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Paper No. 03-326
PHYSICAL AND RHEOLOGICAL PROPERTIES OF
MANGO PUREE
L. S. Kassama1; G. S. Vijaya Raghavan
2 and M.O. Ngadi
2
Graduate student1 and professor
2
Department of Bioresource Engineering, McGill University, Macdonald Campus
Ste Anne-de-Bellevue, Quebec, H9X 3V9
Written for presentation at the
CSAE/SCGR 2003 Meeting
Montreal, Quebec
July 6 – 9, 2003
Abstract
Very limited information is available with regards to physical parameters for the optimization of
mango processing. The physical and rheological properties of mango puree were investigated using
a controlled-stress and controlled strain rheometer and a thermal analysis DSC. Mango puree was prepared from natural ripen mangoes using a blender. A Central Composite Rotatable Design
(CCRD) consisting of a three-factored factorial with two levels was used for the study. The factorswere temperature (20 and 70° C), concentration (12 and 24 Brix), and shear rate (300 and 800 /s). A
response surface analysis was used in optimizing the rheological properties. The rheological behavior was thixotropic, and the yield stress was sensitive to increases in temperatures. The
viscosity of the product was significantly influenced by the independent variables. Thermal analysis
results showed that the glass transition, crystallization and melting were affected by the processvariables. The result of this study could provide a baseline data for better understanding of the
physical properties of mango puree, and thus could enhance and optimize product storage quality
and development of new product.
Keywords: Mango Puree, Rheology, glass transition, crystallization, melting.
Papers presented before CSAE/SCGR meetings are considered the property of the Society. In general, the Society reserves the right offirst publication of such papers, in complete form; however, CSAE/SCGR has no objections to publication, in condensed form, with creditto the Society and the author, in other publications prior to use in Society publications. Permission to publish a paper in full may berequested from the CSAE/SCGR Secretary, PO Box 316, Mansonville, QC J0E 1X0. Tel/FAX 450-292-3049. The Society is notresponsible for statements or opinions advanced in papers or discussions at its meetings.
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INTRODUCTION
Mango ( Mangifera indica L.) is commonly referred as the king of the tropical fruits
because of its palatability. In most tropical countries, it is processed at raw and ripe
stages as jam, pickle and beverages. The total world production is about 24 million tones
(FAOSTAT, 2000). In the recent years, mangoes have become well established in the
global market. Today, the consumption of processed mango products such as mango-
flavored beverages either singly or multi-flavored beverages is rapidly increasing in the
western hemisphere, thus the demand for processed pulp (puree) had dramatically
increased.
Many food materials have distinct physical characteristics in addition to their
nutritional values; most often it is the rheological characteristic that makes significant
contributions to the overall quality of the product (Rielly 1997). For example, to the
consumer, the flow characteristics of some products (tomato ketchup, sauces, mayonnaise
etc) may be as important as the taste; similarly the mouth feel (determined by its
rheological properties) may contribute as much to the pleasure of eating, as does the
flavor. The flow characteristics of pumpable fluids are dependent on their viscosity,
concentration, temperature (Rao, 1995), and because of their wide variation of structure
and composition, foods may exhibit flow behavior ranging from simple Newtonian to
time-dependent non-Newtonian and viscoelastic (Singh and Heldman, 1993). A non-
Newtonian fluid exhibits shear thinning behavior and their viscosities decreases with
increase in shear rate. Mango puree was reported to be pseudo-plastic (shear thinning)
and thixotropic fluid with yield stress (Gunjal and Waghmare, 1987; Manohar et al.,
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1990; Bhattacharya, 1999). The rheological properties obtained from rheometer test may
be represented in terms of constitutive equations between the rate of strain in the fluids
and the applied shear stress. Power law models with or without yield stress has been
extensively used to model the flow behavior of fruit purees.
Whole mango consists of about 82% water, 0.2% fat and about 14%
carbohydrates (Holland et al. 1991). Mango puree like many other fruit purees are
usually stored in the frozen state. Frozen food materials often exhibits phase transition
typical of amorphous polymers (Parks and Thomas 1934; Roos 1987; Slade and Levine
1991). During storage food may loose its integrity as a result of unstable molecular
transformation (Aguilera and Stanley 1999). A different form of quantifying water
mobility and food stability was necessary thus the application of the concept of glass
transition was introduced in food science (White and Cakebread 1966). In storing food
below glass transition temperature (Tg), the rate of any type of changes is severely
reduced and the product becomes virtually stable, while the molecular mobility is
restricted (Jorge et al. 1999). Thermal analysis is important, which could provide
essential information to enhance proper storage temperatures. Differential scanning
calorimeter (DSC) is a thermoanalytical technique for monitoring changes in physical or
chemical properties of materials as a function of temperature (Biliaderis, 1983). In spite
of the significance of thermoanalytical data, no information was found in our literature
search on mango puree.
It is therefore, important to use engineering approach to characterize the physical
properties mango puree. Knowledge of the rheological and thermal properties of fluid
foods is essential for the proper engineering design of continuous process, e.g. to predict
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flow rates in pipes, pump sizes, mixing, and heat transfer for concentration, dehydration,
pasteurization, and sterilization (Holdsworth 1971). Another important practical
application ids the determination of suitable quality control parameters for example,
consistency index (Tiu and Boger, 1974). Thus, the objective of this study was to
investigate the effect of temperature, concentration on the rheological and thermal
properties of mango puree and also to develop predictive models for the rheological
parameters.
MATERIALS AND METHODS
Sample preparation
Tommy Atkins Mango ( Mangifera Indica L.) variety was acquired from local dealer. The
fruit was produced in Mexico. The ripen mango fruits was washed and peeled manually
and the flesh was sliced from the seed carefully and placed in a blender. The puree was
filled into a sterilized glass jars hermetically sealed and was heated in a water bath at
80°C for 15 min. The samples were refrigerated at 4°C till the next step. To acquire
different levels of mango puree concentrations sugar was added, and thoroughly mixed.
Chemical analysis
The pH was determined by using pH meter (Accumet meter, model 25, Denver
Instrument Company, Arvada, CO). The total soluble solids (TSS) was measured using a
hand refractometer (model ATC, 0.90%), Shilac, Japan).
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Rheological measurement
A controlled stress rheometer (AR2000, TA Instruments LTD, Leatherhead, UK) with a
standard steel parallel plate (40 mm) geometry coupled with a built-in peltier plate
temperature control was used. Flow curves were generated by using both the controlled
shear-rate and controlled shear-stress, hence, viscosity was determined from shear
stress/rate curves at different temperatures. Time-dependency (thixotropy) was measured
at different temperatures. Different combinations of shear rates and temperature ram
were used to measure viscosity.
For each test, samples were placed between the parallel plates and allowed two
min to equilibrate prior to all test operations. The data were logged automatically during
the test by a microcomputer attached to a rheometer. The rheograms (flow curves) were
directly fitted to the desired mathematical models by the software (TA instrument
advantage software) based on the Herschel-bulkley’s model (eq. 1):
nk γ σ σ &+= 0 (1)
where σ is shear stress (Pa), 0σ is the yield stress (Pa), k is the consistency coefficient,
and γ & is the shear rate (s-1
).
Thermal analysis
Differential scanning calorimeter (DSC) (Q100-Tzero technology, TA Instruments INC.,
New Castle, DE) equipped with a refrigerated cooling system (RCS) consting of two
stages, cascade and vapor compression refrigeration system with an attached cooling
head, which operates within the ranges of –90 to 550°C was used for the this experiment.
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The DSC was operated through a microcomputer. Nitrogen (Ultra high purity 5) was
used as the purged gas and the flow rate was 50 mL/min at 138 kPa (20 psi). Sample
sizes of 12 to 16 mg were weighed into the hermitic pans and sealed. The samples were
encapsulated in aluminum hermitic pans with the aid of the TA instrument Q series
sample encapsulating press with the hermitic sealing die attachment. The cell resistance
and capacitance, cell constants and temperature calibrations were accomplished by
running empty pans, sapphire and indium (melting point 156.6°C). The heating rate was
5°C/min within the temperature range of –90 to 100°C. The thermograms were generated
with the software (TA instrument advantage software).
Experimental design
The central composite rotatable design (CCRD) (Box and Draper 1987) was used
for the rheology study. The CCRD consisted of a three-factored factorial with two levels.
The factors and their levels are shown in Table 1.
Table 1. Coded and uncoded levels of three predictor variables for mango puree.
LevelsVaraibles
-1 1Midlevel Semi-range
Temperature (°C) 20 70 45 25
Concentration (°Brix) 12 24 18 6
Shear Rate (s
-1
) 300 800 550 250
The matrix for the CCRD optimization experiment is summarized in Table 2. The
CCRD design has eight experimental points in a cube (run No. 1-8), six star points with
an axial distance of 1.682 (run No. 9-14), 3 replications at the central point of the design
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(run No. 15-17) for experimental error determination. All the experimental units (run)
were replicated 3 times.
A full second-order polynomial model of the type shown in Eq. 2 was used to
evaluate the yield (response variable, y) as a function of dependent variables (x) namely
temperature (°C) (denoted by subscript 1), concentration (° Brix) (denoted by subscript
2), shear rate (s-1
) (denoted by subscript 3) and their interactions.
2
333
2
222
2
112323
131312123322110
xb xb xb xb
xb xb xb xb xbb y
+++
++++++=
(2)
The results were analyzed using the Statistical Analysis System (SAS v.8) software.
Non-linear regression analysis (Marquardt Hougaard) was used for estimating the
consistency index (k).
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Table 2. Selected factors and their levels for the first factorial design with the CCRD
design.
Standardized Coded Levels Actual Uncoded levels
Run
X1 X2 X3
Temperature
(°C)
Concentratio
n
(°Brix)
Shear Rate
(S-1)
1 -1 -1 -1 20 12 300
2 1 -1 -1 70 12 300
3 -1 1 -1 20 24 300
4 1 1 -1 70 24 300
5 -1 -1 1 20 12 800
6 1 -1 1 70 12 800
7 -1 1 1 20 24 800
8 1 1 1 70 24 800
9 1.682 0 0 87 18 550
10 -1.682 0 0 3 18 550
11 0 1.682 0 45 28 550
12 0 -1.682 0 45 6 550
13 0 0 1.682 45 18 970
14 0 0 -1.682 45 18 130
15 0 0 0 45 18 550
16 0 0 0 45 18 550
17 0 0 0 45 18 550
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RESULTS AND DISCUSSIONS
Rheological Characterization of Mango Puree
Flow behavior index
Flow behavior index (n) of different combinations of independent variable were
computed from Eq. 1 and are shown in Table 3. The values of the flow behavior index
vary from 0.377 to 0.436 was observed in our studies on mango puree (mango variety,
Tommy Atkins), and 0.26 to 0.35 and average value of 0.286 was reported by (Manohar
et al. 1990), while Gunjal and Waghmare (1987) reported 0.309 to 0.334 and 0.314 to
0.354 within the temperature range 40 to 80°C for varieties Baneshan and Neelum.
Varietal differences, measurement types and equipment could be factors that may have
contributed to the discrepancies. Temperature and concentration had no significant
(p>0.05) on effect flow behavior index, revealed by the regression analysis. These results
are in conformity with that of Manohar et al. (1990) on mango pulp concentrate. Based
on the flow behavior index (n), mango puree used in this study was characterized as a
shear thinning fluid.
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Table 3 Second order design matrix and rheological parameters: flow behavior index
(n), yield stress ( 0σ ) and consistency coefficient (K).
Coded Parameters
RunX1 X2 X1*X2 X1² X2² n
0σ
(Pa)
K
(pa sn)
1 -1 -1 1 1 1 0.377 7.46 9.01
2 1 -1 -1 1 1 0.412 3.46 4.31
3 -1 1 -1 1 1 0.406 8.23 9.37
4 1 1 1 1 1 0.445 3.68 4.56
5 1.4 0 0 2 0 0.412 3.79 5.04
6 -1.4 0 0 2 0 0.391 11.49 13.50
7 0 1.4 0 0 2 0.418 5.33 6.55
8 0 -1.4 0 0 2 0.436 2.51 3.03
9 0 0 0 0 0 0.393 6.81 7.20
10 0 0 0 0 0 0.405 6.21 7.41
11 0 0 0 0 0 0.414 6.02 7.69
The main effects of temperature, concentration and shear rate on viscosity of mango
puree were investigated using response surface analysis. Regression models were
generated and the parameters that were not significant were dropped from the regression
equation. The analysis of variance shows significant (p < 0.001) quadratic effects of the
main variables effects and no significant (p > 0.05) interaction of cross products. The
lack of fit was also significant (p>0.05). Equations 3 to 5 were used to predict the
rheological parameters of mango puree at various independent variables used in this
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study. The second-order surface models derived from the regression analysis are as
follows:
Viscosity
Viscosity was computed based on the Herschel-bulkley’s model and response surface
analysis was used to characterize the effect of concentration (°Brix) and shear rate as
shown in Fig. 1. The predictive equation for viscosity was acquired from a non-linear
equation as shown in Eq. 3:
( )98.0
0703.70433.6076.70307.10226.3037.23.0
2
2
3
2
2
2
1
321
=
−+−−−
+−−−+−−=
R
x E x E x E x E x E x E ν
(3)
where ν represent viscosity at different temperatures ( 1 x ), concentrations ( 2 x ) and shear
rate ( 3 x ) at constant temperature. The canonical analysis indicated that the predicted
response surface is shaped like a saddle as depicted in Fig. 1. The model predicts that the
viscosity was at minima when temperature = 70°C, concentration = 16° Brix and shear
rate = 594 s-1
. Viscosity tends to increase at high concentrations and decreases at higher
shear rate.
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Fig. 1 Effect of concentration (°Brix) and Shear rate (s-1
) on viscosity of mango puree.
Yield stress
The yield stress was obtained for experimented data (shear stress vs. shear rate), which
best fitted the Herschel-bulkley’s models. Response surface analysis (Fig. 2) was
conducted with the yield stress data and the predictive equation is shown as follows (Eq.
4):
)95.0(
022.203x-E07.199.018.072.1
2
2
2
2
1210
=
−−++−=
R
x E x xσ (4)
where 0σ represent yield stress at different temperatures ( 1 x ) and concentrations. Yield
stress tends to increase with increase in concentration and decrease with temperature.
The model predicts that the viscosity was at minima when temperature = 90°C and
concentration = 21° (Brix). The yield stress tends to increase at higher concentrations
50
525
1000
Shear Rate
2
16
30
Concent rat i on
Vi scosi t y
-0. 150
0.033
0.217
0.400
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and decreases at high shear rates. Yield stress ranged from 2.5 to 11(Pa) in this study for
mango puree. Our values were lower than those reported by Manohar et al. (1990) that
ranges from 2 to 180 Pa, while greater than those reported by Bhattacharya (1999) (0.8 to
4 Pa).
Fig. 2 Effect of temperature and concentration (°Brix) on yield stress of mango puree.
Consistency index
The consistency values were computed for shear stress and shear rate data by nonlinear
regression analysis. A predictive model was generated through response surface analysis.
( )96.0²
025.23.014.109.123.02.3 2
2
2
121
=
−−−++−=
R
x E x E x xk (5)
5. 0
17. 5
30. 0
Concent rat i on
5. 0
47. 5
90. 0
Temperature
Yi el d St ess
-3
2
7
12
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where k represent consistency index at different temperatures ( 1 x ) and concentrations.
Figure 3 shows similar behavioral characteristics as yield stress (Fig. 2). The consistent
index values obtained in this work ranged from 3 to 14 Pa*sn whereas the values were in
close agreement with that reported by Manohar et al. (1990) (3 to 19 Pa*sn). The model
predicts that the viscosity was at minima when temperature = 81°C and concentration =
22° (Brix).
Fig. 3 Effect of temperature and concentration (°Brix) on consistency index (K) of
mango puree.
2
16
30
Concent rat i on
5. 0
47. 5
90. 0
Temperature
Consi st ency I ndex
-5.00
1.67
8.33
15. 00
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Time-dependent flow behavior
A typical hysteresis loop indicating the thixotropic behavior (Fig. 4) of mango puree was
observed in this study. The thixotropic behavior shows that no equilibrium was attained
between structural breakdown and reformation processes thus, the structural interaction
decreases continuously with time and the mango puree suffers permanent change as a
result of shear. The area within the hysteresis loop enclosure indicates the degree of
structural breakdown due to shearing. The curve depicts an initial increased rate
followed by a decrease in rate, which confirms that mango puree exhibits shear thinning
behavior with time as also shown in Fig. 1.
12000 200.0 400.0 600.0 800.0 1000
shear rate (1/s)
90.00
0
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
s h e
a r s t r e s s ( P a )
Fig. 4 A typical time-dependent non-Newtonian thixoropic loop for mango puree.
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Differential scanning calorimetric (DSC) analysis
Mango puree crystallization, melting and different step change (transition) peaks at
different levels of concentrations are shown in Table 4. Mango puree exhibits simple
thermograms after cooling and heating in the DSC with well defined single crystallization
and melting peaks (Fig. 5). Increase in total soluble solid (TSS) concentrations shows
shift in peak temperatures toward lower temperature region. Mango puree concentrated
to 10°Brix TSS has a melting temperature of about 4°C, although, by increasing the
concentration to 30°brix, the melting temperature decreased to 0.28°C.
Table 4 Effect of total soluble solid concentration on glass transition temperature of
mango puree.
T1 T2 T3 TC Tm Concentration
(°Brix) (°C)
Sample Mass
(mg)
-63.85 -60.07 -55.50 -15.75 3.5010
(0.6364) (1.3294) (0.9899) (3.0406) (0.3041)15.35
-62.12 -56.93 -51.70 -14.00 2.6412
(0.9750) (0.2858) (0.9644) (0.4243) (0.6505)12.3
-63.14 -57.09 -50.96 -15.68 1.3720
(4.3560) (1.9882) (0.3569) (0.3567) (0.4164)12.3
-63.30 -55.25 -50.35 -17.60 0.3428
(7.9196) (3.7477) (4.1719) (0.7071) (0.1202)13.8
-56.60 -51.63 -46.47 -17.77 0.28
30 (0.0000) (0.2464) (0.6351) (1.1504) (0.2013) 14.05
T1=Onset glass transition temperature, T2 = midpoint glass transition temperature, T3 end point glass
transition temperature, TC = crystallization temperature and Tm = melting temperature; Standard deviation
in parenthesis.
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The effect of soluble solid concentration on mango puree crystallization appeared rather
erratic, although, it tends to increase with increase in concentration, probably due to
decreased water activity of the product.
Fig. 5 Cooling and heating thermgram of mango puree at different levels of
concentrations.
Figure 6 shows thermogram depicting glass transition profiles of different concentrations
of mango puree. The glass transition temperatures increase with increase in TSS
concentration in mango puree. This could be attributed to increases water in content as
concentration of TSS increases. Glass transition temperature increased from –60°C to –
52°C as concentration changed from 10 to 30°Brix, respectively. In general, molecular
stability is achieved within the glass transition temperatures, and quality loss is higher for
a product stored from this region.
-3.5
-2.5
-1.5
-0.5
0.5
H e a t F
l o w ( W / g )
-40 -20 0 20 40
Temperature (°C)
––––––– Mango 30 – – – – Mango 12 ––––– · Mango 20 ––– – – Mango 28 ––– ––– Mango 10
Exo Up Universal V3.7A TA Instruments
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Fig. 6 Glass transition profiles for mango puree at different TSS concentration.
CONCLUSIONS
The flow behavior index (n) varies from 0.37 to 0.44 and does not significantly change at
all levels of total soluble solid concentration range used in this study. Mango puree was
found to be thixotropic time-dependent fluid. The crystallization and melting peaks were
affected by the change in total soluble solid concentration of the mango puree. The glass
transition temperature increases from –60 to –52°C from concentration 10 to 30°Brix
respectively.
ACKNOWLEDGEMENT
We gratefully acknowledge the financial support from the National Science and
Engineering Research Council (NSERC) of Canada.
-0.25
-0.20
-0.15
-0.10
-0.05
H e a t F l o w ( W / g )
-90 -80 -70 -60 -50 -40
Temperature (°C)
––––––– Mango 30 – – – – Mango 12 ––––– · Mango 20 ––– – – Mango 28 ––– ––– Mango 10
Exo Up Universal V3.7A TA Instruments
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