Chemometric techniques offer powerful tools for analyzing complex datasets related to food science. I used Multivariate Curve Resolution (MCR) to decompose Raman spectroscopy data and track crystallization dynamics. In another case, I employed modeling and clustering methods to identify patterns and group behaviors associated with the increase of extractable fat in whole milk powder (WMP) during storage. These tools enabled data-driven interpretation of physicochemical changes and supported predictive analysis.

Image analysis is a powerful method for quantifying structural features in food systems. It enables monitoring of time-dependent changes and the identification of patterns in physical properties. The projects below demonstrate applications such as assessing particle size distribution, morphology, and evaluating milk powder wettability and solubility.

I applied Confocal Laser Scanning Microscopy (CLSM) with selective fluorescent labeling to visualize food microstructure. In these images, lipid fractions were labeled green and protein structures red, allowing clear observation of component distribution.

I employed Scanning Electron Microscopy (SEM) to visualize milk powder surface morphology and monitor crystallization-induced structural changes at high resolution, revealing alterations in particle shape, roughness, and microstructural integrity.

The Angle of Repose is a widely recognized parameter for evaluating the flowability of powdered materials. By applying image capture and post-processing, I quantified the cone angles of milk powder to assess flow behavior and detect physical changes due to formulation or storage.

I used 3D printing techniques to create customized experimental setups. The images below showcase a built-up petridish shelf, specifically designed for a jar container, and a layered holder enabling the separation of powder samples.