African Journal of
Biotechnology

  • Abbreviation: Afr. J. Biotechnol.
  • Language: English
  • ISSN: 1684-5315
  • DOI: 10.5897/AJB
  • Start Year: 2002
  • Published Articles: 12488

Full Length Research Paper

The use of reproductive vigor descriptors in studying genetic variability in nine Tunisian faba bean (Vicia faba L.) populations

Ali Ouji1, Mustapha Rouaissi2, Raoudha Abdellaoui3* and Mohamed El Gazzah1
  1Laboratoire de génétique des populations et Ressources Biologiques, faculté des Sciences de Tunis- Campus universitaire 2092- Tunis; 2Laboratoire de Biotechnologie et de Physiologie végétale, INRA Tunis, rue Hedi karray2049Ariana. 3Laboratoire d’Ecologie Pastorale, IRA Médenine.
Email: [email protected]

  •  Accepted: 07 December 2010
  •  Published: 07 February 2011

Abstract

 

A collection of nine Tunisian faba bean (Vicia faba) populations belonging to three botanical classes (Var. minorvar. equina and var. major) was evaluated using twenty seven agro-morphological traits. Analysis of variance, correlation coefficients and principal components analysis (PCA) were performed based on MVSP 3.13 program. Significant differences between populations were noted for most agro-morphological traits in four main groups. The first group, positively correlated to the two axes, is represented by ‘Bachaar’ belonging to V. faba.  varminor,  the second group, including V. faba. var. minor population (‘Massri’ and ‘Badï’), is positively correlated to the PC1 and negatively correlated to the PC2 while the third group, is composed of two V. faba var. major (‘Malti’ and ‘Batata’) and were positively and negatively correlated to the PC2 and PC1, respectively. Finally, the fourth group negatively correlated to the two axes, gathers the remaining population (‘Chahbi’, ‘Chemlali’, ‘Aguadulce’ and ‘Super Aguadulce’). The dendrogram based on Nei's genetic distance of the 9 populations using UPGMA method, show some genetic drift between populations.

 

Key words: Faba bean, agromorphological traits, principal components analysis, UPGMA method.