adaptability in maize yield based on environment and genotype interaction models

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