physical and rheological properties of mango puree

7/23/2019 PHYSICAL AND RHEOLOGICAL PROPERTIES OF MANGO PUREE

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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.



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.,



2

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



3

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).



4

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.



5

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



6

(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).



7

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



8

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.



9

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



10

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.



11

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



12

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



13

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



14

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.



15

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.



16

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



17

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



18

REFERENCES

Aguillera, J. M. A. and D. W. Stanlet. 1999. Microstructural Principles of Food

Processing and Engineering , 2nd

edition, Gaithersburg, Maryland: Aspen Publishers,

Inc.

Bhattacharya, S. 1999. Yield stress and time-dependent rheological properties of mango

pulp. Journal of Food Science 64(6): 1029-1033.

Biliaderis, C. G. 1983. Differential scanning calorimeter in food research- A Review.

Food Chemistry 10: 239-265.

Box, G. E. P. and N. R. Draper. 1987. Empirical Model-building and Response

Surfaces. NY: John Willey and Sons Inc.

FAOSTAT. 2000. Food and Agriculture Organization, Rome.

Gunjal, B. B. and N. J. Waghmare. 1987. Flow characteristics of pu;p, juice, and nectarof ‘Baneshan’ and ‘Neelum’ mangoes. Journal of Food Science and Technology 24:

20-23.

Holdsworth, S. D. 1971. Application of rheological models to the interpretation of flow

and processing behavior of fluid food products. Journal of Texture Studies 2: 393-

418.

Holland, B., A. A. Welch, I. D. Unwin, D. H. Buss, A. A. Paul and D. A. T. Southgate.1991. The Composition of Foods 5

th edition . Cambridge: Royal Society of

Chemistry and Ministry of Agriculture, Fisheries and Food.

Manohar, B., P. Ramakrishna and R. S. Ramteke. 1990. Effect of pectin content on flow

properties of mango pulp concentrates, Journal of Textural Studies 21: 179-190.

Oliveira, J. C., P. M. Pereira, J. M. Frias, I. B. Cruz and W. M. MacInnes. Application ofthe concepts of biomaterials science to the quality optimization of frozen foods. In

Processing Foods: Quality Optimization and Process assessment,ed. F. A. R.

Oliveira, J. C. Oliveira, 107-130 . Boca Raton, Florida:CRC Press LLC.

Parks,G. S. and S. B. Thomas. 1934. Heat capacities of crystalline, glassy and

undercooled liquid glucose. Journal of Chemical Engineering Society 56: 1423.

Rao, M. A. 1995. Rheological properties of fluid foods. In Engineering Properties of

Foods, edited by Rao, M. A. and S. S. H. Rizvi, 1-53. New York: Marcel Dekker,Inc.

Roos, Y. 1987. Effect of moisture on the thermal behavior of strawberries studied using

differential scanning calorimetry . Journal of Food Science 52: 146-154.



19

Rielly, C. D. 1997. Food rheology. In Chemical Engineering for the Food Industry, ed.P. J. Fryer, D. L. Pyle and C. D. Rielly 195-233. New York: Blackie Academic and

Professional.

Singh, R. P. and D. R. Heldman. 1993 Introduction to Food Engineering, 2

nd

Edition, SanDiego: Academic Press.

Slade, L. and H. Levine. 1991. Beyond water activity: recent advances based on analternative approach to the assessment of food quality and safety. Critical Review.

Food Science and Nutrition 30: 115-117.

Tiu, C. and D. V. Boger. 1974. Complete rheological characterization of time-dependent

products. Journal of Texture studies 5: 329-338.

White, G. W. and S. H. Cakebread. 1966. The glassy state in certain sugar containing

food products. Journal of Food Technology 1: 73-77

physical and rheological properties of mango puree

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