Hemijska industrija 2013 Volume 67, Issue 3, Pages: 465-475
https://doi.org/10.2298/HEMIND120529082P
Full text ( 301 KB)
Cited by
Artificial neural network model of pork meat cubes osmotic dehydratation
Pezo Lato L. (Institute of General and Physical Chemistry, Belgrade)
Ćurčić Biljana Lj. (Faculty of Technology, Novi Sad)
Filipović Vladimir S. (Faculty of Technology, Novi Sad)
Nićetin Milica R. (Faculty of Technology, Novi Sad)
Koprivica Gordana B. (Faculty of Technology, Novi Sad)
Mišljenović Nevena M. (Faculty of Technology, Novi Sad)
Lević Ljubinko B. (Faculty of Technology, Novi Sad)
Mass transfer of pork meat cubes (M. triceps brachii), shaped as 1x1x1
cm, during osmotic dehydration (OD) and under atmospheric pressure was
investigated in this paper. The effects of different parameters, such as
concentration of sugar beet molasses (60-80%, w/w), temperature (20-50ºC),
and immersion time (1-5 h) in terms of water loss (WL), solid gain (SG),
final dry matter content (DM), and water activity (aw), were investigated
using experimental results. Five artificial neural network (ANN) models were
developed for the prediction of WL, SG, DM, and aw in OD of pork meat cubes.
These models were able to predict process outputs with coefficient of
determination, r2, of 0.990 for SG, 0.985 for WL, 0.986 for aw, and 0.992 for
DM compared to experimental measurements. The wide range of processing
variables considered for the formulation of these models, and their easy
implementation in a spreadsheet calculus make it very useful and practical
for process design and control.
Keywords: mass transfer, osmotic dehydration, pork meat, sugar beet molasses, neural network