<![CDATA[This study proposes a classification model of bread doneness using a Mamdani Fuzzy Inference System (FIS) based on the nonlinear interaction between baking temperature and time. Conventional threshold-based baking approaches often fail to represent gradual transitions in doneness levels, limiting their adaptability in intelligent oven systems. The proposed model utilizes two input variables—oven temperature (150–230 °C) and baking time (5–40 minutes)—and produces a normalized doneness output categorized as underbaked, properly baked, and overbaked. Fuzzy rules were formulated based on thermal baking characteristics, and the inference process was implemented through fuzzification, minimum operator rule evaluation, maximum aggregation, and centroid defuzzification. Both direct mathematical calculations and MATLAB Fuzzy Logic Toolbox simulations were conducted to validate the model. For a test case of 190 °C and 18 minutes, the system generated a defuzzified value of 66.6, corresponding to the properly baked category. The results demonstrate consistent output behavior and stable classification performance. The proposed model provides an interpretable and computationally efficient decision framework that can serve as a foundational component for intelligent baking systems.]]>
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