Rourkela: Researchers from the National Institute of Technology (NIT) Rourkela have developed an Internet of Things (IoT)-enabled smart device to monitor the quality of ingredients in processed food. The colourimeter, developed in partnership with teams from the University of the Philippines Los Banos, Philippines, tracks colour and temperature changes in real-time, making it especially useful for studying oleo gels — fat alternatives used in processed foods. Many processed foods rely on solid fats for texture and stability, but these often contain unhealthy trans and saturated fats, increasing the risk of cardiovascular diseases and obesity.
To address this, the food industry has been exploring oleo gels, which convert liquid oils into a gel-like form by using additives such as waxes, plant-based polymers, or other structuring agents and offer a healthier alternative.
However, they are prone to instability due to oil migration resulting from poor crystallisation, affecting food quality. Traditional methods to assess oleo gels’ stability require expensive lab equipment and skilled technicians, making quality control difficult for small food manufacturers. To solve this problem, the research team developed a cost-effective device that detects subtle colour changes in oleo gel during crystallisation. This colourimetric approach provides an effective way to monitor oleo gel stability without requiring complex instrumentation. The integration of IoT technology allows for remote monitoring, data logging, and automated analysis, making it suitable for both research and industrial applications. “This smart device has the potential to improve food safety and quality control processes significantly. In addition to oleo gels, it could be used to monitor various other food products, where colour and temperature play a crucial role in determining the properties and stability of the food products,” said lead researcher Professor Kunal Pal. “In addition to this, the device is also able to detect the freshness of several food products. For example, dairy products, bakery products, confectionery, and plant-based meat substitutes could all benefit from real-time quality assessment using this technology,” Pal added.
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The research team also includes PhD Scholar Deblu Sahu; Assistant Professor Sirsendu Sekhar Ray, North-Eastern Hill University, Shillong; Assistant Professors Sivaraman Jayaraman and Bala Chakravarthy from NIT Rourkela, and Professor Floirendo Flores, Institute of Food Science & Technology, University of the Philippines Los Baños. In the paper, published in the Journal of Food Engineering, the research team envisions that this device will not only enhance food science research but also empower food manufacturers to implement better quality control practices at a lower cost by providing continuous data. The team has also secured a patent for the technology (Patent No. 560281, Application No. 202231075092). At the lab scale, the estimated cost of the device is approximately `50,000, which is lower than that of commercially available devices. As a next step, the research team is trying to detect spoilage in food products early by integrating Artificial Intelligence (AI) into the device to minimise food wastage.