AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability

ABSTRACT This study aimed to propose a clustering methodology with bootstrap resampling using the Additive Main Effects and Multiplicative Interaction Analysis (AMMI) to contribute to better prediction of phenotypic stability of genotypes and environments. It also aims to analyze the genetic diverge...

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Main Authors: Priscila Neves Faria, Carlos Tadeu dos Santos Dias, José Baldin Pinheiro, Lúcio Borges de Araújo, Marcelo Ângelo Cirillo, Mirian Fernandes Carvalho Araújo
Format: Article
Language:English
Published: Universidade Federal De Viçosa
Series:Revista Ceres
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2016000400461&lng=en&tlng=en
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spelling doaj-a55fb938052e4253b07e97beee3b5f7f2020-11-25T01:12:16ZengUniversidade Federal De ViçosaRevista Ceres2177-349163446146810.1590/0034-737X201663040005S0034-737X2016000400461AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stabilityPriscila Neves FariaCarlos Tadeu dos Santos DiasJosé Baldin PinheiroLúcio Borges de AraújoMarcelo Ângelo CirilloMirian Fernandes Carvalho AraújoABSTRACT This study aimed to propose a clustering methodology with bootstrap resampling using the Additive Main Effects and Multiplicative Interaction Analysis (AMMI) to contribute to better prediction of phenotypic stability of genotypes and environments. It also aims to analyze the genetic divergence in the assessment of soybean lines, identify genotypes with high-yielding characteristics, with control of chewing and sucking insect pests, and cluster similar genotypes for the traits evaluated. A total of 24 experiments were conducted in randomized blocks, with two replications subdivided in experimental groups with common controls. AMMI with principal component analysis indicated that PC1 and PC2 were significant, explaining 83.9% of the sum of squares of the interaction. The first singular axis of AMMI analysis captured the highest percentage of "pattern" and, with subsequent accumulation of the dimensions of the axes, there was a decrease in the percentage of "pattern" and an increase in "noise". The Euclidean distance between genotype scores was used as the dissimilarity measure and clusters were obtained by the hierarchical method of Ward. Genotypes 97-8011, 97-8029, 97-8050 and IAS-5 had the best performance and are promising for recommendation purposes, with the greatest stability and best performance on grain yield.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2016000400461&lng=en&tlng=engenotype x environment interactionclusteringpercentile range
collection DOAJ
language English
format Article
sources DOAJ
author Priscila Neves Faria
Carlos Tadeu dos Santos Dias
José Baldin Pinheiro
Lúcio Borges de Araújo
Marcelo Ângelo Cirillo
Mirian Fernandes Carvalho Araújo
spellingShingle Priscila Neves Faria
Carlos Tadeu dos Santos Dias
José Baldin Pinheiro
Lúcio Borges de Araújo
Marcelo Ângelo Cirillo
Mirian Fernandes Carvalho Araújo
AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability
Revista Ceres
genotype x environment interaction
clustering
percentile range
author_facet Priscila Neves Faria
Carlos Tadeu dos Santos Dias
José Baldin Pinheiro
Lúcio Borges de Araújo
Marcelo Ângelo Cirillo
Mirian Fernandes Carvalho Araújo
author_sort Priscila Neves Faria
title AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability
title_short AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability
title_full AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability
title_fullStr AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability
title_full_unstemmed AMMI methodology in soybean: Cluster analysis with bootstrap resampling in genetic divergence and stability
title_sort ammi methodology in soybean: cluster analysis with bootstrap resampling in genetic divergence and stability
publisher Universidade Federal De Viçosa
series Revista Ceres
issn 2177-3491
description ABSTRACT This study aimed to propose a clustering methodology with bootstrap resampling using the Additive Main Effects and Multiplicative Interaction Analysis (AMMI) to contribute to better prediction of phenotypic stability of genotypes and environments. It also aims to analyze the genetic divergence in the assessment of soybean lines, identify genotypes with high-yielding characteristics, with control of chewing and sucking insect pests, and cluster similar genotypes for the traits evaluated. A total of 24 experiments were conducted in randomized blocks, with two replications subdivided in experimental groups with common controls. AMMI with principal component analysis indicated that PC1 and PC2 were significant, explaining 83.9% of the sum of squares of the interaction. The first singular axis of AMMI analysis captured the highest percentage of "pattern" and, with subsequent accumulation of the dimensions of the axes, there was a decrease in the percentage of "pattern" and an increase in "noise". The Euclidean distance between genotype scores was used as the dissimilarity measure and clusters were obtained by the hierarchical method of Ward. Genotypes 97-8011, 97-8029, 97-8050 and IAS-5 had the best performance and are promising for recommendation purposes, with the greatest stability and best performance on grain yield.
topic genotype x environment interaction
clustering
percentile range
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-737X2016000400461&lng=en&tlng=en
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