4.chapter r and d

CHAPTER 4

RESULTS AND DISCUSSION

This chapter deals with the results of the experiments carried out during the course of present

study. Physico-chemical properties of carrot juice and skim milk powder were studied. The

effect of different process parameters such as skim milk powder, carrot juice and inoculum

level, on the physico-chemical, microbial, overall acceptability and storage properties were

observed. The optimization of carrot fortified probiotic yoghurt was carried out according to

central composite rotatable design (CCRD). Twenty different experimental runs were carried

out using Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus as

basic yoghurt cultures and Lactobacillus acidophilus and Bifidobacterium bifidum as

adjuvant cultures for the preparation of carrot fortified probiotic yoghurt. The results were

analyzed for different physico-chemical (syneresis, pH, and water holding capacity),

microbial counts (Lactobacillus acidophilus and Bifidobacterium bifidum counts), overall

acceptability and storage study which are discussed further.

4.1 Some Physico-chemical Properties of Skim Milk Powder and Carrot Juice

The purpose of determination of chemical composition was to get idea about nutritional

quality of ingredients and its suitability to prepare good quality of final product. Various

physico-chemical attributes of Skim Milk Powder and Carrot juice are shown in Table 4.1-

4.2. Total Solids (TS) of carrot juice (by oven drying) were found 8.30 % (w/w) .The results

were in accordance with findings of Salwa et al. reported 7.15 % (w/w) Total solids in carrot

juice [10]. Carrot juice pH was found to be 4.98. Salwa et al. reported that carrot juice pH

falls about 5.85 [10]. The variation in data may be due to various geographical and climatic

conditions such as soil condition, water level, temperature, etc.

Table 4.1 Physio-chemical properties of Skim Milk Powder.

Sr. No. Parameters Quantity

1 Moisture 3.02% (w/w)

2 pH 6.40

3 Acidity 0.158

4 Colour Chalky-White

5 Reconstitutability Very-Good

Table 4.2 Physico-chemical properties of the Carrot juice obtained from the fresh

Carrot.

Sr. No. Parameters Quantity

1 Moisture content 91.7 % (w/w)

2 T.S ( Oven drying) 8.30 % (w/w)

4 pH 4.98

5 Acidity 2.58

6 Total phenolic content 76µg(G.A.E)/ml

7 β-carotene 30.29µg/100g

4.2 Process Optimization by Response Surface Methodology (RSM)

Central composite rotatable design (CCRD) of response surface methodology (RSM) was

applied to optimize the amount of skim milk powder, carrot juice and inoculum level for

syneresis, pH, water holding capacity, overall acceptability, Lactobacillus acidophilus and

Bifidobacterium bifidum count. The experimental range of independent variables was

selected from the literature reviewed. The low and high levels of carrot juice, skim milk

powder and inoculum level were 10 and 20 % (v/v), 14 and 18 % (w/v), 2 to 4 % (v/v)

respectively. For the determination of optimal level of three variables, response surface

approach was applied by using a set of experimental design having three independent

variables at five levels each by using design-expert 6.0 (trial version). The total number of

experiments with three variables were 20 (= 2k+ 2k+8), where k is the number of factors.

Twenty experiments were augmented with six replications at the center points to evaluate the

error. The optimization of the carrot fortified probiotic yoghurt was aimed at finding the level

of independent variables that would give minimum syneresis, pH in range of 3.6 to 4

maximum water holding capacity, maximum overall acceptability, maximum Lactobacillus

acidophilus and Bifidobacterium bifidum count . The second order polynomial equation was

fitted to the experimental data of each dependent variable as given below,

Y i=β0+∑i=1

n

β i x i+∑i=1

n−1

∑j=i+1

n

βij x i x j+∑i=1

n

βii x i2

Where Yi = Response {Y1 = Syneresis (%, v/w), Y2 = pH, Y3 = Water Holding Capacity

(%w/w), Y4 = Lactobacillus acidophilus count (cfu/ml), Y5 = Bifidobacterium bifidum count

(cfu/ml), Y6= Overall Acceptability}

xi = Independent variables (x1 = Skim milk powder (%, w/v), x2 = Carrot juice (%, v/v), x3 =

Inoculum level (%, v/v), βo is the value of fitted response at the central point of design i.e. βi,

βij, βii are the linear, quadratic and cross product regression coefficients, respectively.

The statistical analysis of the experimental data was performed to observe the effect of above

given parameters on measured responses. The adequacy of quadratic models for all responses

was on basis of R2, F-value and p-value at 5 % level of significance. The relative effect of

each process parameter on individual response was compared from the β values

corresponding to that parameter. The magnitude of β values allows comparing the relative

contribution of each independent variable in the prediction of the dependent variable. Higher

the positive value of β of a parameter; higher would be the effect of that parameter and vice

versa. The negative value of β indicates the negative effect of that parameter on measured

response. The response surface and contour plots were generated for different interaction of

the any two variables, while holding the value of remaining variables at the central level.

Such three dimensional surfaces could give accurate geometrical representation and provide

useful information about the behavior of the system within the experimental design. The

experimental design along with the values of various responses for the above parameters is

given in Table 4.3. The experiments were conducted randomly to minimize the effects of

unexplained variability in the observed responses because of external factors.

4.2.1 Diagnostic Checking of Fitted Model and Surface Plots for Syneresis

The results of second order response model in the form of Analysis of variance (ANOVA) for

syneresis of yoghurt are given in Table 4.4.

The ANOVA results indicated that quadratic regression to produce the second order model

was significant (F-value = 51.94). The value of R2 = 97.91 % indicates that only 2.09 % of

total variation was not explained by the model. The value of adjusted determination

coefficient (Adjusted R2 = 96.02 %) was high to advocate a high significance of the model

(Myers and Montegomery) [42]. This suggested that model accurately represents the data in

the experimental region. This also indicated that second order terms were sufficient and

higher order terms were not necessary.

Table 4.4 Regression summery and ANOVA table for syneresis for coded values of

process variables

Source Symbo β- Sum of df Mean F- p-Value

lcoefficien

tSquares Square Value

Model 40.84 498.29 9 55.37 51.94<0.0001

*

A x1 -2.99 122.00 1 122.00 114.45<0.0001

*

B x2 3.99 217.49 1 217.49 204.03<0.0001

*

C x3 -0.81 8.93 1 8.93 8.38 0.0160*

A*A x12 2.83 115.31 1 115.31 108.18

<0.0001

*

B * B x22 -0.53 4.05 1 4.05 3.80 0.0799

C*C x32 -0.53 4.05 1 4.05 3.80 0.0799

A*B x1 x2 -1.00 8.00 1 8.00 7.50 0.0209*

A*C x1 x3 0.75 4.50 1 4.50 4.22 0.0670

B*C x2 x3 0.75 4.50 1 4.50 4.22 0.0670

R2 0.9791

Adjuste

d R20.9602

*Significant at 5 % level.

The magnitude of p-value from Table 4.4 indicates that all linear terms of the variables had

significant effect on syneresis of yoghurt at 5 % level of significance (p < 0.05). The

quadratic terms of skim milk powder, interactive terms of “skim milk powder and carrot

juice”, also had significant effect on syneresis at 5 % level of significance (p < 0.05).

The quadratic model obtained from the regression analysis for syneresis in terms of coded

levels of the variables after eliminating the non-significant terms is as follows:

Syneresis (%, v/w) = 40.84-2.99x1+3.99x2-0.81x3+2.83x12-1.00x1x2 (4.1)

The magnitude of β value from the Table 4.4 revealed that skim milk powder (β = -2.99) has

highest negative linear effect followed by inoculum level (β= -0.81) on the syneresis of

yoghurt at 5 % level of significance (p < 0.05); whereas carrot juice (β = +3.99) has highest

positive linear effect on the syneresis of yoghurt at 5 % level of significance (p < 0.05). This

indicates that with increase in amount of skim milk powder and percent inoculum, there will

be decrease in the syneresis of yoghurt. Decrease in the syneresis of yoghurt with increase in

amount of skim milk powder is due to reduction in free water in more concentrated yoghurt

[43]. The decrease in syneresis of yoghurt with increase in inoculum level is may be due to

the reason that faster acidification rate inhibits the rearrangement in protein network. With

increase in inoculum level, there will be a decrease in electrostatic repulsion between casein

particles which might be a cause of inhibition of rearrangements in protein network [31]. The

β values from the Table 4.4 indicate that the increase carrot juice concentration, will increase

the syneresis of yoghurt. Increase in carrot juice concentration, an increase in syneresis of

yoghurt has been observed, which might be due to sudden decrease in pH. The sudden

decrease in pH with increasing concentration of carrot juice may have resulted in very less

solublisation of casein micelles from colloidal calcium phosphate. Less solublisation of

casein micelles causes less availability of casein to form three dimensional network resulting

in increased syneresis of yoghurt. The increase in syneresis of yoghurt with increase in

strawberry juice which is also acidic in nature has been reported by Vahedi et al. in

strawberry yoghurt [44]. Quadratic terms of skim milk powder had shown a significant

positive effect (p < 0.05) on syneresis produced. The interaction terms of “skim milk powder

and carrot juice” (β = -1.00), had a significant positive effect on syneresis at 5 % level of

significance (p < 0.05).

Fig 4.1 indicates a decrease in syneresis of yoghurt with the increase in skim milk powder

concentration due to reduction in free water in more concentrated yoghurt and increase in

syneresis of yoghurt with increase in carrot juice.

Fig.4.1 Effect of skim milk powder and carrot juice on syneresis (at 3%, v/v inoculum

level).

4.2.2 Diagnostic Checking of Fitted Model and Surface Plots for pH


pH are given in Table 4.5.








The magnitude of p-value from Table 4.5 indicates that only linear terms of the inoculum

level had significant effect on pH at 5 % level of significance (p < 0.05). The quadratic terms

of skim milk powder, carrot juice and inoculum level, interactive teams “skim milk powder

and carrot juice”, and “skim milk powder and inoculum level”, also had significant effect on

pH at 5 % level of significance (p < 0.05).The quadratic model obtained from the regression

analysis for pH in terms of coded levels of the variables after eliminating the non-significant

terms is as follows:

pH = 3.73-0.018x3-0.029x12-0.016 x2

2-0.053 x32 -0.022x1x2-0.022 x1x3 (4.2)

The magnitude of β value (Table 4.5) revealed that skim milk powder (β = -5.325 x10-4) has a

highest negative linear effect followed by carrot juice(2.230 x10-3), inoculum level(-0.018) on

the pH of yoghurt at 5 % level of significance (p < 0.05). The magnitude of β values suggest

that with the increase in inoculum level, amount of skim milk powder and carrot juice

concentration, pH decreased. With increase in inoculum level of yoghurt, the population of

microorganisms will increases [42] conversion of lactose to lactic acid resulting in overall

decrease in pH of yoghurt [14]. With increase in skim milk powder a decrease in pH has been

observed, may be due to more availability of lactose to produce lactic acid [14]. A decrease in

pH of yoghurt has been observed with increase in carrot juice concentration, might be due to

acidic nature of carrot juice.Quadratic terms of skim milk powder,carrot juice and inoculum

level had shown a significant (p < 0.05) effect on pH of yoghurt. The interaction term of

“skim milk powder and carrot juice” (β = -0.022) and “skim milk powder and inoculum

level” (β = -0.022), had a significant negative effect on pH at 5 % level of significance

respectively.

Table 4.5 Regression summery and ANOVA table for pH for coded values of process

variables

SourceSymbo

l

β-

coefficient

Sum of

Squares

d

f

Mean

Square

F-

Valuep-Value

Model 3.73 0.064 97.057 x10-

319.56

<0.0001

*

A x1

-5.325 x10-

43.872 x10-6 1

3.872 x10-

60.011 0.9195

B x2

-2.230 x10-

36.791 x10-5 1

6.791 x10-

50.19 0.6736

C x3 -0.018 4.477 x10-3 14.477 x10-

312.41 0.0055*

A*A x12 -0.029 0.012 1 0.012 33.01 0.0002*

B * B x22 -0.016 3.864 x10-3 1

3.864 x10-

310.71 0.0084*

C*C x32 -0.053 0.041 1 0.041 114.30

<0.0001

*

A*B x1 x2 -0.022 4.050 x10-3 14.050 x10-

311.22 0.0074*

A*C x1 x3 -0.022 4.050 x10-3 14.050 x10-

411.22 0.0074*

B*C x2 x3 7.500 x10-3 4.500 x10-4 14.500 x10-

41.25 0.2902

R2 0.9462

Adjuste

d R20.8979


Fig 4.2 indicates maxima towards the centre and at 14% skim milk pH increased with the

increasing of carrot juice and the pH is decreased at 18% skim milk with the increasing of

carrot juice.

Fig 4.3 indicates that pH increased with the increasing of inoculum level upto 3.50%

inoculum level beyond this slightly decreased at low concentration of skim milk whereas at

18% skim milk pH increased firstly after sometime it decreased abruptly.

Fig. 4.2 Effect of skim milk powder and carrot juice on pH (at 3%, v/v inoculum level)

Fig. 4.3 Effect of skim milk powder and inoculum level on pH (at 15% v/v carrot

juice)

4.2.3 Diagnostic Checking of Fitted Model and Surface Plots for Water Holding

Capacity.


Water Holding Capacity are given in Table 4.6.








Table 4.6 Regression summery and ANOVA table for Water Holding Capacity for

coded values of process variables

SourceSymbo

lβ-coefficient

Sum of

Squares

d

f

Mean

SquareF- Value p-Value

Model 40.76 220.84 9 24.54 46.20<0.0001

*

A x1 1.30 22.97 1 22.97 43.24<0.0001

*

B x2 1.92 50.22 1 50.22 94.56<0.0001

*

C x3 1.77 42.59 1 42.59 80.19<0.0001

*

A*A x12 0.58 4.78 1 4.78 9.00

<0.0133

*

B * B x22 -1.76 44.87 1 44.87 84.48

<0.0001

*

C*C x32 -0.83 9.83 1 9.83 18.51

<0.0016

*

A*B x1 x2 -0.23 0.41 1 0.41 0.76 <0.4030

A*C x1 x3 0.22 0.38 1 0.38 0.71 0.4183

B*C x2 x3 -2.34 43.62 1 43.62 82.12<0.0001

*

R2 0.9765

Adjuste 0.9554

d R2



significant effect on WHC at 5 % level of significance (p < 0.05). The quadratic terms of

skim milk powder, carrot juice and inoculum level, interactive terms “carrot juice and

inoculum level”, also had significant effect on WHC at 5 % level of significance (p <

0.05).The quadratic model obtained from the regression analysis for WHC in terms of coded

levels of the variables after eliminating the non-significant terms was as follows:

WHC= 40.76+1.30x1+1.92x2+1.77x3+0.58x12-1.76x2

2-0.83 x32-2.34x2x3 (4.3)

The magnitude of β value (Table 4.6) revealed that carrot juice (β = 1.92) has a highest

positive linear effect followed by inoculum level (β = 1.77 ),skim milk (β=1.30) on the WHC

at 5 % level of significance (p < 0.05).This indicates that with the increase in amount of

inoculum level, skim milk powder and carrot juice concentration, there will be increase in

WHC. Fig 4.4 indicates that WHC increased with the increase in the concentration of

inoculum when carrot juice at 10 % whereas slightly decreased at 20% concentration of

carrot juice.

Fig. 4.4 Effect of carrot juice and inoculum level on WHC (at 16% w/v skim milk)

4.2.4 Diagnostic Checking of Fitted Model and Surface Plots for Lactobacillus

acidophilus Counts


Lactobacillus acidophilus counts are given in Table 4.7.








Table 4.7 Regression summery and ANOVA table for Lactobacillus acidophilus for


Source Symbol

β-

coefficien

t

Sum of

Squares

d

f

Mean

Square

F-

Valuep-Value

Model 28.27 6402.38 9 711.38 2826.89 <0.0001*

A x1 8.63 1018.17 1 1018.17 4046.06 <0.0001*

B x2 3.96 214.59 1 214.59 852.73 <0.0001*

C x3 16.54 3737.62 1 3737.6214852.7

0<0.0001*

A*A x12 3.63 190.15 1 190.15 755.64 <0.0001*

B * B x22 -0.27 1.08 1 1.08 4.31 0.0647

C*C x32 8.81 1118.61 1 1118.61 4445.18 <0.0001*

A*B x1 x2 0.18 0.25 1 0.25 0.97 0.3471

A*C x1 x3 -0.35 0.98 1 0.98 3.89 0.0767

B*C x2 x3 -4.65 172.79 1 172.79 686.66 <0.0001*

R2 0.9996

Adjuste

d R20.9993



significant effect on Lactobacillus acidophilus counts at 5 % level of significance (p < 0.05).

The quadratic terms of skim milk powder and inoculum level, interactive terms “carrot juice

and inoculum level” also had significant effect on Lactobacillus acidophilus counts at 5 %

level of significance (p < 0.05).The quadratic model obtained from the regression analysis for

Lactobacillus acidophilus counts in terms of coded levels of the variables after eliminating

the non-significant terms was as follows:

Lactobacillus acidophilus count = 28.27+8.63x1+3.96x2+16.54x3+3.63x12+8.81x3

2-4.65x2x3

(4.4)

The magnitude of β value (Table 4.7) revealed that inoculum level (β = 16.54) has a highest

positive linear effect followed by skim milk powder (β = 8.63 ), carrot juice (β=3.96) on the

Lactobacillus acidophilus count at 5 % level of significance (p < 0.05).This indicates that

with the increase in amount of inoculum level, skim milk powder and carrot juice

concentration, there will be increase in Lactobacillus acidophilus count. With increase in

skim milk powder, Lactobacillus acidophilus may get more availability of nutrients and

better protection from lowering of pH, resulting in increased Lactobacillus acidophilus count

[5]. There will be an increase in Lactobacillus acidophilus count with increase in inoculum

level. This might be due to high initial numbers of microorganisms [42].

Fig 4.5 Effect of carrot juice and inoculum level on Lactobacillus acidophilus count (at

16 %, w/v skim milk powder).

Fig 4.5 An increase in Lactobacillus acidophilus count has been observed with increase in

carrot juice concentration and inoculum level because the acidic nature of carrot juice will

favour the growth and multiplication of acid loving Lactobacillus acidophilus. Quadratic

terms skim milk powder and inoculum level had shown a significant (p < 0.05) effect on

Lactobacillus acidophilus count. The interaction term of “carrot juice and inoculum level” (β

= -4.05), had a significant negative effect on Lactobacillus acidophilus count at 5 % level of

significance respectively.

4.2.5 Diagnostic Checking of Fitted Model and Surface Plots for Bifidobacterium

bifidum Counts


Bifidobacterium bifidum count are given in Table 4.8.









significant effect on Bifidobacterium bifidum count at 5 % level of significance (p < 0.05).

All quadratic term, interactive terms “skim milk powder and inoculum level, “carrot juice and

inoculum level”, also had significant effect on Bifidobacterium bifidum count at 5 % level of

significance (p < 0.05). The quadratic model obtained from the regression analysis for

Bifidobacterium bifidum count in terms of coded levels of the variables after eliminating the

non-significant terms is as follows:

Bifidobacterium bifidum count = 17.92+3.25x1-1.84x2+5.08x3-3.27x12-0.801.24x2

2 -2.21x32-

+0.84x1x3-1.20x2x3 (4.5)

The magnitude of β value from the Table 4.8 revealed that inoculum level (β = 5.08) has a

highest positive linear effect followed by skim milk powder (β = 3.25) on the

Bifidobacterium bifidum count whereas carrot juice has linear negative effect (β = -1.84) on

the Bifidobacterium bifidum count at 5 % level of significance (p < 0.05).

Table 4.8 Regression summery and ANOVA table for Bifidobacterium bifidum count for


SourceSymbo

l

β-

coefficien

t

Sum of

Squares

d

f

Mean

Square

F-

Valuep-Value

Model 17.92 768.09 9 85.34 193.15<0.0001

*

A x1 3.25 144.60 1 144.60 327.28<0.0001

*

B x2 -1.84 46.01 1 46.01 104.14<0.0001

*

C x3 5.08 352.80 1 352.80 798.49<0.0001

*

A*A x12 -3.27 154.01 1 154.01 348.56

<0.0001

*

B * B x22 -0.80 9.29 1 9.29 21.03

<0.0010

*

C*C x32 -2.21 70.17 1 70.17 158.81

<0.0001

*

A*B x1 x2 -0.27 0.56 1 0.56 1.27 0.2858

A*C x1 x3 0.84 5.68 1 5.68 12.85 0.0050*

B*C x2 x3 -1.20 11.47 1 11.47 25.96<

0.0005*

R2 0.9943

Adjuste

d R20.9891


This indicates that with the increase in inoculum level, skim milk powder there will be an

increase in Bifidobacterium bifidum count. An increase in Bifidobacterium bifidum count has

been observed with increase in inoculum level might be due to high initial number of

microorganisms [42].

With increase in amount of skim milk powder, Bifidobacterium bifidum get more availability

of nutrients and better protection from lowering of pH, resulting in increased count [5]. Fig

4.6 also indicates increase in Bifidobacterium bifidum count with increase in inoculum level

and there was an increase in Bifidobacterium bifidum count of yoghurt with increasing of

skim milk. Fig 4.7 indicates decrease in Bifidobacterium bifidum count with increase in

carrot juice might be due to higher number of Lactobacillus acidophilus which may have

suppressed growth of Bifidobacterium bifidum.

Fig. 4.6 Effect of skim milk powder and inoculum level on Bifidobacterium bifidum

count (at 15%, v/v carrot juice)

Fig. 4.7 Effect of carrot juice and inoculum level on Bifidobacterium bifidum count (at

16% w/v skim milk)

4.2.6 Diagnostic Checking of Fitted Model and Surface Plots for Overall acceptability


Overall acceptability are given in Table 4.9








The magnitude of p-value from Table 4.9 indicates that linear term of the skim milk and

inoculum had significant effect on overall acceptability at 5 % level of significance (p <

0.05). The quadratic terms of all the variables, also had significant effect on overall

acceptability at 5 % level of significance (p < 0.05).The quadratic model obtained from the

regression analysis for overall acceptability in terms of coded levels of the variables after

eliminating the non-significant terms was as follows:

Overall acceptability = 5.21+0.86x1+0.75x3-0.11x12-0.43x2

2 -0.11 x3

2+0.14x1x3 (4.6)

Table 4.9 Regression summery and ANOVA table for overall acceptability for coded

values of process variables

SourceSymbo

l

β-

coefficien

t

Sum of

Squares

d

f

Mean

Square

F-

Valuep-Value

Model 5.21 20.76 9 2.31 95.54<0.0001

*

A x1 0.86 10.05 1 10.05 416.05<0.0001

*

B x2 -0.054 0.040 1 0.040 1.66 0.2260

C x3 0.75 7.68 1 7.68 318.01<0.0001

*

A*A x12 -0.11 0.18 1 0.18 7.65

<0.0200

*

B * B x22 -0.43 2.68 1 2.68 111.06

<0.0001

*

C*C x32 -0.11 0.18 1 0.18 7.65 <0.0200

*

A*B x1 x2 -0.013 1.250 x10-3 1 1.250 x10-3 0.052 0.8246

A*C x1 x3 0.14 0.15 1 0.15 6.26<0.0313

*

B*C x2 x3 -0.063 0.031 1 0.031 1.29 0.2818

R2 0.9885

Adjuste

d R20.9782


The magnitude of β value (Table 4.9) revealed that skim milk (β = 0.86) has a highest

positive linear effect followed by inoculum level (β = 0.75) on the Sensory at 5 % level of

significance (p < 0.05).Fig indicates that with the increase in amount of skim milk and

inoculum level, there will be increase in overall acceptability of yogurt.

Fig. 4.8 Effect of Skim milk powder and inoculum level on overall acceptability (at 15%

v/v carrot juice)

4.3 Optimization of Process Variables

A numerical multi-response optimization technique was used to find out the optimum levels

of carrot juice, skim milk powder and inoculum level that would give minimum syneresis,

maximum pH, WHC, Lactobacillus acidophilus, Bifidobacterium bifidum count and Sensory

for probiotic yoghurt. The optimum conditions obtained were 17.59 % (w/v) skim milk

powder,12.13 % (v/v) carrot juice , 3.76 % (v/v) inoculum level. Corresponding to these

optimum levels, the predicted value of syneresis, pH, WHC , Lactobacillus acidophilus

Bifidobacterium bifidum count and Overall acceptability were found to be 37.45 %, 3.65,

42.6 %, 54.34 x 109 cfu/ml , 22.96 x 109 cfu/ml and 6.33 respectively. The total phenolic

content and β-carotene of optimized carrot fortified yogurt were found to be 35µg/ml

and13µg/100g.

Unal et al. [34] also used response surface methodology to describe the combined effect of

storage time, locust bean gum and dry matter of milk on the physical properties of low-fat set

yoghurt and found ideal concentrations of dry matter and locust bean gum as 14 and 0.02 gm

per 100 gm, respectively.

4.4 Storage Study of Optimized Sample

The tabular data for the effect of storage on physico-chemical and microbiological

characteristics of the carrot fortified probiotic yoghurt are shown in Table 4.10. The initial

values of percent syneresis for fresh yoghurts were found to be 37.45% which on storage of

28 days found to be 42.1 %. The results are in conformation with the research of Fox et al.

[45], wherein they stated that rate of syneresis is directly related to the acidity and therefore is

inversely related to pH.

During storage, the pH in fresh sample decreased from 3.65 to 3.43. Fig. 4.11 shows that pH

decreased constantly throughout the storage period. This decrease might be attributed to the

utilization of residual carbohydrates by viable microorganisms and production of lactic acid,

small amounts of CO2 and formic acid from lactose. Decrease in pH may also be due to

microorganism’s activity [44].

The water holding capacity of yoghurt decreased from 42.6% to 34.12%. Fig 4.12 shows that

water holding capacity decreased constantly throughout the storage period. Decrease in water

holding capacity; it might be depend on the more syneresis and non stable structure.

The changes in the viable counts of probiotic bacteria from manufacturing to storage during

four weeks of the carrot fortified probiotic yoghurt were monitored during manufacture and

storage of yoghurt for 28 days at 5°C. It was observed that the strains of Lactobacillus

acidophilus and Bifidobacterium bifidum shown good viability in combination with the basic

yoghurt cultures. However, the counts after 28 days remained more than suggested level of

>107cfu gm-1 [46]. The results are in close conformation with Martin who found that probiotic

were acid tolerant and can survived in sufficiently higher numbers to remain viable in

cultured dairy products even during storage. This point could be beneficial to manufacturer in

using these strains on industrial scale, to produce functional products with better viability of

beneficial microorganisms [47].

Table 4.10 Effect of storage on syneresis, pH, Lactobacillus acidophilus count and

Bifidobacterium bifidum count

Response Fresh 1 day 7 days 14

days

21

days

28

days

Syneresis (%, v/w) 37.45 37.90 38.7 39.8 40.6 42.1

pH 3.65 3.64 3.59 3.54 3.49 3.43

WHC(%, w/w) 42.6 41.01 39.45 37.23 36.35 34.12

Lactobacillus acidophilus count

(x109cfu/ml)52.3 53.3 51.1 50.2 48.5 45.5

Bifidobacterium bifidum count

(x109cfu/ml)22.8 23.8 21.3 19.8 15.8 10.3

Lactobacillus acidophilus had shown sharp decrease after 21st day and shown good viability

for 21 days. Bifidobacterium bifidum count shown sharp decrease throughout the storage

period but is more than suggested value of 107 per gm. This dramatic loss termed acidophilus

death may be attributed to hydrogen peroxide produced by the starter lactobacilli. Mahmoud

et al. [48], stated decrease in Lactobacillus acidophilus and Bifidobacterium bifidum due to

antagonist relationship between yoghurt bacteria and probiotic strains and also stated that

dissolved oxygen content directly affected survival of L. acidophilus during storage.

According to Champagne et al. [49], oxygen affects the probiotic cultures in two ways. The

first is a direct toxicity to cells. Certain probiotic cultures are very sensitive to oxygen and die

in its presence, presumably due to the intracellular production of hydrogen peroxide. The

second way the oxygen effects the probiotic cultures is indirect, when oxygen is in the

medium certain cultures, particularly L. delbrueckii, excrete peroxide in the medium and a

synergistic inhibition of bifidobacteria by acid and peroxide has been demonstrated [49].

Shah [38], states that antagonism among the bacteria used in starter cultures caused by

antimicrobial substances such as bacteriocins may decrease the numbers of any sensitive

organisms that may be present in a product or starter culture.

Fig 4.9 Effect of storage on syneresis of carrot fortified probiotic yoghurt

Fig 4.10 Effect of storage on pH of carrot fortified probiotic yoghurt

Fig 4.11 Effect of storage on WHC of carrot fortified probiotic yoghurt

Fig 4.12 Effect of storage on Lactobacillus acidophilus count (cfu/ml) of carrot fortified

probiotic yoghurt

Fig 4.13 Effect of storage on Bifidobacterium bifidum count (cfu/ml) of carrot

fortified probiotic yoghurt

4.chapter r and d

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