Influence of Multi-Speckle Diffusing Wave Spectroscopy data-acquisition and data-analysis parameters during in-situ monitoring of acid-induced milk gelation

Multiple Scattering Diffusing Wave Spectroscopy (MS-DWS) is a powerful technique for characterizing the dynamic behavior of colloidal systems in a non-invasive and real-time manner. However, the accuracy and reliability of MS-DWS measurements depend significantly on the choice of data-acquisition parameters and data processing. Using acidified whole milk as a well-defined colloidal system, the impact of various data-acquisition parameters on the derived microrheological parameters such as the Elasticity index (EI), Macroscopic Viscosity Index (MVI) and Fluidity Index (FI) was shown. Furthermore, the effect of different data-processing approaches, including different fitting strategies and the identification of data segments most relevant for accurately calculating these microrheological parameters, was assessed. By analyzing the effects on the derived parameters, the findings provide practical guidelines for selecting optimal MS-DWS parameters and processing methods to enhance measurement accuracy and reliability. This work advances the in-depth understanding of the MS-DWS methodology and supports its application in diverse scientific and industrial fields requiring fast and precise system characterization.