chle

taSimstan20

Received 16 June 2011Received in revised form

products are still the most dominant sources for probiotic productsin the market.

Although, probiotic sources are not limited with Lactobacillusand Bidobacteria species, they are the most dominant speciesstudied in probiotic formulations. Recent studies showed that

coagulans, Bacillus cereus and Bacillus clausii have probiotic prop-5). Bacillus indicusistance to gastro-rized for its safetyf dietary caroten-t al., 2008).origins which areto possess manyshortening bowelgastric emptying,t disease, slowingons and lowering

serum cholesterol levels (Drehner, 2001). They are added to a va-riety of food products for nutritional and functional enhancementpurposes. Carboxymethylcellulose, locust bean gum, inulin andpolydextrose added high-ber bread (Angioloni & Collar, 2011); thedefatted rice bran hemicelluloses B and insoluble dietary beradded bread (Hu, Huang, Cao, & Ma, 2009); inulin, guar gum andpea ber added pasta (Tudorica, Kuri, & Brennan, 2002); frozenpizzas containing high content dietary ber stabilized rice branour (deDelahaye, Jimenez, & Perez, 2005); cakes enriched with

* Corresponding author. Tel.: 90 212 2856042; fax: 90 212 2857333.

Contents lists availab

LWT - Food Science

w.e

LWT - Food Science and Technology 56 (2014) 187e193E-mail addresses: ozcelik@itu.edu.tr, beraat.ozc@gmail.com (B. zelik).Chocolate is an internationally craved and highly consumedproduct among confectionery products. Latest studies have shownthat chocolate was not only a simple blend of fat and sugar, but alsoa rich source of avonoids and polyphenols which shows highantioxidant activities (Pimentel, Nitzke, Klipel, & de Jong, 2010;Schinella et al., 2010; Vanzani, Rosetto, De Arco, Rigo, & Scarpa,2011). In addition to exhibiting antioxidant activity, chocolatemight serve as a better probiotic carrier than dairy products forintestinal delivery. Possemiers, Marzorati, Verstraete, and Ven deWiele (2010) claimed that chocolate ensured probiotic survival upto 4 times higher than milk-containing products. However, dairy

erties (Cutting, 2010; Hong, Duc, & Cutting, 200HU36 is spore-forming bacteria with a high resintestinal environment and it has been characteas probiotic supplements and its high content ooids (Duc, Fraseer, Tam, & Cutting, 2006; Hong e

Dietary bers are carbohydrates of plantindigestible in small intestine. They are claimedhealth benets such as; lowering calorie intake,transit time, increasing fecal bulk, delayinghelping to reduce the risk of cancer and hearglucose absorption, enhancing immune functi1. Introduction Bacillus species like Bacillus subtilis, Bacillus pumilus, Bacillus7 December 2012Accepted 11 October 2013

Keywords:Bacillus indicus HU36ProbioticSynbiotic chocolateRSMSensory proling0023-6438/$ e see front matter 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.lwt.2013.10.020(maltodextrin and lemon ber) addition on color and organoleptic quality properties of dark chocolate.The viability of B. indicus HU36 in dark chocolate was examined as well in the study. Three-level [1.5, 3.5,5.5 (g/100 g)], two factorial (maltodextrin, lemon ber) Central Composite Design (CCD) was performedfor developing synbiotic chocolate formulation. According to our results, B. indicus HU36 showed survivalrate between 88 and 91% in samples. Descriptive sensory analysis (QDA) and color analysis were per-formed to examine the effects of factors and their levels on quality attributes and describe developedchocolates in detail. While bacteria and dietary ber addition did not show any negative effects onproduct sensory and color properties; dietary ber addition improved some sensorial features signi-cantly i.e. sweetness, rmness and adherence, The validation of the model had been accomplished byapplying the conditions generated by the RSM model. This study is the rst report on the use of B. indicusHU36 in potentially probiotic chocolate production.

2013 Elsevier Ltd. All rights reserved.Article history: The aim of this study was to investigate the effects of probiotic Bacillus indicus HU36 and dietary bersa r t i c l e i n f o a b s t r a c tDevelopment of a novel synbiotic darkBacillus indicus HU36, maltodextrin andresponse surface methodology

zlem Erdem a, Mine Gltekin-zgven a, Ijlal BerkAyse Karadag a, Beraat zelik a,*, Grbz Gnes a,aDepartment of Food Engineering, Faculty of Chemical and Metallurgical Engineering, Ib School of Biological Sciences, Royal Holloway University of London, Egham, Surrey TW

journal homepage: wwAll rights reserved.ocolate enriched withmon ber: Optimization by

s a, Sevcan Ersan a, H. Ezgi Tuna a,on M. Cutting b

bul Technical University, Maslak, TR-34469 Istanbul, Turkey0EX, United Kingdom

le at ScienceDirect

and Technology

lsevier .com/locate/ lwt

ce anapple pomace (Sudha, Baskaran, & Leelavathi, 2007); ice creamenriched with oat ber, wheat ber, apple ber and inulin(Soukoulis, Lebesi & Tzia, 2009); and yoghurts including apple ber,wheat ber, bamboo and inulin (Staffolo, Bertola, Martino &Bavilacqua, 2004) might be given as some examples to the prod-ucts enriched with dietary bers.

Beards, Tuohy, and Gibson (2010) tested the effects of maltitol,polydextrose and resistant starch addition to chocolate. Forty vol-unteers consumed reformulated chocolate samples for over a sixweek period. Their results showed that, consumption of samplescontaining polydextroseemaltitol blend increased the level ofLactobacilli and Bidobacteria levels in faeces after 6 weeks. In-crease in the levels of short chain fatty acids i.e. propionate andbutyrate were observed. Formula development of chocolate pro-vided prebiotic effects to consumers in addition to the decrease inenergy values.

Although chocolate is basically a uniform blend of cocoa, cocoabutter and sugar, its production process is very unique andcomplicated. It consists of 6 main stages as mixing, rening, con-ching, tempering, molding and packaging. Tempering is a stage ofcontrolling cocoa butter crystallization, helps to stabilize thepolymorphic transitions of cocoa butter crystals during storage andprovides the smooth and shiny appearance of chocolate, aswell (Beckett, 2008, 2009; Windhab, 2009).

The aim of this study is to develop the optimum formulation of anovel potentially probiotic and synbiotic dark chocolates enrichedwith novel probiotic strains B. indicus HU36; to investigate thesurvival of B. indicusHU36 in formulations; to evaluate the additionof dietary ber on color and sensorial properties of the product.Formula optimization for synbiotic products was done by using theResponse Surface Methodology (RSM) method.

2. Materials and methods

2.1. Inoculum preparation

B. indicus HU36 was supplied from EU 7th Framework acro-nymed Project COLORSPORE (Project number: 207948). B. indicusHU36 spores were obtained by exhaustion method described byNicholson and Setlow (1990). According to the method, DifcoSporulation Medium (DSM) was streaked with colony of B. indicusHU 36 and incubated overnight at 37 C. Then, a fresh colony wasinoculated into Luria Bertoni (LB) Broth and incubated at 30 C on arolling drum overnight. DSM agar and LB broth were supplied fromOxoid (Basingstoke, UK). Afterward, the culture was grown in anorbital shaking water bath at 37 C until OD600 of the culture wasreached approximately 1.00. Then culture was spread plated onDSM agar and incubated at 30 C for 24 h. Afterward, the level ofvisible sporulation of the culture was checked frequently. Whenmore than 90% of visible sporulation was detected, spores wereharvested with water after removal of vegetative cells by washingwith distilled water. Finally, harvested spores were lyophilized byusing Christ Alpha 1-2 LD Plus Freeze Dryer (Martin Christ GMBH,Osterede am Harz, Germany).

2.2. Chocolate production

Dark chocolate couvertures containing 50 g cocoa/100 g weredonated from Nestle Turkey Gida A.S. Dietary bers (maltodextrin,carboxymethylcellulose, inulin, lemon ber, apple ber, wheat -ber) were all obtained from various local companies in Turkey indried and powdered from, no further process had been applied. Allsamples were produced in laboratory conditions. After couvertureswere melted at 45 C in water bath, lyophilized B. indicus HU36

. Erdem et al. / LWT - Food Scien188spores were added to have 6.08 log cfu/g of chocolate. Dietarybers, particle size 40 micron at most, were mixed with cou-vertures. Then, the mixture was tempered manually according tothe tabliering method (Brown, 2008;Wybauw, 2004). After coolingto room temperature samples were wrapped in aluminum foil forpackaging, stored at 18 C until the corresponding analysis.

2.3. A pre-study on dietary ber determination

A 9-point scale hedonic sensory analyses was performed todetermine the most suitable dietary ber type. To conduct thesensory analysis, chocolate samples were manufactured by using 6different types of dietary ber (maltodextrin, carboxymethylcel-lulose, inulin, lemon ber, apple ber, wheat ber), each containing5 (g/100 g) dietary ber and one control sample without ber wasproduced, as well. None of the samples contained B. indicus HU36.10 voluntary panelists (6 females & 4 males, between 25 and 40years) were chosen from both graduate students and facultymembers of Istanbul Technical University of Food EngineeringDepartment. Panelists were selected according to their interests inchocolate consumption and willingness to participate. They weregiven information about basic sensory attributes of chocolate(appearance, aroma, taste, mouthfeel, texture). Scoring was per-formed by using a 9-point scale, in which points represented theexpressions from 1 to 9 (dislike extremely to like extremely). Thepanels were conducted in two sessions, 4 samples were given toeach panelist in each session.

2.4. Experimental design by using RSM

RSM was employed to investigate the effects of dietary beraddition on probiotic, sensorial and color properties of productformulation. Since the results of sensory analysis conducted on 6dietary bers showed maltodextrin and lemon ber had thehighest acceptability scores, we decided to use those bers as in-dependent factors in the following optimization studies. A twofactorial (dietary ber type: maltodextrin and lemon ber), threelevel [ber concentration: 1.5, 3.5, 5.5 (g/100 g)], central compositedesign (CCD) was applied. 11 sample formulations were generatedby the model, and the results of microbiological, color anddescriptive sensory analysis were used as responses. Sample for-mulations, factor levels and responses are summarized at Table 2,formulations were randomly prepared.

2.5. Viable bacteria count

Viable bacteria count of samples packaged in aluminum foilsand stored at 18 C was performed on the following day of theirpreparation. B. indicus HU36 colonies were determined on DSMagar in accordance with spread plate method; the plates wereincubated at 37 C for 24 h. The microbiological analysis was con-ducted in duplicates.

2.6. Color analysis

Chroma Meter (Model CR-400 Konica Minolta Sensing Inc.,O-saka, Japan) was used for describing color properties of samples.CIELAB color parameters (L*, a*, b*) were measured. L* valuedenes luminance of the samples between 0 and 100 scale inwhich0 denes black and 100 denes white color, a* value describescolor categorizing from green () to red (), while b* value de-scribes color categorizing from yellow() to blue () (Briones &Aguilera, 2005; Nopens et al., 2008). Bottom and top surface colormeasurements of each sample was performed in triplicates.Whiteness Index (WI) for each sample was calculated according to

d Technology 56 (2014) 187e193the Equation (1) (Briones & Aguilera, 2005; Nopens et al., 2008).

Commercial bitter chocolate (Nestle Dark) was used as referencesample for comparison.

Whiteness indexWI 100h100 L*

2a*2

b*2i0:5

(1)

2.7. Sensory proling of samples

The main principles of Quantitative Descriptive Analysis (QDA)(Stone, Sidel, Oliver, Woolsey, & Singleton, 1974) were used toevaluate the sensory attributes of chocolates containing malto-dextrin and lemon ber at different concentrations [1.5, 3.5, 5.5 (g/100 g)].

Focus group studies were conducted by 8 panelists (5 females &3 males, between 25 and 40 years), chosen from both graduatestudents and faculty members of Istanbul Technical University ofFood Engineering Department. Panelists were trained in 3 differentsessions, 2 h long each. The glossary of terms and their denitionsand scores for references were determined and scaled in consensus(Table 3). Afterward, each panelist was asked to score the samplesindividually in a 7-point scale. Each panel consisted of 3 consecu-tive sessions where panelists were asked to score 4, 4 and 3 sam-ples in each session. All panels were completed in 3 days. Panelswere performed in duplicates. Judges scored the samples accordingto the glossary and reference scores as shown in Table 3. Chocolateformulations produced for descriptive analysis did not containbacteria.

Table 1Hedonic analysis results for the determination of bers to be used in the formulations.

a Appearance Aroma Taste Mouthfeel Texture Overall Acceptability

Control 8.83 0.41 8.50 0.84 8.00 0.63 8.33 0.82 8.17 0.75 8.50 0.55LF 8.50 0.83 6.83 0.98 6.33 0.82 6.50 0.84 6.17 0.98 6.83 0.75MD 8.67 0.52 8.33 0.82 7.33 0.82 7.17 0.75 7.00 0.89 7.83 0.98CMC 8.17 0.75 6.83 0.98 1.83 0.41 1.00 0.89 1.17 0.98 1.17 0.98Inulin 7.50 0.55 6.67 0.82 3.67 1.37 3.17 1.17 3.50 1.05 3.33 1.03WF 7.00 1.10 5.33 1.97 4.17 1.17 3.33 1.37 3.00 1.10 3.67 1.21AF 7.33 1.21 6.17 1.47 4.00 1.10 5.00 2.10 4.50 2.17 4.58 1.11

The results represent themeans std deviation of the scores performed by panelists in duplicate. Scoring was performed by using a 9-point scale, in which points representedthe expressions from 1 (dislike extremely) to 9 (like extremely).

a LF lemon ber, MD maltodextrin, CMC carboxymethylcellulose, WF wheat ber, AF apple ber.

Table 2Experimental design with factors and responses.

Factor 1: MDa (g/100 g) 1.5 5.5 5.5 3.5 1.5 3.5 3.5 1.5 3.5 3.5 5.5

Factor 2:LFa (g/100 g) 3.5 1.5 5.5 3.5 1.5 3.5 3.5 5.5 1.5 5.5 3.5

Sample code S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11

069588

11

Smoothnessd 7 7 7 7

555

5

. Erdem et al. / LWT - Food Science and Technology 56 (2014) 187e193 189Brightnessd 5.5 5 5 4Brown colord 5.5 5 5 4.7Bloomd 0 0 0 0.7Cocoa aromad 3.25 3.5 3 3.7Cocoa tasted 3.5 4 3.25 2.5Sweetnessd 3 5.25 6.5 4.5Bitternessd 1.75 0.5 1.25 1.2Bitter aftertasted 1.25 0.5 0.5 1Responsese Bacteriab 5.38 5.40 5.51 5.5L* bottomc 33.13 33.43 33.29 33.3WI bottomc 32.62 32.96 32.89 32.9a* bottomc 6.26 6.42 6.43 6.1b* bottomc 5.36 4.66 3.32 3.4L* topc 32.52 31.03 30.54 34.6WI topc 32 30.45 30.12 34.3a* topc 6.65 6.21 6.19 6.5b* topc 5.12 6.49 4.47 2.5Cocoa aftertasted 3 3 2.5 2.25Bitter avord 2 0.5 1.5 1Cocoa avord 3.75 3 3 2.5Chocolate avord 4 5 4.75 3Hardnessd 5.5 4.75 5.25 5Breakaged 3 3.75 4.25 4Firmnessd 3.25 4.75 6.25 5Smootnessd 5.5 6 6 5.75Melting rated 3.5 3 3.25 4Adherenced 2.5 2.75 4.25 3.25Spreadinessd 3.5 4 3 4Mouthcoatingd 2.75 3 3 3.25

a MD Maltodextrin, LF Lemon ber.b The values represent the average of duplicated measurements for viable bacteria coc The values represent the average of triplicate measurements for color analysis.d The values represent the average of duplicated measurements for sensory analysis.e Responses are listed in order, following the results of microbiological, color and sen5.47 5.53 5.44 5.42 5.35 5.54 5.5233.29 34.47 32.58 33.45 34.21 35.97 32.9632.9 32.02 31.89 32.6 33.49 35.52 32.486.26 6.46 7.59 8.14 6.9 5.63 6.94

3.6 4.11 5.99 6.9 6.88 5.12 4.0532.93 31.77 29.33 32.65 31.93 33.96 32.0632.52 31.12 28.5 31.79 31.27 33.39 31.546.44 7.52 7.58 7.74 6.93 6.33 6.23

3.67 5.26 7.43 7.48 6.43 5.9 5.687 7 7 7 7 7 74.5 5.5 5.75 5 5 4.5 4.254.75 4 5.5 5.75 5.25 4.5 5.250 1 0.5 0.5 0.25 0 04 4 3.25 3.25 4.25 3.75 3.53.25 4 2.75 3 2.75 3 3.51.5 4 4.5 3.75 3.5 5 5.752 2 1.25 1 1.5 1 1.751 1 0.25 0.75 1 0.75 0.25

3.5 2.75 2 2 2.75 2.5 2.252 2 1 1 1.25 1 1.253.5 3.75 3 3 3 2.25 2.54 5 4 4 4.25 4 4.755.5 5.25 5 5 5.5 5.25 5.253.5 4.25 3.5 4.25 4 4.5 4.52.25 4.75 5 5.5 2.75 5.75 5.55.5 5.5 6 5.25 5.75 6 63.25 3.5 3 3.5 3.5 3.5 3.751.75 2.75 3 3.5 2 4 3.754 3.5 3.75 3.5 3.25 4 43 3.25 3.25 2.75 2.75 2.75 3

unts in log cfu/g.

sory analysis, consecutively.

Table 3The glossary of terms, references and their scores dened the quality attributes used in sensory analysis.

Quality Denition Referencesa

Appearance Smoothness Smooth appearance of product surface without lumps of grits dark chocolate 7, halva 0Brightness Intensity of light reection in the product, opposite of opaque cocoa powder 0, dark chocolate 4, pudding 7Brown color Brown color intensity; from light brown to dark brown milk chocolate 0, dark chocolate 5, bitter chocolate 7Bloom White-gray layer of visible lipid/sugar crystals on

the surfacebitter chocolate 0, under-tempered laboratory made samplestored for 1 month 7

Aroma Cocoa aroma The aroma of cocoa powder (from none > very) white chocolate 0, dark chocolate 4, bitter chocolate 7Off-avor Unpleasant and unwanted aroma in the product none 0, intermediate 4, extreme 7

Taste Cocoa taste The intensity of the taste of cocoa in the product white chocolate 0, dark chocolate 5, bitter chocolate 7Sweetness Taste quality most often associated with sucrose

(none > very)water 0, dark chocolate 2, milk chocolate 5, honey 7

Bitterness Taste quality associated with caffeine as in caffeineand quinine(none > very)

white chocolate 0, quinine solution 7

Bitter aftertaste Residual bitter taste intensity in mouth after swallowing white chocolate 0, quinine solution 7fter swallowing white chocolate 0, bitter chocolate 7one > very) white chocolate 0, quinine solution 7

white chocolate 0 , bitter chocolate 7of chocolate white chocolate 0, dark chocolate 7cisor teeth marshmallow 0, bitter chocolate 4, carrot 7ate in rst bite halva 0, carrot 7een tongue mufn 0, milk chocolate 4, bitter chocolate 7

f the product halva 0, pudding 7

while chewing dark chocolate 2, milk chocolate 5, white chocolate 7

hurfa

ulata

. Erdem et al. / LWT - Food Science and Technology 56 (2014) 187e1931902.8. Statistical analysis

Experimental data was analyzed by multiple regressions to tthe second order polynomial equation to all independent factors.

Cocoa aftertaste Residual cocoa taste intensity in mouth aFlavor Bitter avor The avor of aqueous quinine solution (n

Cocoa avor The avor of cocoa (none > very)Chocolate avor Chocolate avor intensity, characteristic

Texture(rst bite)

Hardness The force required to cut using central inBreakage The breakage level of the piece of chocolFirmness Force required to compress sample betw

and palateTexture

(mastication)Smoothness Level of even and consistent continuity o

in mouthMelting rate Time required to melt half of the sample

(slow > fast)Adherence Level of stickiness to molar teethSpreadiness Level of covering the surface of the moutMouthcoating The after-feel lm which covers mouth s

a Dark chocolate denes a commercial product that includes %50 cocoa in formcommercial product that includes %99 cocoa in formulation. A commercial chocolateThe goodness of t of the model was evaluated by the coefcientdetermination (R2) and the analysis of variance (ANOVA). To visu-alize the relationships between the responses and the independentfactors, surface response and contour plots of the tted polynomialregression equations, and the optimal conditions for the targetedresponses were generated by Design Expert 8.0.4 (Stat-Ease, Inc.,MN, USA) Software.

3. Results and discussions

3.1. Preliminary sensory analysis for dietary ber determination

Hedonic analysis showed that (Table 1), samples containingmaltodextrin (MD) or lemon ber (LF) had the highest scores after

Table 4Results of viability of Bacillus indicus HU36 and yield %.

Sample code MDa (g/100 g) LFa (g/100 g) Final count (log cfu/g) Yield (%)

S1 1.5 3.5 5.38 0.13 88.44S2 5.5 1.5 5.40 0.14 88.85S3 5.5 5.5 5.51 0.20 90.69S4 3.5 5.5 5.50 0.23 90.46S5 1.5 1.5 5.47 0.12 89.42S6 3.5 3.5 5.53 0.17 90.99S7 3.5 3.5 5.44 0.16 89.49S8 1.5 5.5 5.42 0.22 89.18S9 3.5 1.5 5.35 0.12 88.09S10 3.5 5.5 5.54 0.18 91.14S11 5.5 3.5 5.52 0.21 90.77

Initial count of the bacteria added to all samples was 6.08 log cfu/g. The valuesrepresent the mean std deviation of duplicated measurements for viable bacteriacounts. Yield values calculated as the ratio of nal bacterial count to initial count.

a MD Maltodextrin, LF Lemon ber.control. In terms of overall acceptability scores, those bers weredistinctively separated from the samples containing carboxy-methylcellulose (CMC), inulin (IN), wheat ber (WF) and apple ber(AF) samples. Addition of CMC, IN, WF and AF showed negative

pudding 0, Nutella 5, honey 7dark chocolate 3, Nutella 7

ce pudding 0, Nutella 7ion. Halva is a commercial product of a national brand. Bitter chocolate denes avored pudding is used.effect (p < 0.01) on taste, mouthfeel, texture and overall accept-ability. Based on the results obtained, maltodextrin and lemon berwere chosen as the most suitable dietary ber types for furtherstudies.

Table 5Regression coefcients and p-values for signicant responses.

Responses Factorsa Coefcient p-value Model t

Sweetness MD conc. (L) 0.955

3.2. Viable bacteria count

Results of viable cell counts showed that in spite of theobserved reduction (w

bottom and top surface L* values than the reference sample (30.52and 29.30 for bottom and top surface). WI values showed similarresults to L* values; showing that the reference sample was darkerthan all samples we produced.

3.4. Model tting (RSM)

The results of color, sensory analysis, and bacterial counts (re-sponses) of the chocolate formulations all the experiments areshown in Table 2. The experimental data was used to calculate thecoefcients of the quadratic polynomial equations, which were

. Erdem et al. / LWT - Food Science an192Fig. 2. Spider diagram of quality attributes (terms and scores were dened in Table 3)of samples (S1eS11) depending on the results of QDA . MD Maltodextrin conc.;

LF Lemon ber conc.used to predict the responses. Analysis of variance (ANOVA) inTable 5 indicated that quadratic polynomial models were adequatefor the prediction of only sweetness, rmness and adherence fea-tures of samples. The models showed no lack of t for sweetness,rmness and adherence because p values of were higher thanp > 0.05 (0.759, 0.068 and 0.713) and coefcients of multiple de-terminations, R2, being 0.985, 0.946, 0.965, all indicate that modelst the experimental data points. The model equations for the re-sponses can be written as follow where MD and LF is maltodextrinand lemon ber concentration (g/100 g):

Sweetness 0:841 0:955MD 0:819LF 4:934:103MD2

0:0266LF2

Firmness 1:037 0:887MD 1:293LF 6:578:103MD2

0:037LF2

Adherence 0:596 0:143MD 0:549LF 0:023MD2

8:223:103LF2

For any of the terms in the models, a small p-value wouldindicate a more signicant effect on the respective responses. Thelinear term of maltodextrin (MD) and lemon ber (LF) concentra-tion had positive effects on sweetness, rmness and adherencevalues.

3.5. Response surface plots

The impact of maltodextrin and lemon ber levels on sweetness,rmness and adherence can be seen in Fig. 1. The increase in lemonber and maltodextrin concentration results in the increase ofsweetness. According to Table 3, sweetness scores of samples areexpected to be between 2 (dark chocolate) and 5 (milk chocolate)and our results for all samples were in this range. Fig. 1a showedthat the more maltodextrin and lemon ber concentration, theelevated rmness of the samples was observed. According toTable 3, the rmness scores are expected to be around 4. In ourmodel rmness score reached to 4, when maltodextrin concen-trationwas 4.5 (g/100 g) and lemon ber concentrationwas slightlyover 3.5 (g/100 g) Fig.1b summarized the effect of maltodextrin andlemon ber concentration on adherence. Mutual increase in theconcentration of bers showed the most increase on adherencescores, this value is always aimed to be kept at minimum; howeverFig. 1c showed that even in minimum ber concentrations, adher-ence score was around 1.75 which showed that dietary beraddition brought slight increase on adherence at any level in thedescribed range in the model.

The results of Quantitative Descriptive Analysis (QDA) tookpart in RSM studies as responses. Flavor proling of samples aresummarized graphically in Fig. 2. Neither of the samples showedbloom nor off-avor and all samples showed very high levels ofsmoothness similar to control sample. In general, QDA resultsshowed that dietary ber addition has signicant impact on onlysweetness, rmness and adherence features of samples among allfeatures compared to control sample.

3.6. Validation of model

Design Expert 8.0.4 software generated optimum formulationsfor targeted responses (sweetness, rmness and adherence). Threeoptimum formulations and one control sample were produced.Sensory analysis was applied to all samples and responses werescored according to the glossary and references set at Table 3.

d Technology 56 (2014) 187e193Maltodextrin and lemon ber concentration of optimum

Table 6Optimum formulations, predicted and experimental results used for model validation.

nes

416

altate.

. Erdem et al. / LWT - Food Science and Technology 56 (2014) 187e193 193formulations, predicted scores and experimental results for re-sponses are summarized in Table 6. Optimization study showedthat, lemon ber level was kept constant at 1.5 (g/100 g), whilemaltodextrin levels changed between 3.20 and 3.91 (g/100 g) informulations. Based on Table 3, sweetness scores fell in the rangebetween bitter and milk chocolate reference scores. On the otherhand, the sweetness score of control chocolate was the closest oneto bitter chocolate (Tables 3 and 6). All samples showed similarrmness and adherence scores to control as bitter chocolatereference. Table 6 also showed that sweetness, rmness andadherence scores were decreased as the level of maltodextrinconcentration decreased. The experimental scores were satisfac-torily close to the values predicted by the model (R2 was 0.95, 0.93and 0.99 for sweetness, rmness and adherence). These resultsconrm the validation of the model generated by Design Expert8.0.4 Software.

4. Conclusion

In conclusion, this study shows B. indicus HU36 can be usedefciently for probiotic bitter chocolate production. Microbiologicalanalysis proved the B. indicus HU36 had a high survival rate in darkchocolate; and all inoculated samples showed desired probioticbacteria load (over 5 log cfu/g product). Descriptive sensory anal-ysis showed that dietary ber addition didnt show negative effects,such as off-flavor, unwanted aroma or taste, on color and organo-leptic properties of samples. Among bers, maltodextrin and lemonber addition had positive effects on the sensory characteristics.Optimum formulations were generated by the RSM model and themodel was validated successfully. According to the results of opti-mization, the lemon ber concentration should be kept constant at1.5 (g/100 g) while maltodextrin concentration should be keptbetween 3.20 and 3.91 (g/100 g) in order to obtain the bestorganoleptic properties of the product.

Acknowledgments

The authors acknowledge the nancial support of EU 7thFramework Programme acronymed Project COLORSPORE (Project

Samples MD (g/100 g) LF (g/100 g) Predicted scores

Sweetness Firm

Opt 1 3.91 1.5 3.77 3.5Opt 2 3.71 1.5 3.59 3.4Opt 3 3.20 1.5 3.06 3.0Control 0 0

Opt 1, 2 and 3 stands for the optimum formulations designed by the model. MD MExperimental scores are the average of responses of 8 panelists performed in duplicnumber: 207948).

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Development of a novel synbiotic dark chocolate enriched with Bacillus indicus HU36, maltodextrin and lemon fiber: Optimiza ...1 Introduction2 Materials and methods2.1 Inoculum preparation2.2 Chocolate production2.3 A pre-study on dietary fiber determination2.4 Experimental design by using RSM2.5 Viable bacteria count2.6 Color analysis2.7 Sensory profiling of samples2.8 Statistical analysis

3 Results and discussions3.1 Preliminary sensory analysis for dietary fiber determination3.2 Viable bacteria count3.3 Color analysis3.4 Model fitting (RSM)3.5 Response surface plots3.6 Validation of model

4 ConclusionAcknowledgmentsReferences