Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Improved feed utilisation in cage aquaculture by use of machine vision

Thesis (MScEng (Process Engineering))--Stellenbosch University, 2008.

Saved in:
Bibliographic Details
Main Author: Dunn, Zelda
Other Authors: Aldrich, C.
Format: Thesis
Language:English
Published: Stellenbosch : Stellenbosch University 2008
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1867614015864176640
access_status_str Open Access
author Dunn, Zelda
author2 Aldrich, C.
author_browse Aldrich, C.
Dunn, Zelda
author_facet Aldrich, C.
Dunn, Zelda
author_sort Dunn, Zelda
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MScEng (Process Engineering))--Stellenbosch University, 2008.
format Thesis
id oai:scholar.sun.ac.za:10019.1/2824
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:45:19.124Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2008
publishDateRange 2008
publishDateSort 2008
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/2824 Improved feed utilisation in cage aquaculture by use of machine vision Dunn, Zelda Aldrich, C. De Wet, L. F. Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering. Automated feeding Automation of aquaculture systems Fish feeding behaviour Aquaculture Dissertations -- Process engineering Theses -- Process engineering Thesis (MScEng (Process Engineering))--Stellenbosch University, 2008. With the harvesting of fish and other aquatic organisms from natural waters having reached its upper limit, aquaculture is vital in providing for the ever increasing demand for fishery products (Boyd, 1999). Not surprisingly, aquaculture has seen considerable growth over the last decade or more. With the rising importance of aquaculture, there is an increased emphasis on cost and reducing of waste for environmental reasons. Therefore, attempts to automate or increase efficiency of feeding are constantly being explored. On an aquaculture unit approximately 60% of all costs are for feed; therefore high quality feeding management is essential for all fish farmers. The rainbow trout farm at Jonkershoek Aquaculture Research farm near Stellenbosch currently have a feeding management system which makes use of traditional hand feeding. Handfeeding is not considered optimal, as the feed intake or pellet loss is not closely monitored resulting in higher operating costs. Automation of aquaculture systems will allow the industry to produce closer to markets, improve environmental control, reduce catastrophic losses, minimize environmental regulation by reducing effluents, reduce production costs and improve product quality. The history of automated control in aquaculture has been brief; most of the systems have been custom-designed, personal computer systems. A very popular approach for an automated feeding system is to monitor waste pellets beneath the feeding zone of the fish, with a feedback loop that can switch off the feeder if this waste exceeds a predetermined threshold. Other approaches use hydroacoustics to monitor waste pellets or demand feeders have also been implemented. These approaches however are not considered optimal as automatic feeders do not necessarily ensure optimal feed intake. Social dominance using demand feeders does not allow even feeding distribution among all sizes of fish. In this project it was investigated whether an automated feeding system can be developed based on fish feeding behaviour. After facing problems with poor visibility at the Jonkershoek Aquaculture farm near Stellenbosch, video data were acquired from the Two Oceans Aquarium in Cape Town. Since it was a feasibility study, the focus was rather to investigate whether a predictive model could be generated for fish feeding behaviour in a more ideal environment which can form a foundation for further research. The well-established multivariate methods of principal components Masters 2008-11-14T10:58:47Z 2010-06-01T08:59:19Z 2008-11-14T10:58:47Z 2010-06-01T08:59:19Z 2008-12 Thesis http://hdl.handle.net/10019.1/2824 en Stellenbosch University application/pdf Stellenbosch : Stellenbosch University
spellingShingle Automated feeding
Automation of aquaculture systems
Fish feeding behaviour
Aquaculture
Dissertations -- Process engineering
Theses -- Process engineering
Dunn, Zelda
Improved feed utilisation in cage aquaculture by use of machine vision
title Improved feed utilisation in cage aquaculture by use of machine vision
title_full Improved feed utilisation in cage aquaculture by use of machine vision
title_fullStr Improved feed utilisation in cage aquaculture by use of machine vision
title_full_unstemmed Improved feed utilisation in cage aquaculture by use of machine vision
title_short Improved feed utilisation in cage aquaculture by use of machine vision
title_sort improved feed utilisation in cage aquaculture by use of machine vision
topic Automated feeding
Automation of aquaculture systems
Fish feeding behaviour
Aquaculture
Dissertations -- Process engineering
Theses -- Process engineering
url http://hdl.handle.net/10019.1/2824
work_keys_str_mv AT dunnzelda improvedfeedutilisationincageaquaculturebyuseofmachinevision