Numerical Taxonomy Helps Identification of Merliniidae and Telotylenchidae (Nematoda: Tylenchoidea) from Iran

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Journal of Nematology

Society of Nematologists

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VOLUME 49 , ISSUE 2 (June 2017) > List of articles

Numerical Taxonomy Helps Identification of Merliniidae and Telotylenchidae (Nematoda: Tylenchoidea) from Iran

REZA GHADERI * / HABIBALLAH HAMZEHZARGHANI / AKBAR KAREGAR

Keywords : Amplimerlinius, correlation, hierarchical cluster analysis, Pratylenchoides, principal component analysis.

Citation Information : Journal of Nematology. Volume 49, Issue 2, Pages 207-222, DOI: https://doi.org/10.21307/jofnem-2017-065

License : (CC BY 4.0)

Received Date : 28-March-2017 / Published Online: 24-July-2017

ARTICLE

ABSTRACT

Numerical taxonomy was used for identification and grouping of the genera, species, and populations in the families
Merliniidae and Telotylenchidae. The variability of each of 44 morphometric characters was evaluated by calculation of the coefficient of variability (CV) and the ratio of extremes (max/min) in the range of 1,020 measured females. Also correlation and regression analyses were made between characters to find potential collinearities. Hierarchical cluster analysis (HCA) was used for (i) grouping 21 genera in the superfamily Dolichodoroidea based on literature data coded for states of 18 diagnostic characters, and (ii) for grouping Iranian populations belonging to selected genera. Furthermore, STEPDISC analysis was used for (i) grouping 11 genera of Merliniidae and Telotylenchidae based on the measurements of 35 characters from 1,007 Iranian female specimens, and (ii) grouping measured females of eight species of Amplimerlinius and Pratylenchoides. The multivariate data analysis approach showed robust enough to summarize relationship between morphometric characters and group genera, species, and populations of the nematodes and in particular help to identify the genera and species of Amplimerlinius and Pratylenchoides.

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