Mri-guided predictive modeling for moisture migration control in reduced-sugar confectionery
An MRI-guided predictive tool that maps water redistribution and local material state in reduced-sugar confectionery, identifies the mechanism limiting moisture migration, and selects barrier or formulation changes to delay texture loss. The validated design rule targets at least 20% less moisture accumulation in the vulnerable layer while preserving texture.
Overview
Reduced-sugar confectionery often loses texture when moisture migrates between layers, causing sogginess, hardening, or loss of crispness. Conventional estimates of water movement assume steady material properties, but sugar replacers such as polyols and soluble fibers can change how the matrix absorbs water and relaxes over time, making those estimates unreliable. This research develops an MRI-guided predictive tool that tracks water redistribution and local material state in intact products, identifies which factor — bulk mobility, structural relaxation, or an interface — limits migration, and then selects a barrier or formulation change to delay texture failure. The result is a validated design rule for formulating and protecting reduced-sugar confectionery.
Technical specifications
The approach combines non-destructive MRI moisture mapping with independent structural and texture measurements to build a mass-conserving model of structure-coupled moisture migration.
Key features:
- MRI maps water redistribution across layered confectionery prototypes in intact form, calibrated against local assays
- Structural characterization using sorption, thermal, microscopy, and co-registered micro-CT to detect where structural change alters migration
- A mass-conserving model that treats evolving matrix state as a driver of transport, distinguishing bulk mobility, structural relaxation, and interface-limited migration
- Prospective validation against Fickian baselines using a withheld formulation and storage history
- Model-driven selection of a barrier or formulation change, tested against matched controls under multiple humidity and temperature challenges
Target performance is at least 20% reduction in moisture accumulation in the vulnerable layer while preserving texture.
Technology readiness level
The project is at an early research stage. During the first months, layered sucrose, polyol, and polyol/fiber prototypes will be built and MRI moisture maps calibrated against local assays. Subsequent phases will follow specimens under two relative humidity levels and constant versus cycling temperature, fit and freeze the coupled model, and validate its predictions on an unseen formulation. The final phase tests the model-selected intervention against matched controls. The validated deliverable will be a design rule ready for industry evaluation in reduced-sugar confectionery development.
About Cornell University
Cornell University is a comprehensive private, land-grant research university with campuses in Ithaca and New York City, combining significant scale with cross-disciplinary breadth. Industry connects through open-access user facilities and prototyping labs, pilot-scale testbeds, and a research and technology park that provide pathways from discovery to demonstration. A statewide extension network and integration with a major hospital system enable real-world deployment, while a graduate campus embedded in New York City’s tech corridor provides direct access to startups, venture investors, and corporate R&D teams. Research is supported by competitive federal funding from agencies such as the National Science Foundation, National Institutes of Health, the Department of Energy, and the U.S. Department of Agriculture. A dedicated technology transfer office streamlines IP management, licensing, startup formation, and corporate partnerships across campuses.
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