Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso

Farias, F. J. C.; Carvalho, Luiz Paulo de; Filho, João Luis Silva; Teodoro, Paulo Eduardo

doi:10.4238/gmr.15028009

Cited by 41 publications

(36 citation statements)

References 17 publications

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“…These methods have been used in Brazil for providing production recommendations related to cotton (Farias et al, 2016), cowpea (Santos et al, 2015), carrot (Silva et al, 2011a), maize (Balestre et al, 2009a,b), and wheat (Silva et al, 2011b;Benin et al, 2012) genotypes. Thus, the aim of this study was to use both AMMI and GGE biplot analyses to identify strawberry genotypes demonstrating high yield and stability thresholds among those grown at three locations in Espírito Santo during two agricultural years.…”

Section: Introductionmentioning

confidence: 99%

“…AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses are currently among the most used adaptability and stability methods undertaken for investigating GE interactions (Farias et al, 2016;Teodoro et al, 2016). Both forms of analysis utilize biplot graphs, which represent a given data matrix.…”

Section: Introductionmentioning

confidence: 99%

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Biplot analysis of strawberry genotypes recommended for the State of Espírito Santo

Costa¹,

Teodoro²,

Bhering³

et al. 2016

Genet. Mol. Res.

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ABSTRACT. Most strawberry genotypes grown commercially in Brazil originate from breeding programs in the United States, and are therefore not adapted to the various soil and climatic conditions found in Brazil. Thus, quantifying the magnitude of genotype x environment (GE) interactions serves as a primary means for increasing average Brazilian strawberry yields, and helps provide specific recommendations for farmers on which genotypes meet high yield and phenotypic stability thresholds. The aim of this study was to use AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses to identify high-yield, stable strawberry genotypes grown at three locations in Espírito Santo for two agricultural years. We evaluated seven strawberry genotypes (Dover, Camino Real, Ventana, Camarosa, Seascape, Diamante, and Aromas) at three locations (Domingos Martins, Iúna, and Muniz Freire) in agricultural years 2006 and 2007, totaling six study environments. Joint analysis of variance was calculated using yield data (t/ha), and AMMI and GGE biplot analysis was conducted following the detection of a significant genotypes x agricultural years x locations (G x A x L) interaction. During the two agricultural years, evaluated locations were allocated to different regions on biplot graphics using both methods, indicating distinctions among them. Based on the results obtained from the two methods used in this study to investigate the G x A x L interaction, we recommend growing the Camarosa genotype for production at the three locations assessed due to the high frequency of favorable alleles, which were expressed in all localities evaluated regardless of the agricultural year.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Biplot analysis of strawberry genotypes recommended for the State of Espírito Santo

Costa¹,

Teodoro²,

Bhering³

et al. 2016

Genet. Mol. Res.

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“…Recently, GGE biplots have been used to investigate GE interactions in several crops, such as cotton (Farias et al, 2016) and sorghum , but not in the common bean in Brazil. Therefore, the aim of this study was to identify common bean genotypes that exhibit high yields and stability in Mato Grosso do Sul, Brazil.…”

Section: Introductionmentioning

confidence: 99%

Selection of common bean (Phaseolus vulgaris L.) genotypes using a genotype plus genotype x environment interaction biplot

Am¹,

Teodoro

et al. 2016

Genet. Mol. Res.

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ABSTRACT. Recently, the genotype plus genotype x environment interaction (GGE) biplot methodology has been used to investigate genotype x environment interactions in several crop species, but has not been applied to the common bean (Phaseolus vulgaris L.) crop in Brazil. The aim of this study was to identify common bean genotypes that exhibit high grain yield and stability in the State of Mato Grosso do Sul, Brazil. We conducted 12 trials from 2000 to 2006 in the municipalities of Aquidauana and Dourados, and evaluated 13 genotypes in a randomized block design with three replications. Grain yield data were subjected to individual and joint analyses of variance. After analyzing the GE interaction, the adaptability and phenotypic stability of the common bean genotypes were analyzed using GGE biplot methodology. The genotypes EMGOPA-201, Xamego, and Aporé are recommended for growing in Mato Grosso do Sul, because they exhibited high grain yield and phenotypic stability.

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“…is one of the main economically important crops in Brazil (Farias et al, 2016). However, to become competitive in the global market, there is a need to identify genotypes with higher quality fiber.…”

Section: Introductionmentioning

confidence: 99%

Number of repetitions for evaluating technological traits in cotton genotypes

et al. 2016

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ABSTRACT. With the changes in spinning technology, technological cotton traits, such as fiber length, fiber uniformity, fiber strength, fineness, fiber maturity, percentage of fibers, and short fiber index, are of great importance for selecting cotton genotypes. However, for accurate discrimination of genotypes, it is important that these traits are evaluated with the best possible accuracy. The aim of this study was to determine the number of measurements (repetitions) needed to accurately assess technological traits of cotton genotypes. Seven experiments were conducted in four Brazilian States (Ceará, Rio Grande do Norte, Goiás, and Mato Grosso do Sul). We used nine brown and two white colored fiber lines in a randomized block design with four replications. After verifying the assumptions of residual normality and homogeneity of variances, analysis of variance was performed to estimate the repeatability coefficient and calculating the number of repetitions. Trials with four replications were found to be sufficient to identify superior cotton genotypes for all measured traits except short fiber index with a selective accuracy >90% and at least 81% accuracy in predicting their actual value. These results allow more accurate and reliable results in future researches with evaluating technological traits in cotton genotypes.

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Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso

Cited by 41 publications

References 17 publications

Biplot analysis of strawberry genotypes recommended for the State of Espírito Santo

Biplot analysis of strawberry genotypes recommended for the State of Espírito Santo

Selection of common bean (Phaseolus vulgaris L.) genotypes using a genotype plus genotype x environment interaction biplot

Number of repetitions for evaluating technological traits in cotton genotypes

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