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CHAPTER – 6

CHARACTERIZATION OF INSTANT SOUP MIX

6.1 INTRODUCTION

Convenience is a multifaceted concept and often listed as the most important

factors that determine the food of choice apart from the cost, health, sensory

acceptability and related concerns (McIntosh, 1996; Rappoport et al., 1993; Steptoe et

al., 1995; Scholderer and Grunert, 2005). Many food manufacturers now use

scientific approach in order to achieve the best product formulations (Granato et al.,

2011). Convenience also decides to a greater extent when, where, what and how to eat

foods (Costa et al., 2007). As a consequence, the demand of ready to eat or ready to

cook minimally processed products has noticeably increased during the recent years

(Lee et al., 2005; Kilinc et al., 2008).

The problem of protein-energy malnutrition in under developed and

developing countries has now transcended socio-economic status in its effects. Thus,

the attentions are being given towards exploring underutilized food sources. Brocken

rice is a valuable byproduct of rice milling industry. Price as well as the utilization

problems has been often faced by the associated entrepreneurs in disposing off their

produce. Brocken rice may thus be better source of nutritive starch as the quality of

rice protein which surpasses that of wheat (Prasad et al., 2010a; Prasad et al., 2010b)

and also better than pure corn starch (Singh and Prasad, 2013b), thus broken rice flour

was considered as suitable nutritive ingredient for various food formulations.

High consumption of fruit and vegetables, as in the Mediterranean diet,

contributes to an increased intake of key nutrients, such as vitamins, minerals,

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antioxidant compounds and dietary fibre, with subsequent beneficial effects on health

(Benetou et al., 2008; Key, 2011). Moreover, the presence of bioactive compounds in

fruits and vegetables has been considered of nutritional importance in the prevention

of chronic non communicable diseases (NCD) such as cardiovascular disease (CVD),

diabetes, cancer and also the neurological disorders (Kalt et al., 1999; Willet, 1994).

The utilization of vegetable as protein source continued to attract attention globally

because of the presence of affordable nutrients particularly to feed low income

populations mainly to combat the protein energy malnutrition problems (Prasad and

Singh, 2014). The pre and processing treatments especially dehydration have been

reported to influence the quality of products (Kulkarni and Govindene 1994;

Waghmore et al., 1999; Krokida and Maroulis 2001). Attempts were also reflected for

preserving the nutritional value of the processed vegetables (Allende et al., 2006) and

becoming the preferred choice of the people due to having rich dietary fibre, vitamins,

minerals, antioxidant and phyto-chemical of physiological role (Suvarnakuta et al.,

2005; Prasad and Sharma, 2012; Janve et al., 2014; Arnao et al., 2001; Kalt et al.,

1999; Willet, 1994).

Dietary sources of essential elements are important for correct physiological

functions of the human body. American Heart Association (AHA) has recommended

the consumption of fat as per their fatty acid compositions. Blended fats or oils are

often referred to as a new generation fat. Also it is considered as the nutraceutical

foods or part of foods that provide health benefits beyond supplying the basic

nutrients, including the potential for prophylactic and curative measures in combating

few diseases (Akoh, 2002; Singh et al., 2014).

Soup is primarily a liquid a heterogeneous food category food, predominantly

served hot, which is prepared using vegetables or meat with stock, juice or water with

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some thickening agent. Soups are classified into two main groups: clear soup and

thick soups. Clear soups are mainly prepared from the use of clear extracts of edible

animal or plant parts while cereal or pulse flour, starch; cream or eggs for the thick

soup (Singh and Prasad, 2014d).

Instant soups are a wide group of dried foods, which play an important role in

the nutrition of people as they satisfy the present and future consumer requirements.

Vegetable soup is a high water containing food. An easy and convenient way of

making a soup is to use a soup base in the form of granule and powder material apart

from the cumbersome way of peeling vegetables, cutting, chopping, hot extraction,

cooking with thickening agent, seasoning and garnishing further before serving. Soup

is often served as the starter, first course or entree before the main meal as it

stimulates appetite and provides quick nourishment, which is mainly responsible for

the improvement of appetite and gastrointestinal responses (Cecil et al., 1999). Also,

it may be considered as the best nutrient vehicle for the all sections of the society.

The extent of starch used in thick vegetable soup is mainly responsible for the

sensory mouth feel by altering the viscosity during reconstitution and subsequent

thermal treatment in its preparation. It is a useful and important to have the all the

nutritional components in the foods to be developed. As starch is the rich source of

carbohydrate but somewhat lacking in the protein, fat, vitamins, minerals,

antioxidants and phenolic compounds. The addition of leaf powder and blended fat

not only improves the nutritional quality of soup but may also enhance the cost

effectiveness with the sensory acceptability.

The commercial production of soups depends on their physicochemical and

rheological behavior during and after preparation. Rheology is the study of

deformation and flow of matter (Barnes et al., 1993) and found very useful for food

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development, processing, handling and associated equipment design (Dak et al., 2006;

Boger and Tiu, 1974; Kaya and Belibagli, 2002; Velez-Ruiz and Barbosa-Canovas,

1998). Even the rheological parameters are used as powerful tool in understanding

changes in food structure during processing (Holdsworth, 1993; Mizrahi, 1979;

Ditchfield et al., 2004; Guerrero and Alzamora, 1997). It is, therefore, important to

understand the ingredient interactions that are critical to the functionalities they

impart to food products both in dry as well as in the reconstituted soup form.

The prepared cost effective, storage stable, quality dry soup mix should show

no sign of caking, the presence of which decreases the consumer acceptability (Castro

et al., 2006; Chen and Wang 2006) even reflects poor performance on machine.

Higher water activity accelerates caking phenomena and leads to increase in lipid

oxidation, enzymatic activity, microbial growth and thus deteriorates faster

(unpublished data). Intrinsic as well as extrinsic factors largely affects the caking

phenomenon (Chen and Wang 2006). Higher temperature and water activity even

affect the optical characteristics and decides the sensory acceptability of powdered

mix.

Many research reports reflect the rheological properties of starch suspensions

(Bhattacharya and Bhat, 1997; Bhattacharya and Bhattacharya, 1994; 1996;

Biliaderis, 1991; Dail and Steffe, 1990a; 1990b; Ramaswamy et al., 1995; Sandhya

and Bhattacharya, 1995; Taylor, 1979), but very limited cited information is available

on the rheological aspects of vegetable soup. Dynamic shear rheological tests have

been used to characterize or classify the viscoelastic properties of macromolecular

dispersions (Rao, 1999). The applications of the rheological characterization coupled

with the mathematical modeling made it be possible to design and operate in a more

scientific way, thus greatly reducing the amount of trial and error experiments.

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Dynamic rheological measurements during manufacturing can be useful in product

quality control. The modeling and description of the rheological properties of various

food materials has always played an important role in food engineering. Due to the

inherent importance of rheological properties in food processing, rheological models

are fitted to data in order to assess the suitability of model in describing the

characteristics of the soup. Numerous rheological models have been used to describe

the flow behavior of food such as Newtonian (one parameter), Power law, Bingham,

and Casson (two parameters) and Herschel–Bulkey models (three parameters). In

general, most fluids food does not exhibit Newtonian behavior. The Power law model

has been used most extensively to describe the rheological behavior (Gratao et al.,

2007; Steffe, 1996). Rheological behavior is influenced by temperature and

concentration during the juice processing. Thus, considering the increasing consumer

demand for soup like foods, under the present work rheological properties of soup

have been assessed.

The mixture of starch, vegetable and fat sources with the other essential

constituents such as salt and seasonings play the vital role in providing the structure

and body of prepared soup. Broken rice flour as chief source thickening or gelling

agent exhibit viscous slurry type materials on the reconstitution and heating in

presence of excess water. Applying the thermal treatment, starch present in the slurry

swells with the leaching of amylose, which may be referred to as the part of pasting

process and leads to gelatinization, which corresponds to the loss of crystalline starch

granules on exceeding 60 °C temperature of the suspension. Loss of birefringence and

X-ray diffraction pattern on change in the moisture content with the structural changes

in the granules (Eliasson and Larsson, 1993; Hoover, 2001; Williams and Bowler,

1982) are very much evident and the possibility of this change with the mixing of

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other non polar materials are scarce in the available literature for the soup systems.

Several methods of component elucidation in terms of physical, chemical,

morphological, rheological, optical and sensory changes of pure starch systems are

available. The associated features of rice flour, vegetable powder and oil component

system in the form of soup mix are explored as part of the characterization part for

both the dry as well as the reconstituted soup form under the present work. The

techniques, such as Fourier transform infra red spectroscopy (FTIR), scanning

electron microscopy (SEM) and X-ray diffraction are also explored (Lim et al., 2001;

Donovan et al., 1983; Kiseleva et al., 2003; Ziegler et al., 2003).

6.2 MATERIAL AND METHODS

The soup ingredients (rice flour, moringa powder and blended oil) considered

as variables for their optimization levels using response surface methodology (RSM)

and the fixed ingredients combination as decided for the instant soup mix (Table 5.6,

Chapter 5) dealt in previous chapter (Chapter 5) was used to prepare the dry mix and

characterized on the basis of selected engineering properties such as physical,

morphological, chemical, nutritional, optical, rheological, and sensory aspects. The

optimized soup mix prepared sample was stored in a polyethylene sealed pouches at

refrigerated temperature (4±2 °C) for at least five days before any experimentation

proceeded further.

6.2.1 Dimensional characteristics

The particle size analysis for the soup mix was done using laser diffraction

particle size analyzer (Malvern Instrument Ltd., Malvern, England). Small quantity

(0.2 g) of the soup mix was placed in a cuvette cell containing the dispersion liquid

and positioned in the laser path with constant stirring for two minutes by the auto in

situ stirrer supplied with the instrument before noting the observations. Size

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distribution was quantified as the relative volume of particles in size bands presented

as size distribution curves. The cumulative weight percent particle size plots and the

mean particle size in micro meter were provided by the instrument’s software

(WingSALD II-2300 for English, US, V3.1). The measurements were done in

triplicate.

6.2.2 Morphological characteristics

Scanning electron micrographs of optimized soup mix with the used dry

ingredients were acquired in the range of 500 to 3500 magnifications using scanning

electron microscope (Jeol JSM-6100, Jeol Ltd, Tokyo, Japan). The sample for

acquiring the micrographs was prepared and mounted on double sided tape on the

used aluminum stubs. Further the adhered samples were coated with gold–palladium

(60:40) at an accelerated voltage of 15 kV in accordance with the method described

by Suksomboon and Naivikul (2006). The obtained pictorial representations of

samples were visually compared for the associated changes during blending of mix.

6.2.3 Gravimetric characteristics

The bulk density (BD) of the soup mix sample was evaluated using the

method suggested by Williams et al., (1983). For bulk density determination, a

circular container of known volume was filled with the sample and gently tapped. The

excess sample was leveled off and the content was weighed. The bulk density was

calculated as the ratio of mass of contents to volume of container. Average of three

replications was reported in kg.m-3

. During the experiments care was taken to avoid

compaction of the sample in the container and also the container was filled to full

volume.

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6.2.4 Frictional characteristics

The angle of repose (AOR) was determined using the relationship:

(6.1)

Where, h and d are the height and diameter of the heap in mm.

Figure 6.1 Angle of repose unit setup

The static coefficient of friction (COF) was determined for four frictional

surfaces namely glass (COFG), galvanized iron sheet (COFGI), plywood surfaces

with horizontal movement (COFPAR) and vertical movement (COFPER). A plastic

cylinder of 50 mm diameter and 60 mm height was placed on an adjustable tilting flat

plate faced with the test surface and filled with nearly 100 g sample. The cylinder was

raised slightly to avoid touching the surface. The structural surface with material

filled cylinder on it was inclined gradually, until the cylinder just started to slide

(Singh and Prasad, 2013a).

6.2.5 Chemical Characterization

The recommended methods of the Association of Official Analytical Chemists

(AOAC, 2000) were adopted for the determination of moisture, crude protein, crude

fat and ash content. Crude protein (N×6.25) was determined adopting the Macro-

Kjeldahl method. Crude fat was determined by exhaustively extracting the dried soup

mix with petroleum ether (40-60°C) in Soxhlet apparatus. Ash content was determined

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by incinerating the pre dried sample placed in a muffle furnace maintained at 550°C

for 6 hours until completion of ash formation. The amount of carbohydrate was

assessed using difference method. The energy value was calculated by multiplying the

mean values of the crude protein, fat and carbohydrate by their physiological energy

change coefficients as 4, 9 and 4, respectively, taking the sum of the products and

expressing the result in kilocalories (Edem et al., 1990).

For the chlorophyll content estimation 1g of sample was weighed and ground

using mortar and pestle with the addition of 20 ml of 80% acetone (Holden, 1960).

The ground sample was centrifuged at 5000 rpm for 5 min. The supernatant was

repeatedly made and collected in volumetric flask till the residue became colorless.

The collected supernatant was made up to a known volume i.e. 100 ml. The optical

density was measured at absorbance 663 and 645 nm against used solvent (80%

acetone) as blank. The total chlorophyll content was expressed in mg/g.

Total antioxidant capacity (TAC) of the samples was measured on the basis of

the scavenging activity of the stable 1, 1- diphenyl- 2-picrylhydrazyl (DPPH) free

radical. A known aliquot of extract was added to 5.0 ml of 0.1 mg methanolic solution

of DPPH. Absorbance at 517 nm was measured after 30 minutes of incubation. Free

radical scavenging activity measured on DPPH radical was expressed as Trolox

equivalent mg/g (Bala et al., 2011). Total phenol content (TPC) was estimated as per

the method reported by Malik and Singh (1980).

6.2.6 Rheological Characterization

6.2.6.1 Cake strength

Cake strength test was performed using texture analyzer plus powder flow

analyzer (Stable Micro Systems, Surrey, United Kingdom). The test began with two

conditioning cycles. The blade leveled the top of the powder column and measured

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the height of the column, after which it moved down through the column and

compacted the powder to a predefined force (2000 g). When the blade reached the

required force it sliced up through the powder and repeated the compaction cycle four

more times. At the beginning of every cycle the blade measured the height of the

column and the height of the powder cake was recorded when the target force was

reached. The fifth time the target force was reached the blade cut through the formed

powder cake at the bottom of the vessel and measured the force required to perform

the task. This force was recorded as the cake strength and represented the work

required to cut the cake (g.mm) and the mean cake strength was the average force to

cut the cake expressed in grams. The column height ratio (current cycle column height

divided by the initial column height) and the cake height ratio (current cycle cake

height divided by initial column height) were recorded to give information about the

settlement and compaction of the powder column.

6.2.6.2 Pasting properties

Pasting properties of rice flour were studied by using rapid visco analyzer

(RVA, Newport Scientific Pty Ltd, Australia). 28 g aqueous dispersion with the

sample (~3g) was equilibrated at 50 °C for one minute. Viscosity profiles of flour

from different samples were recorded and the temperature–time conditions included a

heating step from 50 to 95 °C, a holding phase at 95 °C, a cooling step from 95 to 50

°C. From the Rapid Visco Analyzer (RVA) profiles, pasting temperature, peak time,

peak viscosity, trough, final viscosity, breakdown (peak viscosity minus trough

viscosity) and setback (final viscosity minus trough viscosity) were calculated.

6.2.6.3 Rheological properties

Rheological properties of the soup were determined applying small

deformation dynamic oscillatory measurement technique with the use of Dynamic

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Rheometer (Model MCR301, Anton Paar GmbH, Austria) having the parallel

stainless steel plates of 4 cm diameter for placing the sample with software based

peltier temperature control. Immediately after reconstitution and soup making, the

soup was poured on the lower plate and the upper plate was lowered to maintain the

gap of 1mm thickness. The excess sample was removed and exposed surface was

possibly covered by applying the silicon oil to avoid the chances of any desiccation of

sample during the measurement. The measurements were made at 45±0.1°C. The

linear viscoelastic region (LVR) was first established by running an amplitude sweep

test (1.0 Hz, strain between 0.1% and 100%). The viscoelastic properties of the

samples were quantified by measuring the following dynamic rheological parameters:

storage or elastic modulus (G´), loss or viscous modulus (G´´) as a function of

frequency. In rotational mode, viscosity flow curves were obtained at shear rates

between 0.01 and 1000 s-1

(Thombre and Gide, 2013). The apparent viscosity was

determined as a function of shear rate and the obtained data were fitted to rheological

models (Table 6.1) and consistency coefficient and flow behavior index values were

calculated accordingly (Prasad et al., 2013).

Brookfield viscometer, Spindle No. 2 at 30 rpm was used check the viscosity

of optimized soup (Prasad et al., 2013) at a controlled temperature of 45°C. A 400 ml

beaker was used for all measurements with the guard leg on and enough sample

amounts was added to just cover the immersion grooves on the spindle shafts.

Readings were taken after stabilizing the dial reading of the viscometer and

appropriate factor was applied to get the viscosity of the sample. All viscosity

measurements were carried out immediately after cooking. Each measurement was

replicated three times to report the average viscosity. The empirical data obtained

were converted into viscosity functions (Mitschka, 1982; Prasad et al., 2013).

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The experimental data of soup was fitted to several rheological models,

namely, Bingham, Oswald or Power law, Herschel Bulkely, Casson, Casson Steiner,

Carreau Yasuda, Carreau Gahleitner and Vinogradov Malkinas (Table 6.1). The shear

rate, shear stress and viscosity data were fitted as per subjected selected common

rheological models (Table 6.1). The extent of fitting to any model was adjudged by

finding the coefficient of multiple determinations (R2), root mean square error

(RMSE), chi square (χ2) and mean relative percent error (%E). The flow behavior

index and consistency index (for Oswald or Power law and Herschel Bulkely models)

were estimated by employing the technique of non-linear analysis. The yield stress of

the soup was determined experimentally using the stress relaxation technique

(Keentok, 1982; Bhattacharya and Bhattacharya, 1996); it was also calculated

according to the Casson model, using the linear regression technique (Snedecor and

Cochran, 1968). The best fit model was selected on the basis of the statistical

parameters as R2, RMSE, χ2

and %E (Prasad et al., 2013).

Table 6.1 Rheological models used

S. No. Model Name Equation

1 Bingham

2 Oswald or Power law =K

3 Herschel Bulkely

4 Casson

5 Casson Steiner

6 Carreau Yasuda

7 Carreau Gahleitner

8 Vinogradov Malkin

Where, - shear stress; ὴ - viscosity; – shear rate; n, K, p, a, b - constants

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6.2.7 Optical Characterization

The optical characteristics of the soup mix was evaluated using the Hunter

Colorimeter (Gretag Macbeth, Model No. i5, USA) in terms of L, a and b, where, L

corresponds to the luminance or brightness and a, b to the chromaticity, ‘a’ value

particularly represents the red - green component from positive to negative values; ‘b’

value represents the yellow - blue component in similar ways (Prasad et al., 2010a;

Prasad et al., 2010b).

6.2.8 X-ray diffraction (XRD) characteristics

The X-ray diffraction technique was applied to obtain the X-ray diffraction

(XRD) pattern using an X-ray diffractometer (Rigaku Denki Co. Ltd., Japan) with the

following operating conditions: 40 kV, 30 mA using Cu-Kα X-rays of wavelength (λ)

1.54056 Å and data was taken for the 2θ range of 10–40°with a resolution of

0.05°step size (Prasad et al., 2012).

6.2.9 Fourier transform infrared (FTIR) spectroscopy

Transmission infrared spectra of the films were recorded at room temperature

using a FTIR spectrometer (Perkin–Elmer, Beaconsfield, Buckinghamshire) from 16

scans in the range 700–4000 cm-1

. The sample was placed directly in the sample

holder. A background was collected before each sample was analyzed then subtracted

from the sample spectra prior to further analysis. After every scan, a new reference air

background spectrum was taken. The ATR crystal was carefully cleaned between

samples with hot water and acetone. The cleaned crystal was examined for spectral

authenticity to ensure that no residue remained from the previous sample.

6.2.10 Sensory characteristics

The sensory evaluation of the dry instant soup mix sample was carried out on

9 point hedonic rating scale (Ranganna, 2000). A semi trained panel from the

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members of Food Engineering and Technology department were used for the purpose.

Panelists were obtained the instructions regarding the evaluation procedure in both

written and verbal form before quoting their judgments (Imad et al., 1999). The

sensory attributes considered in the evaluation were sensory color, mouthfeel, flavor

and overall acceptability (Meilgaard et al., 1999).

The consumer acceptance test was conducted in our laboratory with untrained

panelists recruited from the staff and students of the Sant Longowal Institute of

Engineering and Technology, Longowal campus. The sensory color, mouthfeel,

flavor and overall acceptability of the instant soup were evaluated (Appendix – I) on a

9-point hedonic rating scale in which 1 for ‘dislike extremely’ and 9 for ‘like

extremely’ (Watts et al., 1989). The average and the mean values of the scores for

each of the attributes were computed and analyzed statistically.

6.2.11 Reconstitution and Soup Preparation

Soup mix was prepared from the developed and optimized standard recipe

(Table 6.2). The moisture content of developed dry soup mix was found to be

8.95±0.55 % with appreciable amount of protein (7.79±0.46 %) and fat (9.11±0.28

%). 12 gm of dry soup mix was allowed to reconstitute in the small quantity of

distilled water. The prepared slurry was cooked in a steam kettle maximum to 5

minutes with the constant stirring. The prepared soup was then subjected further for

the characterization on the basis of sensory characteristics and rheological behavior.

The prepared soup was tested for the subjected parameters within 10 minutes time.

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Table 6.2 Ingredients percentage in soup mix and after reconstitution

Ingredients Soup mix Reconstituted Soup

Rice flour, % 45.94 5.537

Moringa powder, % 7.38 0.89

Blended Oil, % 4.36 0.526

Carrot, % 15.35 1.85

Peas, % 7.88 0.95

Salt, % 5.39 0.65

Sugar, % 5.39 0.65

Spices and condiments, % 8.30 1.00

6.2.12 Cost Analysis

The term ‘cost’ means the amount of expenses incurred on or attributable to

specified thing or activity. Institute of Cost and Work Accounts (ICWA), India define

cost measurement in monetary terms as the amount of resources used for the purpose

of production of goods or rendering services. Costing is very important as the cost of

a product can decide its profit or loss. There are mainly two costs involved in

determining the cost of a product i.e. direct cost; the cost of those items that become

part of the end-product and indirect cost; all expenses incurred in running a business

and that which cannot be directly identified with the end product are indirect costs.

A realistic and comprehensive knowledge on costing and pricing is required to

build the financial management capabilities of entrepreneurs. This will help in

running the enterprise successfully and enable one to give due importance to costing

and pricing. Optimum pricing of any product should be done so that the product finds

a place in the market because more the price, higher the profitability. For pricing a

product/ service, an entrepreneur could exercise for a desired margin and all possible

efforts to make the price competitive (Awasthi et al., 2006).

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A systematic analysis of the existing food factories cost data can lead to useful

results concerning the particular characteristics of the food industry and to reveal

simple and rapid preliminary cost estimations needed in various studies (Marouli and

Maroulis, 2005). The importance of costing is to be more specific in the discharge of

cost of material, control of labor cost, control of indirect expenses, estimated budget,

price determination, desired revenue and profit and other external factors which affect

the price.

In this study, the theory of the comparison was explained and its boundary

conditions were fixed, in order to be representative of a typical food product.

Afterwards, the unit costs of the soup were calculated, from the purchase of raw

materials to the distribution and storage of the end product.

We derived the name and the concept of Process Target Cost (PTC) from

Target Costing (TC), a strategic accounting system introduced in literature for the

management of product costs (Ewert and Ernst, 1999). A central aspect of TC is the

utilization of reverse costing, in which estimations of selling price and of the profit

margin is used to define the maximum allowable costs for a new product: this

mechanism is also referred to as market driven costing (Cooper and Slagmulder,

1997).

Table 6.3 List of costs considered for the cost analysis of instant soup mix

Cost category Cost description

Raw materials Purchasing cost of raw material

Pre production logistic cost Transportation and storage cost

Production cost Direct and indirect cost

Machine operating cost

Energy cost

Packaging cost

Preventive outages

Post production logistic cost Handling cost

Transportation and storage cost

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Table 6.4 Hypothesis for the cost analysis of instant soup mix

Hypothesis

Transportation costs Labour cost, 40%

Fuel cost, 20%

Maintenance cost, 10%

Amortization cost, 20%

Others, 10%

Handling costs Labour cost, 80%

Machinery cost, 20%

Inventory costs Amortization cost, 50%

Energy costs, 30%

Maintenance cost, 20%

With the boundary conditions hitherto defined we have then proceeded with

the evaluation of effective cost, the total unit costs of the product. These costs were

split in the macro phases of Table 6.3, so as to evaluate the unit production costs of

the product, in order to find the process target cost of the instant soup mix. Route

distances and other hypothesis we have assumed may be seen in Table 6.4. A full list

of the unit costs considered for the soup mix is shown in Table 6.5.

Table 6.5 Cost estimation of the instant soup mix recipe (100 g)

S No. Particulars Rate Quantity Cost (`)

1 Rice flour ` 48.53/kg 55.37 g 2.69

2 Moringa leaf powder ` 98.21/kg 8.90 g 0.87

3 Blended oil ` 83.21/L 5.26 g 0.49

4 Carrot ` 77.82/kg 15.0 g 1.44

5 Peas ` 92.46/kg 7.50 g 0.88

Total (`) 6.37

Misc. ~ @20% of Total 1.27

Grand Total (`) 7.64

The cost estimation of the optimized instant soup mix was represented in

Table 6.5. The cost of the each ingredients of the soup mix was calculated as

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average price of the raw material procured from different places. The

ingredient’s cost grouped in four process phases as raw materials, pre

production logistic cost, production cost and post production logistic cost. The

miscellaneous particulars of the above said recipe contains the other ingredients

as spices and condiments and indirect expenses.

Once the boundary conditions for the comparison were fixed, the calculation

of effective costs of instant soup mix followed directly. As reported in Table 6.5, the

unit and percentage costs of the instant soup mix were calculated according to the

macro phases listed in Table 6.3; moreover, it specifies the post-production logistic

costs for the instant soup mix. The total unit cost for the instant soup mix is equal to

`7.64/100 g. Nonetheless, the postproduction logistics of an instant soup mix does

not need a cold chain and therefore avoids its costs and risks. Further developments of

this work could extend the analysis to applying this to different products. Finally, a

feasibility study should assess the possibility of producing instant soup mix at the

target cost we have calculated.

6.2.13 Storage studies

The optimized instant soup mix (10 g) were sealed using a sealing

machine in low density poly ethylene (LDPE) bags and aluminum laminates

(AL) for the storage period of six months. However, laminated aluminum foil is

a co-extruded product which consists of inner LDPE, middle aluminum layer

and outer polyster layer. The sealed soup mix pouches were then stored at 25±2

°C temperature and 65±5 % relative humidity (FDA, 2003). The soup mix

samples were then analyzed for moisture content (AOAC, 2000) and sensory

characteristics at the regular intervals during the six months of storage studies.

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6.2.14 Statistical analysis

The results were expressed as mean ± standard deviation. Analysis of variance

and Duncan's multiple range test was performed to examine significant differences

(P≤0.05) of sensory attributes among samples. The statistical analyses were conducted

using SPSS for Windows (SPSS Inc., Chicago, IL, USA).

The quality of fitting of experimental data to the selected mathematical models

was tested with different criteria, namely, coefficient of multiple determination (R2),

the mean relative percent error (%E), root mean square error (RMSE). The coefficient

of multiple determinations (R2) was one of the primary criteria for selecting the best

equation. In addition to R2, the various statistical parameters such as; %E, RMSE and

χ2 were used to determine the quality of the fit (Chen and Morey, 1989). The mean

relative percentage deviation modulus (%E) is widely adopted throughout the

literature, with a modulus value below 10% indicative of a good fit for practical

purposes (Lomauro et al., 1985). The measures of errors using %E, RMSE and χ2 are

defined as

(6.9)

(6.10)

(6.11)

6.3 RESULTS AND DISCUSSION

6.3.1 Dimensional characteristics

The particle size and particle size distribution of the instant dry soup mix is

presented in Figure 6.2. Soup mix samples were assessed after uniform mixing of

ingredients as per formulation. The results revealed that the soup mix was composed

of the particles having the average size as 110.28 µm. The rice flour granule used in

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soup mix was found more variable and comparatively lesser in size as compared with

the average soup particle. Studies have further support the fact regarding the reduced

swelling of starch granule in presence of non polar component absorption manly due

to the decreased mobility of water molecules (Kruger et al., 2003) on its

reconstitution with thermal treatment during soup preparation.

Figure 6.2 Effect of soup ingredients (rice flour and moringa leaf powder) on

particle size analysis of optimized instant soup mix

6.3.2 Morphological characteristics

Microscopy has played an important role in increasing understanding of

particle structure of soup mix. The granular structure of soup mix along with the used

0

2

4

6

8

10

12

532 420 331 261 205 162 128 101 79 63 49 39 31 24 19 15 12 9

Part

icle

am

ou

nt,

%

Particle size, µm

Soup mix

Page | 178

ingredients showed significant variation in size and shape when viewed under

scanning electron microscope (Figure 6.3). P

usa

11

21

ric

e fl

ou

r

Mori

nga

lea

f pow

der

Opti

miz

ed i

nst

ant

soup m

ix

Figure 6.3 Effect of soup ingredients (rice flour and moringa leaf powder) on

morphological characteristics of optimized instant soup mix

The non uniform and irregular granules shapes of the used ingredients i.e. rice

flour and moringa leaf powder was observed as per characteristic associated

morphologies. The granules have adhered particles in composite forms for both the

Page | 179

ingredients on the application of blended oil as reflected from the appearance of

granules for the soup mix (Figure 6.3). The shape and size of soup mix have also

found to be affected on forming the agglomeration and reflected with the narrow size

distribution in the particle size analysis, which has found to be in agreement with

earlier reports (Vallons et al., 2011; Naruenartwongsakul et al., 2008).

6.3.3 Gravimetric and frictional characteristics

The bulk density (BD) of optimized soup mix was found to be 494.48±2.68

kg/m3 and in agreement with the work mentioned elsewhere (Muramatsu et al., 2007;

Singh et al., 2005). The experimental value of angle of repose (AOR) was found as

52.87±0.28°, which was found to be similar (Ghasemi et al., 2008) for emptying angle

of repose for rice. The coefficient of friction (COF) was minimum for glass surface

(COFG) and maximum for plywood surface vertically aligned and found as 0.44 to

0.73, respectively. The differences in the values may be due to the fact that the

roughness of the associated used material surface in determining the coefficient of

friction (Correa et al., 2007).

6.3.4 Chemical Characterization

The result of proximate analysis of the dry soup mix sample is presented in

Table 6.6. The analyzed chemical attributes were moisture, protein, fiber, fat,

carbohydrate, ash, total antioxidant capacity and total phenol content. The initial

moisture content of optimized instant soup mix was 8.95±0.55 %. It was found that

ingredients used for soup significantly affected in terms of chemical composition of

soup (Table 6.6). It is evident from these results that crude fat and protein content of

soup are 9.11 and 7.79%, respectively. The energy value of soup was 390.55 kcal per

100 gm, this value fall considerable towards daily energy requirement as reported for

adults (Bingham, 1978). On comparing the nutritive value of developed soup with the

Page | 180

available market sample then found better nutritional properties associated with the

developed soup.

The results obtained for antioxidants and phenolic compounds in soup are

presented in Table 6.6. DPPH assay is one of the most widely used methods for

evaluating antioxidant activity. Antioxidant potential evaluated by scavenging of

DPPH radicals (60.54), that soup sample possessed high potential antioxidant activity.

Total phenolic content in the sample methanolic extracts was 52.31 mg GAE/g extract

(Table 6.6). Phenolic acids are generally considered as good antioxidants; they

express antioxidant activity as chelators and free radical scavengers with special

impact over hydroxyl and peroxyl radicals, superoxide anions and peroxynitrites

(Carocho and Ferreira, 2013). Appreciable amount of total antioxidant capacity (60.54

Trolox equivalent mg/g) with higher phenolic content further made this important

nutritional biomaterial a functional material may be applied for the therapeutic

purposes too.

Table 6.6 Chemical composition of optimized instant soup mix

Particulars Content

Moisture, % 8.95±0.55

Protein, % 7.79±0.46

Fat, % 9.11±0.28

Fiber,% 3.34±0.19

Ash, % 1.46±0.11

Carbohydrate, % 69.35±0.14

Energy, Kcal 390.55±0.64

Chlorophyll, mg/g 7.73±0.08

Total antioxidant capacity, Trolox equivalent mg/g 60.54±0.79

Total phenol content, mg/100g 52.31±0.44

Page | 181

6.3.5 Rheological Characterization

6.3.5.1 Cake strength and Pasting properties

The tendency of any flour to cake can provide important information about the

properties and behavior of the flour on storage and transportation (Cheigh et al.,

2011). Caking takes place because of the transformation of powders into undesirable

lumps ranging from small and soft aggregates that can be broken easily to hard lumps

resulting in loss of flow ability. Cake strength assessed during the experimental test

obtained was 406.89 g reflects the characteristics of the mix for the cake formation

and breakage strength.

The formulated samples of soups as exhibited the pasting behavior is shown in

form of typical visco-gram (Figure 6.4). The RVA characteristics of soup mix as

analyzed are shown (Table 6.7). The pasting properties are found to be influenced by

granule size, composition method of flour preparation and the history of provided

thermal treatments. The increase in viscosity with the rise in the temperature may be

attributed to the removal of water from the amylose granules as they swell and exhibit

the phenomenon (Ghiasi et al., 1982; Nurul et al., 1999). The information for the

change in the pasting process leading to a peak viscosity of 1488 cP and further

reduce to a level of hot and cool paste viscosity as 608 cP and 1448 cP, respectively,

which is vital for the soup system to decide the concentration of the ingredients to be

used (Table 6.7). The increase in viscosity during the cooling period is indicative not

of only the normal inverse relationship between the viscosity and temperature of

suspensions but also of the tendency for various constituents present in the hot paste

to associate or retrograde as the temperature of the paste decreases. A decrease in

pasting temperature of corn starch paste was found with the addition of guar gum

(Sudhakar et al., 1996). Our results also suggest the influence the addition of moringa

leaf powder and blended oil in decreasing the pasting profile in comparison of rice

Page | 182

flour in a pure system (Table 6.7). This behavior is in contrast to observations by

Christianson et al. (1981), who reported a delay in gelatinization of starch granules as

a result of increased viscosity of continuous phase, thereby increasing pasting

temperatures and decreasing peak viscosity. Increases in pasting temperature with

increasing hydrocolloid concentration have also been reported by other researchers

(Song et al., 2006; Yoshimura et al., 1998). It is possible that the composite of

ingredients (blended oil) used in the soup formulations may also have influenced the

swelling of starch granules and/or absorption of water by the polysaccharide (Garti et

al., 1997) in lowering the pasting temperature.

Time (Second)

0 100 200 300 400 500 600 700 800

Vis

cosit

y (

cP

)

0

600

1200

1800

2400 Instant soup mix

0 100 200 300 400 500 600 700 800

Tem

peratu

re (

°C

)

40

50

60

70

80

90

100

Figure 6.4 Pasting profile of instant soup mix

Table 6.7 Pasting characteristics of optimized instant soup mix

Page | 183

Particulars Instant soup mix

Peak Visocity, cP 1488

Hot Paste Viscosity, cP 608

Breakdown Visocity, cP 880

Cool Paste Viscosity, cP 1448

Setback Visocity, cP 840

Pasting Temp, °C 74.25

6.3.5.2 Rheological properties

Rheological properties reflect the force required for the deformation to occur

or flow to set in. Ravindran and Merino (2009) have studied the rheological

characteristics of soup mix. The viscosity of the optimized instant soup was 532 cP.

During gelatinization, starch granules swell to several times then their initial volume.

Swelling is accompanied by leaching of granule constituents, predominantly amylose,

and the formation of a three dimensional network (Eliasson, 1985; Hennig et al.,

1976; Tester and Morrison, 1990). These changes are responsible for the rheological

characteristics exhibited by soup during heating and shearing. Rheological behavior

of soup is governed mainly by starch source as described (Kaur et al., 2004;

Morikawa and Nishinari, 2002; Okechukwu and Rao, 1995; Singh and Kaur, 2004;

Singh et al., 2003).

The rheological data of soup samples as obtained were fitted to selected

rheological models such as Bingham, Oswald or Power law, Herschel Bulkely,

Casson, Casson Steiner, Carreau Yasuda, Carreau Gahleitner and Vinogradov

Malkinas and the determined statistical parameters are shown in Table 6.8. All the

models showed high values of goodness of fitting as the R2 > 0.974, except for the

Page | 184

Bingham model. Figures 6.5, 6.6 and 6.7 show the rheograms of experimental shear

stress and shear rates of soup samples at temperature 45 °C with fitted Bingham,

Oswald or Power law, Herschel Bulkely, Casson and Casson Steiner models. Shear

stress and shear rates of the rheograms show concave curves downwards, therefore

possibility of following the non-Newtonian, shear thinning and pseudoplastic

behavior is evident. The values of rheological parameters, consistency coefficient and

flow behavior index obtained from the Power law curve fitting are presented in Table

6.8. All the flow behavior index values are below 1 supporting the pseudoplasticity

nature of prepared soup. Table 6.8 illustrates that the variations in the consistency

coefficient is reflected on the use of blended oil, moringa leaf powder with rice flour

either alone or in combimbinations. The increase in consistency coefficient for the

soup system may be attributed to the interaction effects among the ingredients.

The shear rate, shear stress and viscosity data were analyzed to examine the

extent of fitting rheological models. The experimental values for shear stress and

shear rate are shown in Figures 6.5, 6.6 and 6.7 along with the fitting of these five

models. The values of model coefficient are presented in Table 6.8 showing higher

goodness of fit with high coefficient of multiple determinations (R2). A close

observation shows that soup sample exhibited a shear thinning, non-Newtonian

behavior and behaves pseudoplastically (n<1) for the soup samples (Prasad et al.,

2013).

Page | 185

Figure 6.5 Shear stress as affected by changing the shear rate for soup

mix with fitted models

Figure 6.6 Shear stress as affected by changing the shear rate for rice

flour and moringa leaf powder with fitted models

20

30

40

50

60

70

Pa

0 200 400 600 1,0001/s

Shear Rate .

10

15

20

25

30

35

40

50

Pa

0 200 400 600 1,0001/s

Shear Rate .

Page | 186

Figure 6.7 Shear stress as affected by changing the Shear rate for rice

flour and blended oil with fitted models

The apparent viscosity and shear rate of the suspensions showed a shear

thinning behavior, as may be seen from the plot (Figures 6.8, 6.9 and 6.10). The shear

thinning phenomenon is more pronounced in optimized soup as compared to other

trials. Figures 6.8, 6.9 and 6.10 shows the viscosity versus shear rate curves for

optimized soup mix compared with the ingredients effect as rice flour, moringa leaf

powder and blended oil. The increase in flow resistance can occur due to

hydrodynamic instabilities which lead to secondary flow effects at high shear rates

(Mezger, 2002). The fitting of the mathematical models to the measured data was

found overlapping as R2 values approaching to 1. Statistical coefficients based on the

predicted and measured parameters for the samples shows a reasonable agreement

(Table 6.8). The model fitting of data with high R2 with reasonably low RMSE,

confirming the applicability of fitted rheological model for the soup systems.

20

30

40

50

60

70

Pa

0 200 400 600 1,0001/s

Shear Rate .

Page | 187

Figure 6.8 Viscosity as affected by changing the shear rate for soup mix

with fitted models

Figure 6.9 Viscosity as affected by changing the shear rate for rice flour

and moringa leaf powder with fitted models

0

0.2

0.4

0.6

0.8

1

1.4

Pa·s

0 200 400 600 1,0001/s

Shear Rate .

0

0.1

0.2

0.3

0.4

0.6

Pa·s

0 200 400 600 1,0001/s

Shear Rate .

Page | 188

Figure 6.10 Viscosity as affected by changing the shear rate for rice flour

and blended oil with fitted models

0

0.2

0.4

0.6

0.8

1.2

Pa·s

0 200 400 600 1,0001/s

Shear Rate .

Page | 189

Table 6.8 Statistical parameters for rheological models

Model Description Model Constants R2 RMSE χ2 %E

Bingham RF+MLP+BO o = 34.481, n = 0.033 0.942 2.123 4.683 3.804

RF+MLP o = 15.014, n = 0.034 0.971 1.521 3.790 4.600

RF+BO o = 27.617, n = 0.035 0.968 1.708 3.164 3.292

Ostwald or Power law RF+MLP+BO K = 14.204, n = 0.212 0.995 0.909 0.855 1.497

RF+MLP K = 3.597, n = 0.360 0.984 1.133 2.052 3.000

RF+BO K = 9.581, n = 0.257 0.974 1.532 3.043 3.113

Herschel-Bulkley RF+MLP+BO o = 20.341, K = 2.694, n = 0.400 0.999 0.211 0.045 0.350

RF+MLP o = 9.283, K = 0.592, n = 0.595 0.999 0.255 0.078 0.490

RF+BO o = 20.933, K = 0.628, n = 0.596 0.998 0.434 0.245 0.923

Casson RF+MLP+BO Ko = 5.220, K = 0.089, p = 2.0 0.991 0.822 0.725 1.486

RF+MLP Ko = 3.141, K = 0.116, p = 2.0 0.998 0.388 0.250 1.191

RF+BO Ko = 4.537, K = 0.101, p = 2.0 0.997 0.536 0.333 1.124

Casson-Steiner RF+MLP+BO Ko = 5.220, K = 0.089 0.991 0.822 0.725 1.486

RF+MLP Ko = 3.141, K = 0.116 0.998 0.388 0.250 1.191

RF+BO Ko = 4.537, K = 0.101 0.997 0.536 0.333 1.124

Carreau-Yasuda RF+MLP+BO a = 6.798, n = 0.153 1.000 0.001 0.000 0.357

RF+MLP a = 6.956, n = 0.212 0.999 0.003 0.001 0.671

RF+BO a = 6.503, n = 0.128 0.999 0.005 0.003 1.312

Carreau-Gahleitner RF+MLP+BO a = 47.455, b = 2.0, p = 0.423 1.000 0.001 0.000 0.357

RF+MLP a = 47.454, b = 2.0, p = 0.392 0.999 0.003 0.001 0.656

RF+BO a = 47.456, b = 2.0, p = 0.431 0.999 0.006 0.004 1.261

Vinogradov-Malkin RF+MLP+BO a = -0.944, b = 0.361, p = 0.325 1.000 0.001 0.000 0.297

RF+MLP a = -0.541, b = 0.001, p = 0.669 1.000 0.000 0.000 0.389

RF+BO a = -1.223, b = 0.408, p = 0.198 1.000 0.003 0.001 0.803

Where RF – Rice flour; MLP – Moringa leaf powder; BO – Blended oil

Page | 190

6.3.6 Optical Characterization

The optical properties, L, a and b values of the soup mix was found to be

59.73±0.05, -6.32 ±0.02 and 24.18±0.03, respectively. Higher L value reflects the use

of more rice flour in improving the lightness of soup, whereas decreased a values

show the higher green color of soup mix sample (Singh and Prasad, 2013a; Singh and

Prasad, 2013b).

6.3.7 X-ray diffraction (XRD) characteristics

The effects of ingredients used in instant soup mix on X-ray diffraction (XRD)

pattern can be used to study the characteristics of soup complexes formed in an

aqueous starch system (Figure 6.11). The crystallinity of starch as measured by X-ray

diffraction is significantly independent for the ingredients. indicated the presence of

A-type patterned starch with strong peaks at around 15.23, 18.11 and 23.34° 2θ and

feeble peaks at 19.77 and 26.52 ° 2θ (Vansteelandt and Delcour 1999; Noosuka et al.,

2005). Higher crystallinity found to be associated with the moringa leaf powder and

could be due to associated with the presence of minerals with the fibrous components.

The broadening of the XRD pattern further indicates the finding of the aggregation of

flours in presence of blended oil (Figure 6.11).

Page | 191

Bragg Angle (Degree)

10 15 20 25 30 35 40

Inte

nsit

y (A

rbit

rary

Uni

t)

Pusa 1121 rice flour

Optimised Soup Mix

Moringa leaf powder

Figure 6.11 Effect of soup ingredients (rice flour and moringa leaf powder) on

X-ray diffraction pattern of optimized instant soup mix

6.3.8 Fourier transform infrared (FTIR) spectroscopy

Fourier transform infrared (FTIR) spectra of optimized instant soup mix as

well as ingredient (rice flour and moringa leaf powder) are shown in Figure 6.12. All

the peaks present in the IR spectra for the ingredients of soup are evident in the mixed

soup sample is indicative for the originality of the preparation and may be considered

as the quality assessment parameters to check the adulterations even. FTIR results

showed a significant increase in peaks associated with soup components (Figure

6.12), this increase in total oxygenated carbon bonds may be attributed to degradation

of the matrix.

Page | 192

7001525235031754000

Tra

nsm

itta

nce

(%

)

0.4

0.5

0.6

0.7

0.8

0.9

1.0 Optimised soup mix

7001525235031754000

0.4

0.5

0.6

0.7

0.8

0.9

1.0

I

I

III

I

II I I

I

I

I

I

7001525235031754000

Tra

nsm

itta

nce

(%

)

0.4

0.5

0.6

0.7

0.8

0.9

1.0 Moringa leaf powder

7001525235031754000

0.4

0.5

0.6

0.7

0.8

0.9

1.0

II

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I

II II II

I

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7001525235031754000

Tra

nsm

itta

nce

0.4

0.5

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1.0Pusa 1121 rice flour

Wavenumbers (cm-1

)

7001525235031754000

0.4

0.5

0.6

0.7

0.8

0.9

1.0

I

I II

II I

I

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I

I

II

Figure 6.12 Effect of soup ingredients (rice flour and moringa leaf powder) on

Fourier Transform Infra-Red spectroscopy profile of optimized

instant soup mix

6.3.9 Reconstitution and Sensory Characteristics

The evaluated soup mix sample was rated for their liking on the basis of

sensory overall acceptability as well as on the basis of sensory color, mouthfeel and

overall acceptability of reconstituted soup (Table 6.9). Mingled perception of taste

along with aroma reflects the sensory flavor, which elicit the acceptability of soups by

the consumers. Statistically significant effect of ingredients on sensory characteristics

of soup was observed (Wang et al., 2010; Cheigh et al., 2011). The mean

Page | 193

sensory scores have reflected that all sensory parameters were found above the

minimum acceptable range being the scores crossed 7 sensory scores on 9 point

hedonic scale.

Table 6.9 Sensory characterization of instant soup mix and prepared soup

Particulars Soup mix Prepared soup

Sensory color - 8.39±0.12

Sensory mouthfeel - 8.11±0.08

Sensory flavor - 8.18±0.05

Overall acceptability 8.23±0.28 8.29±0.09

Overall acceptability indicates the acceptability of the product both in the dry

and reconstituted soup form as represented in Table 6.9. Hedonic scale is used to find

the different aspect of sensory evaluation. The overall acceptability of the product is

significantly affected by the sensory attributes, the sensory color, mouthfeel and

flavor (Mitchell et al., 2011). Moringa leaf powder and blended oil shows the positive

effect on overall acceptability of soup as described earlier.

Figure 6.13 Rice based vegetable supplemented functional instant soup mix

and prepared soup

6.3.10 Storage studies

It may be observed from Table 6.10 that the change in the moisture

content of soup mix was found to be packaging dependent and ranged from

Page | 194

8.95 to 9.38% and 8.95 to 8.99% for LDPE pouches and aluminum laminate

pouches, respectively. The gradual increase in the moisture has led to a level of

9.29% moisture but remained below an ERH of 65% even on the use of LDPE

pouch at the end of the storage studies of six months. There is a significant

difference observed in moisture content in case of LDPE but not in case of

aluminum laminates pouches during the entire storage period. Also the product

remained acceptable both in the dry and reconstituted soup form being the

sensory OAA score remained above 7 despite of minor change in the other

sensory parameters (Table 6.10).

Page | 195

Table 6.10 Effect of storage time on moisture content sensory characteristics of optimized instant soup mix

Storage Time, day (T)

Storage Parameters (S)

Moisture content,% Sensory characteristics (9 point hedonic scale)

Color Mouthfeel Flavour Overall acceptability

LDPE AL LDPE AL LDPE AL LDPE AL LDPE AL

0 8.95F 8.95

BCE 8.39

A 8.39

A 8.11

A 8.11

A 8.18

A 8.18

A 8.29

A 8.29

A

30 8.97F 8.94

DE 8.35

A 8.37

AB 8.08

A 8.10

AB 8.15

A 8.18

A 8.23

A 8.27

A

60 9.05E 8.95

BCE 8.29

B 8.35

B 8.01

B 8.07

B 8.09

AB 8.15

BC 8.15

B 8.25

B

90 9.16D 8.97

ABE 8.20

C 8.35

B 7.95

C 8.03

C 8.04

BC 8.16

B 8.09

C 8.25

B

120 9.21C 8.97

AC 8.07

D 8.30

C 7.93

C 8.02

CD 7.98

C 8.14

C 7.96

D 8.22

C

150 9.29B 8.99

A 7.98

E 8.28

C 7.88

D 8.00

D 7.90

D 8.14

C 7.88

E 8.13

D

180 9.38A 8.99

A 7.86

F 8.16

D 7.85

D 8.01

CD 7.82

E 8.12

D 7.80

F 8.12

D

LDPE - low density polyethylene; AL - aluminum laminates;

Values in a column with same superscript do not differ significantly (p<0.05)

Page | 196

6.4 CONCLUSION

The study showed that the soup ingredients was found to be having the role in

deciding physico-chemical characteristics of instant soup mix and confirmed its direct

influence. The use of rice flour in the preparation soup with the addition of moringa

leaf powder and blended oil has been found to improve the nutritional and functional

components and resulted into the cost effective soup of `7.64/100 g. The granular

structure of soup mix with the average particle size of 110.28 µm was resulted.

The optimized foumultion results in to a soup mix have the moisture content

of 8.95% (wwb), bulk density, 494.48±2.68 kg/m3, energy value of 390.55 kcal/100 g

with appreciable amount of protein, 7.79±0.46%, fat, 9.11±0.28%, fiber, 3.34±0.19%,

carbohydrate, 69.35±0.14%, total antioxidant capacity, 60.54±0.79 as Trolox

equivalent mg/g and phenolic content. 52.31±0.44 mg/100 g with the optical

characteristics in terms of L, a and b values as 59.73±0.05, -6.32±0.02 and

24.18±0.03, respectively; caking properties in terms of cake strength as 406.89 g.

The information for the change in the pasting process leading to a peak

viscosity of 1488 cP and further reduced to a level of hot and cool paste viscosity as

608 cP and 1448 cP, respectively, which is vital for the soup system to decide the

concentration of the ingredients to be used. X-ray diffraction is significantly

independent for the ingredients crystallinity. All the peaks present in the FTIR spectra

for the ingredients of soup are evident in the mixed soup sample is indicative for the

originality of the preparation and may be considered as the quality assessment

parameters to check the adulterations even.

Mathematical models that are described to rheological behavior of soup mix in

terms of shear rate, shear stress and viscosity are analysed. The rheological data of

soup samples were fitted to rheological models such as Bingham, Oswald or Power

Page | 197

law, Herschel Bulkely, Casson, Casson Steiner, Carreau Yasuda, Carreau Gahleitner

and Vinogradov Malkinas All the models showed high values of goodness of fit as R2

> 0.974 except the Bingham model. As the shear stress and shear rates of the

rheograms show concave curves downwards, soup sample therefore exhibited a non-

Newtonian, shear thinning and pseudoplastic behavior.

The mean sensory scores have reflected that the sensory acceptable soup could

be obtained as all sensory parameters were found to have above the minimum 7

sensory scores on 9 point hedonic scale. The minor changes towards sensory

parameters during storage were found but the product remained acceptable till

the storage period of six months.