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Journal of Food Science and Technology logoLink to Journal of Food Science and Technology
. 2020 May 29;58(1):244–254. doi: 10.1007/s13197-020-04536-w

Optimization of prebiotic sucrose-free milk chocolate formulation by mixture design

Aziz Homayouni Rad 1,✉, Haniyeh Rasouli Pirouzian 1,✉
PMCID: PMC7813961  PMID: 33505069

Abstract

The purpose of the current research was to determine optimal situation by applying Simplex lattice mixture design for the formulation of prebiotic sucrose-free milk chocolate. Chocolate samples were prepared using two different sugar alcohols containing xylitol and maltitol along with galactooligosaccharide as prebiotic substance. The effects of sugar alcohols and prebiotic blends on rheological attributes and some physical characteristics were assessed. The outcomes represented the high coefficient of determination (≥ 90%) of fitted models. The optimization of the variables indicated that using 20.857 g maltitol, 7.131 g xylitol and 5.012 g galactooligosaccharide generated the optimized chocolate with the highest desirability (1.00) without undesirable changes in the rheological and physical properties. Furthermore, the optimum formulation was prepared to validate the optimum model. The sensory evaluation of the optimized formulation of chocolate pleased the consumer needs.

Keywords: Sugar alcohols, Prebiotic, Sucrose-free chocolate, Formulation, Simplex-lattice mixture design, Optimization

Introduction

Chocolate with unique taste and flavor is extensively consumed throughout the world and is a rich source of biologically active substances, such as polyphenols, with prominent antioxidant properties. Contrary to all of the aforesaid profits of chocolate, high sucrose content in chocolate is the main restricting factor for diabetic people (Barakat et al. 2017). Furthermore, there is a growing consciousness about the harmful outcomes of sucrose utilization, which after consumption could end in a high glycemic index and hence a sharp increase in plasma glucose (Aidoo et al. 2017). Therefore, the appropriate product for these groups should be formulated with sugar replaces (Kazemalilou and Alizadeh 2017).

Polyols such as maltitol and xylitol are natural sweeteners which are applied as a replacement for sucrose in low-calorie products (Torri et al. 2017). Maltitol and xylitol have a relative sweetness about 80–95% and equal to sucrose respectively (Rasouli Pirouzian et al. 2019) and were admitted as an alternative sweetener by WHO and FDA in several diet foods (Gao et al. 2017). In recent years, the utilization of prebiotics such as galactooligosaccharide (GOS) in food industry has gained attention because these prebiotics electively nourish (Homayouni Rad et al. 2012) the beneficial bacteria (Bifidobacterium and Lactobacillus) in the large intestine contributing to increased health benefits (Bouhnik et al. 2004; Homayouni Rad et al. 2013a, b). Some studies indicated that prebiotics can reduce total cholesterol, LDL, TAG, glucose and insulin (Letexier et al. 2003; Balcazar-Munoz et al. 2003). Chocolate can be used as an appropriate carrier for transfer of prebiotics.

During the last years, polyols and prebiotics have been progressively used in several kinds of chocolates. Konar (2013) studied the influences of polyols on the physicochemical properties of prebiotic (inulin) milk chocolate produced and stated that for chocolates produced with maltitol it is required to optimize conching situations. Sokmen and Gunes (2006) evaluated the influences of sugar alcohols and their particle size distribution just on rheological characteristics of chocolates. No optimized formulation was gained. Suter (2010) prepared a dark chocolate by substituting a part of the sugar with the GOS. The outcomes illustrated that rheological parameters were increased after GOS addition.

The purpose of the current study was to optimize the formulation of prebiotic sucrose-free milk chocolate including polyols (maltitol and xylitol) as low-calorie bulk sweeteners and GOS as a prebiotic ingredient. Moreover, the physicochemical characteristics of this product were determined.

Materials and methods

Materials

Various ingredients including cocoa butter and cocoa mass (Altinmarka, Turkey), whole milk powder (Zarrin-shad, Iran), soy lecithin (Cargill, Netherlands), polyglycerol polyricinoleate (Palsgaard A/S, Denmark), vanilla powder (Polar Bear, China), sucrose (Iran sugar, Co., Iran), maltitol [Roquette Freres, France- with sweetening power of 0.80 in comparison to sucrose (= 1)], and xylitol (Roquette Freres, France- equal in sweetness to sucrose), GOS Purimune™ (GTC Nutrition, Colorado, USA- with sweetening power of 0.4 in comparison to sucrose (= 1), and Stevia SU200 [SteviaPack, Singapore- with sweetening power of 250 in comparison to sucrose (= 1)] were used. Stevia was used to supply appropriate sweetness for chocolates samples including GOS and maltitol.

Sample preparation

Milk chocolates were prepared according to the following formulation: 33.0% sugar (or sugar alcohols and GOS), 13.0% cocoa mass, 27.5% cocoa butter, 26.0% whole milk powder, 0.01% vanilla, 0.3% soy lecithin and 0.2% PGPR.

Chocolate processing

Milk chocolates samples were formulated from the mixture design (Table 1). Chocolate samples were produced by using a pilot ball mill. First one third of the melted cocoa butter was incorporate to the device at 40 °C to be rotated at 40 rpm for 5 min. Then the powdered ingredients with melted cocoa mass along with 33.33% cocoa butter were added to the system and mixed homogeneously. After 1 h mixing, emulsifiers with the residual cocoa butter were added to the ball mill. The whole processing time was 3 h. The produced samples were tempered using temper machine (temper metre (Chocometer, Denmark: Temper index: 4.5–5.5). Then, the tempered chocolate was deposited into plastic moulds and cooled down to 5 °C in a refrigerator. Finally the samples were packed and stored in a dry environment (18 °C) (Homayouni Rad et al. 2019a).

Table 1.

Experimental design and mass fraction of three ingredients in milk chocolate formulation according to mixture design

Mixtures Uncoded values Coded values
Maltitol (%) Xylitol (%) GOS (%) A B C
1 0 100 0 0 33 0
2 0 100 0 0 33 0
3 50 50 0 16.5 16.5 0
4 33.33 33.33 33.33 11 11 11
5 0 50 50 0 16.5 16.5
6 50 0 50 16.5 0 16.5
7 16.66 66.66 16.66 5.5 22 5.5
8 100 0 0 33 0 0
9 0 0 100 0 0 33
10 16.66 16.66 66.66 5.5 5.5 22
11 50 50 0 16.5 16.5 0
12 0 0 100 0 0 33
13 100 00 0 33 0 0
14 66.66 16.66 16.66 22 5.5 5.5
15 (control) 0 0 0 0 0 0
16 (control) 0 0 0 0 0 0
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A = maltitol, B = xylitol, C = GOS

Proximate chemical analysis

The proximate analysis of the chocolate samples (control and formulations containing 100% maltitol, 100% xylitol and 100% GOS) were carried out through some chemical analysis. Crude protein content was measured by a Kjeldhal method (AOAC 2005) and the fat content was estimated by Soxhlet extraction (AOAC 2005). Total minerals were measured as the residue after ashing at 550 °C overnight. Carbohydrate content was calculated by subtracting the sum of moisture, fat, ash and protein content from 100.

Moisture content

The AOAC (1990) method was applied to assess the moisture contents of the chocolate samples. Mean values from 4 replicates were analyzed.

Particle size determination

D90 value measured from particle size distribution to demonstrate the size of the larger particles (Beckett 2009). Thus, the particle size of the chocolates was evaluated using micrometer (Mitutoyo, Tokyo, Japan). Mean values from 4 replicates were analyzed.

Rheological properties

Rheological parameters of the molten chocolates were specified using rheometer (Anton Paar, MCR301, Austria). Chocolates were prepared by heating in an oven at 45 °C for an hour for melting. Chocolate samples were pre-sheared at 5 s−1 and 40 °C before starting the measurement cycle. Shear stress was determined as a function of increasing shear rate from 2 s−1 to 50 s−1 (ICA 2000). The data were fitted to the Casson model and the Casson yield stress and Casson viscosity were deduced from the results (Rasouli Pirouzian et al. 2017). Mean values from 4 replicate measurements were evaluated.

Hardness

The hardness was evaluated by Texture Analyzer (Stable Micro Systems, TA-XT-plus, UK) with a with a trigger force of 5 g and needle geometry. Hardness was defined in kilogram force (kgF) and reported as the maximum penetrating force needed for the needle to penetrate through a sample at 20 °C over a distance of 3 mm at a constant speed of 1 mm/s (Homayouni Rad et al. 2019b). Mean values from 4 replicates were evaluated.

Sensory analysis

Sensory properties including the appearance, texture, flavor (taste, odor), melting rate and overall acceptability of the chocolates were selected. The sensory properties of optimized sucrose-free chocolate formulation versus a control formulation were assessed. The sensory test was performed at University of Medical Sciences (Tabriz, Iran) by 30 trained panelists (which were trained for selected properties). For this purpose the hedonic scale from 1 (extremely dislike) to 5 (extremely like) were used. A Tukey test (α = 0.05) was carried out for the hedonic values to analyze for statistical significant differences between the two formulations. Approval for the research was gained from the Ethics Committee of the Research Vice Chancellor of Tabriz University of Medical Sciences, and written satisfaction was given by all panelists (Popov-Raljic and Lalicic-Petronijevic 2009; Belscak-Cvitanovic et al., 2015).

Experimental design

The simplex lattice mixture design was used to analysis the influence of maltitol (A), xylitol (B) and GOS (C) on the quality properties of the chocolates. The associate factors, moisture content, D90, Casson viscosity, Casson yield stress and hardness were analyzed and the fitted models were exposed to variance analysis (ANOVA) to recognize significance (p < 0.05), determination coefficient (R2) and lack of fit. Multiple response optimizations were applied to determine the combination of tested variables at the same time. Ingredient levels were stated as fractions of the blend with a sum (A + B + C) of 33. These three variables; maltitol, xylitol and GOS, levels and experimental design related to coded and uncoded as 14 blends were presented in Table 1. The 14 points were 6 single-ingredient samples, 4 two-ingredient mixtures and 4 three-ingredient mixtures (Table 1).

All estimated data were represented as mean ± standard deviation (S.D). Calculation work was carried out applying a statistical package (Design Expert®7.0.0 trial version; Stat Ease Inc., Minneapolis, USA).

Results and discussion

Proximate chemical analysis

The results reported in Table 2 indicated that replacement of sucrose by polyols as bulking and sweetening agents and with GOS as a prebiotic ingredient produced chocolates with nearly similar gross composition. Results showed that sucrose-free chocolate samples were not significantly (p > 0.05) different from control in terms of ash, fat and protein contents. The carbohydrate content of the chocolates ranged from 45.19% to 45.64% (p < 0.05). The calculated energy value of the control was 576.8 kcal/100 g. The sucrose-free samples illustrated energy value ranging from 501.80 to 524.04 kcal/100 g presenting fundamental energy reduction (Table 2).

Table 2.

The proximate chemical analysis of chocolates*

Samples Ash (%) Fat (%) Protein (%) Carbohydrate (%) Energy value (Kcal/100 g)
Control 3.38a ± 0.03 41.68a ± 0.08 8.32a ± 0.32 45.64a ± 0.68 576.80a ± 0.12
Chocolate with 100% maltitol 3.39a ± 0.02 41.67a ± 0.13 8.33a ± 0.24 45.47b ± 0.52 523.95b ± 0.06
Chocolate with 100% xylitol 3.39a ± 0.07 41.68a ± 0.21 8.33a ± 0.41 45.33c ± 0.70 524.04b ± 0.22
Chocolate with 100% GOS 3.38a ± 0.11 41.67a ± 0.19 8.32a ± 0.17 45.19d ± 0.26 501.80c ± 0.09
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*Mean of four determinations ± SD. Different letters within columns indicate significant differences (p < 0.05)

Moisture content

Moisture content of the chocolates was recorded between 0.97 g/100 g and 1.44 g/100 g, which were within the appropriate limit (0.5–1.5 g/100 g) (Afoakwa 2010) (Table 3). Upper levels of GOS significantly boosted the moisture content (Fig. 1a). Abbasi and Farzanmehr (2009) noticed higher moisture value for chocolate samples comprising compounds with high hygroscopicity.

Table 3.

Mean and standard deviation of physicochemical parameters

Mixtures Moisture
(g/100 g)		 D90
(μm)		 Casson viscosity (Pa.s) Casson yield
(Pa)		 Hardness
(kgF)
1 1.27 ± 0.18 27.61 ± 0.09 6.62 ± 0.21 7.79 ± 0.28 4.87 ± 0.05
2 1.25 ± 0.13 27.84 ± 0.31 6.59 ± 0.35 7.12 ± 0.10 4.76 ± 0.31
3 1.17 ± 0.27 25.99 ± 0.56 6.01 ± 0.09 5.21 ± 0.42 5.19 ± 0.24
4 1.26 ± 0.05 27.20 ± 0.07 6.49 ± 0.14 6.66 ± 0.43 5.54 ± 0.92
5 1.35 ± 0.31 28.68 ± 0.81 6.99 ± 0.13 8.69 ± 0.23 5.49 ± 0.13
6 1.25 ± 0.19 26.95 ± 0.25 6.33 ± 0.24 6.11 ± 0.06 5.87 ± 0.41
7 1.26 ± 0.12 27.47 ± 0.98 6.65 ± 0.87 7.22 ± 0.19 5.17 ± 0.22
8 1.12 ± 0.24 24.16 ± 0.12 5.78 ± 0.09 3.63 ± 0.33 5.68 ± 0.52
9 1.43 ± 0.16 29.17 ± 0.08 7.08 ± 0.23 8.92 ± 0.32 6.23 ± 0.23
10 1.34 ± 0.03 28.43 ± 0.18 6.97 ± 0.31 8.13 ± 0.07 5.85 ± 0.02
11 1.16 ± 0.54 26.03 ± 0.65 5.87 ± 0.56 5.13 ± 0.08 5.21 ± 0.71
12 1.44 ± 0.09 29.09 ± 0.19 7.06 ± 0.13 8.89 ± 0.23 6.12 ± 0.23
13 1.14 ± 0.33 24.35 ± 0.43 5.81 ± 0.14 3.59 ± 0.20 5.51 ± 0.07
14 1.16 ± 0.17 25.73 ± 0.02 5.86 ± 0.52 4.64 ± 0.12 5.56 ± 0.51
15 0.98 ± 0.29 21.09 ± 0.65 2.54 ± 0.39 2.16 ± 0.41 4.62 ± 0.43
16 0.97 ± 0.64 21.43 ± 0.14 2.13 ± 0.61 2.28 ± 0.11 4.43 ± 0.62
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Fig. 1.

Fig. 1

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Estimated response contour plots illustrating influence of maltitol, xylitol and GOS concentration on physicochemical parameters: a Moisture, b D90, c Casson viscosity, d yield value and e hardness A = Maltitol; B = Xylitol and C = GOS

The optimization tool indicated an optimum amount of 1.17 g/100 g moisture with 18.33 g maltitol, 11.76 g xylitol and 2.91 g GOS if all other parameters are not regarded. The reference chocolate illustrated a mean of 0.975 g/100 g. The regression equation for moisture amount response in terms of L_Pseudo components values, gained from mixture design, was reported in Eq. (1). Where A presents maltitol, B presents xylitol and C presents GOS.

y=1.13A+1.26B+1.43C-0.12AB-0.13AC+0.029BC 1

Generally, the high moisture content of chocolates containing GOS and xylitol can be related to high hygroscopicity of GOS and xylitol compared to median hygroscopicity of maltitol. High moisture retaining capacity of GOS prevents excessive water evaporation during chocolate production (Torres et al. 2010). It is assumed that GOS molecules contain more active hydroxyl groups to link with water molecules and create hydrogen bonds (Homayouni et al. 2019a). Therefore, GOS is more hygroscopic compared to xylitol and maltitol. The relationship between the factors and moisture amount (response) was quadratic (Table 4).

Table 4.

Regression models for quality parameters of chocolates

Moisture D90 Casson viscosity Casson yield stress Hardness
Fitted Model Quadratic (p < 0.0001) Quadratic (p < 0.0001) Quadratic (p < 0.0001) Quadratic (p < 0.0001)

Linear

(p < 0.0001)
Lack of fit p = 0.6054 p = 0.7443 p = 0.0523 p = 0.6593 p = 1.00
R-squared (%) 0.9937 0.9979 0.9752 0.9917 0.9889
R-squared (adjusted) (%) 0.9897 0.9965 0.9597 0.9865 0.9869
Adeq Precision 44.868 78.693 20.531 37.846 50.079
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Homayouni et al. (2018) reported higher moisture value for chocolate samples comprising high concentrations of GOS. This prebiotic absorbs water from the chocolate mass resulting in higher moisture ending in agglomeration in chocolate matrix. In the study of Abbasi and Farzanmehr (2009) higher moisture amount were reported for chocolate samples comprising high levels of maltodextrin, inulin and polydextrose.

D90 values

D90 values of chocolate formulations were found to be < 30 μm with control sample containing the smallest and GOS containing the largest size (Table 3 and Fig. 1b). Particle size of the samples were in the appropriate limit (< 35 μm) suggested for chocolate (Awua 2002). Sugar alcohols and GOS contain several numbers of hydrophilic active sites (-OH). These -OH groups commonly participate in forming intermolecular hydrogen links. Within chocolate production the mentioned groups create intermolecular interactions in chocolate matrix (Homayouni Rad et al. 2019b). This ends in particle agglomeration. Thus, the particle size of the chocolates will not reduce substantially due to high degree of agglomeration (Rasouli Pirouzian et al. 2016).

The relationship between the variables and D90 values was quadratic. The optimization tool forecasted an optimum value of 25.58 μm with 22.90 g maltitol, 6.11 g xylitol and 3.99 g GOS if all other parameters are not regarded. The regression equation for D90 parameter in terms of L_Pseudo components amounts was stated in Eq. (2).

y=24.25A+27.72B+29.15C-0.007577AB+0.99AC+0.98BC 2

Shah et al. (2010) produced sugar-free milk chocolates containing several kinds of inulin and polydextrose. The results indicated that the mean particle size of HPX inulin was significantly higher than control. In a study by Saputro et al. (2017) chocolate samples formulated by palm sugar illustrated higher particle size due to higher degree of agglomeration. Results indicated that the proper particle size of < 30 μm can be achieved in milk chocolate by using sucrose substitutes.

Rheological measurements

Casson plastic viscosity

Results illustrated that substituting sucrose with xylitol, maltitol and GOS had no impact on the mathematical model fitting and the Casson model was the preferred model for describing chocolates rheological parameters. All chocolate samples displayed a shear thinning behavior, indicating that the samples were non-Newtonian fluids. There was an increase in the Casson viscosity upon addition of prebiotic and polyols to the chocolate matrix (Fig. 1c). Casson viscosity values of prebiotic sucrose-free chocolates were between 5.78 and 7.08 Pa.s (Table 3). Chocolates containing 100% GOS illustrated the highest viscosity (mean value of 7.07 Pa.s). The relationship between the factors and Casson viscosity (response) was quadratic.

Casson viscosity values of samples with high levels of maltitol were near the limit stated for milk chocolate (2.2–5.5 Pa.s) (Aeschlimann and Beckett 2000) (Table 3). This statement was confirmed by the optimization tool which forecasted an optimum amount of 6.08 Pa.s with 16.74 g maltitol, 12.07 g xylitol and 4.19 g GOS if all other parameters are not regarded. The regression equation for Casson viscosity response in terms of L_Pseudo components amounts was stated in Eq. (3).

y=5.76A+6.62B+7.09C-0.98AB-0.30AC+0.98BC 3

The viscosity of the chocolate samples was associated on the sweetener kind, D90 and their moisture content (Fig. 2c). Furthermore, particles that are smaller in size, have more surface area, therefore more fat will coat the solid particles and reduces the viscosity (Bouzas and Brown 1995). That could be one reason for lower viscosity of control samples which indicated lower D90 (Table 3).

Fig. 2.

Fig. 2

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Forecasted and tested results used in the validation of model based on optimum formulations (maltitol = 20.857 g, xylitol = 7.131 g and GOS = 5.012 g)

The polyols and GOS used in the study have several hydroxyl groups that have ability to absorb water and link with water molecules, thus the viscosity elevates. These hydrophilic ingredients have potential to create inter- and intra-molecular interactions forming macromolecules. These macromolecules barely are distributed in cocoa butter leading to viscosity increase. In the study of Homayouni et al. (2019a) The various viscosity values of sucrose-free chocolates was attributed to the different spatial structure, hydroxyl numbers and positions of sweeteners in the molecule (Homayouni et al. 2019a).

In the study of Homayouni et al. (2018) higher viscosity in chocolate formulations containing GOS was related to its molecular structure and physical properties including hygroscopicity. Abbasi and Farzanmehr (2009) used maltodextrin, polydextrose (bulking agents) and inulin (prebiotic) in milk chocolate formulation. The Casson viscosity reduced with the increase of inulin (up to 50%). This behavior was attributed to low hygroscopicity of inulin and also its low water binding capacity. A dark chocolate was produced by substituting a part of the sucrose with the GOS to gain levels of 1.28 g of GOS per 40 g chocolate bar. The apparent viscosity was increased upon addition of GOS (Suter 2010).

Casson yield stress

Casson yield values of prebiotic sugar-free chocolate samples were recorded between 3.59 and 8.92 Pa.s (Table 3). There was an increase in the Casson yield values after prebiotic and polyols addition (Fig. 1d). Among sucrose-free chocolates, formulations containing 100% GOS illustrated the highest yield stress (average of 8.91 Pa.s) and formulations containing 100% maltitol indicated the lowest yield value (average of 3.61 Pa.s) (Table 3). The term related with the interaction between the influences of three compounds was remarkable (p < 0.0001) (Table 4). Casson yield values (Table 3) were within the limited range proposed (2–18 Pa) for milk chocolate (Aeschlimann and Beckett 2000).

The optimization tool forecasted an optimum value of 5.99 Pa with 14.44 g maltitol, 10.69 g xylitol and 7.87 g GOS if all other parameters are not regarded. The regression equation for Casson yield value response in terms of L_Pseudo components amounts was presented in Eq. (4).

y=3.56A+7.47B+8.94C-1.52AB-0.70AC+2.31BC 4

The higher yield stress of prebiotic sugar-free chocolates is related to particle–particle interactions, the amount of specific surface area and particle aggregation induced by attendance of moisture and bulk agents (Mongia and Ziegler 2000). Moreover, due to GOS spatial structure there are more active and free hydroxyl groups thus more particle interactions take place and this will increase yield value to some extent.

Higher yield values were also reported with GOS in comparison to control (Suter 2010; Homayouni et al. 2018). The higher yield value of chocolates containing GOS was associated with the higher molecular weight of GOS (Homayouni et al. 2018). Abbasi and Farzanmehr (2009) stated lower yield values for chocolates containing high amounts of inulin (up to 50%). The low yield value was related to low moisture content of chocolates containing inulin. The hygroscopic nature of maltodextrin and polydextrose were the reasons for higher yield values. Bolenz et al. (2006) reported that the chocolates formulated by inulin reduced the yield stress.

Hardness

The hardness value of the samples ranged between 4.43 KgF and 6.23 KgF (Table 3). The hardness amount of the samples varied considerably among the mixture design formulations (Fig. 1e). High amounts of the sucrose replacers lead to a hardening effect of chocolates (Fig. 1e). Chocolate formulations containing 100% GOS recorded the highest hardness with an average of 6.18 kgF and control samples owned the least hardness values (average of 4.53 kgF) (Table 3). In the study of Aidoo et al. (2014) chocolate samples prepared with high contents (100%) of inulin (prebiotic) indicated higher hardness values in comparison to reference.

Considering the hardness, the fitted model was significant (p < 0.0001) (Table 4). The optimization tool clarified that an optimum value of 5.36 kgF with 9.08 g maltitol, 15.89 g xylitol and 8.13 g GOS if all other dependent variables are not considered. The regression equation for hardness response in terms of L_Pseudo components amounts was presented in Eq. (5).

y=5.59A+4.81B+6.17C 5

Afoakwa et al. (2008) reported that the chocolate hardness is related on the type of sugar used in chocolate preparation. Different hardness amounts in chocolate could be attributed to the various structures of sugars and particle–particle interactions. During chocolate production the -OH groups of polyols and GOS take part in intermolecular interactions and creates chains causing a higher hardness (Nabors 2001).

Optimization the chocolate formulation

Taking into account all quality properties and applying the optimization tool which quality parameters were put into standard limits (moisture, D90 Casson viscosity, Casson yield and hardness), formulation containing 20.857 g maltitol, 7.131 g xylitol and 5.012 g GOS was selected as having the maximum desirability (Fig. 2 and Fig. 3). The blend of factors which offers the overall optimum desirability (1.00) is indicated in Fig. 3. Based on optimization results, the best desirable ranges for moisture content, D90, Casson plastic viscosity, Casson yield value and hardness, that indicate the highest resemblance to reference (control), were 1.18, 25.87, 6.02, 5.02 and 5.51 respectively (Fig. 2).

Fig. 3.

Fig. 3

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Contours of estimated response surface indicating the point where optimum level was achieved. A = Maltitol; B = Xylitol and C = GOS

Validation of model

Design Expert software presented optimum chocolate formulations for chosen parameters. Optimum sample was produced. Further tests were carried out and compared with the models prediction. Optimum formulation, predicted amounts and tested outcomes for parameters are presented in Fig. 2. The forecasted and tested amounts for every response were as; moisture content (forecasted value: 1.18 vs. tested value: 1.22), D90 (forecasted value: 25.87 vs. tested value: 27.01), Casson viscosity (forecasted value: 6.02 vs. tested value: 6.24), Casson yield stress (forecasted value: 5.02 vs. tested value: 5.18) and hardness (forecasted value: 5.51 vs. tested value: 5.63). The tested amounts were near to the amounts forecasted by the model. These results confirm the validation of the model produced by software.

Sensory analysis

The results for sensory evaluation of chocolates with optimized formulation and control is illustrated in Fig. 4. Between the two different chocolate formulations, control samples obtained the highest scores (Fig. 4) in the case of all sensory attributes.

Fig. 4.

Fig. 4

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Spider chart representing sensory attributes of chocolate samples

In the case of appearance, the control formulation recorded higher appearance score (4.24) in comparison to optimized formulation (4.15) (Fig. 4). However there were no significant differences (p > 0.05). In the study of Homayouni et al. (2019a) the differences were related to the different arrangement of sugar crystals. They included that different shape and arrangements of sugar crystals have various capability of scattering colors.

Sucrose replacement with optimized formulation of polyols and GOS lowered the flavor perception (p < 0.05) (Fig. 4). Preferably, polyols not cause any aftertaste (Nabors, 2001). However in the current study the sucrose-free chocolate samples were prepared by using Stevia to provide the appropriate sweetness. The slight bitterness and astringency taste observed in the mentioned formulation could be related to the inherent bitterness of Steviol glycosides (Kaushik et al. 2010). Furthermore flavor acceptability and sensory qualities are dependent to rheology of chocolate (Ziegler et al. 2001). The higher rheology parameters obtained for chocolates prepared with polyols and GOS had impact on flavor perception.

Control samples received higher texture and melting acceptability (p < 0.05). The texture is influenced by the factors such as food molecular, microscopic and macroscopic characteristics. Perhaps high levels of sugar alcohols and GOS lead to hardening effect in final product (Shourideh et al. 2010). Also Melting profile is contributed to the texture and structure of sweeteners. Probably polyols and GOS do not completely diffuse into the continuous phase because of their high content of –OH groups. These groups have affinity to escape from fat phase (Homayouni et al. 2019a).

In addition, there were no considerable difference for overall acceptability between the control sample and optimized formulation. Though the relationship between rheological behavior and sensory is complex, the results indictaed that only small differences in the two samples were recorded and the optimized formulation pleased the consumer demand.

The type of ingredient, component concentrations, differences in processing methods and particle size distribution will end in different sensory attributes (Jackson, 1994). In the study of Suter (2010) a sensory analysis confirmed no significant differences between the chocolates prepared with GOS and control and concluded that both samples met commercial chocolate quality. Probably the differences in GOS concentrations used in the chocolate formulation and also different types of panelists resulted in different outcomes. Because trained panelists have a higher knowledge about the flavor and texture properties than a traditional consumer. This probably could influence the sensory results. In their study 50 untrained participants evaluated the chocolates.

Homayouni et al. (2018) reported that higher concentrations of GOS reduced the overall acceptability of chocolates. However using 2.5% GOS presented the optimal sensory results. Also in the study of Rasouli et al. (2016) higher contents of maltitol did not influence the sensory properties of the compound milk chocolate. Homayouni et al. (2019b) stated a notably improved overall acceptability in milk chocolate formulations made with xylitol.

The results of the current study showed the potential use of polyols along with GOS to replace sucrose and obtain the desired sensory attributes. This is important in the case of calorie reduction for patients suffering from diabetes.

Conclusion

Different mixtures of maltitol, xylitol and GOS can be used to improve the physicochemical characteristics for production of sucrose-free prebiotic chocolates. Although increases in Casson viscosity and yield stress were recorded upon polyols and GOS addition but it was noted that these slight increases did not contribute to a noticeable quality change. Overall acceptability showed that no detectable difference was observed among control and optimum formulation of sucrose-free chocolate. Multiple response optimizations using Simplex lattice mixture design was an efficient modeling technique for finding the optimum concentration of polyols and prebiotic preparing a low-calorie chocolate with close resemblance in properties to the reference chocolate. As a whole the results of the current study demonstrated that polyols and prebiotic (GOS) can be used successfully in a milk chocolate matrix. Milk chocolate prepared with polyols and prebiotic ingredient was also appropriate from the point of reduced calorie and they can be presented as functional foods. The impact of polyols and GOS on aroma formation or aroma release in the mouth has also not been covered in this study and would be an interesting issue. Future studies will focus on evaluating acceptances of diabetic milk chocolates by quantitative descriptive analysis (QDA).

Acknowledgements

This study was funded by National Institute for Medical research Development Islamic Republic of Iran application No. 971409.

Footnotes

Publisher's Note

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Contributor Information

Aziz Homayouni Rad, Email: homayounia@tbzmed.ac.ir.

Haniyeh Rasouli Pirouzian, Email: rasoulipirouzian@tbzmed.ac.ir, Email: rasuly_h@yahoo.com.

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