EFFECT OF DIFFERENT LEVELS OF GOAT MILK, SOY MILK AND COW MILK ON CHEMICAL COMPOSITION OF RASOGOLLA

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1 EFFECT OF DIFFERENT LEVELS OF GOAT MILK, SOY MILK AND COW MILK ON CHEMICAL COMPOSITION OF RASOGOLLA Gajendra K. Londhe Dy. Director Research (AHDS) V.N.M.K.V., Parbhani(MS)

2 Introduction Chhanais a base material sandesh, rasogolla, cham-cham, rajbhog, chhanamurki, chhanapodoetc. 4% milk is converted chhana. Bengali sweets West Bengal & other Eastern parts Rasogolla is most popular indigenous milk sweets Rasogollasare marble white balls, spongy and chewy body and smooth texture served in sugar syrup Cow milk is prefered

3 Importance of goat milk Increasing demand goat milk cheeses and yoghurt is increasing in developed countries Increasing levels of disposable incomes People with cow milk allergy & gastro-intestinal ailments Goat milk is dominant -Capric, caprylicacids and MCT Beneficial for human health cardiovascular conditions MCT unique metabolic ability Goat milk exceeds cow milk in MCT : 46% MUFA : 16% PUFA : 25%

4 Importance of soymilk Soymilk is inexpensive source of protein and calorie WHO (1996) recommended soymilk as a supplement of bovine milk & nutritionally comparable with mother s milk Soy milk and its products do not contain cholesterol -major cause of coronary heart disease Free from lactose lactose intolerance Potential health benefits of soy foods Cancer prevension, cardiovascular disease, osteoporosis and lowering cholesterol

5 Objectives Optimization of different levels of goat milk and soy milk on the basis of cow milk for preparation of rasogolla using RSM. Selection of best finished product on the basis of sensory evaluation for further studies. Chemical composition of rasogolla prepared from different levelsofgoatmilkandsoymilkonthebasisofcowmilk.

6 Materials and methods Preparation of soymilk Soybean seeds Blanching (2 min using pressure cooker) Soaking in cold water Grinding Slurry Admixed with water (1:8 ratio) Straining (double-layered muslin cloth) Soymilk (Chauhanet al, 2003)

7 Preparation of rasogolla Goat milk Cow milk Soy milk Mixing Heating (70 C) Coagulation (1% calcium lactate solution at 70 C) Straining whey removal Hanging of chant Kneading (5% Maida) Rolling (app g) Cooking (boiling in 60 per cent sugar syrup for minutes) Soaking (40 per cent sugar syrup at 60 C) Cooling (room temperature) Serving

8 Table 1. Average chemical composition of different milks used for preparation of rasogolla Constituents (%) Cow milk Goat milk Soy milk Moisture Total Solids SNF Fat Total Protein Total Carbohydrates Ash

9 Response Surface Methodology RSM was used to estimate the effect of goat milk & soy milk on the basis of cow milk on sensory attributes. STATE EASE Design Expert Software (version ). Central Composite Rotatable Design, face centered with two factors & 5 center points was used. Quadratic Model used to describe the response variables is as Y = b +b₁x₁+b₂x₂+b₃x₁²+b₄x₂²+b₅x₁x₂ Y = response(dependent variable) X₁ = level of goat milk(independent variable) X₂ = level of soy milk(independent variable) b,b₁,b₂,b₃,b₄& b₅= response model coeficient Table 2. Experimental variables, their coded level and decoded(actual values) Goat milk- A Soy milk- B Standard order Goat milk (%) Soy milk (%)

10 Results Table 3. Effect of goat milk and soymilk on sensory attributes of rasogolla Standard order Goat milk (%) Soy milk (%) Flavour Body & Texture Mouthfeel Colour & Appearance Overall Acceptability

11 Optimization of levels of variables using RSM Suitable levels of goat milk & soymilk verification of sensory status Design Expert Software Optimization command Table 4. Goals for level of goat milk and soymilk on the basis of cow milk and sensory score targeted to predict the optimal combinations. Name Goal set Lower limit Upper limit Factor Goat milk (%) In range Soy milk (%) In range Flavour Maximize Response Body & Texture Maximize Mouthfeel Maximize Colour & Appearance Maximize Overall Acceptability Maximize

12 Design Expert Software suggested formulation on the basis of sensory evaluation 42.52% goat milk & 14.54% soymilk Predicted sensory score Flavour Body & text. Mouthfeel Colour& app. Overall Accp Table 5. Verification of predicted sensory quality of optimized rosogolla Parameter Predicted score Actual score* Calculated t value Flavour Body and texture Mouthfeel Colour and appearance Overall acceptability *Average of triplicate experiments; Table t0.05 is 4.30 Contd

13 Table 6. Effect of goat milk and soymilk & cow milk on chemical composition of rasogolla Standard order Goat milk (%) Soy milk (%) Moisture (%) T.S (%) Fat (%) Total Protein (%) Total Carbohydrates (%) Ash (%)

14 Table 7. Coefficient of full second order polynominal model for coded chemical composition to different levels of goat milk, soymilk & cow milk in rasogolla Factor Moisture (%) T.S (%) Fat (%) Total Protein (%) Total Carbohydrates (%) Ash (%) Intercept A-Goat milk -0.61** 0.61** 0.45** 0.18* ** B- Soy milk 0.28** -0.61** ** -0.29* A ** 0.36** * 0.52** B * -0.35** AB ** 0.43* R Adeq Precision Model F value **P 0.01, *P 0.05

15 Fig.3 Response surface relating to moisture as influenced by levels of goat milk, soymilk& cow milk for rasogolla Design-Expert Software Factor Coding: Actual Moisture Design points above predicted value Design points below predicted value X1 = A: Goat Milk X2 = B: Soy Milk Moisture B: Soy Milk A: Goat Milk

16 Fig.4 Response surface relating to total solids as influenced by levels of goat milk, soymilk& cow milk for rasogolla Design-Expert Software Factor Coding: Actual Total Solids Design points above predicted value Design points below predicted value X1 = A: Goat Milk X2 = B: Soy Milk Total Solids B: Soy Milk A: Goat Milk

17 Fig.5 Response surface relating to fat as influenced by levels of goat milk, soymilk& cow milk for rasogolla Design-Expert Software Factor Coding: Actual Fat Design points above predicted value Design points below predicted value X1 = A: Goat Milk X2 = B: Soy Milk Fat B: Soy Milk A: Goat Milk

18 Fig. 6 Response surface relating to total protein as influenced by levels of goat milk, soymilk& cow milk for rasogolla Design-Expert Software Factor Coding: Actual Total Protein Design points above predicted value Design points below predicted value X1 = A: Goat Milk X2 = B: Soy Milk Total Protein B: Soy Milk A: Goat Milk

19 Fig. 7 Response surface relating to total carbobydrate as influenced by levels of goat milk, soymilk& cow milk for rasogolla Design-Expert Software Factor Coding: Actual Total Carbohydrates Design points above predicted value Design points below predicted value X1 = A: Goat Milk X2 = B: Soy Milk Total Carbohydrates B: Soy Milk A: Goat Milk

20 Fig. 8 Response surface relating to ash as influenced by levels of goat milk, soymilk& cow milk for rasogolla Design-Expert Software Factor Coding: Actual Ash Design points above predicted value Design points below predicted value X1 = A: Goat Milk X2 = B: Soy Milk Ash B: Soy Milk A: Goat Milk

21 Response Surface Equation for Chemical Parameters Moisture = A B A B A² B² TotalSolids = A-0.28B-0.21AB+0.36A²+0.13B² Fat = A-0.13B-0.027AB-0.060A²+0.19B² TotalProtein = A+0.27B-0.37AB-0.16A²-0.35B² TotalCarbohydrates = A-0.29B+0.43AB+0.52A²+0.24B² Ash = A B+0.007AB-0.002A² B²

22 Chemical composition of rasogollawith optimized levels of goat milk, soy milk & cow milk on sensory basis Final formulation on the basis of cow milk Goat milk : % Soy milk : % Table 8. Comparison of optimized rasogolla with cow milk rasogolla Constituents (%) Cow milk Optimized Moisture Total Solids Fat Total Protein Total Carbohydrate Ash

23 Conclusion Incorporation of goat milk and soy milk in cow milk is feasible for preparation of good quality rasogolla Incorporation of % goat milk and 14.54% soy milkisbestonthebasisofsensoryevaluation. Incorporation of goat milk and soy milk increases the protein& yield of product. Reduces the cost of product. Value added health benefit product could be prepared using this combination.

27 Fatty acid profile of goat milk vscow milk Goat milk Cow milk Difference (%) for goat milk C4:0 butyric C6:0 caproic C8:0 caprylic C10:0 capric C12:0 lauric C14:0 myristic C16:0 palmitic C18:0 stearic C6-14 total MCT C4-18 total SAFA C16:1 palmitoleic C18:1 oleic C16:1-22:1 total MUFA C18:2 linoleic C18:3 linolenic C18:2-18:3 18:3 total PUFA a MCT: medium chain triglycerides; SAFA: saturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids.

28 Table 14. Cost structure of rasogollaprepared from cow milk and optimized rasogolla(cow milk + goat milk + soy milk) Sr. No. Particulars Rate (Rs.) Cow milk rasogolla Optimized rasogolla Quantity Amount (Rs.) Quantity Amount (Rs.) 1 Cow milk (ml) 32.00/lit Goat milk (ml) 41.00/lit Soy milk (ml) 6.00/lit Chhana obtained (gm.) Sugar (60% syrup) (gm.) 30.00/kg Electric charges (Unit) 7.00/Unit Labour (hr.) 15.00/hr Miscellaneous Rasogollaobtained (gm.) Total cost of rasogolla Cost of drained weight rasogolla/kg. 12 Cost including packaging charges /Tin

Fig. 19 Cost structure of cow milk rasogolla with optimized rasogolla Cow milk Rasogolla Optimized Rasogolla 2.00% Rs. 192.60/kg. 1.60% Rs. 147.05/kg.

29 Fig. 19 Cost structure of cow milk rasogolla with optimized rasogolla Cow milk Rasogolla Optimized Rasogolla 2.00% Rs /kg. 1.60% Rs /kg. 6% 17% 13.46% 62% Cow milk Sugar Labour Electric charges Miscellaneous 1.60% 17% 5% 11.20% 51% Cow milk Goat milk Soymilk Sugar Labour Electric charges Miscellaneous 28%

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