<p dir="ltr">Understanding the nonlinear rheological properties of food is essential for improving processes involving large-amplitude deformation such as pumping, extrusion, and consumer consumption. The development of mathematical analyses for analyzing these nonlinear responses has witnessed a notable upswing in the past decades. A novel mathematical analysis called "Sequence of Physical Processes" (SPP) was developed by Rogers et al. in 2011. Ever since, SPP has shown tremendous potential in characterizing and predicting the nonlinear rheological behavior of soft materials and polymers, yet more investigations are required to validate the efficacy of the SPP approach in the realm of food materials. Therefore, this thesis focuses on applying SPP method onto a range of food materials. Most importantly, we compared the analysis with the results obtained from the well-established Ewoldt-McKinley method of coupling “Fourier Transform with Chebyshev Decomposition” (FTC). As a result, it is found that SPP can provide a detailed picture of the material’s deformation history within an oscillation cycle. The time-dependent nature of SPP data allows a more accurate capture of important rheological transitions, which leads to a higher correlation with compositional and microstructural changes in comparison to the FTC method. Recognizing the potential of SPP analysis in studying food materials, this research emphasizes the necessity for further exploration across a diverse array of food types. The thesis contributes valuable insights to the evolving landscape of nonlinear rheological understanding, with the potential to improving methodologies in food processing.</p>