Metabolic food matrix design for healthy weight management in companion animals
A metabolically structured food matrix approach for pet food that controls nutrient release during digestion using macronutrient interactions, potentially enhancing satiety signaling (GLP-1 and PYY) and supporting health...
Thermomechanical vacuum processing for removing compounds from coconut water
A Jet cooking thermomechanical process that removes low molecular weight aromatic compounds from coconut water to reduce rancidity and lipid oxidation, while preserving high molecular weight compounds responsible for cha...
Hybrid bio-polymer material for biodegradable food packaging skin layers
A hybrid bio-polymer combining corn starch, plant protein, and PLA developed through steam injection and extrusion processes. Designed as a biodegradable skin layer for food packaging with improved mechanical and barrier...
Stabilized creatine delivery via buffered gel systems
Introducing a high-solids gel system designed to stabilize creatine in food applications. This innovative matrix uses hydrocolloids and a citrate buffer to control pH and reduce degradation, offering a scalable, cost-eff...
Structured starch-bioactive energy matrix for sustained energy
The Structured Starch-Bioactive Energy Matrix (SBEM) is an innovative food-grade ingredient system engineered to deliver sustained physical and mental energy. It integrates slow-digestible starch, plant proteins, and mic...
Starch-based materials for enhancing shelf-stable pasta products
This innovative solution uses modified starches to improve pasta's shelf stability, texture, and nutritional profile, reducing reliance on chemical stabilizers. It employs annealing and heat-moisture treatments to enhanc...
Optimizing water dynamics in potato processing
This research focuses on reducing water carryover in potato slices during processing by optimizing pre-frying treatments and drying conditions. The goal is to improve frying efficiency, reduce oil absorption, and enhance...
Predictive machine learning for resilient corn hybrids
Utilizing machine learning to predict the performance and resilience of modern corn hybrids by analyzing molecular, structural, and chemical transformations to optimize breeding strategies for future climates.
Results may appear later and can be imperfect.
Results may appear later and can be imperfect.
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