Stability and adaptability of upland rice genotypes

Balestre, Márcio; Santos, Vanderley Borges dos; Soares, Antônio Alves; Reis, Moisés Souza

doi:10.1590/s1984-70332010000400011

Cited by 24 publications

(21 citation statements)

References 7 publications

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“…The high accumulated per cent value of explanation of the sum of squares on the first two axes of interaction, the adaptability and stability of rice genotypes can be graphically interpreted, considering only biplots with the first two axes of the GE interaction. This value was relatively higher than that reported for rice by Anandan et al (2009) in coastal saline environments and Balestre et al (2010) in upland environments and Kumar et al (2011) in rice who also applied the AMMI analysis. The use of phenotypic means is widespread in stability and adaptability studies on different crops, but it should not be seen as an optimal procedure to predict the genotypic values, due to the strong influence of the "noise" or interferences (block, plot, location, year, etc.…”

Section: Stability and Adaptability Analysis Using Ammi Modelcontrasting

confidence: 61%

Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India

Krishnamurthy

Sharma

et al. 2016

Cereal Research Communications

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Genotype × environment (G × E) interaction effects are of special interest for identifying the most suitable genotypes with respect to target environments, representative locations and other specific stresses. Twenty-two advanced breeding lines contributed by the national partners of the Salinity Tolerance Breeding Network (STBN) along with four checks were evaluated across 12 different salt affected sites comprising five coastal saline and seven alkaline environments in India. The study was conducted to assess the G × E interaction and stability of advanced breeding lines for yield and yield components using additive main effects and multiplicative interaction (AMMI) model. In the AMMI1 biplot, there were two mega-environments (ME) includes ME-A as CARI, KARAIKAL, TRICHY and NDUAT with winning genotype CSR 2K 262; and ME-B as KARSO, LUCKN, KARSA, GOA, CRRI, DRR, BIHAR and PANVE with winning genotypes CSR 36. Genotypes CSR 2K 262, CSR 27, NDRK 11-4, NDRK 11-3, NDRK 11-2, CSR 2K 255 and PNL 1-1-1-6-7-1 were identified as specifically adapted to favorable locations. The stability and adaptability of AMMI indicated that the best yielding genotypes were CSR 2K 262 for both coastal saline and alkaline environments and CSR 36 for alkaline environment. CARI and PANVEL were found as the most discernible environments for genotypic performance because of the greatest GE interaction. The genotype CSR 36 is specifically adapted to coastal saline environments GOA, KARSO, DRR, CRRI and BIHAR and while genotype CSR 2K 262 adapted to * Corresponding author; E-mail: krishnagene@gmail.com Cereal Research Communications 44, 2016 alkaline environments LUCKN, NDUAT, TRICH and KARAI. Use of most adapted lines could be used directly as varieties. Using them as donors for wide or specific adaptability with selection in the target environment offers the best opportunity for widening the genetic base of coastal salinity and alkalinity stress tolerance and development of adapted genotypes. Highly stable genotypes can improve the rice productivity in salt-affected areas and ensure livelihood of the resource poor farming communities.350 KriShnamurthy et al.: G×E Interaction of Rice for Salty Environments

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Section: Stability and Adaptability Analysis Using Ammi Modelcontrasting

confidence: 61%

Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India

Krishnamurthy

Sharma

et al. 2016

Cereal Research Communications

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“…GxE can be studied by measures of adaptability and stability, which allows of a simple interpretation of a large dataset. In the context of mixed models, the harmonic mean of the relative performance of genetic values (MHPRVG) (Resende, 2007) has been shown to be one of the efficient alternatives for the simultaneous evaluation of genotypes for yield, adaptability, and stability, mainly when unbalanced data are produced (Balestre et al, 2010;Borges et al, 2010). This mixed model approach has been used efficiently in the analyses of numerous crops, such as sugarcane (Bastos et al, 2007), carrot (Silva et al, 2011), common beans (Torres et al, 2015), corn (Mendes et al, 2012;Faria et al, 2017), and rice (Colombari Filho et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Adaptability and stability of flood-irrigated rice cultivars released to the subtropical region of Brazil

Streck

Júnior

Fagundes

et al. 2018

Pesq. agropec. bras.

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The objective of this work was to estimate the effects of genotype x environment interaction and the genetic potential of flood-irrigated rice cultivars, released between 1972 and 2017, for the state of Rio Grande do Sul, Brazil. The experiments were carried out in the field, in all agroclimatic regions of flood-irrigated rice crop in the state, between the 2005/2006 and 2015/2016 crop years, totaling 60 environments (trials), with 1,961 experimental units. Twenty-five cultivars of irrigated rice were evaluated for the traits grain yield, plant height, days to flowering, and whole grain quality after milling. The values of adaptability and stability were estimated with the aid of mixed models. The rice cultivars BRS Pampa, BRS Pampeira, and BRSCIRAD 302 showed simultaneously high-genotypic grain yield, adaptability, stability, good agronomic traits, and good whole-grain yield after milling. 'BRSCIRAD 302' and 'BRS Pampa' show high-yield stability and can be recommended for all rice cultivation regions of Rio Grande do Sul. 'BRS Pampeira' is responsive to environmental improvements and is indicated for high-technology conditions.

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“…That way, the hybrids plotted nearer the center of this “target” are those that have the best combination between adaptability and stability as presented by Balestre et al [22]. …”

Section: Methodsmentioning

confidence: 85%

Selection Index in the Study of Adaptability and Stability in Maize

Oliveira

Pinho

Ferreira

et al. 2014

The Scientific World Journal

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This paper proposes an alternative method for evaluating the stability and adaptability of maize hybrids using a genotype-ideotype distance index (GIDI) for selection. Data from seven variables were used, obtained through evaluation of 25 maize hybrids at six sites in southern Brazil. The GIDI was estimated by means of the generalized Mahalanobis distance for each plot of the test. We then proceeded to GGE biplot analysis in order to compare the predictive accuracy of the GGE models and the grouping of environments and to select the best five hybrids. The G × E interaction was significant for both variables assessed. The GGE model with two principal components obtained a predictive accuracy (PRECORR) of 0.8913 for the GIDI and 0.8709 for yield (t ha−1). Two groups of environments were obtained upon analyzing the GIDI, whereas all the environments remained in the same group upon analyzing yield. Coincidence occurred in only two hybrids considering evaluation of the two features. The GIDI assessment provided for selection of hybrids that combine adaptability and stability in most of the variables assessed, making its use more highly recommended than analyzing each variable separately. Not all the higher-yielding hybrids were the best in the other variables assessed.

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Stability and adaptability of upland rice genotypes

Abstract: -The aim of this study was to identify upland rice genotypes with high

Cited by 24 publications

References 7 publications

Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India

Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India

Adaptability and stability of flood-irrigated rice cultivars released to the subtropical region of Brazil

Selection Index in the Study of Adaptability and Stability in Maize

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