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A research team has developed a rapid and cost-effective method for detecting multiple allergens in gluten-free flour using near-infrared spectroscopy and multivariate chemometric analysis.
Detecting allergenic ingredients in food products is a critical concern for consumers, regulatory agencies, and the food industry. To address this challenge, researchers at the University of Illinois at Urbana-Champaign have leveraged near-infrared (NIR) spectroscopy and multivariate analysis (MVA) to develop a rapid and cost-effective method for detecting multiple allergens in gluten-free flour.
Traditional methods for allergen detection, such as DNA and protein-based techniques, are time-consuming, labor-intensive, and require skilled technicians. In this study, published in the Journal of Food Composition and Analysis, a benchtop NIR system and a filter-based NIR spectrometer were employed as efficient tools for allergen detection (1).
The team utilized partial least squares regression (PLSR) in combination with various spectral pre-processing methods to establish an accurate predictive model. By analyzing the NIR spectra, only nine dominant wavelengths were identified as key indicators for allergen detection. Based on these wavelengths, the researchers developed a highly precise PLSR model (R2p = 0.99, RMSEP = 3.25%) for detecting multiple allergenic ingredients in gluten-free flour.
The efficacy of the selected nine wavelengths was further compared to a similar model using filter-based NIR data with only 10 spectral bands. The PLSR model based on the selected wavelengths outperformed the filter-based NIR model (R2p = 0.96, RMSEP = 6.32%), demonstrating superior predictive accuracy.
The study highlights the effectiveness of NIR spectroscopy combined with MVA in rapidly identifying multiple allergenic ingredients in gluten-free flour. By utilizing a reagent-free approach, this method offers a streamlined and cost-effective solution for food allergen testing. Additionally, the research suggests the potential for developing a low-cost, miniature sensor that can simultaneously detect multiple allergens using the selected wavelengths.
This innovative technique has significant implications for food safety, allergen labeling, and consumer health. It can provide manufacturers and regulatory agencies with a practical tool to ensure accurate allergen information on food labels, enhancing transparency and enabling individuals with food allergies to make informed choices.
The study sheds light on the promising application of NIR spectroscopy and multivariate analysis in allergen detection, offering a promising avenue for further research and development in the field of food safety.
(1) Wu, Q.; Oliveira, M. M.; Achata, E. M.; Kamruzzaman, M.Reagent-free detection of multiple allergens in gluten-free flour using NIR spectroscopy and multivariate analysis. J. Food Comp. Anal. 2023, 120, 105324. DOI: 10.1016/j.jfca.2023.105324