A team of scientists from Nanyang Technological University, Singapore (NTU Singapore) in collaboration with scientists from Jiangnan University, China, and Monash University, Australia recently came forward with an electric-nose that scans the barcode on fish, chicken, and beef.
The e-nose called PEGS works by reading a barcode that reacts with gases produced by the decaying process, and the barcode's reactivity to these gases is fairly similar to how the mammal olfactory system works.
To make it a portable process, the team has developed a smartphone app that can yield results in about 30 seconds and has 98.5% accuracy.
The findings are published in Advanced Materials.
What's the use?
The e-nose shows potential in reducing food waste, it can be turned into something that end-consumers can use. Prof. Chen Xiaodong, director of the Innovative Centre for Flexible Devices at NTU says, "These barcodes help consumers to save money by ensuring they do not discard products that are still fit for consumption, which also helps the environment. The biodegradable and non-toxic nature of the barcodes also means they could be safely applied in all parts of the food supply chain to ensure food freshness."
The team has filed a patent and is now collaborating with a Singaporean agribusiness company to expand its use into other perishables.
In a mammalian olfactory system, gases produced by rotting meat bind to certain receptors in the nose, and this generates signals for our brain to decode. Then, the brain gathers these impulses and organizes them into patterns, allowing mammals to pick out rotting odors.
Each bar in the barcode acts as a receptor, they are made of chitosan (a type of complex sugar) embedded on a cellulose derivative. They are loaded with different types of dye. Then these dyes react with the gases that result from the rotting and change in color according to concentrations of gases.
How it was developed
Scientists developed a classification system with three labels: fresh, less fresh, and spoilt. It's based on an international standard system. For five days, they measured the levels of ammonia and bioamines found in fish packages wrapped in clear-PVC and stored at 40°F (4°C). They then read the barcodes glued in the inner side of the PVC wrap that didn't come into contact with the fish.
The researchers explain that they utilized a type of algorithm called "deep convolutional neural network" and trained it with images of different barcodes to identify patterns associated with different smell prints.
To gauge e-nose's accuracy, they took six commercially packed meat packages and kept it at 77°F (25°C) over 48 hours while taking measurements at different time intervals.
The paper reads that they were 100% accurate in identifying spoiled meat and 96-99% accurate in fresh and less fresh meat.
Prof. Chen said they're aiming towards a "broadly applicable new platform for food quality control" and concluded by saying, "While e-noses have been extensively researched, there are still bottlenecks to their commercialization due to current prototypes’ issues with accurately detecting and identifying the odor. We need a system that has both a robust sensor set-up and a data analysis method that can accurately predict scent fingerprints, which is what our e-nose offers."