The cluster analysis indicates that 10 populations of Gloriosa superba formed three major cluster groups (Fig.2) . Cluster I represents three populations, populations 1, 8 and 10. Cluster II represents population 2. Cluster III represents 6 populations (populations 3, 7, 5, 9, 4 and 6). The UPGMA dendrogram in the present study showed that some populations from different regions were located in the same clusters for eg. The population 1 (Udaiyarpalaiyam) and the population 10 (Kottayam) were grouped together despite the geographical distance of 236 km between them. On the contrary two geographically close populations, those of Kozhikode and Yelagiri Hills, were distributed into separate clusters and showed a rather large genetic distance. Fig.2 UPGMA (based on Nei’s genetic distance) dendrogram showing the relationship between various populations of Gloriosa superba AMOVA studies show that most of genetic variation in Gloriosa superba is distributed within populations rather than between them, indicating restricted populations. Table 5 Analysis of molecular variance (AMOVA) for various populations of Gloriosa superba from the study area employing RAPD markers IV. DISCUSSION An AMOVA analysis (Table 5) and PCA (based on morphological characters) also did not show any regional assemblage among the populations. Genetic relationships among various populations of Gloriosa superba The proportion of RAPD loci polymorphic per population ranged from 57.84% (Yelagiri Hills) to 74.59% (Kottayam). Amova analysis reveals that 95.9% of the total molecular variation is due to genetic difference within populations and only 4.1% is due to genetic difference among populations (Table 5). RAPD result based on There is much environmental influence accounting for the horticultural variability observed. Therefore, when compared with RAPD techniques, horticultural traits are relatively less reliable and inefficient for precise discrimination of closely related genotypes and analysis of their genetic similarities. In particular, knowledge of population genetic structure provides a historical perspective of evolutionary changes that characterize a species and allow us to predict how populations will respond to future events of natural and artificial origin 17. Under the climate change scenario, for management and protection programs, the genetic structure of species at population level has received special attention in the past few years 18. The presence of unique genetic characteristics distinguishes members of a given population from those of any other. High diversity is an indicator of better adaptability of a population. Irrespective of the plant parts used, 66 Proceedings of the International Conference on Climate Change, Biodiversity and Ecosystem Services for the Sustainable Development Goals (SDGs): Policy and Practice 27-29 June 2016, Cha-am, Phetchaburi, Thailand
Proceedings of International Conference on Climate Change, Biodiversity and Ecosystem Services for the Sustainable Development Goals : Policy and Practice 27-29 June 2016 at the Sirindhorn International Environmental Park, Cha-am, Phetchaburi, Thailand
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