Integration of morphometrics and machine learning enables accurate distinction between wild and farmed common carp

Autor:	Omid Jafari, Mansour Ebrahimi, Seyed Ali-Akbar Hedayati, Mehrshad Zeinalabedini, Hadi Poorbagher, Maryam Nasrolahpourmoghadam, Jorge M. O. Fernandes
Jazyk:	angličtina
Předmět:	Space and Planetary Science morphometrics machine learning fish morphology domestication fisheries management Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Algoritmer og beregnbarhetsteori: 422 [VDP] Paleontology General Biochemistry Genetics and Molecular Biology Ecology Evolution Behavior and Systematics Landbruks- og Fiskerifag: 900::Fiskerifag: 920::Akvakultur: 922 [VDP]
Zdroj:	Life Life; Volume 12; Issue 7; Pages: 957
ISSN:	2075-1729
DOI:	10.3390/life12070957
Popis:	Morphology and feature selection are key approaches to address several issues in fisheries science and stock management, such as the hypothesis of admixture of Caspian common carp (Cyprinus carpio) and farmed carp stocks in Iran. The present study was performed to investigate the population classification of common carp in the southern Caspian basin using data mining algorithms to find the most important characteristic(s) differing between Iranian and farmed common carp. A total of 74 individuals were collected from three locations within the southern Caspian basin and from one farm between November 2015 and April 2016. A dataset of 26 traditional morphometric (TMM) attributes and a dataset of 14 geometric landmark points were constructed and then subjected to various machine learning methods. In general, the machine learning methods had a higher prediction rate with TMM datasets. The highest decision tree accuracy of 77% was obtained by rule and decision tree parallel algorithms, and “head height on eye area” was selected as the best marker to distinguish between wild and farmed common carp. Various machine learning algorithms were evaluated, and we found that the linear discriminant was the best method, with 81.1% accuracy. The results obtained from this novel approach indicate that Darwin’s domestication syndrome is observed in common carp. Moreover, they pave the way for automated detection of farmed fish, which will be most beneficial to detect escapees and improve restocking programs.
Databáze:	OpenAIRE
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