Use of quantile regression and discriminant analysis to describe growth patterns in farmed gilthead sea bream (Sparus aurata)

Aquaculture

Volumn 292, Issue 1-2, 2009, Pages 30-36

  Mayer, P ^a   Estruch, V ^a   Marti P ^b   Jover, M ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b GRAMASA SA (Currently in PISCIMAR SA)   (Spain)

Author keywords

Discriminant analysis; Heterogeneous growth; Homogeneous growth; Quantile regression; TGC growth model

Indexed keywords

DISCRIMINANT ANALYSIS; GROWTH MODELING; GROWTH RESPONSE; NUMERICAL MODEL; PERCIFORM; REGRESSION ANALYSIS; TEMPERATURE GRADIENT;

EURASIA; EUROPE; MEDITERRANEAN REGION; MEDITERRANEAN SEA; SOUTHERN EUROPE; SPAIN;

ARCHOSARGUS RHOMBOIDALIS; SPARUS AURATA;

EID: 67349095828     PISSN: 00448486     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aquaculture.2009.03.035     Document Type: Article

References (16)

1. Cade B.S., and Noon B.R. A gentle introduction to quantile regression for ecologist. Front Ecol. Environ. 1 8 (2003) 412-420
2. Cho C.Y., and Bureau D.P. Development of bioenergetic models and the Fish-PrFEQ software to estimate production, feeding ration and waste output in aquaculture. Aquat. Living Resour. 11 (1998) 199-210
3. Dumas A., France J., and Bureau D.P. Evidence of three growth stanzas in rainbow trout (Oncorhynchus mykiss) across life stages and adaptation of the thermal-unit growth coefficient. Aquaculture 267 (2007) 139-146
4. García-García, B., 1994. Factores que influyen sobre el consume de oxígeno, ingesta y crecimiento de la dorada (Sparus aurata L.): una aproximación al establecimiento de modelos lineales. Doctoral Thesis, Universidad de Murcia, Spain.
5. Irwin S., O'Halloran J., and FitzGerald R.D. The relationship between individual consumption and growth in juvenile turbot, Scophthalmus maximus. Aquaculture 204 (2002) 65-74
6. Iwama G.K., and Tautz A.F. A simple growth model for salmonids in hatcheries. Can. J. Fish. Aquat. Sci. 38 (1981) 649-656
7. Jobling M. The thermal growth coefficient (TGC) model of fish growth: a cautionary note. Aquac. Res. 34 (2003) 581-584
8. Jobling M., Arnesen A.M., Baardvik B.M., Christiansen J.S., and Jorgensen E.H. Monitoring feeding behaviour and food intake: methods and applications. Aquac. Nutr. 1 (1995) 131-143
9. Kaushik S.J. Nutritional bioenergetics and estimation of waste production in non-salmonids. Aquat. Living Resour. 11 (1998) 211-217
10. Koenker R., and Bassett G. Regresión quantiles. Econometrica 46 (1978) 33-50
11. Koenker R., and Bassett G. Robust tests for heteroscedasticity based on regression quantiles. Econometrica 50 (1982) 43-61
12. Lupatsch I., Kissil G.W., and Sklan D. Defining energy and protein requirements of gilthead sea bream (Sparus aurata) to optimize feeds and feeding regimes. Isr. J. Aquac. 55 (2003) 243-257
13. Mayer P., Estruch V., Blasco J., and Jover M. Predicting the growth of gilthead sea bream (Sparus aurata) farmed in marine cages under real production conditions using temperature and time-dependent models. Aquac. Res. 39 (2008) 1046-1052
14. Petridis D., and Rogdakis L. The development of growth and feeding equation for seabream, Sparus aurata L., culture. Aquac. Res. 27 (1996) 413-419
15. Research Development Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2005). 3-900051-07-0. http://www.R-project.org URL http://www.R-project.org
16. Yu K., Lu Z., and Stander J. Quantile regression: applications and current research areas. The Statiscian 52 (2003) 331-350 part 3