- Photos: Nanyang Technological University
Professor Chen Xiaodong, Director of Innovative Centre for Flexible Devices (iFLEX) at NTU and the Director of Max Planck – NTU Joint Lab for Artificial Senses, is an award-winning and highly decorated researcher and inventor. His research topics cover interactive materials and devices, integrated nano-bio interfaces, and cyber-human interfaces and systems. He has filed more than 50 patents, nine of which had been licensed for commercial development, and is involved in a multitude of research and industrial projects.
How did the idea come up of an “e-nose” to evaluate food freshness?
The global number of food-borne disease outbreaks has been increasing. There are about 1.5 billion cases reported annually, resulting in three million deaths globally. Since food can be contaminated through improper practices in its value chain, it’s imperative to develop accurate and efficient freshness monitoring to address concerns while minimising wastage. The conventional technique for monitoring meat freshness is through Total Volatile Basic Nitrogen (TVB-N) by Conway’s Method. Despite its high accuracy, this is a destructive test that requires meat grinding, pre-treatment, and titration, which can be inefficient. As such, we came up with the idea to develop a real-time monitoring technique that eliminates the tedious sample preparation process while reducing waste. The result is the invention of an artificial olfactory system that mimics the mammalian nose to assess the freshness of meat non-destructively in real-time with an accuracy of 98.5%, which is deployable across the food supply chain.
What was the biggest challenge in bringing this to fruition?
The biggest challenge was the creation of the barcode reader. This went through rounds of trials to select the sensing materials that can change colour over time as they react with varying types and concentrations of emitted gases during the meat decay process. These result in a unique combination of colours known as the meat’s scent fingerprint. From there, we prepared a large library of colours to train the e-nose to recognise and predict meat freshness, contributing to the final AI-powered freshness monitoring system.
What implications could the e-nose have for the worldwide food industry?
Our invention could address food safety and supply chain transparency through real-time monitoring of food freshness in the global food industry and supply chains. For instance, a food safety officer could use our AI-powered e-nose at any point of the food value chain for almost instantaneous quality control. Moreover, food companies and their distribution partners can manage fresh perishables more efficiently, devising market strategies to drive change towards a safer and more sustainable food future.
What other possibilities can you see in its use?
The e-nose could also be deployed for other food including non-meat products, by evaluating and tweaking its sensing materials and barcode colours accordingly.
What scientific trends will most impact on the food industry in coming years?
I think data science and analytics will continue to have the most impact. Applications in the food industry include predicting shelf-life, providing better supply-chain transparency, measuring key quality attributes, safeguarding food safety, and preventing cross-contamination.