Literature DB >> 19262809

Cluster analysis of longidorus species (nematoda: longidoridae), a new approach in species identification.

Weimin Ye, R T Robbins.   

Abstract

Hierarchical cluster analysis based on female morphometric character means including body length, distance from vulva opening to anterior end, head width, odontostyle length, esophagus length, body width, tail length, and tail width were used to examine the morphometric relationships and create dendrograms for (i) 62 populations belonging to 9 Longidorus species from Arkansas, (ii) 137 published Longidorus species, and (iii) 137 published Longidorus species plus 86 populations of 16 Longidorus species from Arkansas and various other locations by using JMP 4.02 software (SAS Institute, Cary, NC). Cluster analysis dendograms visually illustrated the grouping and morphometric relationships of the species and populations. It provided a computerized statistical approach to assist by helping to identify and distinguish species, by indicating morphometric relationships among species, and by assisting with new species diagnosis. The preliminary species identification can be accomplished by running cluster analysis for unknown species together with the data matrix of known published Longidorus species.

Entities:  

Keywords:  Longidorus; cluster analysis; hierarchical; identification; morphometrics

Year:  2004        PMID: 19262809      PMCID: PMC2620778     

Source DB:  PubMed          Journal:  J Nematol        ISSN: 0022-300X            Impact factor:   1.402


  3 in total

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

Authors:  Reza Ghaderi; Habiballah Hamzehzarghani; Akbar Karegar
Journal:  J Nematol       Date:  2017-06       Impact factor: 1.402

2.  Description of Longidorus azarbaijanensis n. sp. (Dorylaimida: Longidoridae) from Iran.

Authors:  Farshad Gharibzadeh; Ebrahim Pourjam; Majid Pedram
Journal:  J Nematol       Date:  2018-09-03       Impact factor: 1.402

3.  Clinical clustering with prognostic implications in Japanese COVID-19 patients: report from Japan COVID-19 Task Force, a nation-wide consortium to investigate COVID-19 host genetics.

Authors:  Shiro Otake; Shotaro Chubachi; Ho Namkoong; Kensuke Nakagawara; Hiromu Tanaka; Ho Lee; Atsuho Morita; Takahiro Fukushima; Mayuko Watase; Tatsuya Kusumoto; Katsunori Masaki; Hirofumi Kamata; Makoto Ishii; Naoki Hasegawa; Norihiro Harada; Tetsuya Ueda; Soichiro Ueda; Takashi Ishiguro; Ken Arimura; Fukuki Saito; Takashi Yoshiyama; Yasushi Nakano; Yoshikazu Mutoh; Yusuke Suzuki; Koji Murakami; Yukinori Okada; Ryuji Koike; Yuko Kitagawa; Akinori Kimura; Seiya Imoto; Satoru Miyano; Seishi Ogawa; Takanori Kanai; Koichi Fukunaga
Journal:  BMC Infect Dis       Date:  2022-09-14       Impact factor: 3.667

  3 in total

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