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Morphometric analysis of <i>Dactylorhiza hatagirea</i> (D. Don), a critically endangered orchid in cold desert Ladakh region of India


Ashish R. Warghat
Prabodh K. Bajpai
Hemant Sood
Om P. Chaurasia
Ravi B. Srivastava

Abstract

The morphometric study was conducted during 2009 to 2010. About 28 morphological characters were measured under 13 natural populations of Dactylorhiza hatagirea. Geographic variation in morphology reflects phenotypic responses to environmental gradients and evolutionary history of populations and species. At points, beside its broad geographic range (Nubra, Suru and Indus valley) characterization of Dactylorhiza phenotype is normally accomplished by use of morphological descriptors, hence as a first step, phenotype collection and its morphometric analysis was assessed. However, plant height, leaf length, lowermost leaf length, length of second leaf from base and mean length from lowest bract to the top of inflorescence are presented to account for the remarkable variation in morphological characters. Tirith population showed more values of this trait while Skurru showed less value. From this, it is concluded that Tirith showed great morphometric variation as compared to other population. Multivariate morphometric techniques, principal component analysis (PCA), multidimensional scaling (MDS) and cluster analysis were used to determine whether these populations can be reliably morphologically similar or dissimilar. The first two principal components encompass more than 75% variation among population. The results of PCA and MDS analysis were comparable to the cluster analysis, which shows considerable phenotypic variation in morphological and horticultural traits that can be utilized in its genetic improvement. To support this study, further constructive information were provided on the status of the populations of D. hatagirea which may increase the conservation value of this site and resolve the suitable areas with taxonomic and nomenclatural controversies.

Keywords: Morphological characters, principal component analysis (PCA), multidimensional scaling (MDS), plant height, leaf length, leaf width


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eISSN: 1684-5315