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Principal component and hierarchical cluster analyses for classification and categorization of sesame germplasm

DOI: 10.5958/2348-7542.2015.00050.9    | Article Id: 021 | Page : 345-350
Citation :- Principal component and hierarchical cluster analyses for classification and categorization of sesame germplasm. Res. Crop. 16: 345-350
Amit Singh, Ram Avtar, Nisha Kumari, O. Sangwan, R. K. Sheoran ramavtarola@yahoo.in
Address : Department of Genetics & Plant Breeding, CCS Haryana Agricultural University, Hisar-125 004 (Haryana), India; 1Department of Biochemistry

Abstract

Principal component and hierarchical cluster analyses were carried out with 19 agro-morphological traits in 80 germplasm accessions of sesame (Sesamum indicum L.). Principal factor analysis identified eight principal components which explained about 65% variability. PC 1 explained maximum i. e. 10.40% of total variation in agro-morphological traits and PC 2 depicted 8.84% of total morphological variability, while PC 3 had 8.52% of the total variation. Varimax rotation enabled loading of similar type of variables on a common principal factor permitting to designate them as seed yield, maturity, capsule characters and oil content factors. The germplasm accessions viz., GC 19, GC 23, GC 25, GC 26, GC 48 and GC 49 were found to be superior on the basis of principal factor scores with regard to seed yield, its main components and oil content when both the principal factors were considered together. These accessions may further be utilized in breeding programmes for evolving sesame varieties with high seed yield and superior oil content. Hierarchical cluster analysis categorized all the 80 accessions into eight clusters containing 1 to 40 accessions. Based on the inter-cluster distances, maximum genetic diversity was observed between C V and C VIII (92.57) followed by C I and C VIII (91.99), C IV and C VII (88.60) and C V and C VII (87.96) which indicated that germplasm accessions from these clusters could usefully be hybridized for getting superior recombinants in segregating generations. The results of cluster and principal factor analyses supported each other.

Keywords

Cluster  components  germplasm  principal factor  sesame  variability.

References

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