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Improved feed utilisation in cage aquaculture by use of machine visionDunn, Zelda 12 1900 (has links)
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
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