Intelligent feeding control methods in aquaculture with an emphasis on fish: a review
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Date
2017-08
Journal Title
Journal ISSN
Volume Title
Publisher
Wiley Publishing Asia Pty Ltd
Abstract
In aquaculture, feeding is the primary factor determining efficiency and cost, so it
is important to know when to stop feeding to maximize efficiency. Until now, fish
feeding has been mostly based on artificial discrimination, which is usually timeconsuming
and laborious. In recent years, intelligent feeding control according to
changes in behaviour and growth status has gained increasing attention. This
approach involves many methods as well as monitoring and feedback equipment
and can automatically determine the feeding demands of fish. This review summarizes
the development of intelligent feeding control methods, such as mathematical
models, acoustic methods and computer vision, in aquaculture over the
past three decades. All methods have unique application scenarios and models for
the culture to which they are most suitable, and the advantages and disadvantages
of each method in the laboratory as well as in pond, cage and recirculating aquaculture
systems are analysed. Studies show that improvements in sensor accuracy
and hardware and software processing speed have promoted the development of
new technologies and methods, providing effective or potential support for intelligent
feeding control. However, its accuracy and intelligent are still need to be
improved to meet the needs of actual feeding scenarios. Through close collaborations
between engineers and fish behaviourists, the feeding machine and system
will be more elaborate and precise on the basis of the above methods, and the
level of intelligence will be further improved.
Description
Keywords
acoustic, aquaculture, computer vision, feeding behaviour, intelligent feeding control, mathematical model