eng Enviro Research Publishers Current Research in Nutrition and Food Science Journal 2347-467X 2322-0007 2025-11-20 13 3 1256 1267 10.12944/CRNFSJ.13.3.17 24883 article Raluca Cimpean 1 Daniel Berean 2 Anca Becze 3 Nastasia Belc 4 Sorin Daniel Dan 1 Faculty of Veterinary Medicine, Department of Animal Breeding and Food Safety, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Cluj-Napoca, Romania Faculty of Veterinary Medicine, Department of Reproduction, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Cluj-Napoca, Romania Research Institute for Analytical Instrumentation, National Institute for Research and Development of Optoelectronics INOE 2000, Cluj-Napoca, Romania Food Bioresources Research Division, National Institute of Research and Development for Food Bioresources (IBA Bucharest), Bucharest, Romania Nutritional profiling of fast-food products is essential for both consumer transparency and industrial quality control, yet conventional methods such as Kjeldahl, Soxhlet, and gravimetric assays are time consuming and require specialized laboratories. Near-infrared (NIR) spectroscopy offers a rapid and non-destructive alternative, but its reliability in complex food matrices such as burgers and pizzas remains underexplored. In this study, four types of burgers (10 samples each, three replicates) and thirteen types of pizzas (three replicates each) were analyzed using both reference methods and a Tango FT-NIR spectrometer to determine protein, fat, carbohydrates, sugars, ash, dietary fiber, and dry matter. Results indicated excellent agreement between NIR and classical methods for major components, including protein, fat, carbohydrates, and dry matter, with no statistically significant differences (p > 0.05). However, sugars showed systematic deviations, with overestimation in burgers (p < 0.05) and underestimation in pizzas (p < 0.01). Ash content also differed significantly in pizzas (p < 0.05), while dietary fiber showed the largest discrepancy, with NIR consistently underestimating values (p < 0.05). Despite these limitations, NIR displayed high repeatability, with standard deviations below 0.2% for most parameters. These findings confirm NIR as a robust and efficient tool for routine nutritional screening in fast food, though reference methods remain indispensable for sugars and dietary fiber. https://www.foodandnutritionjournal.org/volume13number3/comparative-evaluation-of-near-infrared-spectroscopy-and-classical-reference-methods-for-nutritional-analysis-of-fast-food-products/ Fast-Food Analysis Food Quality Control Near-Infrared Spectroscopy Nutritional Composition Reference Methods