Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software

Detalhes bibliográficos
Autor(a) principal: Soares, Diogo Alexandre Marques
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.1/12361
Resumo: This Thesis aims to optimise the algorithms used to estimate actual biomass and weight distribution in gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) cages by the Aquanetix Software. For this, we first try to understand the practical functioning of a fish farm that uses cages and how can the used procedures affect the collection of data or its veracity. Then, we use the data collected by the company and the observations made on the field in order to attempt the optimization of the algorithms that estimate biomass and weight distribution of the Aquanetix Software. The data parameters analysed were the moving average of the estimated biomass, mortality, density, number of fish and mean weight. Two time periods were tested for the moving average of the estimated biomass, at fourteen and thirty days prior to the first harvest. Between these two periods, the one at thirty days seemed to provide the better biomass estimation. Mortality and density showed to have no apparent influence in the deviations found between the biomass estimations and the total biomass harvested. The number of fish was found to be overestimated in the majority of the studied cages (n=7), with the exception of only cage 109. The mean weight was found to be underestimated in the majority of the studied cages, with the exception of only cage 03. At the end, all proposed goals were achieved. In conclusion, every cage of sea bream studied (n=4) shows an under estimation of the mean weight of fish at first harvest, which in turn leads to an underestimation of the biomass. This suggests that every sea bream cage is currently being under fed, most likely, due to a fault on the feeding model which is probably overestimating the specific feeding rate (SFR) for this species. Alterations should be made to the feeding model in order to resolve this unbalance. The results for the sea bass cages were shown to be more inconclusive since all of the studied cages for this species (n=3) appear to have no common reason to explain the errors found for the estimation of their biomass.
id RCAP_9c2e7fcd55ba4cc24157038e8fa4ff2d
oai_identifier_str oai:sapientia.ualg.pt:10400.1/12361
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management softwareSparus aurataDicentrarchus labraxAquacultura em jaulasModelo de alimentaçãoBiomassaThis Thesis aims to optimise the algorithms used to estimate actual biomass and weight distribution in gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) cages by the Aquanetix Software. For this, we first try to understand the practical functioning of a fish farm that uses cages and how can the used procedures affect the collection of data or its veracity. Then, we use the data collected by the company and the observations made on the field in order to attempt the optimization of the algorithms that estimate biomass and weight distribution of the Aquanetix Software. The data parameters analysed were the moving average of the estimated biomass, mortality, density, number of fish and mean weight. Two time periods were tested for the moving average of the estimated biomass, at fourteen and thirty days prior to the first harvest. Between these two periods, the one at thirty days seemed to provide the better biomass estimation. Mortality and density showed to have no apparent influence in the deviations found between the biomass estimations and the total biomass harvested. The number of fish was found to be overestimated in the majority of the studied cages (n=7), with the exception of only cage 109. The mean weight was found to be underestimated in the majority of the studied cages, with the exception of only cage 03. At the end, all proposed goals were achieved. In conclusion, every cage of sea bream studied (n=4) shows an under estimation of the mean weight of fish at first harvest, which in turn leads to an underestimation of the biomass. This suggests that every sea bream cage is currently being under fed, most likely, due to a fault on the feeding model which is probably overestimating the specific feeding rate (SFR) for this species. Alterations should be made to the feeding model in order to resolve this unbalance. The results for the sea bass cages were shown to be more inconclusive since all of the studied cages for this species (n=3) appear to have no common reason to explain the errors found for the estimation of their biomass.Cabrita, Elsa Alexandra Martins e SilvaThomaz, Diogo FernandesSapientiaSoares, Diogo Alexandre Marques2019-02-22T12:34:52Z2018-12-1320182018-12-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.1/12361urn:tid:202167305enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-18T17:41:33Zoai:sapientia.ualg.pt:10400.1/12361Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:32:00.018914Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
title Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
spellingShingle Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
Soares, Diogo Alexandre Marques
Sparus aurata
Dicentrarchus labrax
Aquacultura em jaulas
Modelo de alimentação
Biomassa
title_short Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
title_full Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
title_fullStr Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
title_full_unstemmed Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
title_sort Optimisation of algorithms to predict biomass and size distribution of fish reared in cages, using the Aquanetix production management software
author Soares, Diogo Alexandre Marques
author_facet Soares, Diogo Alexandre Marques
author_role author
dc.contributor.none.fl_str_mv Cabrita, Elsa Alexandra Martins e Silva
Thomaz, Diogo Fernandes
Sapientia
dc.contributor.author.fl_str_mv Soares, Diogo Alexandre Marques
dc.subject.por.fl_str_mv Sparus aurata
Dicentrarchus labrax
Aquacultura em jaulas
Modelo de alimentação
Biomassa
topic Sparus aurata
Dicentrarchus labrax
Aquacultura em jaulas
Modelo de alimentação
Biomassa
description This Thesis aims to optimise the algorithms used to estimate actual biomass and weight distribution in gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) cages by the Aquanetix Software. For this, we first try to understand the practical functioning of a fish farm that uses cages and how can the used procedures affect the collection of data or its veracity. Then, we use the data collected by the company and the observations made on the field in order to attempt the optimization of the algorithms that estimate biomass and weight distribution of the Aquanetix Software. The data parameters analysed were the moving average of the estimated biomass, mortality, density, number of fish and mean weight. Two time periods were tested for the moving average of the estimated biomass, at fourteen and thirty days prior to the first harvest. Between these two periods, the one at thirty days seemed to provide the better biomass estimation. Mortality and density showed to have no apparent influence in the deviations found between the biomass estimations and the total biomass harvested. The number of fish was found to be overestimated in the majority of the studied cages (n=7), with the exception of only cage 109. The mean weight was found to be underestimated in the majority of the studied cages, with the exception of only cage 03. At the end, all proposed goals were achieved. In conclusion, every cage of sea bream studied (n=4) shows an under estimation of the mean weight of fish at first harvest, which in turn leads to an underestimation of the biomass. This suggests that every sea bream cage is currently being under fed, most likely, due to a fault on the feeding model which is probably overestimating the specific feeding rate (SFR) for this species. Alterations should be made to the feeding model in order to resolve this unbalance. The results for the sea bass cages were shown to be more inconclusive since all of the studied cages for this species (n=3) appear to have no common reason to explain the errors found for the estimation of their biomass.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-13
2018
2018-12-13T00:00:00Z
2019-02-22T12:34:52Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.1/12361
urn:tid:202167305
url http://hdl.handle.net/10400.1/12361
identifier_str_mv urn:tid:202167305
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833598703896625152