Analysis of the Effect of Protein Content and Preheating Temperature on the Hardness of SPC Biscuits Using the Fuzzy Logic Method

This study aimed to analyze and model the non-linear effect of protein content and preheating temperature on the hardness of Soy Protein Concentrate (SPC)-based biscuits using the Sugeno fuzzy logic method. A descriptive quantitative approach was employed, utilizing the Sugeno-type Fuzzy Inference System (FIS) designed and implemented using MATLAB software. The inputs were protein concentration (7-16%) and preheating temperature (70-90°C), with biscuit hardness (747.5-2176.5 gf) as the output. The system successfully mapped the complex interactions through nine fuzzy if-then rules. The results showed that increasing protein content generally increases hardness, particularly at higher preheating temperatures. However, excessive heating at medium protein content led to a decrease in hardness due to structural degradation. The defuzzification surface indicated that the preheating temperature has a relatively stronger influence on the final hardness than protein content. The developed fuzzy model provides accurate and interpretable predictions (e.g., 11.5% protein and 80°C yields a medium hardness of 1.45 x 10³ gf), proving its effectiveness as an adaptive decision-support tool for optimizing high-protein biscuit production.