Researchers at McGill University have developed an eco-efficient, user-friendly technology that quickly measures the antioxidant content of maple syrup. The innovative method contributes to increasing transparency about a health-related aspect of the syrup's nutritional value and allows for on-site quality testing without the need for costly lab assessments.
"Our new technology offers a practical solution for both producers and consumers. Producers can evaluate the antioxidant content of maple syrup on-site, enhancing transparency and quality control," said Li Xiao, PhD student in the Department of Food Science and Agricultural Chemistry and lead researcher on the project.
These evaluations can be shared with customers, allowing them to make decisions based on the levels of antioxidants in the maple syrup. Antioxidants can be beneficial in reducing health risks. When consumed, they scavenge certain free radicals generated in the human body and reduce the damage caused by oxidation.
The researchers developed a simple, rapid, accurate approach combining artificial intelligence and Raman spectroscopy, an advanced technology in which a device shines a light on a sample and reads the unique way the molecules vibrate, to determine whether maple syrups contain varying levels of antioxidants. This method allows for complete testing within one minute, making it faster than traditional chemical assays that can take several hours, or even days.
"Traditional detection methods for antioxidant capacity are usually labour-intensive and less eco-friendly, as they require complicated sample preparation and the use of chemical reagents," said Xiao.
The researchers say this technology could pave the way for testing the antioxidant content of various food products, not just maple syrup.
The team confirmed that the antioxidant capability of maple syrup cannot be accurately assessed based solely on its colour. They also demonstrated that a Raman spectroscopy can be used effectively to evaluate the antioxidant activities of syrup.
The deep-learning artificial intelligence models demonstrated high accuracy in predicting antioxidant profiles.
"This method allows for real-time assessment of antioxidant profiles of maple syrup in the field," said Dr. Xiaonan Lu, Professor in the Department of Food Science and Agricultural Chemistry and corresponding author of this work.
The development of this technology is particularly relevant for the food industry, where demand for transparency and health-related information is increasing. The method offers an efficient solution for testing maple syrup quality, supporting both small-scale producers and large manufacturers in evaluating their products' antioxidant levels.
About the study
Rapid determination of total phenolic content and antioxidant capacity of maple syrup using Raman spectroscopy and deep learning by Li Xiao, Jinxin Liu, Marti Z Hua and Xiaonan Lu, was published in Food Chemistry.
