Multivariate pattern of quantitative trait variation in triploid banana and plantain cultivars

Osuji, Julian O.; Okoli, Bosa E.; Vuylsteke, D; Ortíz, Rodomiro

doi:10.1016/s0304-4238(97)00101-5

Cited by 23 publications

(10 citation statements)

References 6 publications

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“…However, PCA could not resolve the population structure into clear-cut clusters due to complex pedigrees, although Osuji et al [38] used this approach to distinguish between different Musa triploids. This phenomenon could be attributed to differences in carbon source to sink capacities.…”

Section: Discussionmentioning

confidence: 99%

Trait variation and genetic diversity in a banana genomic selection training population

et al. 2017

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Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

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Section: Discussionmentioning

confidence: 99%

Trait variation and genetic diversity in a banana genomic selection training population

et al. 2017

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“…Modern genetic analyses have been applied to unravelling the evolution of Musa species, for example in D' Hont et al (2000), Jarret et al (1992), Osuji et al (1997) and Raboin et al (2005). The genus Musa is commonly divided into four sections: Eumusa, Rhodochlamys, Callimusa and Australimusa (but see Wong et al 2001 for a revision of this classification).…”

Section: The Musaceae In Africa: Botanical and Geographical Overviewmentioning

confidence: 99%

Bananas and Plantains in Africa: Re-interpreting the linguistic evidence

Blench

2009

Ethnobot. Res. App.

102

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“…The separation of species into sections and the delimitation of sectional boundaries in Musa have been done mainly on the basis of morphological differences, geographical distribution and hybridization studies (Simmonds 1966;Argent 1976;Swennen and Vuylsteke 1987;Ortiz 1997;Osuji et al 1997;Karamura 1999). Morphological traits, however, are subject to genotype × environment interaction which reduces their discriminatory power for germplasm classification, particularly when accessions only display subtle differences, as commonly found within the M. acuminata complex (Simmonds 1962;Tezenas du Montcel 1988).…”

Section: Introductionmentioning

confidence: 99%

Analysis of genetic diversity and sectional relationships in Musa using AFLP markers

et al. 2002

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The AFLP technique was used to assess the genetic diversity and sectional relationships in 39 accessions representing the four main sections of the genus Musa. Eight AFLP + 3 primer pairs produced 260 polymorphic bands that were used in cluster and PCO analysis. A wide range of variability was observed among the species within the sections of the genus Musa. AFLP data was useful in separating the different sections of the genus as well as differentiating the different genomic groups of section Eumusa. Section Rhodochlamys ( x = 11) appeared as a distinct entity and clustered closely with the Musa acuminata Colla complex of section Eumusa that has the same basic chromosome number. This relationship is congruent with previous studies. However, unlike previous proposals that questioned the identity of Rhodochlamys as a separate taxonomic unit, PCO analysis of the AFLP data showed that it is a distinct entity. Musa laterita Cheesman ( Rhodochlamys) and Musa schizocarpa Simmonds clustered with the M. acuminata complex suggesting that they may be sources of useful genes for the improvement of the cultivated bananas. Callimusa formed a distinct unit and was closer to Australimusa than to the other sections. Although both sections share the same basic chromosome number of x = 10 these sections are genetically distinct

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Multivariate pattern of quantitative trait variation in triploid banana and plantain cultivars

Cited by 23 publications

References 6 publications

Trait variation and genetic diversity in a banana genomic selection training population

Trait variation and genetic diversity in a banana genomic selection training population

Bananas and Plantains in Africa: Re-interpreting the linguistic evidence

Analysis of genetic diversity and sectional relationships in Musa using AFLP markers

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