Optimization of textural properties of noodles with soluble fiber, dough mixing time and different water levels

Journal of Cereal Science 69 (2016) 104e110

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Journal of Cereal Science journal homepage: www.elsevier.com/locate/jcs

Optimization of textural properties of noodles with soluble fiber, dough mixing time and different water levels Deepak Mudgil a, *, Sheweta Barak a, B.S. Khatkar b a b

Department of Dairy and Food Technology, Mansinhbhai Institute of Dairy and Food Technology, Mehsana, Gujarat, 384002, India Department of Food Technology, GJUS&T, Hisar, Haryana-125001, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 July 2015 Received in revised form 10 February 2016 Accepted 25 February 2016 Available online 3 March 2016

Partially hydrolyzed guar gum as soluble fiber source has been investigated for fiber fortified noodles with health benefits. The study investigated the effect of soluble fiber level (1e5 g/100 g of flour), water level (30e40 ml/100 g of flour) and mixing time (2e6 min) on textural properties such as hardness, adhesiveness, cohesiveness, chewiness and resilience. The addition of soluble fiber in flour for noodles making was found to have a significant effect on all the hardness, adhesiveness, cohesiveness, chewiness and resilience whereas water level and mixing time showed significant effect on hardness, adhesiveness and cohesiveness of noodles. The optimized values for soluble fiber level, water level and mixing time were 3.4 g/100 g of flour, 36.0 ml/100 g of flour and 5 min, respectively. Results revealed that fortification of noodles with PHGG (3.4%) increased the soluble fiber content to 3.62% as compared to control noodles (1.07%). © 2016 Elsevier Ltd. All rights reserved.

Keywords: Wheat flour Soluble fiber Noodles Textural properties

1. Introduction Modern life style including low physical activity and poor food habits leads to health problems such as increased obesity, diabetes mellitus and cardiovascular diseases (Sayago-Ayerdi et al., 2011). The addition of dietary fiber to traditional and staple foods can solve these health related problems (Slavin and Lloyd, 2012). Dietary fiber is the edible plant portions or analogous carbohydrates which are undigestable and absorbable in the human small intestine with complete or partial fermentation in the large intestine. Dietary fiber may include polysaccharides, oligosaccharides, lignin, and associated plant substances which undigestable and absorbable in human digestive tract. Beneficial physiological functions performed by dietary fiber may include laxation, blood cholesterol attenuation and blood glucose attenuation (AACC, 2001). Guar gum is galactomannan obtained from seed endosperm of guar plant known as Cyamopsis tetragonolobus. Guar gum is used as thickening and stabilizing agent in many processed food products such as tomato ketchup, ice cream, beverages, bakery and confectionery products (Mudgil et al., 2011, Mudgil et al., 2012a). Complex carbohydrate i.e. galactomannan can perform beneficial functions in

* Corresponding author. E-mail address: [email protected] (D. Mudgil). http://dx.doi.org/10.1016/j.jcs.2016.02.015 0733-5210/© 2016 Elsevier Ltd. All rights reserved.

human physiology. It lowers the cholesterol level, control diabetes and regulate bowel digestive system in human beings (Mudgil et al., 2014a). Guar galactomannan composed of galactose and mannose units. When incorporated in diet the galactomannan serve as a dietary fiber because it is not digested by our intestinal secretions and due to its water solubility, it is termed as soluble dietary fiber. Native guar gum forms a very viscous solution when dispersed in water and contributes to the high water absorption and viscosity of the system. In food applications native guar gum is used as thickener at very low concentration i.e. 0.50% maximum. This is the reason why it cannot be incorporated at higher concentration as such in food products as it affects the product sensory as well as processing properties (Mudgil et al., 2012b). Hence enzymatic hydrolysis of guar gum is done to produce partially hydrolyzed guar gum (PHGG). Enzymatic hydrolysis of native guar gum reduces mannose chain length in guar galactomannan which leads to the reduction of degree of polymerization from 3295 to 29 (Mudgil et al., 2012c). The reduction in degree of polymerization results in low viscosity of PHGG (5 cps) as compared to native guar gum (5500cps) (Mudgil et al., 2014b). Studies showed that PHGG is similar in basic molecular structure to native guar gum. Enzymatic hydrolysis of guar gum primarily causes the reduction in chain length of polysaccharide and thus reduces the molecular weight and viscosity of guar gum. Fortification of food products with soluble fiber is in considerable

D. Mudgil et al. / Journal of Cereal Science 69 (2016) 104e110

interest as it could contribute to increasing demand of daily recommended fiber intake. In past studies it has been reported that PHGG is tasteless, odorless and give transparent solution in water with low viscosity upto 10 mPa s. These properties made it a unique source of water soluble dietary fiber (Greenberg and Sellman, 1998). In Asian countries, noodles constitute an integral part of the diet. Noodles are processed from refined wheat flour (Zhang et al., 2010). Attempts have been made by scientists to improve nutritional properties of food products (Singh et al., 1996; Ellis, 1985). Researchers have tried to incorporate nutritionally significant material such as fiber and fiber source in noodles and evaluate the textural and sensory characteristics of noodles with composite wheat flour (Izydorczyk et al., 2005; Mohamed et al., 2005; Lagasse et al., 2006). Understanding of technological functions of ingredient and process variables would be a need for industrial production of soluble fiber enriched noodles in order to attain optimum textural quality. Fortification of dietary fiber in food products involves a major problem that negatively affects the product's functional properties (Shukla and Srivastava, 2014). Response surface methodology (RSM) is a statistical and mathematical approach used for development, improvement, and optimization of processes. It can also be applied to processes for cost reduction and efficient process development. It relates the processing variables to regression equations which describe the interrelationship between processing variables and responses (Brennan and Samyue, 2004). RSM can be applied to study the effect of the independent variables, alone or in combination, on the processes. In addition, it also generates a mathematical model which describes interrelations between independent variables and dependent variables (Montgomery, 1984; Myers and Montgomery, 1995). Owing to its high viscosity, native guar gum cannot be used as a source of dietary fiber at higher concentration in the wheat products as it hampers the dough handling and processing properties. Thus, partially hydrolyzed guar gum was prepared and used for high fiber noodle formulation as it does not affect the dough properties due to its low viscosity. The present study was employed to understand the effect of processing parameters such as PHGG level, water level and mixing time upon the textural properties such as hardness, adhesiveness, cohesiveness, chewiness and resilience of noodles. To study the interrelationship among processing variables and for their optimization, second order polynomial models were developed to obtain noodles with optimum textural properties such as hardness, adhesiveness, cohesiveness, chewiness and resilience of noodles. 2. Material and methods 2.1. Materials Guar gum was obtained from Hindustan Gums and Chemicals, Haryana, India. To obtain a uniform particle size fine powder guar gum sample was passed through 200 mesh sieve and was stored under refrigerated conditions before analysis. All chemical of Analytical Reagent (AR) grade were obtained from Central Drug House, New Delhi, India. Cellulase enzyme (Aspergillus niger) was obtained from USB, Cleveland, Ohio, USA. Refined wheat flour and salt were procured from local market Hisar, India. 2.2. PHGG preparation Native guar gum was subjected to enzymatic hydrolysis to prepare partially hydrolyzed guar gum. Hydrolysis of guar gum was carried out using cellulase from Aspergilus niger (1.0 mg/g) at pH 6

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in aqueous solution maintained at 50
C. Partially hydrolyzed guar gum aqueous solution obtained after enzymatic hydrolysis showed a viscosity of 5cps. The solution was then filtered, freeze dried and ground to powder. Before analysis it was passed through 200 mesh sieve to obtain uniform particle size fine powder as that of native guar gum (Mudgil et al., 2014b). 2.3. Analysis of wheat flour, native guar gum and PHGG Moisture, fat, protein and ash content of wheat flour, native guar gum and PHGG was determined following standard method of analysis (AOAC, 1990). Enzymatic method of Furda was employed to determine total dietary fiber (TDF), soluble dietary fiber (SDF) and insoluble dietary fiber (IDF) in native guar gum and PHGG (Furda, 1981). Aqueous solution of guar gum (GG) and partially hydrolyzed guar gum (PHGG) at 1% concentration (w/w) were used for viscosity estimation. Viscosity of gum solutions was analyzed using viscometer (Brookfield, USA) with spindle no. 4 (GG) and 2 (PHGG) at 20 rpm and 25
C temperature. Average molecular weight (Mv) of guar gum and partially hydrolyzed guar gum was determined from intrinsic viscosity using Mark-Houwink's equation, [h] ¼ k Mva with a ¼ 0.732 and k ¼ 3.8  104 (Robinson et al., 1982). 2.4. Experimental design In the present study, response surface methodology was employed for the optimization of variables. It involves the design of experiment, selection of variables levels in experimental runs, mathematical models fitting and selection of optimized levels of variables with respect to optimized response levels. A central composite design (CCD) was used to investigate the effect of three independent variables at five different levels on response pattern and to determine the optimum combination of variables. Twenty experiments were conducted for the present research work. Present study was conducted to study the effect of processing parameters such as PHGG level, water level and mixing time on textural properties of noodles such as hardness, adhesiveness, cohesiveness, chewiness and resilience. The independent variables optimized were X1(PHGG level), X2 (water level), X3 (mixing time) for dependent response Y1 (hardness), Y2 (adhesiveness), Y3 (cohesiveness) Y4 (chewiness) and Y5 (resilience). The minimum and maximum values for PHGG level was set at 1% and 5%. Maximum level of PHGG fortification in noodle was fixed at 5% on the basis of results obtained from screening trails which reveal that PHGG fortification in noodles above 5% leads to unacceptable higher cooking loss due to its water solubility. Another reason for selecting maximum limit of PHGG at 5% level was its fiber content; PHGG fortified noodles at 5% level can provide around 8 g of fiber per serving (serving size 200 g). Water levels varied from 30% to 40% as the optimum water requirement for noodle making is 35% (Barak et al., 2014). The mixing time was varied from 2 min to 6 min as the optimum mixing time for noodle making was 4 min as described in section 2.5. Twenty combinations of complete design (including central points ¼ 6, star points ¼ 6, number of factorials ¼ 8 & alpha ¼ 1.682) were performed in random order (Table 1). The model proposed for responses was

Y ¼ b0 þ

i¼3 X i¼1

bi X i þ

i¼3 X i¼1

bii Xii2 þ

i¼3 X

bij Xi Xj þ e

(1)

i < j¼2

where b0 is the value for the fixed response at the central point of the experiment; and bi, bii and bij are the linear, quadratic and cross-product coefficients, respectively.

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Table 1 Experimental design for partially hydrolyzed guar gum fortified noodles with respective variables (X) and response value (Y). Run

X1

X2

X3

Y1

Y2

Y3

Y4

Y5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

1.81 1.81 5.00 1.81 1.81 4.19 3.00 3.00 4.19 3.00 4.19 3.00 4.19 3.00 3.00 1.00 3.00 3.00 3.00 3.00

37.97 32.03 35.00 37.97 32.03 32.03 35.00 30.00 32.03 35.00 37.97 35.00 37.97 35.00 35.00 35.00 35.00 35.00 35.00 40.00

2.81 2.81 4.00 5.19 5.19 5.19 4.00 4.00 2.81 4.00 5.19 4.00 2.81 2.00 4.00 4.00 4.00 6.00 4.00 4.00

9.26 9.11 11.3 9.23 9.36 9.8 7.48 7.84 9.5 6.68 9.89 7.7 9.91 8.06 7.37 10.5 7.84 8.13 7.75 7.96

0.2409 0.231 0.2913 0.2737 0.279 0.2893 0.1945 0.2671 0.2702 0.1956 0.2826 0.1855 0.2817 0.2004 0.2217 0.2616 0.1939 0.2394 0.2072 0.2602

0.5153 0.4935 0.5039 0.5346 0.4714 0.495 0.3949 0.4091 0.4327 0.4461 0.5177 0.4086 0.4343 0.3897 0.4372 0.5845 0.4123 0.4678 0.3901 0.4312

3.504 3.348 3.926 3.591 3.563 4.018 3.743 3.859 3.982 3.645 3.997 3.719 3.947 3.672 3.856 2.831 3.735 3.783 3.829 3.924

4.358 4.362 5.384 4.612 4.353 4.746 4.978 4.765 5.09 4.983 4.719 5.126 4.871 4.952 5.231 4.43 4.816 4.934 5.019 4.818

X1(PHGG level, g/100 g of flour), X2 (water level, ml/100 g of flour), X3 (mixing time, min) for dependent response Y1 (hardness, N), Y2 (adhesiveness, N.mm), Y3 (cohesiveness, ratio), Y4 (chewiness, N.mm) and Y5 (resilience, ratio).

2.5. Preparation of noodles Control white salted noodles (without PHGG) were prepared according to Barak et al. (2014), with slight modifications. Wheat flour (100 g) was mixed with 35 ml water and 2 g sodium chloride in a mixer for 4 min at a medium speed (86 rpm). For preparation of PHGG fortified noodles, wheat flour was mixed with partially hydrolyzed guar gum at replacement levels of 1, 1.81, 3, 4.19 and 5%. The dough was then passed through the rolls of noodle making machine at 3 mm gap, it was folded and passed through the rolls twice again. The dough sheet was subjected to rest for 1 h and then again rolled through the sheeting rolls three times at progressively smaller gap settings of 2.40 mm, 1.85 mm and 1.30 mm, respectively. The sheet was then cut into noodle strands by machine. Noodles were put into plastic bags and stored at 4
C for 24 h until cooked. Noodles (10 g) were cooked in 400 ml of boiling water for 5 min and subsequently rinsed in cold water to prevent the overcooking of the noodles. Effect of water level from 30% to 40% and mixing time 2e6 min on noodles supplemented with PHGG from 1% to 5% was studied. 2.6. Texture profile analysis of cooked noodles Cooked noodles were analyzed for textural characteristics such as hardness, adhesiveness, cohesiveness, chewiness and resilience. Textural properties were measured using Texture Profile Analysis (TPA) with Texture Analyzer, TA-XT2i (Stable Micro Systems, Surrey, United Kingdom). The TPA was calculated from the areas of the forcee time curves of two compressions using a flat-end cylindrical plunger (25-mm probe) descending to 70% of the original height of the noodles. Crosshead speeds of 4.0, 1.0 and 1.0 mm s1 were maintained for pretest, test and post test settings, respectively. Five independent observations were made using two cooked noodle strands (2-cm long) placed side by side.

hardness, adhesiveness, cohesiveness, chewiness and resilience of the cooked noodles. Analysis of variance (ANOVA) and regression analysis using Design-Expert 8.0.4.1 (Stat Ease, Minneapolis, Minnesota, USA) were conducted for model fitting. A second-order polynomial was fitted to the data to obtain regression equations. The terms in the regression equations was examined for statistical significance. The significance of the models was examined using model analysis, coefficient of determination (R2) value and lack of fit test (Weng et al., 2001). A model with insignificant lack of fit is adequate for explaining the response. Coefficient of determination (R2) is the ratio of explained variation to the total variation and it also explained the fitness of the model. The effect of variables at linear, quadratic and interactive level on the response was described. 2.8. Optimization Numerical optimization technique of the Design-Expert (v. 8.0.4.1) software was used for optimization of the multiple responses. The desired goal for each dependent variable was selected. For numerical optimization all independent variables were kept within range while the dependent variables, cohesiveness, chewiness and resilience of noodles were maximized, whereas hardness and adhesiveness of noodles were minimized. In order to search a solution, the goals are combined into an overall composite function, D(x), called the desirability function (Myers and Montgomery, 1995), which is defined as:

DðxÞ ¼ ðd1  d2  …  dn Þ1=n

(2)

where, d1, d2,…,dn are the responses and ‘n’ is the total number of responses in the measure. The numerical optimization determines a point that enhances the desirability function to maximum. Response surface graphs were generated with the help of commercial statistical package Design-Expert (v. 8.0.4.1). The response surface graphs obtained from experimental data showed the effect of variation in independent variables on the responses. 2.9. Characterization of control and optimized noodles Control noodle was prepared without addition of PHGG and at optimum level of water and mixing time. Optimized noodles were prepared using optimum values of PHGG, water level, and mixing time obtained from Numerical optimization technique of the Design-Expert. Cooking yield and cooking loss of noodles were determined by method used by Inglett et al. (2005). Cooking yield (%) ¼ [(weight of cooked noodles-weight of dried noodles)/ weight of dried noodles]  100 (3) Cooking loss (%) ¼ [weight of dried residue/weight of dry noodles before cooking]  100. (4) Enzymatic method of Furda was employed to determine soluble dietary fiber (SDF) in control and optimized PHGG fortified noodles (Furda, 1981). 3. Results and discussion 3.1. Wheat flour, native guar gum and PHGG analysis

2.7. Data analysis The data obtained from experiments was analyzed for optimization of processing variables with respect to the responses, viz.

Moisture, protein, ash and fat content, total dietary fiber (TDF), insoluble dietary fiber (IDF) and soluble dietary fiber (SDF) of wheat flour, native and partially hydrolyzed guar gum has been presented

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in Table 2. Results revealed that partial hydrolysis of guar gum led to decrease in moisture, protein, viscosity and molecular weight, however, an increase in fat and ash content as compared to native guar gum was observed. These results are in accordance with the results reported by Greenberg and Sellman (1998). TDF, IDF & SDF in native guar gum was not determined due to its very high viscosity. Analysis result showed that PHGG contained 83.1% total dietary fiber out of which 80.4% was soluble dietary fiber and can be considered a rich source of total dietary fiber (TDF) and soluble dietary fiber (SDF). These findings are in agreement with the results reported by Yoon et al. 2008. Viscosity of native guar gum was very high (5500cps) as compared to PHGG (5 cps). Enzymatic hydrolysis of native guar gum also reduced its molecular weight from 889742 to 7936 Da (Table 2). 3.2. Diagnostic checking of the models Response surface analysis was done to study the experimental data. Model terms were examined for statistical significance with analysis of variance (ANOVA). Lack of fit test (F-values) for all the models were observed insignificant which describe the adequacy of models to predict responses. R2 values for all the models were more than 0.92 (except for resilience R2 ¼ 0.82) which further validated the model. All the models were statistically adequate and were used to study the effect of independent variables or processing parameters on the various responses. The result of the regression analysis and analysis of variance (ANOVA) for all the models is reported in Table 3. 3.3. Response surface plotting Response surfaces were studied to investigate the effect of independent variables such as PHGG level, water level and mixing time on responses, hardness, adhesiveness, cohesiveness, chewiness and resilience of noodles. Figs. 1 and 2 represents the response surface graphs obtained from experimental data. 3.4. Effect of process variables on hardness of noodles Hardness is a measure of firmness of the noodles. Hardness of noodles is contributed by the strength of gluten proteins network. Variations in hardness of noodles with changes in water level and PHGG level are shown in Fig. 1a. On PHGG supplementation, hardness of noodles first decreased and then increased. Hardness of the noodles was observed minimum at 2.5e3.0% of PHGG level. Mohamed et al. (2005) also reported decrease in hardness of noodles when fortified with Nutrim OB- a soluble fiber source. Shukla and Srivastava (2014) also reported a reduction in hardness of noodles fortified with millet flour. The decrease in noodle Table 2 Physicochemical analysis of native and partially hydrolyzed guar gum. Parametersa

Wheat flour

Native guar gum

PHGGc

Moisture (%) Ash (%) Protein (%) Fat (%) SDF (%) IDF (%) TDF (%) Viscosity (cps) Molecular Weight (Da)

11.06 0.41 12.34 1.31 e e 2.4 e e

10.82 0.69 4.32 0.33 ndb ndb ndb 5500 889742

8.0 2.6 2.0 1.1 80.4 2.7 83.1 5.0 7936

a b c

The values are average of determinations made in triplicates. not determined (due to high viscosity of guar gum). partially hydrolyzed guar gum.

107

hardness could be attributed to the dilution of gluten network due to addition of PHGG (Izydorczyk et al., 2005). Similar results were reported by Zhang et al. (2010) when noodles were fortified with sweet potato flour. The effect of mixing time on the hardness of cooked noodles is shown in Fig. 1b. Mixing time did not affect the hardness characteristic of noodles significantly. However, the optimum range for softer noodles was observed between 3.5 and 4.0 min Fig. 1c represents the effect of mixing time and water level on hardness of cooked noodles. Lowest hardness was observed near 33.5% water level and 3.5e4.0 min of mixing time. 3.5. Effect of process variables on adhesiveness of noodles Adhesiveness is a measure of stickiness of noodles and is negatively related to noodle quality. Relationship between water level and PHGG level with adhesiveness is shown in Fig. 1d. Adhesiveness characteristic of the noodles decreased with supplementation of noodles with PHGG upto 3% replacement level. Gluten and soluble fiber binds water which suppresses noodle adhesiveness (Husniati and Anastasia, 2013). In the present study, PHGG bound the free water which resulted in decreased adhesiveness values in cooked noodles. Similarly, Zhang et al. (2010) also reported that incorporation of sweet potato flour (SPF) upto 10% in noodles decreased the adhesiveness and further SPF addition increased the adhesiveness. Increase in water level of noodles upto 35% decreased the adhesiveness of noodles. Fig. 1e represents the effect of PHGG level and mixing time on adhesiveness of noodles. At lower mixing time upto 2 min, adhesiveness of noodles remained almost unchanged upto 3% supplementation of PHGG. Minimum adhesiveness was observed at 3.5e4.0 min of mixing time. However, further increase in mixing time, increased the adhesiveness value of cooked noodles. This could be due to increase in thiol groups in the overmixed dough which are responsible for stickiness of dough. The effect of mixing time and water level on adhesiveness of noodles is shown in Fig. 1f. 3.6. Effect of process variables on cohesiveness of noodles Cohesiveness is the measure of strength of internal bonds, particularly gluten and is related to consumer acceptability of noodles. Fig. 1g represents the effect of water and PHGG levels on cohesiveness of noodles. Cohesiveness of the noodles decreased with increase in PHGG level while it increased with rise in water level. Minimum cohesiveness was observed in the region 3.0e3.7% PHGG level. The optimum water absorption for noodles should hydrate the surface of flour particles to form cohesive noodle granule during mixing and to develop the gluten during sheeting (Oh et al., 1985). The decrease in cohesiveness of noodles upon addition of PHGG was due to dual effect of PHGG on noodle dough. Firstly, replacement of wheat flour with PHGG decreased the gluten proteins in the flour and secondly, the added water was taken up by PHGG, which led to reduced availability of water for gluten network formation. However, at higher water levels, sufficient water was available for gluten formation, which resulted in increased cohesiveness value of cooked noodle (Barak et al., 2014).Relationship between mixing time, PHGG level, water level and cohesiveness is shown in Fig. 1h and Fig. 1i. 3.7. Effect of process variables on chewiness and resilience of noodles Chewiness is the energy needed to break down the noodles to the swallowing state. Resilience describes the rubbery state of the noodles and is a measure of recoverable energy after compression (Mohamed et al., 2005). It depends on the overall gluten proteins

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Table 3 Regression analysis of second order polynomial models for various responses. Predictor

Intercept X1 X2 X3 X1 X2 X1 X3 X2 X3 X21 X22 X23 ANOVA Model (F-value) Lack-of-fit (F-value) R2 [%] c.v. [%]

b (coded factors) Hardness

Adhesiveness

Cohesiveness

Chewiness

Resilience

7.460 0.260** 0.053 0.045 0.060 0.007 0.075 1.310*** 0.250 ** 0.320**

0.20 0.011*** 0.0001 0.012*** 0.00002 0.0076* 0.0041 0.030*** 0.025*** 0.0096***

0.41 0.020*** 0.011* 0.020*** 0.007 0.019** 0.008 0.050*** 0.006 0.009

3.75 0.28*** 0.017 0.042* 0.030 0.027 0.014 0.12*** 0.066** 0.008

5.03 0.24 0.007 0.021 0.063 0.093 0.057 0.091 0.13 0.078

18.69 0.74 94.4 4.5

19.98 0.66 94.7 4.8

13.74 0.67 92.5 4.5

19.49 1.64 94.6 2.4

5.11 1.91 82.1 3.5

c.v. - coefficient of variation. X1(PHGG level, g/100 g of flour), X2 (water level, ml/100 g of flour), X3 (mixing time, min) for dependent response Y1 (hardness, N), Y2 (adhesiveness, N.mm), Y3 (cohesiveness, ratio), Y4 (chewiness, N.mm) and Y5 (resilience, ratio). *significant at p < 0.1, ** significant at p < 0.05, *** significant at p < 0.01; X1, PHGG level; X2, water level; X3, mixing time.

network which provides viscoelasiticity to the dough system. Chewiness of the noodles increased with the increase in PHGG level (Fig. 2a) while water level and mixing time did not show any significant effect on the chewiness of noodles (Fig. 2b). The reason for

increase in chewiness of the cooked noodles with PHGG supplementation may be due to the viscosity effect of PHGG at higher concentration which may further enhance the viscoelasiticity of the overall gluten network and hence the increased chewiness.

Fig. 1. (aei):Effect of PHGG level, water level and mixing time on hardness, adhesiveness and cohesiveness of noodles.

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Fig. 2. (aef): Effect of PHGG level, water level and mixing time on chewiness and resilience of noodles.

Resilience of cooked noodles showed increasing trend with increase in water and PHGG levels (Fig. 2d). The optimum region for maximal resilience was found to be at 3.5e4.0% PHGG level and 35% water level. 3.8. Optimization of variables and model verifications Design-Expert (v. 8.0.4.1) software was used for numerical optimization of processing variables. Optimum values of processing variables were obtained after assigning certain constraints (maximize or minimize) on response variables (i.e. hardness, adhesiveness, cohesiveness, chewiness and resilience). Optimum values of processing variable and responses are shown in Table 4. Confirmative test was conducted for verification of model using optimum levels of independent variables (PHGG level 3.4%, water level 36.0% and mixing time 5 min). The experimental values obtained at optimum conditions of processing variables were 8.05, 0.23, 0.49, 3.9 and 5.1 for hardness, adhesiveness, cohesiveness, chewiness and resilience of noodles, respectively, were similar to the predicted values. Thus, the confirmative test validated the experimental results as well as regression model. 3.9. Characterization of control and optimized noodles PHGG supplementation at 3.4% concentration increased the

Table 4 Numerical optimization of processing variables. Parameters

Goal

Lower limit

Upper limit

Optimum value

PHGG level (%) Water level (%) Mixing time (min) Responses Hardness (N) Adhesiveness (N.mm) Cohesiveness Chewiness (N.mm) Resilience

in range in range in range

1.0 30.0 2.0

5.0 40.0 6.0

3.4 36.0 5.0

maximize minimize maximize maximize maximize

6.68 0.1855 0.3897 2.831 4.353

11.3 0.2913 0.5845 4.018 5.384

8.03 0.22 0.45 3.88 5.0

values of cooking loss and soluble fiber content of cooked noodles (Table 5). Cooking yield of noodles fortified with PHGG decreased from 270.53 to 261.34%. The increase in cooking loss from 4.91 to 6.09 may be due to loss of PHGG because of its water soluble nature during cooking of noodles. An appreciable increase in soluble fiber content of cooked noodles (3.62%) fortified at 3.4% PHGG level was observed as compared to control noodles (1.07%). This increase in soluble fiber is quite sufficient to cater the need of daily fiber requirement.

4. Conclusion Response surface methodology was effectively utilized for optimization of processing variables (PHGG level, water level and mixing time) for preparation of partially hydrolyzed guar gum fortified noodles. Model validation was performed by analyzing various significant statistical aids such as coefficient of determination (R2), F-value, lack-of-fit test, coefficient of variation (c.v.). All these statistical terms revealed the adequacy of model. It can be concluded that PHGG level was found to have significant effect on all the responses except resilience of noodles whereas water level showed significant effect on noodles cohesiveness (p < 0.1). Mixing time showed significant effect on adhesiveness (p < 0.01), cohesiveness (p < 0.01) and chewiness (p < 0.1) of noodles. The predicted and actual values were in agreement with each other. Present results suggest that noodles supplemented with PHGG nearly at 3.4% level results in noodles with softer texture, maximum cohesiveness, chewiness and resilience of noodles and minimum

Table 5 Characterization of control and optimized noodles.

Cooking loss (%) Cooking yield (%) Soluble fiber (%) Insoluble fiber (%)

Control noodles

3.4% PHGG fortified noodles

4.91 270.53 1.07 0.87

6.09 261.34 3.62 1.09

The values are average of determinations made in triplicates.

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