Abstract

Characterization of selected spider plant accessions from Kenya and South Africa was performed in order to individuate those with distinct morphological traits for future improvement programs. For this purpose, thirty two accessions of spider plant, 23 sourced from Kenyan genebank and nine sourced from South African genebank, were planted at the University of Nairobi’s Kabete field station, in a randomized complete block design with 3 replications. Eleven morphological traits based on modified FAO (1995) spider plant descriptors were used in characterization. Traits evaluated were growth habit, flower colour, stem colour, stem hairiness, petiole colour, petiole hairiness, leaf colour, leaf pubescence, leaf shape, leaf blade tip shape, and number of leaflets per leaf. The scored data were analyzed using DARwin software v6 and Genstat v14. Shannon diversity index (H’), multivariate methods of principal component analysis and hierarchical clustering analyses of unweighted pair group method of arithmetic mean were assessed for all the traits. Estimates of Shannon-Weaver diversity index (H’) for the morphological traits were generally high (H’>0.500). The H' index indicated inter-country diversity to be greater than the intra-country diversity. Principal component analysis identified seven important morphological traits (stem colour, stem hairiness, petiole colour, petiole hairiness, leaf hairiness, leaf shape and number of leaflets per leaf) for characterizing spider plant accessions. The hierarchical cluster analysis revealed two major clusters (Cluster I and II) for the 32 accessions grown, with clustering of accessions occurring along regional basis. Cluster I consisted of South African accessions only while cluster II had mainly Kenyan accessions and two South African accessions. The relatively high levels of dissimilarity revealed in this study among the accessions for traits evaluated, especially accessions from the two different countries, indicates high prospects for genetic improvement of the crop through cross breeding by using materials from different geographical origins.

Keywords:

Cat, indigenous vegetables, Principal Component Analysis (PCA), Unweighted Pair Group Method of Arithmetic Averaging (UPGMA),

References

Competing interests

The authors have no competing interests.

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The authors have no competing interests.