Detecting salmon spoilage with filter paper sensor technology

Flinders University researchers have constructed and tested a solid-state fluorescent sensor loaded on filter papers that can instantly and accurately measure the rate of spoilage in Atlantic salmon — and can easily be applied to other seafood.

As spoilage can account for at least 10% of all seafood production, the device could provide cost benefits for the seafood industry.

According to Flinders University Professor of Aquaculture Jian Qin, who led the study with Flinders colleague Professor Youhong Tang, the simple device could become commercially viable and enable real-time monitoring of spoilage in seafood to ensure food safety.

The core of the new spoilage analysis technology is understanding that biogenic amines (BA) have an important physiological function of living cells, but a high level of BA in seafood has an adverse impact on human health and can cause food poisoning.

Therefore, BA have become important indicators for the evaluation of food freshness and edibility — and reading these amines can be done via a simple and cost-effective method using filter papers loaded with an AIEgen, such as dihydroquinoxaline derivative (H + DQ2), to monitor salmon spoilage.

The research found that as spoilage in the salmon samples increased, triggering more amine vapours, so too did the intensity of the readings on the treated filter papers. Results from the study have been published in the journal Food Chemistry.

"This study provides a quick and simple way for testing amine vapour from fish and provides baseline information for developing an easy-to-use, onsite method to evaluate seafood quality for customers," said Professor Tang, from Flinders' Institute of NanoScale Science and Technology and Medical Device Research Institute.

The research team will now do further optimisation tests on the paper strips and the AIEgen loading to provide a more robust solution for daily usage towards commercial applications.

The team also wants to align the AIEgen-loaded paper strips with smartphone apps to transfer information for quantitative evaluation.

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