Instrumental Textural Profile Analysis of Soy Fortified Pressed Chilled Acid Coagulated Curd (Paneer)

Abstract

Studies were conducted to observe the effect of varying fat content in milk (0–6%) and varying proportion of soy milk (7.5°B, 0–40%) in the blend on the textural properties of Soy Fortified Paneer (SFP). Instrumental Texture Analyzer of Stable Micro System was used to measure the texture of paneer containing varying level of fat and soy solids for texturel profile analysis (TPA). Texture profile data, thus obtained, were used to develop regression models between fat content in milk and proportion of soy milk in blend with that of the dependent variable hardness, cohesiveness, chewiness, springiness and adhesiveness. The high correlation coefficients of each developed model confirmed its suitability in representing experimental data. Based on to these models SFP samples prepared using a blend (15:85 v/v) of soy milk (7.5°B) and buffalo milk (3.12%) was found to be suitable for producing textural characteristics similar to that of control paneer sample.

Keywords:

• Buffalo milk
• Coagulation
• Pressing
• RSM
• Soy milk
• Soy fortified paneer
• Textural profile analysis

Introduction

Paneer is highly nutritious heat–acid coagulated indigenous milk product, which occupies an important place in Indian diet. However, the high cost of paneer has restricted its use to mainly the elite and upper middle class of society and poses a great hurdle in its popularization particularly among the middle class and the poor. Milk fat is one of the major factors for high cost of paneer with its possible dietary risk factor in causing coronary heart disease (CHD).

In view of the high cost and increasing occurrence of coronary complications there is considerable interest to reduce/replace the milk fat in paneer. This amount to the manufacture of paneer like products utilizing nonconventional food solids, which are not only cheaper but also can be converted into product that resembled closely to paneer in textural and nutritional characteristics. Soybean is one such food material, which is popular for producing low cost high nutritional value product. Soybean products represent an inexpensive and abandoned source of protein.

Replacing a part of milk used in making paneer with soybean milk could give economical and nutritional product. Addition of the soy solids in milk influences textural and sensory characteristics of paneer.

Many researchers have recommended blending of soy milk with buffalo milk for the preparation of paneer and cheese.1 2 3 Addition of soymilk to buffalo milk up to 20% had no adverse effect on quality of paneer, which resembled with milk paneer in taste, colour and springiness.4 5 Fortification of milk with soy and groundnut were reported to decrease hardness of paneer.6 Mixing of soymilk with cow milk during cheese making resulted in products with higher moisture content and weaker body and texture as compared to those made from the cow milk only.7 8 9 In order to prepare soy fortified paneer (SFP) of a desired sensory and textural quality the selection of a proper blend of soy milk and buffalo milk as well as their composition is very important.

Possibility of using milk of varying fat content in association with soy milk has not been properly explored and the contribution of the milk fat content and soy solids on textural characteristics of paneer is not clearly understood. This article describes the effect of the variations of fat content in buffalo milk and soy solid incorporation on textural characteristics of paneer. Effort has also been made to establish models to estimate the textural characteristics of SFP and to optimize the milk fat and soy solid based formulations.

Material and Methods

Preparation of Soy Fortified Paneer (SFP)

Twenty-five different combinations of soy milk (7.5°B, fat 1.71 ± 0.04, 4.76 ± 0.03) and buffalo milk (fat 6–6.6%, protein 3.78 ± 0.06) standardized to varying fat content (0–6%) were used for preparation of SFP samples (Table 1).

Table 1 Levels, codes, and intervals of variations of independent variables

		Levels
Variables	Codes	−1	−0.5	0	0.5	1	Interval of variation
Fat content in buffalo milk (%)	FAT	0	1.5	3	4.5	6	1.5
Proportion of soy milk in blend (%)	SOY	0	10	20	30	40	10

Soymilk was prepared from whole soy beans using the boiling water grinding technique.10 The SFP samples were prepared using the method similar to that prescribed by Bhattacharya et al.11 Buffalo–soy milk blends, heated to 363°K, were cooled to 343°K and coagulated with citric acid 1% w/v. Obtained whey was drained out and coagulum is kept for pressing under 147–196 kP pressure for 20–30 min. The pressed mass was then cooled by dipping in chilled water (277°K) for 2 h. Process flow chart for the preparation of soy fortified paneer is given in Fig. 1.

Figure 1. Process flow chart for the preparation of soy fortified paneer.

Instrumental Texture Profile Analysis (TPA)

TPA tests were performed using TA.XT2 Texture Analyzer (Texture Technologies Corp., UK, Model TA.XT2, version 05.16) of Stablemicro System equipped with 5-kg load cell. The analyzer is linked to a computer that recorded the data via a software program XT.RA Dimension, version 3.7H, Texture Technologies Corp., Scarsdale, NY. Experiments were carried out by compression test that generated plot of force (N) vs. time (s), from which texture values were obtained. A 25 mm diameter perplex cylindrical probe was used to compress 10 mm diameter and approximately 10 mm long paneer samples. In the first stage the samples were compressed up to 80% of their original length. The speed of the probe was fixed at 0.5 mm s⁻¹ during the pretest, compression and the relaxation of the samples. During the testing, the samples were held manually against the base plate. The typical textural profile (force-time) curve obtained with one complete run is presented in Fig. 2. The data obtained from curve were used for the calculation of the textural parameters as follows12:

Figure 2. Typical texture profile curve generated by the texture analyzer TA.XT 2.

Design of Experiment

The experimental plan was prepared using the factorial design to evaluate the combined effect of the independent variables, viz. fat content in milk (FAT) and proportion of soy milk in the blend (SOY) on instrumental textural parameters of SFP samples viz. hardness (HD), cohesiveness (CO), chewiness (CH), springiness (SP), and adhesiveness (AD). Levels were selected based on the literature survey and preliminary experiments. The values of the FAT and SOY were coded within +1 and −1 level. The coding of ε _i (real value of independent variables) into X _i was performed using the equation

where ε _i is actual value of the factor, i in original units, ε _{i  (mean)} is the mean of high and low levels of the factor, i and ε _{i  (min)} is minimum value of factor, i.

The relationship between the coded (X ₁, X ₂) and actual values of FAT and SOY were:

Levels, codes, and intervals of variation of variables are presented in Table 1. Response Surface Methodology (RSM)13 was used to study the effect of independent variable on textural characteristics followed by optimization of the blend proportion utilizing the prediction models. A mathematical function, f, was assumed for describing the relationship between each of the response variables, η _i (i.e., the textural characteristics) and the factors (FAT and SOY), ε _i , such as

The exact mathematical representation of the function (f) is either unknown or extremely complex. However, a second order polynomial equation of the following form was assumed to relate η _i and ε _i ;

where, β _o, β _i , β _ii , β _ij are regression coefficients.

Nonlinear regression equations relating the real values of the factor (FAT and SOY) with that of the response variable (HD, CO, CH, SP, and AD) were developed.

A computer programme was developed for multiple regression analysis. This programme had the provision to discard the terms of the regression models, having F value less then 1, that are not significant at any level for any degree of freedom13 and to recompute the coefficients of the remaining terms. The recomputed coefficients of the model were further subjected to the F test 1% level of significance.

Optimization of the FAT and SOY was done by solving the developed equations for specific value of each instrumental textural parameter. The equations were solved for the values of the control paneer sample prepared in the laboratory using buffalo milk (6% fat) only.

Results and Discussion

Textural and rheological properties of coagulated dairy product are affected by their structure. The microstructure of these products consists of a continuous protein matrix with a loose and open structure with space occupied by the fat globules dispersed through the protein network.14 The structural arrangement of the network determines the textural characteristics and is affected by the factors such as the composition and manufacturing processes. Changes in the texture profile parameters of the SFP, which may be classified, as green cheese can be explained in similar manner

Texture profile data for the SFP sample prepared using different combinations of FAT and SOY are shown in Table 2. Data reported are the average of five measurements for three replicates of each combination.

Table 2 Texture profile data of SFP sample prepared using different combinations of fat content in milk and proportion of soy milk in the blend

Variables
FAT		SOY		Textural characteristics
ε F	X1	ε S	X 2	Hardness (N)	Cohesiveness	Adhesiveness (N s)	Springiness	Chewiness (N)
0	−1	0	−1	11.176	0.743	−0.002	0.682	5.663
0	−1	10	−0.5	8.320	0.710	−0.002	0.618	3.651
0	−1	20	0	8.049	0.684	−0.013	0.737	4.058
0	−1	30	0.5	7.007	0.668	−0.008	0.806	3.773
0	−1	40	1	8.550	0.658	−0.009	1.059	5.958
1.5	−0.5	0	−1	10.765	0.706	−0.008	0.661	5.023
1.5	−0.5	10	−0.5	4.977	0.593	−0.039	0.709	2.093
1.5	−0.5	20	0	5.335	0.652	−0.019	0.543	1.889
1.5	−0.5	30	0.5	4.559	0.656	−0.021	0.646	1.929
1.5	−0.5	40	1	5.769	0.630	−0.025	0.846	3.075
3	0	0	−1	12.272	0.678	−0.006	0.665	5.525
3	0	10	−0.5	7.011	0.645	−0.022	0.566	2.560
3	0	20	0	5.281	0.604	−0.028	0.661	2.108
3	0	30	0.5	3.329	0.611	−0.033	0.562	1.143
3	0	40	1	2.821	0.584	−0.034	0.701	1.155
4.5	0.5	0	−1	12.037	0.646	−0.017	0.876	6.812
4.5	0.5	10	−0.5	6.946	0.596	−0.039	0.583	2.414
4.5	0.5	20	0	4.238	0.599	−0.033	0.566	1.437
4.5	0.5	30	0.5	4.159	0.620	−0.027	0.508	1.310
4.5	0.5	40	1	2.303	0.585	−0.046	0.677	0.912
6	1	0	−1	13.721	0.622	−0.015	1.112	9.491
6	1	10	−0.5	8.496	0.597	−0.025	0.856	4.342
6	1	20	0	3.975	0.672	−0.016	0.532	1.421
6	1	30	0.5	2.444	0.570	−0.043	0.660	0.919
6	1	40	1	1.617	0.569	−0.050	0.721	0.663
Standard deviation				3.406	0.046	0.013	0.153	2.231

ε—real values, X—Coded value.

A typical full response model (Eq. (5)) was fitted to the data for each dependent variable. Second-degree polynomial equations were used to approximate the function. Despite the fact that full model appears to reasonably represent the data, better fit were obtained with reduced model. Regression models for the different textural characteristics of SFP are shown in Table 3 with coefficient of correlation.

Table 3 Regression models for the textural characteristics of the soyfortified paneer

Textural characteristics	Regression model	R ^2
Hardness (HD)	11.16 − 0.497 FAT − 0.357 SOY + 0.153 FAT^2 + 0.0072SOY^2 − 0.0394 FAT SOY	0.9761
Cohesiveness (CO)	0.721 − 0.0316 FAT − 0.0015 SOY + 0.0029 FAT^2	0.8395
Chewiness (CH)	5.53 − 0.549 FAT − 0.233 SOY + 0.177 FAT^2 + 0.006 SOY^2−0.0349 FAT SOY	0.9743
Springiness (SP)	0.705 − 0.0423 FAT − 0.010 SOY + 0.017 FAT^2 + 0.0004 SOY^2 − 0.0031 FAT SOY	0.9239
Adhesiveness (AD)	−0.0076 − 0.0067 FAT + 0.00097 FAT^2 − 0.00014 FAT SOY	0.8410

Coefficient of each term of the model were subjected to F test at 5% and 1% significance level with corresponding degree of freedom.13 Effect of each factor on individual textural parameters of SFP is discussed below.

Hardness

Hardness (force necessary to attain a given deformation) is the most commonly evaluated characteristics while determining paneer texture. The coefficients of the first order terms in the equation (Table 3) with real variables indicated that hardness of the product decreases with the increasing FAT and SOY. The FAT was found to have more influence on hardness then SOY. Interaction of FAT with SOY showed negative effect on hardness of SFP.

The effect of linear term of SOY, quadratic terms of FAT and SOY, and its interactions term were highly significant. Decrease in hardness of SFP can be explained by increase in moisture content of product probably due to the increase of soymilk proportion in the blend. Increase in hardness with decrease in fat content may be because of the compact protein matrix with less open spaces, which are occupied by milk fat globules. With reduction in fat content of SFP compact appearance of the protein network increased and number of milk fat globules dispersed within the network decreased.14

Cohesiveness

Cohesiveness, which is defined as the extent to which a material can be deformed before its rupture, depends upon the strength of internal bonds. Negative signs of coefficients of variables FAT and SOY in the regression model indicate decrease in cohesiveness with increase in fat content of milk and proportion of soy milk in blend. Effects of these variables were highly significant where as quadratic term of this model was found to be nonsignificant. The nature of the protein matrix and extent of fat dispersion may contribute to cohesiveness or tendency to adhere to itself.

Chewiness

Energy required to masticate a solid food product to make it ready for swallowing is known as chewiness. This textural characteristic of the SFP was found to be affected negatively by both the variables, FAT and SOY. Linear, quadratic, and interaction terms of the model developed for chewiness were found significant.

Springiness

Springiness is the rate and extent to which a deformed material goes back to its undeformed condition after the force is removed. Springiness responded negatively with variables FAT and SOY. However, effect of FAT on springiness was found to be nonsignificant. Other linear, quadratic, and interaction terms of model have significant effect on springiness of the SFP.

Adhesiveness

Adhesiveness, which is a force necessary to remove the material that adheres to the mouth during eating, decreased with increase of FAT in the SFP. Soy solids alone had no effect on the adhesiveness but in association with fat it decreases the adhesiveness of SFP. Linear, quadratic, and interaction terms of models for adhesiveness were observed to be significant. Protein content has been the dominant factor influencing adhesiveness of protein rich products of varying composition.15 Most adhesive cheese was those containing an open and loose protein matrix as in the higher fat cheese. Olson and Johnson16 reported low fat cheeses exhibiting a higher degree of stickiness when masticated.16 Decrease in adhesiveness in SFP with increase in fat content in milk and proportion of soymilk in blend can be explained in similar manner.

Optimization of FAT and SOY

Proportion of soymilk in blend and fat content of the milk control the textural characteristics of SFP. To obtain textural characteristics in the SFP similar to those in control paneer made from whole milk (6% fat) the limiting values of hardness (5.33–5.64 N), cohesiveness (0.568–0.646), chewiness (1.52–2.15 N), springiness (0.510–0.646), and adhesiveness (−0.030 to −0.043 N s) as obtained for paneer sample of 6% fat with no soy solid, were put respectively into equations given in Table 3. The constraints given in the Table 4 were used to find out the ranges of FAT and SOY for optimum responses.

Table 4 Constraints (lower bound and upper bound) set for independent variables

	Lower bound (≥)		Upper bound (≤)
Independent variable	Real	Coded	Real	Coded
FAT (X 1)	0	−1	6	+1
SOY (X 2)	0	−1	40	+1

For the optimum responses of hardness, cohesiveness, chewiness, springiness, and adhesiveness the ranges of FAT and SOY (Table 5) were found out using Generalized Reduced Gradient (GRG2) nonlinear optimization code using solver suit of Microsoft Excel package.

Table 5 Ranges of independent variables for optimum responses

	Responses
Independent variables	Hardness	Cohesiveness	Chewiness	Springiness	Adhesiveness
FAT
Lower bound (≥)	2.651	1.5	2.420	2.747	3.996
Upper bound (≤)	3.350	6.0	2.958	5.773	4.984
SOY
Lower bound (≥)	14.478	10	14.7683	19.390	17.717
Upper bound (≤)	16.223	36.53	19.141	25.188	33.254

To get the common range of the independent variables the upper and lower bound values were plotted using floating bar diagram for fat content and soymilk proportion separately (Fig. 3). The common range of the fat content of milk and proportion of soy milk in blend observed to be 3.1–3.4% (A–B) and 14–16% (A′–B′) respectively in Fig. 3. Efforts were made to decide optimum conditions in such a way so that maximum values of textural attribute should come within the range of values of control paneer sample made from buffalo milk. In this process adhesiveness value was compromised for higher side while deciding optimum fat content of buffalo milk. Adhesiveness and springiness values were compromised for higher and lower values respectively while deciding soymilk proportion in blend. This blend gives the SFP (Fat 11.24%, Protein 24.45%) with the textural characteristics almost same as that of milk paneer made from buffalo milk of 6% fat content.

Figure 3. Optimization of fat content in buffalo milk and proportion of soy milk in blend for SFP with textural characteristics similar to those of control paneer sample made from buffalo milk of 6% fat content.

Graphically obtained optimized values were further confirmed by solving this problem in Student LINGO software, Release 6 (LINDO System Inc., Chicago). This problem was solved by developing a model using maximization of cohesiveness as a objective function. This was followed with the constraint as

Solution of this problem give optimized value for fat content in milk as 3.3% and proportion of soymilk in the blend as 15.5%.

Conclusion

High fat percentage of paneer not only increases its cost but also identified as a factor responsible for causing coronary heart disease (CHD). Production of low fat paneer with high nutritional value is a need of present time. Utilizing soybean with reduction in fat percentage of milk for the manufacture of paneer like products can produce cheaper and nutritious product, which closely resembles to paneer in textural and nutritional characteristics. Standardization of blend in terms of fat content of milk and soymilk helps in producing SFP of desired textural characteristic.

Based on the predicted model for hardness, cohesiveness, chewiness, springiness and adhesiveness of SFP as a function of fat content in milk and proportion of soy milk in blend 3.1–3.4% fat content in milk and 14–16% soymilk in the blend was found to be optimum. This resulted in SFP (Fat 11.24%, Protein 24.45%) with the textural characteristics at par with control paneer made from 6% milk fat.