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Fuzzy Logic Approach for Process Optimization of Gluten‐Free Pasta
Author(s) -
Sakre Nilesh,
Das Amit B.,
Srivastav Prem P.
Publication year - 2016
Publication title -
journal of food processing and preservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.511
H-Index - 48
eISSN - 1745-4549
pISSN - 0145-8892
DOI - 10.1111/jfpp.12662
Subject(s) - amaranth , fuzzy logic , sensory system , mathematics , sensory analysis , response surface methodology , food science , product (mathematics) , process (computing) , computer science , process engineering , artificial intelligence , statistics , engineering , chemistry , biology , geometry , operating system , neuroscience
The aim of the present investigation was to optimize the process condition and formulation for production of amaranth and oat‐based gluten‐free pasta using a single‐screw extruder. In the present study, process condition and formulation were optimized using rotatable central composite design followed by sensory optimization using fuzzy logic. The process was optimized using nonlinear regression analysis and desirability of pasta samples on the basis of physical properties such as water solubility index, cooking loss and hardness. After numerical analysis, three pasta samples with different flour compositions were identified with the same desirability (0.95). A sensory study was conducted to select the best among the three samples based on human acceptability. The sensory score was analyzed using fuzzy logic. The results of sensory analysis showed that formulation containing 33 g amaranth, 26 g oat, rice 50 g/100 g and process conditions of 80C, 245 rpm, and 35% led to the highest acceptability values according to the optimization analysis performed. Practical Applications The results and approaches presented in the article may find practical application during new food product development. Sensory assessment is the integral part of new food product development. In mathematical optimization, without appropriate sensory analysis, there will be a risk of market failure of new food product. The approaches suggested in the present research will be more efficient for optimization of composition and processing parameters for new food product.