Applying a Taguchi-based fuzzy logic approach to optimize hydrothermal pretreatment of canola seeds using multi-response performance index

Abstract

The Taguchi method with fuzzy logic was applied for optimizing the hydrothermal pretreatment of canola with multiple performance responses (oil extraction yield, free acidity and peroxide index) using published data. The canola seeds had been subjected to hydrothermal pretreatments using steam in an autoclave whose base was perforated, under different conditions of temperature (100, 120 and 130 °C), time (5, 15 and 30 min) and granulometry (entire, broken and ground seeds), and the responses were measured as performance characteristics of the process. The output value that represents the responses was called multi-response performance index (MRPI), and the significance of the experimental factors was analyzed by ANOVA. A confirmation test of the optimum parameters was carried out to verify the optimum parameters, obtaining a predicted MRPI of 0.588, while the experimental value was of 0.849, and the MRPI calculated using the predicted values from the literature was of 0.577.