The study was conducted to assess intraspecific variation/interrelationships and to determine the association of geographical distribution and phenotypic diversity in the Jatropha curcas accessions studied. Ex situ mo...The study was conducted to assess intraspecific variation/interrelationships and to determine the association of geographical distribution and phenotypic diversity in the Jatropha curcas accessions studied. Ex situ morphological characterization of 13 Jatropha curcas genotypes from various sources was undertaken using 21 quantitative traits. The generated data was subjected to two phenetic analysis methods （principal components analysis and cluster analysis）. Principal Components Analysis （PCA） reduced the collected data to 5 principal components that cumulatively explained 88.81% of total variance. PCA also subdivided the Jatropha provenances into distinct groups on the basis of height. The two clustering mechanisms, Average Linkage-Unweighted Pair Group Method with Arithmetic Mean （UPGMA） and Centroid Method （UPGMC）, divided the provenances into two major groups and revealed the divergence of Tubao-Philbio from the rest of the provenances. However, the study failed to adequately establish a relationship between spatial dispersal and phenotypic divergence in the Jatropha genotypes implying possible genetic homogeneity for the accessions studied. Screening for more quantitative traits and the use of more advanced molecular marker technologies are therefore recommended for a more accurate estimation of genetic diversity in Jatropha.展开更多
文摘The study was conducted to assess intraspecific variation/interrelationships and to determine the association of geographical distribution and phenotypic diversity in the Jatropha curcas accessions studied. Ex situ morphological characterization of 13 Jatropha curcas genotypes from various sources was undertaken using 21 quantitative traits. The generated data was subjected to two phenetic analysis methods （principal components analysis and cluster analysis）. Principal Components Analysis （PCA） reduced the collected data to 5 principal components that cumulatively explained 88.81% of total variance. PCA also subdivided the Jatropha provenances into distinct groups on the basis of height. The two clustering mechanisms, Average Linkage-Unweighted Pair Group Method with Arithmetic Mean （UPGMA） and Centroid Method （UPGMC）, divided the provenances into two major groups and revealed the divergence of Tubao-Philbio from the rest of the provenances. However, the study failed to adequately establish a relationship between spatial dispersal and phenotypic divergence in the Jatropha genotypes implying possible genetic homogeneity for the accessions studied. Screening for more quantitative traits and the use of more advanced molecular marker technologies are therefore recommended for a more accurate estimation of genetic diversity in Jatropha.
