Comparative Performance of Forty-Eight Rice Genotypes in Diverse Environments 
 Using the Ammi and GGE Biplot Analyses

Ogunbayo, S. A.; Sié, Moussa; Ojo, D. K.; Popoola, A. R.; Oduwaye, O.A.; Daniel, IO; Sanni, Kayode; Akinwale, M. G.; Toulou, B.; Shittu, A.; Gregorio, Glenn B.; Mercado, E.

doi:10.3923/ijpbg.2014.139.152

Cited by 11 publications

(9 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The dynamic state of salt stress over years further confounds the individual genotype performance. This is a bit different than in other studies 21 , 29 because of the high soil heterogeneity among locations as well as variation over the years. As breeders, we like to develop a highly adaptive genotype that is good over environments and years but, for the regional perspective, this is not practical in the long term just to avoid the buildup of virulent races that can devastate large areas such as the infamous devastation of maize crops in the United States in the late 1960s and early 1970s because of Bipolaris maydis race T (formerly known as Helminthosporium maydis ) disease on maize hybrids 49 .…”

Section: Discussioncontrasting

confidence: 77%

“…Among these, HA-GGE biplots had been argued to be efficient in evaluating environments and genotypes from multi-location trials (MLTs) 27 . Biplot analysis has also been tried in rice for genotype and environment evaluation 28 , 29 and for line × tester data 30 , etc. But, GGE biplots have not been efficiently used for studies on the performance of genotypes across various salinity stress locations except by Sharifi (2012), who selected the best parents for salinity tolerance-contributing traits based on general combining ability (GCA) and specific combining ability (SCA) estimates depicted on a GGE biplot 31 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of mega-environments and rice genotypes for general and specific adaptation to saline and alkaline stresses in India

Krishnamurthy

Sharma

et al. 2017

Sci Rep

View full text Add to dashboard Cite

In the present study, a total of 53 promising salt-tolerant genotypes were tested across 18 salt-affected diverse locations for three years. An attempt was made to identify ideal test locations and mega-environments using GGE biplot analysis. The CSSRI sodic environment was the most discriminating location in individual years as well as over the years and could be used to screen out unstable and salt-sensitive genotypes. Genotypes CSR36, CSR-2K-219, and CSR-2K-262 were found ideal across years. Overall, Genotypes CSR-2K-219, CSR-2K-262, and CSR-2K-242 were found superior and stable among all genotypes with higher mean yields. Different sets of genotypes emerged as winners in saline soils but not in sodic soils; however, Genotype CSR-2K-262 was the only genotype that was best under both saline and alkaline environments over the years. The lack of repeatable associations among locations and repeatable mega-environment groupings indicated the complexity of soil salinity. Hence, a multi-location and multi-year evaluation is indispensable for evaluating the test sites as well as identifying genotypes with consistently specific and wider adaptation to particular agro-climatic zones. The genotypes identified in the present study could be used for commercial cultivation across edaphically challenged areas for sustainable production.

show abstract

Section: Discussioncontrasting

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Identification of mega-environments and rice genotypes for general and specific adaptation to saline and alkaline stresses in India

Krishnamurthy

Sharma

et al. 2017

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Two-way interactions of all combinations and the three-way interactions (G x L x Y) (except for fertile tillers) showed significant variation for all traits revealing the inconsistence performance of genotypes for different traits across locations and over the years. Similar results were reported by Hasan et al (2014), Ogunbayo et al (2014) and Bose et al (2014) for rice genotypes performance across sites and over seasons. The result in AMMI analysis of variance for grain yield revealed that environment (E), genotype (G) and genotype by environment (GE) interaction were highly significant (P<0.001).…”

Section: Results and Discussion 31 Variation In Traitssupporting

confidence: 90%

Stability and Performance Assessment in 18 Short-Duration Rice Genotypes under Rain Fed Lowland Production Conditions of Ethiopia

2021

JEES

View full text Add to dashboard Cite

In order to identify high yielding and stable short-duration lowland rice genotypes, field experiment was conducted with 18 rice genotypes for three consecutive years (2013)(2014)(2015) at five locations in a randomized complete block design of three replications. Combined analysis of variance showed highly significant differences for the genotype and environments. The genotype by environment interaction (GEI) was also highly significant indicating differential response of genotypes to environments. The partitioning of total sum of squares exhibited that the GEI effect was a predominant source of variation (34.44%), followed by the environment and genotype effects of 24.3% and 19.04%, respectively. The GEI effect was nearly two times higher than that of the genotype effect, suggesting the presence of different environment groups. In the AMMI analysis, the first six interaction principal component axes (IPCA1 to IPCA6) were highly significant and together explained 92.18% of interaction sum of squares. AMMI stability value (ASV) discriminated genotypes G17, G16 and G8 as the stable genotypes. But, based on the yield stability index (YSI), the most stable genotypes with high grain yield were genotypes G16 and G11. AMMI1 and GGE biplots also recommended G16 and G11as stable and high yielding genotypes, whereas G2 as unstable but high yielding. Thus, genotypes G16 and G11could be released for wider adaptation while genotype G2 for specific adaptation.

show abstract

“…For the improved genotype development, it is important to evaluate the phenotypic performance of the new cultivars in various conditional environments (either in different locations during the same season or in different seasons/years in the same location) [29]. To identify the genetic stability of a trait in a mutant population, the evaluation of the genotype of the modified traits, using molecular markers, should be conducted after phenotypic evaluation [30].…”

Section: Discussionmentioning

confidence: 99%

Mutation Breeding of a N-methyl-N-nitrosourea (MNU)-Induced Rice (Oryza sativa L. ssp. Indica) Population for the Yield Attributing Traits

et al. 2019

View full text Add to dashboard Cite

Difficulties in breeding new rice cultivars that have a high yield, are acceptable quality, and are tolerant to environmental stresses have been the major constraint of rice production in many developing countries, as these traits are determined by multiple genes associated with complicated and uncontrollable gene segregations.Furthermore, the gene/QTL (quantitative trait locus) introduced to the cultivar is unstable due to the interaction among the active genes, which determine the phenotypic performance, not yet been well understood or controllable. In this study, the N-methyl-N-nitrosourea (MNU)-induced mutation was applied to the heterozygote of the F1 generation from the cross between TBR1 (female) and KD18 (male parent). The phenotype and genotype of the M2 and M3 generations were evaluated and showed that the mutant population phenotypes, including the plant height, semi-dwarfism, amylose content, protein content, gel consistency, grain yield, and spikelet fertility, varied. Interestingly, no segregation among the genotypes in the M2 and M3 generations was observed, while the genotypes of the control population were either paternally inherited or indeterminable when using 28 polymorphism simple sequence repeat (SSR) markers that were identified on parental lines from 200 markers. The MNU-induced mutation caused maternal inheritance in the segregating populations, as primarily important agronomic traits were maternally succeeded from the female line TBR1. The findings of this study indicated that, through the use of MNU, the breeding of rice cultivars with close genetic backgrounds (similarity coefficient = 0.52) could be shortened by the maternal control of important qualities, such as pest and disease resistance and high yield, thus contributing to sustainable rice production for rice farmers. Further examination of rice cultivars with a greater difference in the genetic background should be subsequently conducted.

show abstract

Comparative Performance of Forty-Eight Rice Genotypes in Diverse Environments Using the Ammi and GGE Biplot Analyses

Cited by 11 publications

References 5 publications

Identification of mega-environments and rice genotypes for general and specific adaptation to saline and alkaline stresses in India

Identification of mega-environments and rice genotypes for general and specific adaptation to saline and alkaline stresses in India

Stability and Performance Assessment in 18 Short-Duration Rice Genotypes under Rain Fed Lowland Production Conditions of Ethiopia

Mutation Breeding of a N-methyl-N-nitrosourea (MNU)-Induced Rice (Oryza sativa L. ssp. Indica) Population for the Yield Attributing Traits

Contact Info

Product

Resources

About