Articles
THERMAL BEHAVIOR OF MILK DRINK FLAVORED WITH DATE SYRUP MEASURED BY MDSC AND PREDICTED BY ARTIFICIAL NEURAL NETWORKS (ANNS)
Article number
882_136
Pages
1181 – 1193
Language
English
Abstract
The thermal behavior of a new drink of milk flavored with concentrated date syrup was evaluated.
A modulated differential scanning calorimeter (MDSC) was utilized to study the thermal properties of milk-dibbs drinks at different concentrations for a temperature range of -65 to 65°C. The concentrated date syrup (dibbs) added ranged from 10 to 30 ml/100 ml milk.
Onset melting temperature, melting point of fusion, and latent heat of fusion for all concentrations (0-30 ml dibbs/100 ml milk) fell within the ranges -6.03 to -18.94°C, 0.44 to -5.46)°C and 275.7 to 164.3 J g-1, respectively.
The apparent specific heat values decreased with the increase of milk-dibbs drink concentration in both phases (liquid and solid). The mean values of apparent specific heat above freezing (10 to 65°C) were 4.16, 3.92, 3.81, 3.70, 3.38 and 2.90 kJ kg-1 C-1 for 0, 10, 15, 20, 25, 30 ml dibbs/100 ml milk, respectively.
At the phase change, the peak areas were higher for the high water content solutions.
However, the dibbs heat flow curve obtained did not exhibit phase transition at the studied temperature range, which can be attributed to the high °Brix values (75%) of sugar concentration.
The specific heat values of pure dibbs fell within the range 1.48 kJ kg-1 C-1 (at -65°C) to 4.12 kJ kg-1 C-1 (at 65°C). It was found that the Artificial Neural Networks (ANNs) technique is a powerful tool to predict the apparent specific heat based on temperature, concentration of milk-dibbs drink, Brix, pH, and water activity.
A modulated differential scanning calorimeter (MDSC) was utilized to study the thermal properties of milk-dibbs drinks at different concentrations for a temperature range of -65 to 65°C. The concentrated date syrup (dibbs) added ranged from 10 to 30 ml/100 ml milk.
Onset melting temperature, melting point of fusion, and latent heat of fusion for all concentrations (0-30 ml dibbs/100 ml milk) fell within the ranges -6.03 to -18.94°C, 0.44 to -5.46)°C and 275.7 to 164.3 J g-1, respectively.
The apparent specific heat values decreased with the increase of milk-dibbs drink concentration in both phases (liquid and solid). The mean values of apparent specific heat above freezing (10 to 65°C) were 4.16, 3.92, 3.81, 3.70, 3.38 and 2.90 kJ kg-1 C-1 for 0, 10, 15, 20, 25, 30 ml dibbs/100 ml milk, respectively.
At the phase change, the peak areas were higher for the high water content solutions.
However, the dibbs heat flow curve obtained did not exhibit phase transition at the studied temperature range, which can be attributed to the high °Brix values (75%) of sugar concentration.
The specific heat values of pure dibbs fell within the range 1.48 kJ kg-1 C-1 (at -65°C) to 4.12 kJ kg-1 C-1 (at 65°C). It was found that the Artificial Neural Networks (ANNs) technique is a powerful tool to predict the apparent specific heat based on temperature, concentration of milk-dibbs drink, Brix, pH, and water activity.
Publication
Authors
A.M. Alhamdan
Keywords
MDSC, thermal behavior, dates syrup, milk drink, ANN
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