Researchers have conducted a preliminary study on the potential use of near-infrared (NIR) and Raman spectroscopy for predicting ice cream mix viscosity. The study highlights the promising performance of NIR spectroscopy and serves as a starting point for further investigations into in situ application of these analytical tools in the ice cream manufacturing process.
Many of us may not think about the viscosity of the ice cream we consume regularly, but it is usually an important indicator of the quality of the ice cream (1). The viscosity can affect certain characteristics about ice cream, including its texture (1). But how do we measure viscosity, and what is the best way to do so?
strawberry, vanilla, chocolate ice cream woth waffle cone on marble stone backgrounds | Image Credit: © ahirao - stock.adobe.com
In a recent study published in Applied Spectroscopy, researchers from the University of Manchester and Unilever R&D Colworth Science Park set out to answer this question (1). In particular, they investigated whether spectroscopic techniques such as near-infrared (NIR) and Raman spectroscopy can assess the viscosity of ice cream mixes (1). The results are encouraging, and because partial least squares regression (PLSR) can develop predictive models for viscosity analysis, the researchers were able to determine to what extent NIR and Raman spectroscopy can be used feasibly as analytical tools to assess viscosity (1).
Traditionally, viscosity measurements have been conducted offline using methods like rheometry (1). However, this study focused on developing PLSR models by analyzing spectral data obtained from NIR and Raman spectroscopic methods (1). The first step was to create a range of viscosity values. To accomplish this step, ice cream mixes were prepared with varying fat content, and they were also subjected to different homogenization conditions (1). The individual PLSR models demonstrated some predictive ability and outperformed the integrated model derived from data fusion (1).
The study results revealed that NIR spectroscopy was the better technique over Raman to be used for viscosity analysis (1). This was because NIR spectroscopy exhibited lower prediction errors and higher coefficients of determination (1). However, it is important to note that additional factors, such as implementation limits, can influence which method should be utilized (1).
Although this study provides a preliminary comparison of spectroscopic methods for quantitatively assessing the viscosity of aged ice cream mixes, it also serves as a starting point for future in situ application studies. The potential of NIR and Raman spectroscopy as nondestructive and real time techniques holds promise for enhancing the efficiency of viscosity analysis in the ice cream manufacturing process (1).
By exploring these spectroscopic tools, researchers aim to enable more rapid and accurate viscosity measurements, leading to improved process control and the ability to adjust formulations on the fly, ultimately enhancing the quality and consistency of ice cream products in the food industry (1).
(1) Cruz, C.; Arafeh, A.; Martin, P. A.; Fonte, C. P.; De Simone, A.; Oppong, F. K.; Jeatt, W.; Rodgers, T. L.Assessment of Near-Infrared and Raman Spectroscopy as Analytical Tools to Predict Viscosity of Ice Cream Mixes. Appl. Spectrosc. 2023, ASAP. DOI: 10.1177/00037028231176824
AI Boosts SERS for Next Generation Biomedical Breakthroughs
July 2nd 2025Researchers from Shanghai Jiao Tong University are harnessing artificial intelligence to elevate surface-enhanced Raman spectroscopy (SERS) for highly sensitive, multiplexed biomedical analysis, enabling faster diagnostics, imaging, and personalized treatments.
Artificial Intelligence Accelerates Molecular Vibration Analysis, Study Finds
July 1st 2025A new review led by researchers from MIT and Oak Ridge National Laboratory outlines how artificial intelligence (AI) is transforming the study of molecular vibrations and phonons, making spectroscopic analysis faster, more accurate, and more accessible.
AI and Dual-Sensor Spectroscopy Supercharge Antibiotic Fermentation
June 30th 2025Researchers from Chinese universities have developed an AI-powered platform that combines near-infrared (NIR) and Raman spectroscopy for real-time monitoring and control of antibiotic production, boosting efficiency by over 30%.