Functional properties of foods. Database and model prediction

content, feed rate, screw speed, screw configuration. Other affecting factors may include raw material
formulation, pre-processing treatments, initial particle size of milled materials, and the milling procedure. A
preliminary statistical investigation shows that we have a strong relationship between WAI or WSI and 4
independent variables such as die temperature, feed moisture content of food product in wet base %, screw
speed of extruder and blend level% mainly for starchy and proteinaceous extruded food products. It is found
from the modelling exercise that using a model, which considers power law dependency of all independent
variables, provides the best performance in the model:
WAI or WSI
a
T
T o
where WAI: water absorption index (dimensionless), WSI: water solubility index (%), T: die temperature of
extruder ( o C), X: feed moisture content of food product in wet base %, S: screw speed of extruder (rpm), M:
mixture of blend %, variables with subscripts: reference steady average values of independent variables,
a,b,c,d,e: dimensionless adjustment parameters.
Similarly, concerning the property of PDI the intended model is:
b
PDI a
T
T
o
t
t
where PDI: protein dispersibility index (%), T: is the temperature of the product which was exposed during
preparation ( o C), t: is the corresponding residence time (10 3 *s), variables with subscripts: reference steady
average values of independent variables, a,b,c: dimensionless adjustment parameters.
The parameter estimation was performed by the Levenberg–Marquardt (LM) algorithm. The LM algorithm is
an iterative technique that locates the minimum of a multivariate function that is expressed as the sum of
squares of nonlinear real-valued functions. The software package Stargraphics Centurion v. XV (Manugistics
Inc. Rockville, MD, USA) was used for the nonlinear regression analysis.
RESULTS & DISCUSSION
b c
X
X
o
c
o
Table 1 presents, in a compact form, the main information concerning the examinee properties. The
minimum, maximum, average values and the standard deviation for each of six properties are presented in the
first four columns. The main food systems and the factors which altered the value of properties are presented
in the fifth and sixth columns respectively. Finally, the total number of experimental data which was
retrieved is presented in the final column.
Table 1. Data compiled from literature about examinee functional properties used in statistical analysis
Property MIN MAX AVG SD a Food System Main Factor N b
WAI 0.3 14.4 4.8 1.9 Corn, Wheat,
Rice Flours
WSI 0.2 94.8 22.4 15.4 Corn, Wheat,
Rice Flours
PDI 1.3 100.0 42.0 42.0 Soybean
Products
NSI 2.5 94.0 40.7 19.4 Soybean
Products
Extrusion parameters,
blends
Extrusion parameters,
blends
pH, Heat, Enzymatic
Hydrolysis
pH, Heat, Enzymatic
Hydrolysis
GI 1.0 100.0 71.0 25.1 Wheat Products Genotype, Fertilization,
Location, Subunits
WG 0.2 60.9 29.6 9.2 Wheat Products Genotype, Fertilization,
Location, Subunits
a Standard Deviation; b Number of retrieved data
S
S o
d e
M
M
o
Due to the large number of replicates, a fundamental prerequisite for the least squares fitting of the models to
the corresponding data sets is equal variance of the different observations. The results of these tests show that
the variance was almost steady. The results of the nonlinear regression analysis of fitting the equation 1 to the
experimental points are shown in Table 2. In this table the standard experimental error and the standard
deviation between experimental and calculated values are also presented. In most cases the values of the
1268
1083
1067
780
3400
2354
(1)
(2)