Morphometrics of the tribe <i>Merremieae</i> Austin (Convolvulacae) from India

Abstract

Sixteen species of the tribe Merremieae Austin (Convolvulaceae) from India were morphometrically analyzed with the help of Principal component analysis (PCA) and cluster analysis to explain the relationship between them. PCA showed that quantitative characters like corolla breadth, fruit breadth and length of paracot leaf play important role in bringing together all the species in the same tribe while the characters like leaf length, leaf breadth, petiole length, pedicel length, calyx length and calyx breadth play vital role in the delimitation of taxa within the tribe Merremieae. IntroductionThe Convolvulaceae is one of the largest families of angiosperms consist of 52 genera and 1650 species (Mabberley, 2008) and mainly distributed in the tropical and subtropical regions of the world. Some members of the family Convolvulaceae are medicinally as well as economically important (Austin, 1982;Chopra et al., 1995;Kamalutheen et al., 2009;Sahu and Gupta, 2014).The tribe Merremieae Austin is a diverse tribe in the family Convolvulaceae. Due to many overlapping characters in the members of tribe Merremieae, their proper identification is confusing, which may be due to the lack of sound morphological characters to define it and increase in the number of published species in this tribe. The tribe possesses four genera, viz., Hewittia R. Wight & Arnott, Merremia Dennst. ex Endl., Operculina Silva Manso and Xenostegia Austin & Staples. The genus Hewittia is represented by a single species, Merremia by 70 species, Operculina by 15 species and Xenostegia by only two species in the world (Mabberley, 2008). The present study reveals that, in India the genus Hewittia is represented by a single species, while the genera Operculina and Xenostegia consist of two species each, and the genus Merremia is represented by 11 species.Numerical taxonomy plays important role in segregation of taxa. Cluster analysis (CA) and Principal component analysis (PCA) techniques are commonly used in determining the phylogenetic relationships among different taxa. Applying various methods of numerical taxonomy many authors, e.g. Sneath and Sokal (1973), Chiapella (2000), Gomez-Campo et al. (2001), Sonibare et al. (2004), Henderson (2006, Soladoye et al. (2010), Rahman et al. (2013) and many others have interpreted interrelationship among different genera and families of flowering plants. According to Sonibare et al. (2004) cluster analysis provides a hierarchical classification of entities (taxa) based on the similarity matrix, while PCA is a second method used for reducing the dimensions of the original data which allows visual interpretation of the relationships.