Application of soybean oil and glycerol in animal feed production, ANN model
Author(s) -
Danka Dragojlović,
Lato Pezo,
Dušica Čolović,
Strahinja Vidosavljević,
Milada Pezo,
Radmilo Čolović,
Bojana Kokić,
Olivera Djuragic
Publication year - 2019
Publication title -
acta periodica technologica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.134
H-Index - 15
eISSN - 2406-095X
pISSN - 1450-7188
DOI - 10.2298/apt1950051d
Subject(s) - glycerol , soybean oil , dispersion (optics) , nozzle , pulp and paper industry , artificial neural network , production (economics) , food science , microbiology and biotechnology , biological system , chemistry , materials science , process engineering , mathematics , chemical engineering , chromatography , computer science , biology , biochemistry , engineering , artificial intelligence , mechanical engineering , physics , optics , economics , macroeconomics
In the past few decades the diet preparation in feed production has evolved towards more complicated technological operations, which include different liquid addition. A wide scale of different liquids is used in contemporary animal feed production, from oils and glycerol to more expensive products in a liquid form, such as enzymes, flavourings, amino acids, vitamins and others. In the presented study the liquid addition in feed production was observed, with a specific goal to investigate the spraying systems in order to better understand the effects of fluids, such as soybean oil and glycerol, on feed production. The dispersion angles of spraying nozzle for glycerol and soybean oil were determined as an indicator of the uniform application of liquids during feed production. Dispersion of the material was accomplished using the two-fluid nozzle. The performance of Artificial Neural Network (ANN) was compared with experimental data in order to develop rapid and accurate method for prediction of dispersion angle. The ANN model showed high prediction accuracy (r2 = 0.945).
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