Artificial neural network identification of heterotrophic marine bacteria based on their fatty-acid composition

1997 ◽  
Vol 44 (12) ◽  
pp. 1185-1191 ◽  
Author(s):  
M. Giacomini ◽  
C. Ruggiero ◽  
S. Bertone ◽  
L. Calegari
2018 ◽  
Vol 69 (2) ◽  
pp. 251 ◽  
Author(s):  
A. A.T. Penteado ◽  
A. C. Nogueira ◽  
K. M.B. Gandra ◽  
D. Barrera-Arellano ◽  
C. J. Steel

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.


2007 ◽  
Vol 155 (6) ◽  
pp. 364-367 ◽  
Author(s):  
M. Nie ◽  
W. Q. Zhang ◽  
M. Xiao ◽  
J. L. Luo ◽  
K. Bao ◽  
...  

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