Optymalizacja procesu wytwarzania dietetycznych produktów skrobiowych metodą płaszczyzny odpowiedzi (ang.).pdf

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ACTA Acta Sci. Pol., Technol. Aliment. 8(4) 2009, 51-62
ISSN 1644-0730 (print) ISSN 1889-9594 (online)
RESPONSE SURFACE OPTIMIZATION
OF MANUFACTURING OF DIETARY STARCH
PRODUCTS
Joanna Le Thanh-Blicharz 1 , Wojciech Białas 2 ,
Grażyna Lewandowicz 2
1 Institute of Agricultural and Food Biotechnology in Warsaw
2 Poznań University of Life Science
Background. The development of food ingredients that beneficially affect the human or-
ganism has attracted much interest recently. Especially important seems to be resistant
starch i.e. starch fraction which resists hydrolysis catalysed by amylases present in the
gut. Although research on starches resistant to amylolytic enzymes began in 1990s, there
is still lack of cheap and easy methods of its production. The aim of the work was to op-
timize the process of high pressure homogenization of potato starch pastes in order to re-
duce their digestibility to the utmost.
Material and methods. The optimization of the homogenization process was examined
by means of the commercial software STATISTICA. Homogenisation was performed for
the pastes of the concentration of 5%. Digestibility of the obtained starch samples was
evaluated by the amount of glucose formed after 16 h of hydrolysis with the mixture of
pancreatic alpha-amylase and glucoamylase.
Results. It was found that high pressure homogenization of starch pastes provides prod-
ucts of digestibility reduced up to 50%. Moreover, it was proved that at low temperatures,
it is necessary to apply high pressure and low number of passages. At high temperatures,
it is necessary to apply low pressure and high number of passages. Medium values of all
of parameters did not provide low values of digestibility.
Conclusions. The application of the response surface methodology (RSM) for develop-
ment of dietary starch products allows a quick identification of important process factors
(such as temperature, pressure or numbers of passages) and shows interactions between
them.
Key words: starch modification, homogenization, digestibility, response surface metho-
dology (RSM)
© Copyright by Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu
Corresponding author – Adres do korespondencji: Dr inż. Joanna Le Thanh-Blicharz, Department
of Food Concentrates and Starch Products in Poznań, Starołęcka 40, 61-361 Poznań, Poland,
e-mail: lethanh@man.poznan.pl
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52
J. Le Thanh-Blicharz ...
INTRODUCTION
Starch is primarily considered as a source of energy and it mainly determines its nu-
tritive importance. However, in many foodstuffs starch escapes complete digestion by
amylases in the alimentary tract, which makes it possible to apply them as a dietary food
product. From nutritional point of view, starch can be classified into three basic groups:
rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch
(RS) [Englyst et al. 1992]. Firstly, rapidly digested and slowly digested starch were
defined by the amount of glucose released after hydrolysis at 37°C for 20 and 100 min-
utes respectively. Resistant starch was recognised as the starch not hydrolysed after 120
minutes of incubation [Englyst et al. 1992]. However, the development in understanding
of the phenomena relating to digestion in the human gastrointestinal tract requires changes
in the defining of resistant starch. Now, it is postulated that resistant starch is the frac-
tion which does not undergo hydrolysis with the mixture of pancreatic alpha-amylase
and glucoamylase at the temperature of 37°C for the time of 16 hours [Akerberg et al.
1998, Champ et al. 1999, 2001]. Moreover, recently a new category of enzyme resistant
starch has been formulated, namely very resistant starch (VRS), which is not digested
for a long time, up to 24 h and more [Soral-Śmietana and Wronkowska 2004].
Starch modification techniques have been developed for industrial processing to
produce a wide range of potential food ingredients. However, interest in modified
starches has been restricted mainly to technological aspects with little concern about the
possible impact of the modification on the digestibility and fermentability of the prod-
uct. Physical modification of starch is mainly applied to change the granular structure
and convert native starch into cold water-soluble starch or small-crystallite starch. The
major methods used in the preparation of cold water-soluble starches involve instanta-
neous boiling-drying of starch suspensions on heated rolls (drum-drying), puffing, con-
tinuous boiling-puffing-extruding, and spray-drying [Jarowrenko 1986]. Among the
physical processes applied to starch modification, high pressure treatment has attracted
special attention as an example of “minimal processing”. The effect of high pressure on
starch is dependent on the environmental conditions (moisture content, pressure value,
temperature) and the origin of the starch [Stute et al. 1996, Bauer and Knorr 2005,
Błaszczak et al. 2007, Kawai et al. 2007, Buckow et al. 2007]. As an effect of ultra high
pressure treatment (above 400 MPa), starches gelatinise but show very little swelling
and maintain their granular character, which results in quite different paste and gel
properties of the UHP-gelatinised starches compared to the heat-gelatinised starches
[Stute et al. 1996]. Our previous work has concerned a typical high pressure treatment
of starch, that is homogenization of the starch pastes instead of the hydrostatic pressure
treatment of the granular starch-water mixtures. It proved that the high pressure homog-
enization of the starch pastes could be the way for the manufacturing of the starch prod-
ucts which reveal decreased digestibility [Grajek et al. 2004]. However, the relationship
between parameters of the processing and digestibility level is not clear. The large num-
ber of experiments necessary to establish an adequate functional relationship between
the observed responses (digestibility) and the high-pressure homogenization parameters
(pressure, temperature and number of passages), make the experimentation time con-
suming and prohibitively expensive. For that reason, response surface methodology
(RSM) seemed to be the most suitable experimental design strategy. RSM is a collection
of mathematical and statistical tools used to model and analyse problems whose desired
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Response surface optimization of manufacturing of dietary starch products
53
responses are influenced by many variables [Montgomery 2001]. The response surface
method permits to define empirical models such as linear, linear with two-factor interac-
tion or quadratic polynomials which describe accurately how responses behave at all
values of the studied variables in the experimental region. However, it should be
stressed that in order to calculate quadratic polynomial model coefficients, each design
variable has to be studied at three distinct levels at least. The aim of the work was to
optimize the process of high pressure homogenization of potato starch pastes in order to
reduce their digestibility to the utmost. In particular, the Box-Benkhen design (BBD)
constructed by combining two-level factorial designs with incomplete block designs has
been used to determine the optimal conditions for high pressure homogenization of
starch pastes.
MATERIAL AND METHODS
Materials
Commercial potato “Superior Standard” starch (Polish product) manufactured
by Potato and Starch Company WPPZ Luboń S.A. was used as a raw material.
Methods
Homogenization. Starch suspensions of the concentration of 5% were gelatinised
and then sterilized at 121°C for 20 min. Homogenization was performed using the GEA
Niro Soavi (Italy) homogenizer. Homogenized starch pastes were dried with Mobile
Miner TM 2000 (Niro A/S) spray dryer.
Experimental design. In this study, the effects of homogenization pressure (X 1 ),
temperature (X 2 ) and number of passages (X 3 ) on digestibility of starch samples (Y)
was evaluated using the Box-Behnken design. As shown in Table 1, the variable levels
X i were coded as x i according to the following equation:
x
(
i
1,0,
1)
2X
i
X
(min)i
X
(max)i
(1)
X
X
(max)i
(min)i
where x i is the dimensionless value of an independent variable, X i the real value of an
independent variable and X (min)i , X (max)i are the lower and the upper limit of the inde-
pendent variable respectively. A total of 17 experiments were performed and the central
point was repeated five times to estimate the experimental error variance. The order in
which the experiments were performed was randomised, according to the requirement
for the observations to be distributed independently and randomly, which additionally
helps to avoid the influence of unknown nuisance variables. The set points were se-
lected according to the results obtained during a preliminary study.
A multiple regression analysis of the data was carried out to obtain empirical models
that define response (Y) in terms of the independent variables. For a three-factor sys-
tem, the following second-order polynomial equation was then applied to the data by the
multiple regression procedure (equation 2):
Acta Scientiarum Polonorum, Technologia Alimentaria 8(4) 2009
344807566.004.png
54
J. Le Thanh-Blicharz ...
Y
b
0
b
1
x
1
b
2
x
2
b
3
x
3
b
12
x
1
x
2
b
13
x
1
x
3
b
23
x
2
x
3
b
11
x
2
1
b
22
x
2
2
b
33
x
2
3
(2)
with Y, being the predicted response; b 0 , intercept; b 1 , b 2 and b 3 , linear coefficients; b 11 ,
b 22 and b 33 , squared coefficients and b 12 , b 13 and b 23 , interaction coefficients. The accu-
racy and general ability of the above polynomial model was evaluated by the adjusted
coefficient of determination Adj-R 2 , significance of total regress F-value and non sig-
nificance of lack of fit F-value. The commercial software STATISTICA, version 6.0 PL
from StatSoft, Inc. (2004) was used for regression and graphical analyses of the ob-
tained data.
Table 1. Independent variables and their levels for the design used in the present study
Variable
Coded values
real
–1.0
0
+1.0
coded
unit
real values
Pressure
X 1
MPa
x 1
4.0
22.0
40.0
Temperature
X 2
°C
x 2
50.0
67.5
85.0
Number of passages
X 3
–
x 3
5.0
10.0
15.0
Digestibility. The rate of digestion of starch was determined by its hydrolysis with
the mixture of pancreatic alpha-amylase and glucoamylase at the temperature of 37°C,
at particular periods of time, followed by the measurement of the released glucose using
glucose oxidase. Porcine pancreatic alpha-amylase type VI-B (Sigma) as well as glu-
coamylase AMG 300L (Novozymes) were used for the analyses. The amount of re-
leased glucose was determined colorimetrically at the λ = 500 nm using Liquick Cor-
Glucose diagnostic kit (Cormay, Poland). Four replicates were made for each probe and
standard deviation was calculated.
RESULTS AND DISCUSSION
Statistical analysis
In order to find the optimum conditions for high pressure homogenization of the
starch pastes experiments were performed according to the BBD experimental plan
(Table 2). Analysis of variance indicated that the response surface model developed for
the digestibility of starch samples was statistically significant by the probability of the F
test at the level below 0.0001 (Table 3). Furthermore, the probability value of the lack-
of-fit test was higher than 0.05, indicating that the regression model is in good predic-
tion of the experimental results. As it was mentioned above, the precision of a model
can be checked by the adjusted coefficient of determination Adj-R 2 . It is well known
that the closer the Adj-R 2 is to 1, the better the model fits the experimental data.
As shown in Table 4, the value of Adj-R 2 was equal 0.9202 indicating a close agreement
between the experimental results and the theoretical values predicted by the model
equation, which can be proved by Figure 1.
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Response surface optimization of manufacturing of dietary starch products
55
Table 2. Box-Behnken experiments design matrix with experimental value of starch pastes diges-
tibility
Variable
Response
digestibility
%
Trial
number
X 1 : Pressure, MPa
X 2 : Temperature, °C
X 3 : Number of passages
real
coded
real
coded
real
coded
1
40.0
1.0
67.5
0.0
15.0
1.0
55.84
2
22.0
0.0
50.0
–1.0
5.0
–1.0
54.52
3
40.0
1.0
85.0
1.0
10.0
0.0
63.41
4
22.0
0.0
67.5
0.0
10.0
0.0
67.98
5
22.0
0.0
67.5
0.0
10.0
0.0
67.62
6
40.0
1.0
67.5
0.0
5.0
–1.0
60.32
7
4.0
–1.0
85.0
1.0
10.0
0.0
58.94
8
22.0
0.0
85.0
1.0
15.0
1.0
61.52
9
4.0
–1.0
67.5
0.0
5.0
–1.0
61.49
10
22.0
0.0
85.0
1.0
5.0
–1.0
71.39
11
22.0
0.0
67.5
0.0
10.0
0.0
67.89
12
22.0
0.0
67.5
0.0
10.0
0.0
67.72
13
4.0
–1.0
50.0
–1.0
10.0
0.0
68.8
14
22.0
0.0
67.5
0.0
10.0
0.0
67.44
15
22.0
0.0
50.0
–1.0
15.0
1.0
69.96
16
40.0
1.0
50.0
–1.0
10.0
0.0
64.42
17
4.0
–1.0
67.5
0.0
15.0
1.0
59.72
Table 3. ANOVA table of starch pastes digestibility
Factor
Sum of squares
df
Mean square
F-value
p
Model
387.922
7
55.417
25.706
< 0.0001
b 1
3.075
1
3.075
1.426
0.2665
b 2
22.161
1
22.161
10.280
0.0125
b 3
17.480
1
17.480
8.108
0.0216
b 11
28.206
1
28.206
13.083
0.0068
b 33
110.784
1
110.784
51.388
< 0.0001
b 12
19.580
1
19.580
9.082
0.0167
b 23
207.914
1
207.914
96.444
< 0.0001
Lack of fit
14.812
4
3.703
6.084
0.0541
Pure error
2.434
4
0.608
Total SS
405.169
15
Acta Scientiarum Polonorum, Technologia Alimentaria 8(4) 2009
344807566.001.png

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