Non-Contact Characterization of TPA-like Texture Properties of Gel-Based Soft Foods Using a Controlled Airflow-Laser...

Texture characteristics are critical quality evaluation indicators for soft foods. Traditional texture profile analysis (TPA) relies on probe-sample contact and may cause irreversible structural damage, limiting its application in nondestructive or online detection. In this study, a non-contact and nondestructive Controlled Airflow-Laser Texturemeter (CAFLT) system was developed to achieve rapid multi-parameter texture characterization. The system integrates programmable airflow loading with laser displacement sensing to implement a TPA-like double-cycle loading protocol, simultaneously acquiring time-applied airflow pressure (T-AP) and time-displacement (T-D) responses. Gelatin-maltose composite gels with graded Bloom strengths (CL50-CL250) were used as model samples. Texture-related descriptors were extracted using a dual-curve feature framework and compared with traditional TPA measurements. The CAFLT system produced a double-peak response pattern resembling that of traditional TPA and showed clear monotonic trends with increasing gel strength. Hardness_CAFLT exhibited a strong correlation with the reference TPA hardness value (r = 0.97). In addition, Gumminess_CAFLT showed a positive association with traditional gumminess (r = 0.87), but should be interpreted within the CAFLT-specific loading framework. Multivariate principal coordinates analysis further demonstrated clear multivariate discrimination among samples. Additionally, the time-domain descriptor t_Peak1 showed a strong power-law relationship with Bloom strength (R2=0.96), indicating enhanced sensitivity to mechanical differences under small-deformation conditions. Overall, the CAFLT system provides a feasible approach for non-contact, nondestructive, and quantitative texture evaluation of soft foods, and shows strong potential for real-time quality monitoring and intelligent food inspection.