Handheld Near-Infrared Spectroscopy-Based Intelligent Screening of Allergen-Containing Flour Cross-Contamination in Gluten-Free Flour

Controlling cross-contamination with allergen-containing ingredients is critical for ensuring product integrity and safety. Gluten-free flour is particularly susceptible to cross-contamination by common allergen-containing flours such as wheat, peanut, soybean, and sesame during production and processing. This study aims to develop a rapid screening and quantification strategy for allergen-containing flour cross-contamination in gluten-free flour using handheld near-infrared spectroscopy integrated with multivariate data analysis. A total of 330 gluten-free flour samples were prepared, including non-contaminated controls and allergen-containing flour cross-contaminated samples (1–25%, w/w). Spectral data were collected using a handheld NIR spectrometer. PCA was applied for exploratory data analysis and visualization of sample distribution. SIMCA was used for qualitative classification of cross-contamination presence, followed by PLSR for quantitative prediction of individual allergen-containing flour addition levels. Independent hold-out validation demonstrated 100% accuracy, sensitivity, and specificity for the classification model under the investigation conditions. For quantitative analysis, the PLSR models achieved Rval > 0.96 with low RMSEP values. Overall, the results demonstrate reliable performance and effective discrimination capability under the investigated conditions. This handheld NIR approach would be a rapid, non-destructive screening tool for high-level allergen-containing flour cross-contamination, such as preliminary raw-material screening, in-process monitoring, or rapid screening following potential cross-contact events in gluten-free production.