Formulation of fats using neural networks: commercial products and pilot-plant production

Authors

  • Jane Mara Block Laboratório de Óleos e Gorduras, Faculdade de Engenharia de Alimentos
  • Daniel Barrera-Arellano Laboratório de Óleos e Gorduras, Faculdade de Engenharia de Alimentos
  • Rodrigo Almeida
  • Fernando C. Gomide
  • Roberto Book Moretti

DOI:

https://doi.org/10.3989/gya.2003.v54.i3.237

Keywords:

Blending, Fat formulation, Hydrogenated fats, Neural networks, Shortenings

Abstract


In the present work, trials were carried out to verify the range of application of a neural network, designed to formulate fats from 3 raw materials from soybean. For evaluation, 17 randomly selected commercial products, originally formulated with unknown raw materials, were used. Apart from the commercial products, 3 different table margarines were formulated using conventional methods and the neural network, and produced in pilot-plant scale. According to the results obtained, the neural network presented a success index of 64.7% in the formulation of commercial products. With respect to the products formulated and produced in pilot-plant scale, the results obtained using the network were similar to those obtained using the conventional formulation methods.

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Published

2003-09-30

How to Cite

1.
Block JM, Barrera-Arellano D, Almeida R, Gomide FC, Book Moretti R. Formulation of fats using neural networks: commercial products and pilot-plant production. grasasaceites [Internet]. 2003Sep.30 [cited 2023Feb.6];54(3):240-4. Available from: https://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/237

Issue

Section

Research

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