Naslov
Seasonal blood chemistry patterns of shade fish Argyrosomus regius

Autori
Čož-Rakovac, Rozelinda ; Strunjak-Perović, Ivančica ; Topić Popović, Natalija ; Šmuc, Tomislav ; Jadan, Margita ; Galetović, Sonja ; Čolak, Slavica ; Lovrinov, Mario ; Milina, Ana

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Diseases of Fish and Shellfish ; 14th EAFP International Conference ; Prague, September 14-19, 2009 / EAFP Committee - Prag : HALAMA Publishing House, 2009, 287-287

ISBN
978-8087082-13-3

Skup
Diseases of Fish and Shellfish ; 14th EAFP International Conference

Mjesto i datum
Prag, Češka Republika, 14.09.2009. - 19.09.2009

Vrsta sudjelovanja
Poster

Vrsta recenzije
Nije recenziran

Ključne riječi
Argyrosomus regius; blood

Sažetak
Plasma biochemical profile was examined in cage cultured shade fish Argirosomus regius in order to evaluate physiological profile and provide detailed picture of its seasonal changes. Biochemical procedures were employed to study trygliceride (TRIG), cholesterol (CHOL), total protein (TP), glucose (GLU), urea (BUN), inorganic phosphate (PHOS), calcium (Ca), creatine kinase (CK), lactate dehydrogenase (LDH), ammonia (NH3), magnesium (Mg), aspartate aminotransferase (AST), amylase (AMYL), alkaline phosphatase (ALKP), creatinine (CREA), gamma glutamyltransferase (GGT) and total bilirubin (TBIL). The results were evaluated through different statistical analyses. Conventional statistical methods do not provide solutions that meet the goals of the research, so machine learning methodology was used to construct and evaluate classifiers as well as to assess parameter (plasma metabolites and enzymes) importances with respect to the target variable (season). It is evident that about half of the parameters (UREA, ALKP, NH3, CHOL, Ca, PHOS, GLU and CREA) have significant importance (i.e. exhibit significant differences between seasons) for seasonal discrimination models. It is also important to stress that using only a subset of most important parameters is generally enough to obtain high accuracy classifiers, which suggests rather high correlation between these parameters on a seasonal scale.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Veterinarska medicina, Biotehnologija

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