IPez: An expert system for the taxonomic identification of fishes based on machine learning techniques

被引：33

作者：

Guisande, C. ^{[1
]}

Manjarres-Hernandez, A. ^{[2
]}

Pelayo-Villamil, P. ^{[3
]}

Granado-Lorencio, C. ^{[4
]}

Riveiro, I. ^{[1
]}

Acuna, A. ^{[1
]}

Prieto-Piraquive, E. ^{[4
]}

Janeiro, E. ^{[5
]}

Matias, J. M. ^{[5
]}

Patti, C. ^{[6
]}

Patti, B. ^{[6
]}

Mazzola, S. ^{[6
]}

Jimenez, S. ^{[7
]}

Duque, V. ^{[7
]}

Salmeron, F. ^{[8
]}

机构：

[1] Univ Vigo, Fac Ciencias, Vigo 36200, Spain

[2] Univ Nacl Colombia, Inst Amazon Invest IMANI, Leticia, Colombia

[3] Univ Antioquia, Grp Ictiol, Medellin 1226, Colombia

[4] Univ Seville, Fac Biol, E-41012 Seville, Spain

[5] Univ Vigo, Dept Ingn Recursos Nat & Medio Ambiente, Vigo 36310, Spain

[6] CNR, Ist Ambiente Marino Costiero, I-91026 Mazara Del Vallo, TP, Italy

[7] Ctr Oceanog Canarias, Inst Espanol Oceanog, Tenerife 38120, Spain

[8] Ctr Oceanog Malaga, Inst Espanol Oceanog, Fuengirola 29640, Spain

来源：

FISHERIES RESEARCH | 2010年 / 102卷 / 03期

关键词：

Classification and regression trees; Morphology; Taxonomy; Identification; Fishes;

D O I：

10.1016/j.fishres.2009.12.003

中图分类号：

S9 [水产、渔业];

学科分类号：

0908 ;

摘要：

The taxonomic identification of fishes is a time-consuming process for those who are not specialists and, therefore, are more liable to make mistakes. We measured morphometric characters in more than 8900 individuals belonging to 6 classes, 43 orders, 192 families, 510 genera and 847 marine and freshwater species. The aim was to determine if the taxonomic identification of juvenile and adult fishes is possible using these measurements. We developed the expert system IPez, which is based on machine learning techniques, and found that, when the number of individuals measured of a species and, hence, included in the database of IPez, is higher than approximately 15 individuals, IPez identifies correctly 100% of new individuals of this species that are not included into the database. Moreover, besides helping in the taxonomic identification of fish, this software allows the determining of the main morphometric characters that have promoted or are promoting divergence among closely related species. The software is free and available at the web page http://www.ipez.es/index%20ingles.html. We suggest increased international collaboration to introduce more species into IPez. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：240 / 247

页数：8

共 18 条

[1]

Abe S., 2005, ADV PTRN RECOGNIT

[2] SmcHD1, containing a structural-maintenance-of-chromosomes hinge domain, has a critical role in X inactivation [J].

Blewitt, Marnie E. ;

Gendrel, Anne-Valerie ;

Pang, Zhenyi ;

Sparrow, Duncan B. ;

Whitelaw, Nadia ;

Craig, Jeffrey M. ;

Apedaile, Anwyn ;

Hilton, Douglas J. ;

Dunwoodie, Sally L. ;

Brockdorff, Neil ;

Kay, Graham F. ;

Whitelaw, Emma .

NATURE GENETICS, 2008, 40 (05) :663-669

[3] Advances in morphometric identification of fishery stocks [J].

Cadrin, SX .

REVIEWS IN FISH BIOLOGY AND FISHERIES, 2000, 10 (01) :91-112

[4] The evolution of morphological diversity [J].

Foote, M .

ANNUAL REVIEW OF ECOLOGY AND SYSTEMATICS, 1997, 28 :129-152

[5]

Friedman J., 2001, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, V1

[6] Automated species identification: why not? [J].

Gaston, KJ ;

O'Neill, MA .

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2004, 359 (1444) :655-667

[7]

Gauld I.D., 2000, P303

[8]

Guisande C., 2006, TRATAMIENTO DATOS DI, P356

[9]

Hosmer D.W., 1989, Applied Logistic regression

[10] Integrating information on marine species identification for fishery purposes [J].

Lleonart, Jordi ;

Taconet, Marc ;

Lamboeuf, Michel .

MARINE ECOLOGY PROGRESS SERIES, 2006, 316 :231-238

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