Wheat and Cassava Flour-Based Composite Formulation of Cookies: Optimization of the Ingredient’s Level by Simplex Lattice Design and Sensory Evaluation Using Fuzzy Logic

Autor: Nandan Sit, Manas Jyoti Das, Sankar Chandra Deka, Sourav Chakraborty, Khurshida Singamayum
Rok vydání: 2021
Předmět:
Zdroj: Journal of Biosystems Engineering. 46:93-103
ISSN: 2234-1862
1738-1266
DOI: 10.1007/s42853-021-00090-1
Popis: The present study aims to develop value added cookies using composite formulation of wheat and cassava flour using simplex lattice mixture design and sensory evaluation by applying fuzzy logic approach. Based on the simplex lattice mixture design, optimized formulations of the cookies using wheat flour, dry chips flour, and fermented cassava flour were developed. The impacts of the composite flour on different quality traits of the cookies specifically rheology, color, texture, and sensory properties were studied. The optimized formulations of the cookies were determined as wheat flour of 77.50%, dry chips flour of 16.67%, and fermented cassava flour of 5.83% of total flour. The responses under this formulation were color value (L* value) of 67.23, the maximum breaking strength of 23.55 N, and loss tangent of 0.29. Investigation of the rheological properties based on loss tangent values demonstrated solid elastic behavior of the cookie’s dough. Furthermore, sensory evaluation by applying fuzzy logic approach revealed cookies prepared with the optimum formulation as the best sample based on appearance, aroma, taste, and texture. The present study has the credentials to support that the developed composite flour-based cookies are the effectual alternative of accessible bakery items as evidenced by the results with improved quality properties.
Databáze: OpenAIRE
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