Grasas y Aceites, Vol 69, No 2 (2018)

Zero trans biscuits with soybean-based fats formulated using an artificial neural network


https://doi.org/10.3989/gya.1216172

A. A.T. Penteado
Department of Food Technology, School of Food Engineering, University of Campinas, Brazil
orcid http://orcid.org/0000-0003-1030-7076

A. C. Nogueira
Department of Food Technology, School of Food Engineering, University of Campinas, Brazil
orcid http://orcid.org/0000-0002-1450-5574

K. M.B. Gandra
Food Department, School of Nutrition, Federal University of Ouro Preto, Brazil
orcid http://orcid.org/0000-0002-7934-9218

D. Barrera-Arellano
Department of Food Technology, School of Food Engineering, University of Campinas, Brazil
orcid http://orcid.org/0000-0002-8217-8392

C. J. Steel
Department of Food Technology, School of Food Engineering, University of Campinas, Brazil
orcid http://orcid.org/0000-0002-0911-5889

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.

Keywords


Cookie; Interesterified fat; Marie-type; Neural network; Trans fat

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