A Comprehensive Study of Air-Frying and Deep-Fat Frying of Tortilla Chips: Mass and Heat Transfer, Physicochemical Properties, Microstructural Analysis, and Acrylamide Formation

Air frying (AF) has emerged as a promising alternative to deep-fat frying (DFF) for producing tortilla chips with improved quality attributes. This study integrated real-time kinetics of mass and heat transfer, color development, and shrinkage with acrylamide formation, texture, and microstructural data obtained during AF (140–170 °C) and DFF (170 °C) processing of tortilla chips. Effective diffusivity coefficients increased with temperature from 1.22 × 10−9 to 3.84 × 10−9 m2/s, apparent thermal diffusivity from 2.04 × 10−10 to 8.63 × 10−9 m2/s, and the browning index rate constant (k) from 0.059 to 0.104 min−1. Arrhenius-type relationships for the effective moisture and apparent thermal diffusivity coefficients and the browning index yielded empirical equations with activation energies from 22.25 to 67.42 kJ/mol, supporting equipment design, process optimization, and preliminary industrial-scale estimations. AF at 170 °C for 15 min lowered acrylamide content 1.7-fold (37.59 μg/kg) relative to DFF for 2 min (64.57 μg/kg). Overcooking at 170 °C for 30 min produced a 7.3-fold increase in acrylamide content, from 34.07 to 247.17 μg/kg, compared with optimal AF conditions. Acrylamide content correlated strongly with the browning index through a second-order model (R2 = 0.97). Microstructural analysis revealed temperature-dependent starch gelatinization, crust formation, crack development, and fat distribution patterns. AF also had lower fat content (6.10%) than DFF (27.22%). Factorial design and principal component analysis integrated sixteen response variables, distinguishing optimal from overcooked conditions as distinct quality classes suitable for computer vision-based process control. Overall, AF tortilla chip processing yields superior quality and advantages over DFF. Industrial relevance The empirical Arrhenius equations derived for effective moisture diffusivity, apparent thermal diffusivity, and browning index provide preliminary baseline engineering data useful for understanding cooking kinetics and supporting future equipment design and scaling studies from laboratory to industrial scale. The 4.5-fold reduction in oil content and 7.3-fold reduction in acrylamide compared to DFF support AF as a viable industrial process for producing tortilla chips with improved nutritional characteristics. The integration of real-time thermographic and digital imaging with transport phenomena demonstrates the feasibility of implementing computer vision systems in AF equipment to prevent overcooking, control acrylamide formation, and ensure consistent product quality across household, restaurant, and industrial scales.