Abstract

This study applied Artificial Neural Network (ANN) technology to formulate zero trans fat blends derived from soybeans and to evaluate their performance when applied to the processing of sweet laminated biscuits. For the formulation of the blends, two interesterified soybean fats and soybean oil were used as bases. They were characterized in terms of melting point, solid fat content and fatty acid composition; and the biscuits produced were analyzed for their technological (dimensions, mass, volume, expansion, instrumental color and texture, moisture gradient and cracking) and physicochemical characteristics (total fat and moisture contents, water activity and fatty acid composition). It was possible to verify the use of ANN to develop zero trans fats derived from soybeans for application in sweet laminated biscuits, which represents an operational and financial advantage. Moreover, we showed the viability of using soybean fats/oil, raw materials of greater availability and lower cost, for the production of biscuits.

Highlights

  • The fat blends were produced using soybean oil (SO) and soybean-based interesterified fats (B1 and Base 2 (B2)), in order to obtain a similar behavior to the solid fat content of commercial low trans fats (LTF), using a previously trained Artificial Neural Network (ANN)

  • The network was trained with 62 samples, with the percentage of each raw material used in the formulations of the sample as input data, and the solid fat content and the melting point of the samples as output data (Gandra, 2011)

  • As it was observed that some solutions presented the same responses or very close responses, and they were categorized into four different groups: BLD1 (6% Base 1 (B1) + 34% B2 + 60% SO), BLD2 (13% B1 + 19% B2 + 68% SO), BLD3 (24% B1 + 9% B2 + 67% SO) and BLD4 (0% B1 + 46% B2 + 54% SO)

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Summary

Objectives

This study aimed to evaluate the performance of low trans fats derived from soybean and formulated using an Artificial Neural Network (ANN) in sweet laminated biscuits (Marie-type)

Methods
Results
Conclusion
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