AMMI analysis to evaluate the adaptability and phenotypic stability of sugarcane genotypes

Silveira, Luís Cláudio Inácio da; Kist, Volmir; Paula, Thiago Otávio Mendes de; Barbosa, Márcio Henrique Pereira; Peternelli, Luiz Alexandre; Daros, Edelclaiton

doi:10.1590/s0103-90162013000100005

Cited by 43 publications

(32 citation statements)

References 12 publications

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“…(Table 3). These values are lower when compared with other reports using RB clones (Silveira et al, 2012;Fernandes Junior et al, 2013;Silveira et al, 2013;Antunes, Schöffel, Silva, Eicholz, & Harter, 2016), nevertheless, those differ in the series of clones, environments and seasons.…”

Section: Resultscontrasting

confidence: 62%

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Adaptability and Phenotypic Stability of the Sugarcane RB Genotype by the AMMI Method

Magalhães¹,

Silva²,

Rocha³

et al. 2018

JAS

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The objective of this work is to evaluate the adaptability and phenotypic stability of the RB sugarcane genotype using the AMMI method. The experiments were performed in five production units in the state of Pernambuco, in cultivars of sugarcane soca and ressoca, using 14 RB sugarcane genotypes-11 RB clones of series 2004 and three cultivars as controls. Each combination of production unit × cutting was considered as environment, for a total of 13 environments. The experimental design was with random blocks, and four repetitions. We estimated the parameters tons of sugarcane per hectare (TCH) and tons of pol per hectare (TPH). The genotype G12 displayed general adaptability, phenotypic stability and high productivity for the two parameters. The genotypes G10, G13 and G14 had the highest yield, largest contribution of G×E, indicating specific adaptability. The environments A12 and A13, in Primavera, are recommended for preliminary selection trials.

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Section: Resultscontrasting

confidence: 62%

“…genotype and environment effects as additive components and the effect of the interaction as multiplicative . It uses variance analysis and the deconvolution of individual values, in a unified way to evaluate trials of multiple yield (Silveira et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Adaptability and Phenotypic Stability of the Sugarcane RB Genotype by the AMMI Method

Magalhães¹,

Silva²,

Rocha³

et al. 2018

JAS

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“…In all, 88.90% of the sum of squares of the GE interaction could be explained by the AMMI3 model, with 67.00, 14.00, and 7.90% explained by IPCA1, IPCA2, and IPCA3, respectively. The values explained by these models were greater than those previously observed in other crops (Oliveira and Godoy, 2006;Paderewski et al, 2011;Silveira et al, 2013). By providing more degrees of freedom than the main effects of genotype and environment, the GE interaction absorbs most of the noise component corresponding to unpredictable and uninterpretable responses of the model, which are caused by experimental error.…”

Section: Ammi Analysis Of Ge Interactionmentioning

confidence: 68%

“…Similar results were obtained for other crops. These results, in which most of the variation is explained by environmental effects and GE interaction, demonstrate that the selection of the best genotypes is not straightforward (Oliveira and Godoy, 2006;Mohammadi and Amri, 2009;Silveira et al, 2013).…”

Section: Ammi Analysis Of Ge Interactionmentioning

confidence: 86%

Adaptability and stability analysis of the juice yield of yellow passion fruit varieties

Oliveira¹,

Freitas²,

Jesus³

2014

Genet. Mol. Res.

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ABSTRACT. This study analyzed the genotype x environment interaction (GE) for the juice productivity (JuProd) of 12 yellow passion fruit varieties (Passiflora edulis Sims. f. flavicarpa Deg.) using additive main effects and multiplicative interaction (AMMI) model and auxiliary parameters. The experiments were conducted in eight environments of Bahia State, Brazil, using a randomized block design with three replications. Analysis of variance showed significant effects (P ≤ 0.01) for environments, genotypes, and GE interaction. The first two interaction principal component axes (IPCAs) explained 81.00% of the sum of squares of the GE interaction. The AMMI1 and AMMI2 models showed that varieties 09 and 11 were the most stable. Other parameters, namely, the AMMI stability value (ASV), yield stability (YSI), sustainability, and stability index (StI), indicated that other varieties were more stable. These varying results were certainly a consequence of methodological differences. In contrast, the ranking of varieties for each of the stability parameters showed significant positive correlations (P ≤ 0.05) between IPCA1 x (ASV, YSI), JuProd x (StI, YSI), YSI x ASV, and StI x YSI. Cluster analysis based on the genotypic profile of the effects of the GE interaction identified three AMMI analysis of passion fruit groups that correlated with the distribution of varieties in the AMMI1 biplot. However, the classification of stable genotypes was limited because the association with the productivity was not included in the analysis. Variety 08 showed the most stable and productive behavior, ranking above average in half of the environments, and it should be recommended for use.

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“…Since its disclosure, this methodology has been widely used for studies on adaptability in several important cultivated species such as wheat (Kempton, 1984;Crossa et al, 1999;Paderewski et al, 2011), Corn (Hirotsu, 1983;Ndhlela et al, 2014), soybeans (Gauch, 1988;Zobel et al, 1988;Yokomizo et al, 2013), sugar cane (Silveira et al, 2013), and rice (Samonte et al, 2005).…”

Section: Methodologies Based On Multivariate Methodsmentioning

confidence: 99%

Evolution of methodology for the study of adaptability and stability in cultivated species

Carvalho¹,

Silva²,

Rocha³

et al. 2016

Afr. J. Agric. Res.

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The GxE interaction only became widely discussed from evolutionary studies and evaluations of the causes of behavioral changes of species cultivated in environments. In the last 60 years, several methodologies for the study of adaptability and stability of genotypes in multiple environments trials were developed in order to assist the breeder's choice regarding which genotypes are more stable and which are the most suitable for the crops in the most diverse environments. The methods that use linear regression analysis were the first to be used in a general way by breeders, followed by multivariate analysis methods and mixed models. The need to identify the genetic and environmental causes that are behind the GxE interaction led to the development of new models that include the use of covariates and which can also include both multivariate methods and mixed modeling. However, further studies are needed to identify the causes of GxE interaction as well as for the more accurate measurement of its effects on phenotypic expression of varieties in competition trials carried out in genetic breeding programs.

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AMMI analysis to evaluate the adaptability and phenotypic stability of sugarcane genotypes

Cited by 43 publications

References 12 publications

Adaptability and Phenotypic Stability of the Sugarcane RB Genotype by the AMMI Method

Adaptability and Phenotypic Stability of the Sugarcane RB Genotype by the AMMI Method

Adaptability and stability analysis of the juice yield of yellow passion fruit varieties

Evolution of methodology for the study of adaptability and stability in cultivated species

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