The relationship between feed efficiency, growth and group dominance dynamics in turbot (Scophthalmus maximus)

Luis Gomez-Raya, Wendy M. Rauw, Santiago Cabaleiro, Rubén Caamaño, L. Alberto Garcia-Cortes, Antti Kause

Abstract


Variation among families of turbot (Scophthalmus maximus) in growth, feed efficiency, and body weight variation was investigated. A total of 672 turbot (Scophthalmus maximus) originating from eight families (84 full-sibs per family) were used in this experiment. Body weight (BW) was recorded individually four times between approximately 250 and 370 days of age. Feed intake was measured for each tank during the three corresponding time periods. Feed efficiency was estimated for each tank based on the calculations of residual feed intake (RFI) and feed conversion ratio (FCR). The within-tank coefficient of variation in body weight (CV-BW) and residual body weight variation (RBWV) were calculated to evaluate group dominance dynamics. Components of variation attributable to families were estimated from linear and quadratic random regression orthogonal polynomials. The random quadratic family component explained 14% (RFI), 22% (FCR), 76% (BW), 50% (CV-BW), and 45% (RBWV) of the total variance. The family components were significant for BW, CV-BW and RBWV (p<0.001), and was very close to significance for FCR (p=0.052). The correlation between the intercept (grand mean) of RFI and FCR was highly significant (r=0.94). Intercepts of RFI and FCR were positively correlated with CV-BW and RBWV (r=0.09 to 0.12), however, the correlations were not significant. The results indicate differences between families in FCR, which may be used in selection programs aimed at improving feed efficiency.


Keywords


aquaculture, fish

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References


Árnason T, Björnsson B, Steinarsson A, Oddgeirsson M, 2009. Effects of temperature and body weight on growth rate and feed conversion ratio in turbot (Scophthalmus maximus). Aquaculture 295: 218-225. https://doi.org/10.1016/j.aquaculture.2009.07.004

Aubin J, Papatryphon E, Van der Werf HMG, Chatzifotis S, 2009. Assessment of the environmental impact of carnivorous finfish production systems using life cycle assessment. J Cleaner Prod 17: 354-361. https://doi.org/10.1016/j.jclepro.2008.08.008

Bouza C, Vandamme S, Hermida M, Cabaleiro S, Volckaert F, Martinez P, 2014. Turbot (Scophthalmus maximus). AquaTrace species leaflet. 24 pp. https://aquatrace.eu/documents/80305/142567/turbot+leaflet.pdf

Bureau DP, Hua K, 2010. Towards effective nutritional management of waste outputs in aquaculture, with particular reference to salmonid aquaculture operations. Aquac Res 41: 777-792. https://doi.org/10.1111/j.1365-2109.2009.02431.x

Chavanne H, Janssen K, Hofherr J, Contini F, Haffray P, Aquatrace Consortium, Komen H, Nielsen EE, Bargelloni L, 2016. A comprehensive survey on selective breeding programs and seed market in European aquaculture fish industry. Aquacult Int 24: 1287-1307. https://doi.org/10.1007/s10499-016-9985-0

Crews DH, 2005. Genetics of efficient feed utilization and national cattle evaluation: A review. Genet Mol Res 4: 152-165.

Danancher D, García-Vázquez E, 2007. Turbot - Scophthalmus maximus. In: Genetic impact of aquaculture activities on native populations. Genimpact - Evaluation of genetic impact of aquaculture activities on native populations; Svåsand T, Crosetti D, García-Vázquez E, Verspoor E (Eds.). Final Scientific Report, July 2007, pp: 55-61.

Doupé RG, Lymbery AJ, 2003. Toward the genetic improvement of feed conversion efficiency in fish. J World Aquacult Soc 34: 245-254. https://doi.org/10.1111/j.1749-7345.2003.tb00063.x

FIS, 2015. Seabream production falls, but seabass and turbot ones grow. Fish Information & Services, World News, September 22.

">http://www.fis.com/fis/worldnews/worldnews.asp?monthyear=9-2015&day=22&id=79409&l=e&country=0&special=&ndb=1&df=0

Fox HE, White SA, Kao MHF, Fernald RD, 1997. Stress and dominance in a social fish. J Neurosci 17: 6463-6469.

Frank SA, 1995. Mutual policing and repression of competition in the evolution of cooperative groups. Nature 377: 520-522. https://doi.org/10.1038/377520a0

Gilmour KM, DiBattista JD, Thomas JB, 2005. Physiological causes and consequences of social status in salmonid fish. Integr Comp Biol 45: 263-273. https://doi.org/10.1093/icb/45.2.263

Gilmour AR, Cullis BR, Welham SJ, Thompson R, 2009. ASREML Discovery Reference Manual, University of Adelaide, Adelaide, SA, Australia.

Gjedrem T, 1983. Genetic variation in quantitative traits and selective breeding in fish and shellfish. Aquaculture 33: 51-72. https://doi.org/10.1016/0044-8486(83)90386-1

Gjedrem T, 2000. Genetic improvement of cold-water fish species. Aquac Res 31: 25-33. https://doi.org/10.1046/j.1365-2109.2000.00389.x

Gjedrem T, Robinson N, Rye M, 2012. The importance of selective breeding in aquaculture to meet future demands for animal protein: A review. Aquaculture 350-353: 117-129. https://doi.org/10.1016/j.aquaculture.2012.04.008

Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Pretty J, Robinson S, Thomas SM, Toulmin C, 2010. Food security: The challenge of feeding 9 billion people. Science 327: 812-818. https://doi.org/10.1126/science.1185383

Grima L, Quillet E, Boujard T, Robert-Granié C, Chatain B, Mambrini M, 2008. Genetic variability in residual feed intake in rainbow trout clones and testing of indirect selection criteria. Genet Sel Evol 40: 607-624.

Grima L, Vandeputte M, Ruelle F, Vergnet A, Mambrini M, Chatain B, 2010. In search for indirect criteria to improve residual feed intake in sea bass (Dicentrarchus labrax). Part I: Phenotypic relationship between residual feed intake and body weight variations during feed deprivation and re-feeding periods. Aquaculture 300: 50-58. https://doi.org/10.1016/j.aquaculture.2010.01.003

Herd RM, 2009. Residual feed intake. In: Resource allocation theory applied to farm animal production; Rauw WM (Ed.). CABI Publ, Wallingford, UK. pp: 89-109.

Herd RM, Bishop SC, 2000. Genetic variation in residual feed intake and its association with other production traits in British Hereford cattle. Livest Prod Sci 63: 111-119. https://doi.org/10.1016/S0301-6226(99)00122-0

Irwin S, O'Halloran J, FitzGerald RD, 2002. The relationship between individual consumption and growth in juvenile turbot, Scophthalmus maximus. Aquaculture 204: 65-74. https://doi.org/10.1016/S0044-8486(01)00641-X

Jamrozik J, Schaeffer LR, 1997. Estimates of genetic parameters for a test day model with random regression for yield traits of first lactation Holsteins. J Dairy Sci 80: 762-770. https://doi.org/10.3168/jds.S0022-0302(97)75996-4

Jamrozik J, Kistemaker GJ, Dekkers JCM, Schaeffer LR, 1997. Comparison of possible covariates for use in a random regression model for analysis of test day yields. J Dairy Sci 80: 2550-2556. https://doi.org/10.3168/jds.S0022-0302(97)76210-6

Janhunen M, Kause A, Vehviläinen H, Järvisalo O, 2012. Genetics of microenvironmental sensitivity of body weight in rainbow trout (Oncorhynchus mykiss) selected for improved growth. PLoS ONE 7: e38766. https://doi.org/10.1371/journal.pone.0038766

Janssen K, Chavanne H, Berentsen P, Komen H, 2017. Impact of selective breeding on European aquaculture. Aquaculture 472: 8-16. https://doi.org/10.1016/j.aquaculture.2016.03.012

Jobling M, 1993. Bioenergetics: feed intake and energy partitioning. In: Fish Ecophysiology; Rankin JC & Jensen FB (Eds.). Chapman & Hall, London, UK, pp: 1-44. https://doi.org/10.1007/978-94-011-2304-4_1

Jobling M, 1995. Simple indices for the assessment of the influences of social environment on growth performance, exemplified by studies on Arctic charr. Aquacult Int 3: 60-65. https://doi.org/10.1007/BF00240922

Kankainen M, Setälä J, Kause A, Quinton C, Airaksinen S, Koskela J, 2016. Economic values of supply chain productivity and quality traits calculated for a farmed European whitefish breeding program. Aquacult Econ Manag 20: 131-164. https://doi.org/10.1080/13657305.2016.1155961

Kause A, Tobin D, Dobly A, Houlihan D, Martin S, Mäntysaari EA, Ritola O, Ruohonen K, 2006a. Recording strategies and selection potential of feed intake measured using the X-ray method in rainbow trout. Genet Sel Evol 38: 389-409. https://doi.org/10.1186/1297-9686-38-4-389

Kause A, Tobin D, Houlihan DF, Martin SAM, Mäntysaari EA, Ritola O, Ruohonen K, 2006b. Feed efficiency of rainbow trout can be improved through selection: Different genetic potential on alternative diets. J Anim Sci 84: 807-817. https://doi.org/10.2527/2006.844807x

Kause A, Kiessling A, Martin SAM, Houlihan D, Ruohonen K, 2016. Genetic improvement of feed conversion ratio via indirect selection against lipid deposition in farmed rainbow trout (Oncorhynchus mykiss Walbaum). Brit J Nutr 116: 1656-1665. https://doi.org/10.1017/S0007114516003603

Koch RM, Swiger LA, Chambers D, Gregory KE, 1963. Efficiency of feed use in beef cattle. J Anim Sci 22: 486-494. https://doi.org/10.2527/jas1963.222486x

Kolstad K, Grisdale-Helland B, Gjerde B, 2004. Family differences in feed efficiency in Atlantic salmon (Salmo salar). Aquaculture 241: 169-177. https://doi.org/10.1016/j.aquaculture.2004.09.001

Li HW, Brocksen RW, 1977. Approaches to the analysis of energetic costs of intraspecific competition for space by rainbow trout (Salmo gairneri). J Fish Biol 11: 329-341. https://doi.org/10.1111/j.1095-8649.1977.tb04126.x

Lymbery AJ, 2000. Genetic improvement in the Australian aquaculture industry. Aquac Res 31: 145-149. https://doi.org/10.1046/j.1365-2109.2000.00435.x

Mambrini M, Sanchez MP, Chevassus B, Labbe L, Quillet E, Boujard T, 2004. Selection for growth increases feed intake and affects feeding behavior of brown trout. Livest Prod Sci 88: 85-98. https://doi.org/10.1016/j.livprodsci.2003.10.005

Martins CIM, Aanyu M, Schrama JW, Verreth JAJ, 2005. Size distribution in African catfish (Clarias gariepinus) affects feeding behavior but not growth. Aquaculture 250: 300-307. https://doi.org/10.1016/j.aquaculture.2005.05.034

Martins CIM, Schrama JW, Verreth JAJ, 2006. The relationship between individual differences in feed efficiency and stress response in African catfish Clarias gariepinus. Aquaculture 256: 588-595. https://doi.org/10.1016/j.aquaculture.2006.02.051

McCarthy ID, Houlihan DF, Carter CG, Moutou K, 1993. Variation in individual food consumption rates of fish and its implications for the study of fish nutrition and physiology. P Nutr Soc 52: 427-436. https://doi.org/10.1079/PNS19930083

Naylor RL, Goldburg J, Primavera JH, Kautsky N, Beveridge MCM, Clay J, Folke C, Lubchenco J, Mooney H, Troell M, 2000. Effect of aquaculture on world fish supplies. Nature 405: 1017-1024. https://doi.org/10.1038/35016500

Polanco JF, Bjorndal T, 2013. Turbot markets. Constraint by recession, Spanish demand dictates production. Global Aquaculture Advocate July/August: 56-58. Food security: the challenge of feeding 9 billion people. Science 327: 812-818.

Quinton C, Kause A, Ruohonen K, Koskela J, 2007. Genetic relationships of body composition and feed utilization traits in European whitefish (Coregonus lavaretus L.) and implications for selective breeding in fishmeal- and soybean meal-based diet environments. J Anim Sci 85: 3198-3208. https://doi.org/10.2527/jas.2006-792

Rauw WM, 2012. Feed efficiency and animal robustness. In: Feed efficiency in the beef industry; Hill RA (Ed.). John Wiley & Sons, Ames, IA, USA. pp: 105-122. https://doi.org/10.1002/9781118392331.ch8

Rauw WM, Soler J, Tibau J, Reixach J, Gomez Raya L, 2006. The relationship between residual feed intake and feed intake behavior in group-housed Duroc barrows. J Anim Sci 84: 956-962. https://doi.org/10.2527/2006.844956x

Rauw WM, Larrán AM, Garcia-Cortés LA, Rodriguez ML, Fernández J, Pinedo J, Villarroel M, Toro MA, Tomás Almenar C, Gomez-Raya L, 2016. Feed efficiency of Rainbow trout (Onchorynchus mykiss) kept at high and low stocking density. Int J Recirc Aquac 13: 1-8.

Rutten MJM, Komena H, Bovenhuis H, 2005. Longitudinal genetic analysis of Nile tilapia (Oreochromis niloticus L.) body weight using a random regression model. Aquaculture 246: 101-113. https://doi.org/10.1016/j.aquaculture.2004.12.020

Sae-Lim P, Kause A, Janhunen M, Vehviläinen H, Koskinen H, Gjerde B, Lillehammer M, Mulder HA, 2015. Genetic (co)variance of rainbow trout (Oncorhynchus mykiss) body weight and its uniformity across production environments. Genet Sel Evol 47: 46. https://doi.org/10.1186/s12711-015-0122-8

Schaeffer LR, 2004. Application of random regression models in animal breeding. Livest Prod Sci 86: 35-45. https://doi.org/10.1016/S0301-6226(03)00151-9

Silverstein JT, Hostuttler M, Blemings KP, 2005. Strain differences in feed efficiency measured as residual feed intake in individually reared rainbow trout, Oncorhynchus mykiss (Walbaum). Aquac Res 36: 704-711. https://doi.org/10.1111/j.1365-2109.2005.01278.x

Sonesson AK, Meuwissen THE, 2009. Testing strategies for genomic selection in aquaculture breeding programs. Genet Sel Evol 41: 37. https://doi.org/10.1186/1297-9686-41-37

Ward AJW, Webster MM, Hart PJB, 2006. Intraspecific food competition in fishes. Fish Fish 7: 231-261. https://doi.org/10.1111/j.1467-2979.2006.00224.x




DOI: 10.5424/sjar/2018161-12069