, Volume 178, Issue 2, pp 151–158 | Cite as

Agronomic and molecular characterization of gamma ray induced banana (Musa sp.) mutants using a multivariate statistical algorithm

  • Rosa Karla Nogueira Pestanana
  • Edson Perito Amorim
  • Cláudia Fortes Ferreira
  • Vanusia Batista de Oliveira Amorim
  • Larissa Santos Oliveira
  • Carlos Alberto da Silva Ledo
  • Sebastião de Oliveira e Silva


Bananas are tropical fruits grown worldwide playing a key role in market trade and especially used as main food source for low income populations. In Brazil, bananas are mainly consumed in natura, occupying the second largest internal market. Nevertheless, this crop presents low availability of productive commercial varieties with good agronomic characteristics. A strategy undertaken to solve this problem is the development of new cultivars through conventional genetic breeding methods. However, this strategy presents some obstacles such as female sterility and low number of seeds. In order to overcome these shortcomings, use of mutation induction aiming the selection of mutants with desirable agronomic characteristics seems to have great potential for developing new cultivars. The objective of the present work was to evaluate the genetic variability in putative banana ‘Pacovan’ (AAB genome, subgroup Prata Type) mutants submitted to gamma ray irradiation, using a set of agronomical and molecular data (ISSR markers). The distance between the putative ‘Pacovan’ mutants varied from 0.26 to 0.64 with cophenetic correlation coefficient of 0.7669. Four mutants were selected based on best agronomical characteristics and height. This data also shows that there is variability that can be explored after the irradiation of ‘Pacovan’ banana mutants, which can be used in the genetic breeding program of banana aiming to develop short new varieties that also present good agronomic characteristics. This is the first attempt to use combined data in order to evaluate the genetic variability in putative banana mutants.


In vitro mutagenesis ISSR markers Multivariate analysis Musa sp 



The authors wish to thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for funding this project and also the Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB) for granting the scholarship of the first author.


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Rosa Karla Nogueira Pestanana
    • 1
  • Edson Perito Amorim
    • 2
  • Cláudia Fortes Ferreira
    • 2
  • Vanusia Batista de Oliveira Amorim
    • 2
  • Larissa Santos Oliveira
    • 1
  • Carlos Alberto da Silva Ledo
    • 2
  • Sebastião de Oliveira e Silva
    • 2
  1. 1.Universidade Federal do Recôncavo da BahiaCruz das AlmasBrazil
  2. 2.Embrapa Mandioca e FruticulturaCruz das AlmasBrazil

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