Implementing Topological Data Analysis for Monitoring Mass Transfer during Vacuum-Assisted Osmotic Dehydration of Apples.

This study applies topological data analysis (TDA) to real-time experimental images of grape juice impregnation in apple samples with the goal of monitoring and quantifying the evolution of mass transfer under different processing conditions. We monitored the effective diffusivity () of water, solutes, and biocompounds during osmotic procedures using 40, 50, and 60 °Brix grape juice concentrate (GJC) by computing a topological descriptor of the real-time images known as the Euler characteristic curves (ECC). Osmotic procedures were osmodehydration (OD, absolute pressure, = 598 mmHg) and OD assisted with vacuum (ODVP, = 498 mmHg/10 min). The modified slope method for cubic geometry estimated considering shrinkage and time evolution with > 0.80. Results show that samples treated with OD have higher shrinkage (20-25%) compared to those treated with ODVP. Water was greater with ODVP and increased ( ≤ 0.05) at higher GJC concentrations. Solutes and total monomeric anthocyanins were higher in OD and decreased with an increasing GJC concentration. Our TDA of real-time images revealed a double-peak structure of the ECC, which is characteristic of diffusion processes. We also found a simple topological metric (the difference between the maximum and minimum values of the ECC) that correlates positively with the diffusion coefficient ( > 0.7858) in OD experiments and negatively ( < -0.9567) in ODVP at 60 °Brix. The TDA also indicated that the OD treatment at 40 °Brix resulted in uniform impregnation and redistribution of solutes within the impregnated samples after reaching osmotic equilibrium. The proposed TDA approach opens the door to nonintrusive, image-based monitoring of impregnation experiments, enabling high-throughput screening.