INTRODUCTIONConventional yogurt is a product made byfermentation of milk. Bacteria ferment milk sugarsand produce acid which can act on milk proteinand produce textured yogurt [1]. Nowadays, manypeople have lactose intolerance and are allergic to dairyproducts. For them, plant-based yogurt is an alternative.In this work, we used oats, peanut, or coconut milkas an alternative to cow milk. These ingredients increasethe nutritive value of yogurt and provides it with anhonest flavor. Fermentation of plant materials usingmixed cultures was found to be mutually beneficial forthe human body. Mutualism was found to exist betweenproteolytic Lactobacillus bulgaricus and non-proteolyticStreptococcus thermophilus as the former releases freeamino acids and peptides as a nitrogen source, while thelatter supplies growth factors such as pyruvic acid, folicacid, formic acid, and carbon dioxide [2]. L. bulgaricusand S. thermophilus are used in yogurt as startercultures [3].The fermentation time determines the aciditylevel of yogurt. Longer fermentation produces highlyacidic yogurt [4]. A low sugar content in plant milkembarrasses acid production by carboxylic acid bacteria,which requires sucrose addition. Stabilizers andgelling agents are used to improve yogurt texture andcreaminess, mostly pectin, starch, gelatin, and gums.They turn into a gel when heated in the presence ofliquid. They are widely utilized in jams and jellies [5].Proper heat treatment of plant-based milk isimportant before fermentation for starch to gelatinize.It increases the viscosity of yogurt and helps preventphase separation. In addition, it decreases the quantity ofendogenous microbes before starter inoculation [1].275Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282Coconut milk has a milky white color. Its nutritionalcontent includes fat, ash, water, carbohydrate, protein,and their derivatives. The effectiveness of extractionand the composition of coconut milk rely on theprocessing parameters such as temperature of addedwater and pressing conditions. The fat content alsoplays an important role in the flow properties of milk [6].According to the National Centre for BiotechnologyInformation, lauric acid has antifungal and antiviralproperties which fight against many human diseases.Lauric acid also reduces cholesterol and triglycerides,which is helpful in treating cardiovascular diseases [7].Oat grains are a rich source of beta-glucan, a dietarysoluble fiber. They have a 5–9% lipid content and arerich in polyunsaturated fatty acids, including linoleicacid, an essential fatty acid. In addition, oats containavenanthramide, an antioxidant, as well as tocotrienolsand tocopherols, vitamin E-like compounds. Oats havecardiovascular benefits due to their cholesterol-reducingproperties. They have a high content of starch (60%),protein (11–15%), and lipids (5–9%). Their essentialamino acids include oleic acid (45.60 g/kg), linoleic acid(36.2–40.4%), and linolenic acid (38.4–41.6%). Thus,oats milk plays a key role in competing with numeroussubstitutes of dairy milk in the continuously expandingmarket of dairy and non-dairy products [8].Peanut milk and its products have high dietarybenefits for all age groups due to a high contentof protein, essential fatty acids (linoleic and oleicacids), and minerals. Peanut milk also containshexanal, an important component responsible for itsundesirable beany flavor which is entirely eliminatedby fermentation or cooking. The stability of peanutmilk and its products is highly enhanced by heatingat 66–87°C for about 15–20 min and homogenization.This increase in stability is caused by the solubility ofproteins [9].We aimed to formulate a plant-based yogurt,optimize its ingredients and process conditions, aswell as analyze its physicochemical, rheological, andnutritive qualities.STUDY OBJECTS AND METHODSRaw peanut, coconut, and oats were procuredfrom the local market in Erode, India. We used theVegan Greek Yogurt Starter Culture (Alla’s Posh Flavors,Uttar Pradesh, India) that contained live culturesof Lactobacillus bulgaricus and Streptococcusthermophilus stored in a freezer at –18°C. Xanthan gum,pectin, and corn starch were of the Urban Platter brands.Peanut milk was prepared by immersing raw peanutsin potable water for about 8–10 h at room temperature.Then, the soaked peanuts were blended using a foodprocessor with an adequate amount of water and filteredwith cheesecloth/muslin or a strainer. The supernatant wascollected.Coconut milk was prepared from fresh and maturedcoconut endosperm which was cut into pieces and blendedusing a food processor with an adequate amount of waterand filtered with cheesecloth/muslin or a strainer. Thesupernatant was collected.Oats milk was prepared by soaking freshly boughtoats in water for about 30 min until they absorbed enoughmoisture for milk extraction. Then, they were blended andfiltered using cheesecloth/muslin. The milk was extractedby ensuring enough beta-glucan was present in thesupernatant.To prepare a cow milk yogurt alternative, the milksamples were pasteurized at an optimum temperatureof 72°C for 20 min by a double boiling method to avoidgelatinization. This method uses the steam from thesimmering water to warm the milk in the bowl gentlywith indirect heat. Then, the milk was cooled to 45°C. Thestarter cultures (L. bulgaricus and S. thermophilus)were added as 0.4% of the milk mixture weight. Afterinoculation, 10% of sucrose was added to the milkmixture to optimize the growth of lactic acid bacteria.To strengthen the gel network of the yogurt, we addedcorn starch (5%) at above 60°C, xanthan gum (0.15%) atabove 70°C under continuous stirring, and pectin (0.75%)at above 25°C. The milk was incubated at 41°C for 18 hto maintain the humidity and temperature in favorableconditions for the growth of microorganisms. The formedyogurt was cooled to a room temperature of 27°C andstored in a refrigerator at 4°C for 1 h.The physiochemical properties of the yogurt wereanalyzed using the AOAC method, 1995. They includedpH, titratable acidity, moisture content, total solids, fat, ash,protein, and carbohydrates.Viscosity was measured using a Brookfield DV-IIIUltra rheometer, with a CPE 40 spindle. The sampleswere measured at different RPM at different shear rates.Particularly, we measured the shear rate, shear stress,viscosity, and torque. The shear rate was kept constant forall the trials to measure changes in viscosity.The flow behavior was determined by plotting theshear rate versus viscosity and the n-value was determinedfrom the power equation. The power equation wasgenerated by a power line in a trendline model graph. Then-value was determined from the negative power value inthe equation. The n-value was estimated to be less than 1 todetermine the flow behavior of the yogurt [10].The centrifugal acceleration test was performedto determine the syneresis rate of the yogurt. In a testtube, 5 g of a yogurt sample was placed and centrifuged at1.200×g for 0, 3, 6, 9, 12, and 15 min at room temperature.To estimate the initial syneresis rate, the volume of theserum separated from the samples was measured ateach time interval, which was expressed as milliliters ofserum released per gram of sample per unit of time. Toevaluate the syneresis rate for that day, the average of 5 tests(except 0) was calculated [11].The cups containing 100 mL of a yogurt sample at10°C were provided for sensory analysis. Each samplewas assessed in three repetitions for flavor, texture,appearance, color, and overall acceptability on a nine-pointhedonic scale, where 1 = the least/lowest; 9 = the most/276Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282highest. The panelists were trained about the sensoryattributes before the sensory analysis.Design Expert software (version 13.0) was used tooptimize the development of a plant-based yogurt. Theresponse surface methodology (RSM) explored therelationship between explanatory variables and one ormore response variables. The mixture simplex-latticedesign was used to find the optimum combination ofconstituents in the range between 5 and 10. The valuesof sugars and stabilizers were taken as constant. Timeand temperature of incubation were also taken asconstant for improved product quality. The mixtureconsisted of peanut milk, coconut milk, and oats milk in14 combinations (Table 1).Statistical and data analysis. To represent the fittedresponse value, the linear, special cubic, and specialquartic models (Equations (1) – (3)) were used. To makepredictions about the response for given levels of eachfactor, the equations could be used in terms of codedfactors. The statistical significance of each equation wasdetermined by variance analysis (ANOVA).Y = b1X1+b2X2+b3X3 (1)Y = b1X1 + b2X2 + b3X3 + b1b2X1X2 + b1b3X1X3 ++ b2b3X2X3 + b1b2b3X1X2X3 (2)Y = b0 + b1X1 + b2X2 + b3X3 + b12X1X2 + b13X1X3 ++ b23X2X3 + b1123X1^2X2X3 + b1223X1X2^2X3+ (3)+ b1233X1X2X3^2+ewhere Y is the predictive dependent variable (sensoryanalysis, viscosity, flow behavior, syneresis rate); b isthe equation coefficient; X is the proportion of pseudocomponents[12].For Simple Quartic, X1, X2 and X3 are the proportionsof each number grade; b0 is the constant, b1, b2 and b3 arethe coefficients of linear terms; b12, b13 and b23 are thecoefficients of two-term interactions; b1123, b1223 and b1233are the coefficients of special three-term interactions.RESULTS AND DISCUSSIONFitting for the best model. Table 2 shows theresults of mixture design studies. The independent anddependent variables were fitted to linear, cubic, andspecial quartic models and the residuals plots wereformulated to check the goodness of model fit. Lowstandard deviation, low predicted sum of squares, andhigh predicted R-squared were the parameters for thebest model [13]. The linear model was found to be bestfitted for sensory analysis and viscosity. The specialcubic model was best fitted for the response flowbehavior. The special quartic model was found to be bestfitted for syneresis.The linear and the quadratic models were usedto relate the response to the operating factors of theexperiment design. The fit of the polynomial models wasanalyzed using the coefficient of determination R² andthe adjusted R², with statistical significance tested bythe F-test. A large value specified that variations in theresponse could be revealed by the regression equation.To point out the statistical significance, the desiredlarger F-value was tested by the P-value. The modelthat showed a confidence interval greater than 95%(prob > [t] < 0.05) by the probability test was regardedas statistically significant. The Prob > F-value for thelinear model was less than 0.0032 R² and the adjustedR² was found to have a maximum of 0.6474 and 0.5833,respectively. Although the cubic model was found tobe aliased, the linear model was selected for furtheranalysis of viscosity.Table 1 Yogurt formulations based on oats milk, peanut milk,and coconut milk in a three-component mixture constrainedsimplex-lattice designRun Ingredients, mLX1 (oats milk) X2 (peanut milk) X3 (coconut milk)1 10.000 5.000 10.0002 7.500 7.500 10.0003 5.000 10.000 10.0004 10.000 10.000 5.0005 7.500 10.000 7.5006 9.167 6.667 9.1677 9.167 9.167 6.6678 7.500 7.500 10.0009 10.000 10.000 5.00010 5.000 10.000 10.00011 6.667 9.167 9.16712 8.333 8.333 8.33313 10.000 5.000 10.00014 10.000 7.500 7.500Table 2 Experimental design for viscosity, sensory analysis,flow behavior, and syneresis rate for each plant-based yogurtformulationRun Response 1Viscosity, PResponse 2SensoryanalysisResponse 3Flow behavior(n-value)Response 4Syneresisrate,mL/min1 49.050 8.0 0.139 0.03242 53.810 7.0 0.058 0.02103 49.467 6.5 0.134 0.03144 56.960 6.0 0.034 0.01255 55.685 6.0 0.020 0.01286 49.051 8.0 0.140 0.03357 55.680 6.5 0.020 0.01708 53.760 7.0 0.068 0.02209 56.961 6.0 0.034 0.016010 49.460 6.0 0.133 0.035611 49.000 6.5 0.134 0.035412 53.960 6.6 0.078 0.024013 49.010 8.0 0.130 0.031214 55.980 7.0 0.060 0.0110277Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282Table 3 ANOVA for the linear model of plant-based yogurtviscositySource Sumof squaresdf MeansquareF-value P-valueModel 93.03 2 46.51 10.10 0.0032Linearmixture93.03 2 46.51 10.10 0.0032Residual 50.66 11 4.61Lack of fit 50.66 7 7.24 13950.78 < 0.0001Pure error 0.0021 4 0.0005Cor total 143.69 13Figure 1 3D surface graph (a) and diagnostic plots (b) of the effect of independent variables on viscosity of the plant-based yogurt(A: Oats milk, B: Peanut milk, C: Coconut milk)The ANOVA results for the model fitted for viscosityare shown in Table 3. As we can see, the linear effectsof coconut (X3), oats (X1), and peanut (X2) milk onthe yogurt viscosity were found to be significant.Considering the significant factors, equation (4)represents the model developed for viscosity.Viscosity = 65.25X1 + 65.64X2 + 28.72X3 (4)The interaction effect of the process parameterswas studied using response surface plots, which helpedpredict the optimal levels of each parameter to achievemaximum viscosity. Figure 1a shows the influence ofthree parameters on viscosity. According to Table 2,runs 5, 9, and 14 show greater viscosity. This means thatviscosity increased with an increase in peanut and oatsmilk, but decreased with an increase in coconut milk.The optimum region was determined by settingthe maximum viscosity as the goal. In a study byYe et al., the increase in viscosity was due to a higherprotein content in peanut and oats milk [14]. Brückner-Gühmann et al. suggested that due to a high contentof protein, oats could be used as a plant-based gellingagent even at temperatures below the temperature ofdenaturation [15]. The addition of pectin and xanthangum also influenced the viscosity range. Figure 1bshows that viscosity ranged from 48.000 to 58.000 P.Our results showed that peanut and oats milk, as wellas stabilizers, had a greater effect on the viscosity ofthe plant-based yogurt than other components, such ascoconut milk or sucrose.The cubic model was used to relate the response tothe operating factors of the experiment design. Thefit of the polynomial models was analyzed using thecoefficient of determination R², the adjusted R², withstatistical significance tested by the F-test. A large valuespecified that response variations could be revealedby the regression equation. To point out the statisticalsignificance, the desired larger F-value was tested by theP-value. The model that showed a confidence intervalgreater than 95% (prob > [t] < 0.05) by the probabilitytest was regarded as statistically significant. TheProb > F-value for the special cubic model was lessthan 0.0135 R² and the adjusted R² was found to have amaximum of 0.8467 and 0.7154, respectively. The cubicmodel was selected for further analysis of flow behavior.The ANOVA results for the model fitted for theflow behavior are shown in Table 4. As can be seen, thecubic effects of coconut (X3), oats (X1), and peanut (X2)milk on the flow behavior were found to be significant.Considering the significant factors, equation (5)represents the model developed for the flow behavior.Flow behavior = – 19.43355X1 – 20.93901X2 –– 20.43434X3 + 85.28998X4 + 85.42010X5 + (5)+ 89.18653X6 – 229.73535X7where X4 = oats milk + peanut milk, X5 = oats milk ++ coconut milk, X6 = peanut milk + coconut milk,X7 = oats milk + peanut milk + coconut milk.The interaction effect of the process parameterswas studied using response surface plots, which helpedto predict the optimal levels of each parameter forachieving maximum flow behavior. Figure 2a showsthe influence of three parameters on the flow behavior.The flow behavior depends on viscosity and the shearrate. This was determined by the power law model. Thepower law does not consider yield stress since it is a58565452504848 50 52 54 56 58PredictedActualPredicted vs. Actuala b Viscosity, PC (5.000)B (10.000)C (10.000)A (10.000)B (5.000)A (5.000)585654525048278Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282non-Newtonian fluid model. The relationship betweenviscosity and the shear rate in the power law model isdefined as η = mγn–1, where η is apparent viscosity,γ is the shear rate, and m and n are the power lawconstants [16].Figure 2b shows that the n-value of the flow behaviorranged from 0 to 0.14. Yogurt is a thixotropic fluid withn < 1, where n is the flow behavior index (dimensionless)indicating the non-Newtonian or Newtonian character.According to Ghica et al., n < 1 determines a non-Newtonian pseudo plastic fluid, n > 1 determines anon-Newtonian dilatant fluid, and n = 1 determines aNewtonian fluid [10]. Table 2 shows changes in the flowbehavior with respect to viscosity and the compositionof milk. The lesser the viscosity, the greater the flowbehavior. This was due to the influence of stabilizers andthe composition of milk.The linear model was used to relate the responseto the operating factors of the experiment design. Thefit of the polynomial models was analyzed using thecoefficient of determination R² and the adjusted R²,with statistical significance tested by the F-test. A largevalue specified that variations in the response could berevealed by the regression equation. To point out thestatistical significance, the desired larger F-value wastested by the P-value. The model with a confidenceinterval greater than 95% (prob > [t] < 0.05) by theprobability test was regarded as statistically significant.The Prob > F-value for the linear model was less than0.0001 R² and the adjusted R² was found to have amaximum of 0.9222 and 0.9080, respectively. Althoughthe cubic model was found to be aliased, the linearmodel was selected for further analysis of sensoryevaluation.The ANOVA results for the model fitted for sensoryevaluation are shown in Table 5. As we can see, thelinear effects of coconut (X3), oats (X1), and peanut (X2)milk were found to be significant on sensory attributes.Considering the significant factors, equation (6)represents the model developed for sensory evaluation.Sensory evaluation = 9.64X1 +0.14X2 + 10.50X3 (6)The interaction effect of the process parameterswas studied using response surface plots, which helpedpredict the optimal levels of each parameter to achievemaximum sensory values. Figure 3a shows the influenceof three parameters on sensory evaluation. We founda decrease in sensory values with higher contents ofpeanut milk. However, higher contents of coconut andoats milk provided maximum sensory values. This wasdue to the nutty flavor of peanut producing off-flavor.A (5.000) В (10.000)C (10.000)B (5.000)A (10.000)C (5.000)0.140.120.100.080.060.040.020Flow behavior (n-value)A (5.000) В (10.000)C (10.000)B (5.000)A (10.000)C (5.000)0.140.120.100.080.060.040.0200.140.120.100.080.060.040.0200 0.02 0.04 0.06 0.08 0.10 0.12 0.14PredictedActualPredicted vs. Actuala bFigure 2 3D surface graph (a) and diagnostic plots (b) of the effect of independent variables on flow behaviorof the plant-based yogurt (A: Oats milk, B: Peanut milk, C: Coconut milk)Table 4 ANOVA for the special cubic model of yogurt flow behaviorSource Sum of squares df Mean square F-value P-valueModel 0.0257 6 0.0043 6.45 0.0135Linear mixture 0.0170 2 0.0085 12.81 0.0046X4 (oats milk + peanut milk) 0.0059 1 0.0059 8.81 0.0208X5 (oats milk + coconut milk) 0.0035 1 0.0035 5.24 0.0558X6 (peanut milk + coconut milk) 0.0006 1 0.0006 0.9169 0.3702X7 (oats milk + peanut milk + coconut milk) 0.0037 1 0.0037 5.50 0.0514Residual 0.0047 7 0.0007 – –Lack of fit 0.0046 3 0.0015 66.81 0.0007Pure error 0.0001 4 0.0000 – –Cor total 0.0304 13 – – –279Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282Ye et al. noted that the application of flavoringagents improved the sensory and overall acceptabilityof peanut milk-based yogurt [14]. This confirmed earlierreports that adding flavoring agents and fruits to yogurtincreased the product range, as well as consumers’liking of the product [17].Figure 3b shows that the overall acceptance rangedfrom 6 to 8. According to Table 2, runs 1, 6, and 13showed higher sensory values in the formulations witha lower quantity of peanut milk compared to oats andcoconut milk. Therefore, the flavor problem in peanutmilk yogurt could be corrected or improved by applyingcommercial flavoring agents.The simple cubic and quadratic models were usedto relate the response to the operating factors of theexperiment design. The fit of the polynomial modelswas analyzed using the coefficient of determination R²and the adjusted R², with statistical significance testedby the F-test. A large value specified that variationsin the response could be revealed by the regressionequation. The P-value was used to test whether F-valuewas large enough to point out statistical significance.The model with a confidence interval greater than 95%(prob > [t] < 0.05) by the probability test was regardedas statistically significant. The Prob > F-value for thespecial quartic model was less than 0.0300 R² and theadjusted R² was found to have a maximum of 0.9083and 0.7616, respectively. Although the cubic modelwas found to be aliased, the special quartic model wasselected for further analysis of syneresis.The ANOVA results for the model fitted for syneresisare shown in Table 6. As can be seen, the quartic effectsof coconut (X3), oats (X1), and peanut (X2) milk werefound to be significant on syneresis. Considering thesignificant factors, equation (7) represents the modeldeveloped for syneresis.Syneresis = 0.0338X1 + 0.0321X2 ++ 0.0146X3 – 0.0433X4 – 0.0403X5 – 0.0442X6 ++ 0.8024X7 + 0.7247X8 – 0.1370X9 (7)where X4 = oats milk + peanut milk, X5 = oats milk+ coconut milk, X6 = peanut milk + coconut milk,X7 = oats milk2 + peanut milk + coconut milk, X8 = oatsmilk + peanut milk2 + coconut milk, X9 = oats milk +peanut milk + coconut milk2.The interaction effects of the process parameterswere studied using response surface plots, whichhelped predict the optimal levels of each parameterto achieve minimum syneresis rate values. Figure 4ashows the influence of three parameters on syneresis.We found that syneresis was minimum when viscositywas maximum, i.e., syneresis decreased as viscosityincreased. Figure 4b represents the syneresis valuesranging from 0.01 to 0.04.According to Table 2, runs 4, 5, 9, and 14 hadminimum syneresis with maximum viscosity values.This was due to the binding of molecules in higherviscosity that holds the water during syneresis. In astudy by Dönmez et al., the interaction with caseinmicelles in conventional yogurt influenced the strengthof the casein network and the stabilized yogurt structure,increasing the consistency by reducing the syneresis rateTable 5 ANOVA for the linear model of yogurt sensoryevaluationSource Sum ofsquaresdf MeansquareF-value P-valueModel 6.74 2 3.37 65.17 < 0.0001Linearmixture6.74 2 3.37 65.17 < 0.0001Residual 0.5689 11 0.0517 – –Lack of fit 0.4439 7 0.0634 2.03 0.2577Pure error 0.1250 4 0.0313 – –Cor total 7.31 13 – – –Table 6 ANOVA for the special quartic model of syneresisSource Sum of squares df Mean square F-value P-valueModel 0.0010 8 0.0001 6.19 0.0300Linear mixture 0.0006 2 0.0003 15.35 0.0073X4 (oats milk + peanut milk) 0.0002 1 0.0002 7.88 0.0377X5 (oats milk + coconut milk) 0.0001 1 0.0001 4.12 0.0982X6 (peanut milk + coconut milk) 0.0001 1 0.0001 4.97 0.0763X7 (oats milk2 + peanut milk + coconutmilk)0.0001 1 0.0001 3.32 0.1281X8 (oats milk + peanut milk2 +coconut milk)0.0001 1 0.0001 2.71 0.1608X9 (oats milk + peanut milk + coconutmilk2)1.869E-06 1 1.869E-06 0.0940 0.7715Residual 0.0001 5 0.0000 – –Lack of fit 0.0001 1 0.0001 20.59 0.0105Pure error 0.0001 4 4.041E-06 – –Cor total 0.0011 13 – – –280Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282at certain concentrations [18]. The syneresis value alsodepends on the composition of the stabilizers used.Optimization of component proportion. Wesolved the equations to yield the average values of eachindependent variable in order to obtain the optimalyogurt. This allowed us to find a desirable combinationof oats, coconut, and peanut milk (Table 7). Then, weanalyzed the optimized yogurt for viscosity, sensoryevaluation, flow behavior, and syneresis rate. Theoptimized yogurt consisted of 7.134 mL of peanut milk,10 mL of oats milk, and 7.866 mL of coconut milk. Itspredicted values of syneresis, viscosity, flow behavior,and sensory evaluation were 0.0138081, 53.4733,0.0648189, and 7.20565, respectively, with a desirabilityvalue of 0.717.Physiochemical analysis of raw milk andoptimized yogurt. The optimized plant-based yogurtand raw milk were exposed to nutritional analysisto compare the predicted and actual values (Table 8).This ensured adequate nutritional values in thedeveloped yogurt.CONCLUSIONOur results showed the effectiveness of the mixturesimplex-lattice design approach for optimizing yogurtbased on plant milk. According to our experimentalresults and counter plots, an increase in peanut andoats milk improved the viscosity and reduced theflow behavior and syneresis rate. The samples withhigher contents of peanut milk received low sensoryvalues. This indicates that peanut milk has to be usedin minimum amounts with stabilizers, such as cornstarch, pectin, and xanthan gum, to ensure optimumtexture properties. The plant-based yogurt with an8.58.07.57.06.566.0 6.5 7.0 7.5 8.0 8.5PredictedActualPredicted vs. Actuala bSensory analysisB (10.000)C (10.000) A (5.000)C (5.000)A (10.000)8.58.07.57.06.56.0B (5.000)Figure 3 3D surface graph (a) and diagnostic plots (b) of the effect of independent variables on sensory evaluation of the plantbasedyogurt (A: Oats milk, B: Peanut milk, C: Coconut milk)Figure 4 3D surface graph (a) and diagnostic plots (b) of the effect of independent variables on syneresis rateof the plant-based yogurt (A: Oats milk, B: Peanut milk, C: Coconut milk)0.0400.0350.0300.0250.0200.0150.010 0.015 0.020 0.025 0.030 0.035PredictedActualPredicted vs. Actuala bSyneresis, mL/minB (10.000)C (10.000)A (5.000) C (5.000)A (10.000)0.0300.0250.0200.0150.0100.040B (5.000)0.0350.0100.040Table 7 Optimum ingredient proportions for plant-basedyogurtComponents PercentageOats milk 40Coconut milk 31.5Peanut milk 28.5281Baskar N. et al. Foods and Raw Materials. 2022;10(2):274–282optimized composition was found to have high sensorialacceptance. The physiochemical analysis of raw milkand the optimized yogurt showed adequate amounts ofnutrients.CONTRIBUTIONThe authors were equally involved in the writingof the manuscript and are equally responsible for anypotential plagiarism.Table 8 Physiochemical analysis of raw milk and optimized plant-based yogurtResponses Predicted value foroptimized yogurtActual value foroptimized yogurtRaw materialsOats milk Peanut milk Coconut milkSensory analysis 7.20 7.30 – – –Viscosity, P 53.47 53.76 43.31 40.69 30.72Syneresis rate, mL/min 0.013 0.011 – – –Flow behavior 0.064 0.068 – – –Moisture, % – 46 45 42 39pH – 5.500 6.908 6.512 7.412Titratable acidity – 3.560 0.966 1.066 1.066Total solids, % – 11.49 22.90 11.46 12.10Fat, % – 9.45 6.78 4.40 9.40Protein, % – 17 16 19 12Ash, % – 0.490 0.344 0.394 1.240Carbohydrates, % – 27.00 30.80 32.80 34.40CONFLICT OF INTERESTThe authors declare no conflict of interest.ACKNOWLEDGEMENTSWe thank the management of Kongu EngineeringCollege, Perundurai, Erode, India for their support withour work.