Fuzzy Logic-Based Optimization for Pseudocereal Processing: A Case Study on Buckwheat

In response to the increasing consumer interest in the health benefits of plant-based foods, in this study, fuzzy logic modeling (FLM) was used to optimize the lactic fermentation process of several buckwheat (Fagopyrum esculentum)-based substrates (B-bSs), which were bio-prospected for the development of pseudocereal-based fermented foodstuffs. The experimental methodology involved obtaining B-bSs, either green or roasted, under various milling conditions and subjecting them to two different types of thermal treatment. This experimental design allowed us to obtain a set of experimental data, based on which a fuzzy system was developed and calibrated. The main physicochemical characteristics (pH, total titratable acidity, dynamic viscosity, and color) and sensory attributes (appearance, color, aroma, taste, texture or mouthfeel, and overall acceptability) of B-bSs were evaluated. The fuzzy logic approach proved useful for monitoring the evolution of lactic fermentation and for the rapid and accurate identification of situations that require technological interventions, acting as a reliable tool for the ongoing optimization of fermentation processes. Our study’s results showed that the optimal technological variants identified using FLM corresponded to green buckwheat milled with a 0.12 mm gap disk and a hammer mill and subjected to ultrasonic water bath treatment. The hedonic descriptive sensory evaluation also validated this conclusion.