Classification of genetic diversity and choice of parents for hybridization in cowpea Vigna unguiculata (L.) Walp for humid savanna ecology

Genetic variability in a crop population is important for successful plant breeding. Sixteen cucumber (Cucumis sativus L.) genotypes were evaluated in the early and late planting seasons to estimate the magnitude of their genetic variability and heritability. Genotypes were also classified into groups based on the performance and determination of the highest discriminating trait that accounted for greater variability using cluster analysis and principal component analysis (PCA), respectively. The measured agronomic traits were vine length, number of branches, number of leaves, and leaf area 8 wk after planting, days to flower initiation, days to 50% flowering, number of staminate flowers per plant, number of pistillate flowers per plant, fruit length, fruit girth, fruit weight per plant, number of fruits per plant, mean fruit weight, and total fruit yield ha -1 . A high coefficient of variation was recorded for most traits in both seasons and high variability was found among genotypes. High broad-sense heritability was associated with all the traits in both seasons, except for mean fruit weight in the early planting season and fruit girth, mean fruit weight, and total fruit yield in late planting season. Cluster analysis and its comparison of means showed that 'Beit Alpha', 'Ashely', 'Straight 8', and 'Sumter' from cluster F in the early planting season and 'Beit Alpha' and 'Ashely' from cluster E in the late planting season expressed the best agronomic traits and yield potentials. Hence, selection for any trait would favor genotypes in these clusters. Principal component analysis involved vine length as the most discriminating trait that accounted for greater variability in cucumber in both the early and late planting seasons, and it should be considered in cucumber improvement programs.

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“…Therefore, selecting for fruit yield must consider these traits. This corroborates the report by Aremu et al (2007) in their work with cowpea.…”

Section: Principal Component Analysis (Pca)supporting

confidence: 82%

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Ene

Ogbonna

Agbo

et al. 2016

Chilean J. Agric. Res.

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“…It further suggests that, selections from any cluster group for seed yield must take into consideration these traits. This corroborates the report of Aremu et al (2007) working with cowpea and Olika et al (2011) working with coffee. The first four principal axes accounted for over 60% of the total variation among the 18 characters describing the accessions.…”

Section: Character Estimationsupporting

confidence: 82%

“…The clustering scores among principal components axes suggest that some relationships exist among individuals within a cluster. But SLCA is a better technique in that it sufficiently provides a clearer and more informative display of relative positions of the genotypes (Aliyu and Fawole, 2001;Aremu et al, 2007). It also provides information on the minimum percentage similarity among the accessions.…”

Section: Character Estimationmentioning

confidence: 99%

“…The classification of a range of genetic variability among genotypes is pivotal to the maintenance and further acquisition of germplasm resources even as accessions from diverse origins are needed as parents stocks for the development of improved varieties (Aremu et al, 2007). Numerous approaches have been employed to estimate genetic variability in germplasm collections.…”

Section: Abbreviations: Nihort National Horticultural Researchmentioning

confidence: 99%

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Morphological classification of genetic diversity in cultivated okra, Abelmoschus esculentus (L) Moench using principal component analysis (PCA) and single linkage cluster analysis (SLCA)

C¹,

O²,

D³

et al. 2011

Afr. J. Biotechnol.

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29 okra accessions sourced from different agro-ecological regions in Nigeria and grown during the rainy season of 2007 at Abeokuta (derived savannah) were evaluated for genetic diversity using principal component analysis (PCA) and single linkage cluster analysis (SLCA). The experiment was laid out in a randomized complete block design (RCBD) with five replications. The accessions were classified into six and five cluster groups by PCA and SLCA respectively. The mean contributions of plant height, days to flowering, branches per plant, fresh pod width, mature pod width, fresh pod length, pod weight per plant, pod per plant, seeds per pod, and seed weight per plant were relatively high in the principal axes confirming the major contributions of these traits to seed yield in okra. The first four principal axes accounted for over 60% of the total variation among the 18 characters describing the accessions. Accessions 29, 9 and 14, which appears to be the most diverse may be useful as source for variable characters in okra improvement among the accessions studied been the most distant.

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“…Entre essas técnicas, as mais empregadas são: a análise por componentes principais, quando os dados são obtidos de experimentos sem repetições; a análise por variáveis canônicas, quando os dados são obtidos de experimentos com repetições; e os métodos de agrupamento, cuja aplicação depende da utilização de uma medida de dissimilaridade previamente estimada (OLIVEIRA et al, 2003). Vários trabalhos que avaliam a diversidade e a divergência genética em feijão-caupi foram realizados, utilizando-se caracteres morfoagronômicos (AREMU et al, 2007;OLIVEIRA et al, 2003;PASSOS et al, 2007;PHANSAK, et al, 2005) e marcadores moleculares (BA et al, 2004;NKONGOLO, 2003;XAVIER et al, 2005).…”

Section: Introductionunclassified

Análise multivariada e índice de seleção na identificação de genótipos superiores de feijão-caupi

et al. 2010

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RESUMO. Objetivou-se com esse trabalho avaliar a divergência genética de genótipos de feijão-caupi por meio de técnicas multivariadas e identificar aqueles que apresentam a melhor combinação para diferentes características por meio de índice de seleção. O experimento foi desenvolvido na Universidade Federal do Ceará, no período de fevereiro a junho de 2008, utilizando-se 47 genótipos de feijão-caupi de várias procedências. O experimento foi constituído de parcelas de uma fileira contendo oito plantas, sem repetição. Os caracteres avaliados foram o porte da planta; a posição da vagem na copa da planta; o número de vagens por planta; o comprimento das vagens; o número de sementes por vagem; o peso de 100 sementes e a produção; o número de dias para a floração e o ciclo; a forma do grão e a cor do grão. A técnica multivariada de componentes principais, associada aos métodos de Tocher e de Distância Euclidiana Média, foi utilizada na avaliação da divergência genética. O índice de seleção de soma de ranks foi utilizado na identificação de genótipos superiores. Novas combinações gênicas promissoras podem surgir nos cruzamentos entre os genótipos CE-264 e CE-200, CE-274 e CE-93, CE-200 e CE-274, e CE-93 e CE-282. Foi possível identificar 13 genótipos apresentando características superiores quanto aos caracteres de produção, precocidade e qualidade do grão. Palavras-chave:Vigna unguiculata L., análise multivariada, feijão-de-corda, genitores, índice de seleção.ABSTRACT. Multivariate analysis and selection index for identification of cowpea genotypes. This work aimed to evaluate the genetic divergence among cowpea genotypes through multivariate techniques and identify those with the best combination for size, production and quality of grain using a selection index. The experiment was carried out at the Federal University of Ceará in the period from February to June 2008, using 47 cowpea genotypes. The experiment was carried out in a plot with eight plants, without replications. The following traits were analyzed: plant size, pod position in plant, number of pods per plant, pod length, number of seeds per pod, weight of a hundred seeds, grain yield, number of days to flowering and cycle, shape and color of grain. The main component coupled with the methods of Tocher and Euclidian distance was used to evaluate the genetic divergence. The rank sum selection index was used to identify genotypes with superior characteristics. New genetic combinations can appear in the crossings between genotypes. Thirteen genotypes demonstrated superiority for production, earliness and grain quality traits.

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Classification of genetic diversity and choice of parents for hybridization in cowpea Vigna unguiculata (L.) Walp for humid savanna ecology

Cited by 39 publications

References 10 publications

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Studies of phenotypic and genotypic variation in sixteen cucumber genotypes

Morphological classification of genetic diversity in cultivated okra, Abelmoschus esculentus (L) Moench using principal component analysis (PCA) and single linkage cluster analysis (SLCA)

Análise multivariada e índice de seleção na identificação de genótipos superiores de feijão-caupi

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