Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax)
The aim of the study was to validate a dummy regression approach for predictive modelling the fillet fatty acid (FA) composition of cultured European sea bass with dietary FA composition and lipid fillet content as independent variables. The model used our own data on gilthead sea bream as reference...
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John Wiley & Sons
2016
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Online Access: | http://hdl.handle.net/10261/145657 https://doi.org/10.1111/are.12563 https://doi.org/10.13039/501100004837 https://doi.org/10.13039/501100003359 https://doi.org/10.13039/501100000780 |
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ftcsic:oai:digital.csic.es:10261/145657 2024-02-11T10:09:17+01:00 Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) Ballester-Lozano, Gabriel F. Benedito-Palos, Laura Mingarro, Mónica Navarro, Juan Carlos Pérez-Sánchez, Jaume Ministerio de Ciencia e Innovación (España) Generalitat Valenciana Diputación de Castellón European Commission 2016-04 http://hdl.handle.net/10261/145657 https://doi.org/10.1111/are.12563 https://doi.org/10.13039/501100004837 https://doi.org/10.13039/501100003359 https://doi.org/10.13039/501100000780 unknown John Wiley & Sons Postprint https://doi.org/10.1111/are.12563 Sí issn: 1365-2109 Aquaculture Research 47(4): 1067-1074 (2016) http://hdl.handle.net/10261/145657 doi:10.1111/are.12563 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003359 http://dx.doi.org/10.13039/501100000780 open artículo http://purl.org/coar/resource_type/c_6501 2016 ftcsic https://doi.org/10.1111/are.1256310.13039/50110000483710.13039/50110000335910.13039/501100000780 2024-01-16T10:21:16Z The aim of the study was to validate a dummy regression approach for predictive modelling the fillet fatty acid (FA) composition of cultured European sea bass with dietary FA composition and lipid fillet content as independent variables. The model used our own data on gilthead sea bream as reference subgroup dataset and data from turbot, sole and European sea bass as dummy variables. Most of the observed variance within and among species was explained by the regression model without statistical significant interactions on blocks between diet composition and fish species subgroups. For the validation of European sea bass FA descriptors, predictive values derived from data on fish reared at laboratory scale were plotted against those obtained in farmed fish harvested at commercial size. A close linear association near to equality was found for 12 representative FAs, including saturated FAs, monoenenes and polyunsaturated FAs. This finding reinforces the possibility to produce tailored and healthy seafood products according to the guidelines of essential FA requirements in humans. FA algorithms for all the species in the model are hosted at www.nutrigroup-iats.org/aquafat as a multispecies tool to interrogate the nutritionally regulated FA composition of four cultured marine fish species of a high added value. This study was founded by Spanish (AQUAFAT, AGL2009-07797, Predictive modelling of flesh fatty acid composition in cultured fish species with different muscle lipid content) and EU (ARRAINA, KBBE-2011-5-288925, Advanced research initiatives for nutrition and aquaculture) projects. Additional founding was obtained from the “Generalitat Valenciana” (research grant PROMETEO 2010/006). GFB-L was recipient of a Spanish PhD fellowship from the Diputación Provincial de Castellón. Peer Reviewed Article in Journal/Newspaper Turbot Digital.CSIC (Spanish National Research Council) Aquaculture Research 47 4 1067 1074 |
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Open Polar |
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Digital.CSIC (Spanish National Research Council) |
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ftcsic |
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unknown |
description |
The aim of the study was to validate a dummy regression approach for predictive modelling the fillet fatty acid (FA) composition of cultured European sea bass with dietary FA composition and lipid fillet content as independent variables. The model used our own data on gilthead sea bream as reference subgroup dataset and data from turbot, sole and European sea bass as dummy variables. Most of the observed variance within and among species was explained by the regression model without statistical significant interactions on blocks between diet composition and fish species subgroups. For the validation of European sea bass FA descriptors, predictive values derived from data on fish reared at laboratory scale were plotted against those obtained in farmed fish harvested at commercial size. A close linear association near to equality was found for 12 representative FAs, including saturated FAs, monoenenes and polyunsaturated FAs. This finding reinforces the possibility to produce tailored and healthy seafood products according to the guidelines of essential FA requirements in humans. FA algorithms for all the species in the model are hosted at www.nutrigroup-iats.org/aquafat as a multispecies tool to interrogate the nutritionally regulated FA composition of four cultured marine fish species of a high added value. This study was founded by Spanish (AQUAFAT, AGL2009-07797, Predictive modelling of flesh fatty acid composition in cultured fish species with different muscle lipid content) and EU (ARRAINA, KBBE-2011-5-288925, Advanced research initiatives for nutrition and aquaculture) projects. Additional founding was obtained from the “Generalitat Valenciana” (research grant PROMETEO 2010/006). GFB-L was recipient of a Spanish PhD fellowship from the Diputación Provincial de Castellón. Peer Reviewed |
author2 |
Ministerio de Ciencia e Innovación (España) Generalitat Valenciana Diputación de Castellón European Commission |
format |
Article in Journal/Newspaper |
author |
Ballester-Lozano, Gabriel F. Benedito-Palos, Laura Mingarro, Mónica Navarro, Juan Carlos Pérez-Sánchez, Jaume |
spellingShingle |
Ballester-Lozano, Gabriel F. Benedito-Palos, Laura Mingarro, Mónica Navarro, Juan Carlos Pérez-Sánchez, Jaume Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) |
author_facet |
Ballester-Lozano, Gabriel F. Benedito-Palos, Laura Mingarro, Mónica Navarro, Juan Carlos Pérez-Sánchez, Jaume |
author_sort |
Ballester-Lozano, Gabriel F. |
title |
Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) |
title_short |
Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) |
title_full |
Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) |
title_fullStr |
Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) |
title_full_unstemmed |
Up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured European sea bass (Dicentrarchus labrax) |
title_sort |
up-scaling validation of a dummy regression approach for predictive modelling the fillet fatty acid composition of cultured european sea bass (dicentrarchus labrax) |
publisher |
John Wiley & Sons |
publishDate |
2016 |
url |
http://hdl.handle.net/10261/145657 https://doi.org/10.1111/are.12563 https://doi.org/10.13039/501100004837 https://doi.org/10.13039/501100003359 https://doi.org/10.13039/501100000780 |
genre |
Turbot |
genre_facet |
Turbot |
op_relation |
Postprint https://doi.org/10.1111/are.12563 Sí issn: 1365-2109 Aquaculture Research 47(4): 1067-1074 (2016) http://hdl.handle.net/10261/145657 doi:10.1111/are.12563 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100003359 http://dx.doi.org/10.13039/501100000780 |
op_rights |
open |
op_doi |
https://doi.org/10.1111/are.1256310.13039/50110000483710.13039/50110000335910.13039/501100000780 |
container_title |
Aquaculture Research |
container_volume |
47 |
container_issue |
4 |
container_start_page |
1067 |
op_container_end_page |
1074 |
_version_ |
1790609098384867328 |