Developed by Ekrem Misimi, a research scientist at SINTEF Fisheries and Aquaculture Research, the system that combines machine vision with pattern recognition methods which feed geometrical descriptions of the size, colour and shape of salmon into a PC. The resulting computer analysis then calculates the fish grade according to its quality. He has recently defended his doctoral thesis on accurate mathematical descriptions that enable machines to sort fish according to quality.
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| The fish-processing industry currently grades salmon by hand. Consumers prefer salmon fillets that are regular in quality – like this one. (Photo: SINTEF Fisheries and Aquaculture Research) |
Most salmon processers employ manual sorting, but if sensors took over this job, significant savings and set up costs could be avoided.
“The Norwegian fish-processing industry has been slow to introduce modern technology, and the production costs of a kilo of salmon in this country are an average of 5 – 10 kroner higher than in countries that compete with us. Exports of processed salmon are also still low, so the industry has a lot to gain by adopting these new methods,” explains Misimi.
Automation Could Improve Consistency
The new method simply takes photos of the colour cards and stores the values obtained, so that the colour of a fillet can be compared with values from the table. This objective method agrees well with the methods that human being use to analyse colours, and is also rapid and does not require physical contact with the fish.
Today, fish are graded manually by employees who assess their shape, colour and any surface injuries, since consumers demand salmon fillets that are fresh and regular in colour and shape. This can be difficult to achieve using current technology.
Colour is an important indicator of the quality of salmon fillets, and at present, a special ruler and a colour-matching card are used to sort the fillets that fall within approved limits from those that have to be rejected.
If the salmon was stressed at slaughter, it tends to stiffen rapidly, and when it is stored on ice the fillets can change colour and shape. These stressed fillets cannot be processed until they have passed through the stage of rigor mortis after two or three days, and meanwhile the product is losing freshness.
There are also issue relating to blood in the stomach cavity which is common cause of downgrading at the processing stage.
“Machine vision and image analysis enables us to sort fish into production, ordinary and superior classes, while any revealing blood in the stomach cavity, with an accuracy of 90 percent, says Misimi.
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