Alternative methodology for Scott-Knott test

Bhering, Leonardo Lopes; Cruz, Cosme Damião; Vasconcelos, Edmar Soares de; Ferreira, Adésio; Resende, Marcio F. R.

doi:10.12702/1984-7033.v08n01a02

Cited by 27 publications

(24 citation statements)

References 1 publication

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“…Following the detection of a significant triple interaction [genotypes x agricultural years x locations (G x A x L)], we conducted cluster analysis of genotypes and locations means groups for each year using the Scott-Knott test, modified by Bhering et al (2008). Thus, the genotypes and locations used in each agricultural year have subsequently undergone adaptability and stability analysis using both AMMI (Gauch and Zobel, 1988) and GGE biplot (Yan et al, 2000) methods.…”

Section: Methodsmentioning

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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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: Methodsmentioning

confidence: 99%

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

Costa¹,

Teodoro²,

Bhering³

et al. 2016

Genet. Mol. Res.

Self Cite

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“…O agrupamento dos genótipos foi realizado por meio do teste de Scott e Knott (1974), modificado por Bhering et al (2008). Para a realização das análises dos 11 genótipos de bananeira, considerando as 30 características agronômicas dos frutos, utilizou-se do aplicativo genético-estatístico Genes (CRUZ, 2006).…”

Section: Methodsunclassified

Desempenho agronômico de genótipos de bananeira no recôncavo da Bahia

et al. 2014

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Objetivou-se com este trabalho avaliar o desempenho agronômico de genótipos tri- e tetraploides de bananeira, em dois ciclos de produção, visando a selecionar os mais promissores para recomendação de cultivo na região do Recôncavo da Bahia. O delineamento utilizado foi o de blocos casualizados, com 11 genótipos distribuídos em 3 blocos, com quatro plantas úteis por parcela, conduzidos em espaçamento de 3 m x 2 m. Analisaram-se os seguintes caracteres agronômicos: altura da planta (m); diâmetro do pseudocaule (cm); número de folhas vivas na floração; número de folhas vivas na colheita; comprimento do engaço (cm); diâmetro do engaço (cm); peso do cacho (kg); peso das pencas (kg); peso individual da penca (g); número de pencas; número de frutos por cacho; espessura da casca (mm); comprimento do pedicelo (cm); diâmetro do pedicelo (mm); suscetibilidade ao despencamento (Lb); firmeza da polpa com casca; peso do fruto (g); comprimento do fruto(cm); diâmetro do fruto (mm); índice de alongamento; peso da polpa (g); rendimento polpa/casca; rendimento da polpa (%); diâmetro da polpa (mm); espessura da casca (mm); firmeza da polpa (Lb); acidez titulável (%); sólidos solúveis (ºBrix); ratio (SS/AT) e pH. Das trinta variáveis mensuradas, doze foram significativas para a fonte de variação 'ciclos'. Em relação à interação 'genótipos x ciclos', é possível afirmar que não houve comportamento diferenciado dos genótipos do primeiro para o segundo ciclos de produção, excluindo-se a 'altura de planta', o 'número de folhas vivas na floração', o 'diâmetro do fruto' e a 'espessura da casca'. Em relação ao efeito dos 'genótipos', os resultados mostraram-se significativos para todas as características, exceto para suscetibilidade ao despencamento. Considerando os dados agronômicos, os genótipos da série YB e as cultivares BRS Princesa e BRS Garantida mostram-se promissoras para o cultivo na região do Recôncavo da Bahia, pois apresentaram bom desempenho agronômico.

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“…Planned extensions include extension of the method to factorial up to fifth order, methods using poisson distribution, dendrogram graphic option with p-values obtained for each group, and an alternative method of the Scott-Knott test proposed by [1]. …”

Section: Resultsmentioning

confidence: 99%

ScottKnott: A Package for Performing the Scott-Knott Clustering Algorithm in R

Jelihovschi

Faria

Allaman

2014

Tend. Mat. Apl. Comput.

114

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ABSTRACT. Scott-Knott is an hierarchical clustering algorithm used in the application of ANOVA, when the researcher is comparing treatment means, with a very important characteristic: it does not present any overlapping in its grouping results. We wrote a code, in R, that performs this algorithm starting from vectors, matrix, data.frame, aov or aov.list objects. The results are presented with letters representing groups, as well as through graphics using different colors to differentiate distinct groups. This R package, named ScottKnott is the main topic of this article.

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Alternative methodology for Scott-Knott test

Cited by 27 publications

References 1 publication

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

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

Desempenho agronômico de genótipos de bananeira no recôncavo da Bahia

ScottKnott: A Package for Performing the Scott-Knott Clustering Algorithm in R

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