Journal of
Plant Breeding and Crop Science

  • Abbreviation: J. Plant Breed. Crop Sci.
  • Language: English
  • ISSN: 2006-9758
  • DOI: 10.5897/JPBCS
  • Start Year: 2009
  • Published Articles: 409

Full Length Research Paper

Genetic diversity studies for quantitative traits of tomato (Solanum lycopersicon L.) genotypes in Western Tigray, Northern Ethiopia

Shushay Chernet
  • Shushay Chernet
  • Humera Agricultural Research Center, Tigray Agricultural Research Institute, P. O. Box 62, Humera, Ethiopia
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Derbew Belew
  • Derbew Belew
  • Jimma University College of Agriculture and Veterinary Medicine, P. O. Box 307, Jimma, Ethiopia.
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Fetien Abay
  • Fetien Abay
  • Department of Crop and Horticultural Sciences, Mekelle University, P. O. Box 231, Mekelle, Ethiopia.
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  •  Received: 16 June 2014
  •  Accepted: 06 August 2014
  •  Published: 01 September 2014


The objective of the study was to estimate genetic diversity among tomato genotypes. Thirty-six genotypes introduced from different countries were evaluated at Humera Agricultural Research Center, Northern Ethiopia, during 2010/2011 in 6 × 6 simple lattice design with two replications. Cluster analysis was made by average linkage method. Mahalanobis distance (D2) was used to estimate the genetic distance between pair of clusters. Estimates of cluster analysis revealed that the thirty-six genotypes were grouped in to six distinct clusters. Genetic distance between any pair of clusters showed very highly significant difference. The maximum and minimum distances were recorded between clusters IV and V (1805.00) and cluster II and III (81.94) respectively. This indicated the existence of a possibility to improve genotypes through hybridization from any pair of clusters and subsequent selection can be made from the segregant generations. Principal component analysis showed that the first six principal components explained about 83.03% of the total variation. Generally, the study confirmed presence of adequate genetic diversity between any pair of clusters which could be exploited through hybridization.


Key words: Cluster analysis, Mahalanobis distance, principal component analysis, eigenvalue, eigenvector.