Solid state of processed carbohydrate matrices from maltodextrin and sucrose

Journal of Food Engineering 129 (2014) 30–37

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Solid state of processed carbohydrate matrices from maltodextrin and sucrose Markus W. Tackenberg a,b, Markus Thommes b, Heike P. Schuchmann a, Peter Kleinebudde b,⇑ a b

Institute of Process Engineering in Life Sciences, Section I: Food Process Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany Institute of Pharmaceutics and Biopharmaceutics, Heinrich-Heine-University, Duesseldorf, Germany

a r t i c l e

i n f o

Article history: Received 24 October 2013 Received in revised form 19 December 2013 Accepted 1 January 2014 Available online 9 January 2014 Keywords: Encapsulation Sucrose Maltodextrin Plasticization Melting Caramelization

a b s t r a c t Various mixtures of maltodextrin, sucrose, and water, as typical compounds of food matrices used for flavour encapsulation via extrusion, were processed in a batch mixing process. Plasticization, melting and caramelization just as the formation of amorphous sucrose were studied. All matrices were plasticized within 2 min, resulting in a loss of crystalline sucrose. Melting occurred due to water loss higher than 55%. Caramelization could be correlated to a specific mechanical energy input higher than 300 Wh/kg. The glass transition temperature of the caramelized matrices could not be fitted with the Gordon Taylor equation, based on the used compounds. Increasing sucrose content in the preblended powder mixture combined with increasing sample water content increased the crystalline fraction within the matrix. These findings enable a systematically investigation of matrices for encapsulation of flavours within the batch mixing process, which can help to transfer the flavour encapsulation to an extrusion process. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Carbohydrate matrices, containing a high (HMWC) and a low (LMWC) molecular weight carbohydrate are of great interest for the food and pharmaceutical industry. Matrices containing these substances often are used for stabilization and encapsulation of liquid and lipophilic flavours, aromas or essential oils (Goubet et al., 1998; Uhlemann and Reiss, 2010; Versic, 1988). Spray-drying and extrusion are the most commonly and commercially used processes for flavour stabilization (Goubet et al., 1998). For extrusion processes the combination of amorphous maltodextrins or modified starches as HMWC with different crystalline Abbreviations: a, time interval of the recording rate for torque (s); AS, part of amorphous sucrose within the amorphous fraction (%); cc, crystalline content (%); DE, dextrose equivalent; DoE, design of experiments; DSC, differential scanning calorimetry; GT, Gordon & Taylor (equation); i, intensity; HMWC, high molecular weight carbohydrate; k, Gordon Taylor constant; LMWC, low molecular weight carbohydrate; MD, maltodextrin; PT, product temperature (°C); Q2, coefficient of prediction; R2, coefficient of determination; RP, repeatability; RS, rotation speed (1/s or 1/min); SME, specific mechanical energy (Wh/kg); SUC, (crystalline) sucrose (%); t, process time (s or min); s, torque (Nm); Tg, glass transition temperature (K or °C); w, weight fraction (); WC, sample water content (%); WCA, water content within the amorphous fraction of the sample (%); XRPD, X-ray powder diffraction. ⇑ Corresponding author. Tel.: +49 211 81 14220; fax: +49 211 81 14251. E-mail addresses: [email protected] (M.W. Tackenberg), markus. [email protected] (M. Thommes), [email protected] (H.P. Schuchmann), [email protected] (P. Kleinebudde). 0260-8774/$ - see front matter Ó 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jfoodeng.2014.01.003

disaccharides (LMWC) like sucrose, fructose, maltose or lactose is well described (Attwool and Blake, 1996; McIver et al., 2002; Risch, 1988; Uhlemann and Reiss, 2010). Uhlemann and Reiss (2010) recommended a mixture of a maltodextrin and a disaccharide leading to high aroma retention. Kilburn et al. (2005) and Townrow et al. (2007) investigated the influence of water and LMWC on maltodextrins and proved that amorphous LMWC led to an increased molecular packing of the carbohydrates which increased the stability of encapsulated flavours. Amorphous LMWC just as water decrease the glass transition temperature (Tg) of HMWC (Roos and Karel, 1991a). The Tgmix [K] of a binary matrix is usually calculated using the Gordon and Taylor Eq. (1) (Gordon and Taylor, 1952; Roos and Karel, 1991a, 1991c):

Tg mix ¼

w1 Tg 1 þ kw2 Tg 2 w1 þ kw2

ð1Þ

where Tg1, Tg2 and Tgmix are the glass transition temperatures [K] of the amorphous substances 1, 2, and the binary matrix, w1 and w2 are the weight fractions of the substances 1 and 2, and k is the GT constant. At storage temperatures below Tgmix, the matrix is a glassy solid, characterized by a low molecular mobility as well as hard and brittle mechanical properties and a viscosity of approximately 1011–1012 Pas (Ferry, 1980; Palzer, 2010). The release or evaporation of an entrapped aroma in such a glassy solid is reduced to a

M.W. Tackenberg et al. / Journal of Food Engineering 129 (2014) 30–37

minimum. Increasing the temperature above Tgmix, the matrix turns into a processible, rubbery state. In this state recrystallization of the LMWC is found, and release of stabilized flavour increases (Gunning et al., 1999; Levi and Karel, 1995; Roos and Karel, 1991b). Additionally crystallization of LMWC induces flavour loss (Carolina et al., 2007; Labrousse et al., 1992; Rifa and Voilley, 1991). During the extrusion process the rubbery state is received, but by leaving the die the matrix is cooled below Tg and turns into the glassy state. The loss of the crystalline structure of the LMWC during the process is desirable, due to the encapsulating properties of amorphous LMWC in a binary carbohydrate matrix (Kilburn et al., 2005; Palzer, 2010; Townrow et al., 2007). Amorphous substances are also characterized by a rapid dissolution rate in water which is favourable in application (Palzer, 2010). Twin-screw extruders are used in industry for the encapsulation of flavours in these matrices (Attwool and Blake, 1996; McIver et al., 2002). The extruder configuration, process parameters and the composition of the carbohydrate blends are often corporate intellectual property. Risch (1988) and Uhlemann and Reiss (2010) described extrusion of maltodextrins with LMWC as a melting process. When water is added, plasticization of the carbohydrate blend has also to be regarded. In commercial extrusion based processes sucrose often is chosen as LMWC in accordance to the available patents (Attwool and Blake, 1996; McIver et al., 2002). Crystalline sucrose melts between 160 and 192 °C, depending on water content and purity (Roos, 1993a; Roos et al., 2013; Roos and Karel, 1991b). Melting of amorphous maltodextrins depends on the glass transition temperature (Tg), which is mainly influenced by the combined water and the molecular weight of the maltodextrin (Roos and Karel, 1991a). In a plasticization process water leads to a decrease of Tg of the maltodextrin below ambient temperature. In addition, crystalline sucrose will dissolve in the water and in the plasticized, rubbery maltodextrin. The aim of this study was to investigate the influence of process parameters and composition of the carbohydrate blends on the solid state of the processed matrices. In this context the understanding of the formation and stabilization of amorphous sucrose was a major objective. A small scale batch mixing process was used to obtain various carbohydrate matrices, containing maltodextrin and sucrose. This is intended as a first step to design a later continuous extrusion process. Since decades this approach is utilized in polymer science and since the last years in pharmaceutical technology (Liu et al., 2010; Sundararaj and Macosko, 1995). A considerable advantage of a batch process in comparison with an extrusion process is the possibility to vary selected process parameters, like rotation speed, filling level, process time, etc., independently from each other. Schuchmann (2008) described the difficulties and interactions between material-, extruder- and process parameters using the example of designing a food cooking extrusion process. A batch mixing process is well described for melt and blending processes of polymers (Bousmina et al., 1999; Brahimi et al., 1991) as well as for starch processing (Teixeira et al., 2007), but not for various maltodextrin sucrose blends. Process parameters that can be varied are rotation speed, process time, chamber temperature and filling level of the chamber, whereas maltodextrin sucrose ratio and water content are material parameters of relevance. Chamber temperature and filling level were set constant, whereas rotation speed, process time, powder composition and added water content were investigated in this study. Preliminary tests had shown, that a chamber temperature of lower than 110 °C did not lead to detectable torque and thus to a melting of the carbohydrate mixtures within 5 min. Temperatures between 90 and 130 °C were given by McIver et al. (2002) as temperature range of interest in

31

extrusion processes. Thus, a constant chamber temperature of 105–108 °C was selected. By the injection of water the volume of the mixed powder decreased and plasticization started. A constant amount of 80 g preblended maltodextrin sucrose mixture was selected regarding an useful filling level. At rotation speeds higher than 100 rpm an increased filling level led to expansion of the matrix out of the chamber. A moisture content up to 10% was pointed out by Risch (1988) for encapsulation processes using extrusion. 10% was selected as maximum water content regarding the sum of the amount of injected water and the combined water in the powder blends. For the quantification of the fraction of crystalline sucrose within the processed carbohydrate matrices an X-ray powder diffraction (XRPD) method was developed. Differential scanning calorimetry (DSC) was used for the detection of Tg of the carbohydrate matrices. A design of experiments (DoE) was applied to systematically evaluate the influences of the process parameters and the carbohydrate composition to the solid state properties of the processed carbohydrate matrices. 2. Experimental 2.1. Materials Maltodextrin DE 12 (GlucidexÒ 12 D, Roquette Frères, Lestrem, France), sucrose (Bäko Puderzucker, BÄKO Marken und Service eG, Bonn, Germany) and deionized water were used in this study. A water content, measured by Karl-Fischer Titration, of 5.1 ± 0.1% and 0.6 ± 0.1% was obtained for the maltodextrin and sucrose, respectively. 2.2. Batch mixing process Sucrose and maltodextrin mixtures containing 25%, 50% or 75% sucrose were blended in a bin blender (LM20, Bohle, Ennigerloh, Germany) for 10 min at 25 rpm and used for further investigations. The 55 ml volume mixing chamber of a torque rheometer (an instrumented batch mixer with counter rotating blades, W 50 EHT, Brabender GmbH & Co. KG, Duisburg, Germany) was heated up to a temperature of 105–108 °C. 80 g Of the preblended powder mixture and a fraction of water (added water content – AWC) were added within the first 30 s of the process into the chamber. AWC was calculated with Eq. (2):

AWC ½% ¼ 100

mwater mpowder þ mwater

ð2Þ

where mwater [g] is the injected amount of water and mpowder [g] is the amount of the preblended powder mixture. Product temperature and torque were recorded during the process every 2 s. Samples of approx. 1 g were taken after 4, 6 and 11 min of mixing process. After each time step, the rotation speed was reduced to 20 rpm and the experiment time was stopped. Afterwards the process was restarted and the experiment time was continued. All samples were collected, cooled, and stored in bottles with airtight snap-on-caps at 25 °C. 2.3. Water content The water content (WC) was examined based on the dry mass by Karl-Fischer-Titration (Schöffski, 2000) in a V 20 (Mettler-Toledo, Giessen, Germany). Approximately 250 mg of each sample were dissolved in 5.0 g of an equal mixture of methanol (Hydranal Methanol Dry, Riedel-deHaen, Seelze, Germany) and formamide (Hydranal Formamid Dry, Riedel-deHaen, Seelze, Germany) in

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M.W. Tackenberg et al. / Journal of Food Engineering 129 (2014) 30–37

bottles with snap-on-caps. 600 lL of each dissolved sample was injected into the working fluid (equal mixture of methanol formamide) and titrated by the addition of Hydranal Composit 5 (Riedel-deHaen, Seelze, Germany). The injection of the dissolved sample into the working fluid was performed in triplicate and the average was calculated.

2.4. Crystallinity Approx. 300 mg of crystalline sucrose, amorphous maltodextrin and binary mixtures containing 20%, 40%, 60%, and 80% of sucrose were mixed manually in a mortar. This was performed in duplicate for each substance and blend. The carbohydrate powders were stored over a saturated salt solution of potassium carbonate (relative humidity: 43%) at 25 °C under air circulation by fan for >24 h. The pure substances and blends were compressed with a hydraulic press to tablets with a diameter of 13.0 mm at a pressure of 206–216 MPa for 30–45 s. The sample holder with the tablet was transferred into the diffractometer (X’pert PRO, PANalytical B.V., Almelo, The Netherlands). 0 The diffractometer with Cu Ka radiation (k = 1.5406 Å A) operated with a tube voltage of 40 kV and tube current of 40 mA from 10 to 30° 2h with a step size of 0.0167° and a counting time of 0.375 s/step. The obtained XRPD pattern of sucrose was compared to measurements of Brown and Levy (1973) and Kimura et al. (2010) to confirm the peak free parts of the pattern (10.00°–11.09°; 13.75°–15.09°; 16.97°–17.83°; 21.38°–21.51°; 22.78°–23.01°; 26.78°–27.04°; 27.86°–28.38°; 28.83°–30.00°). Based on the peakfree fragments of the pattern a baseline was calculated by a polynomial equation for each sample (Fig. 1). The peak intensities of the XRPD raw data and the polynomial fit were summed over the 2 theta angle (RiXRPD raw data and Ripolynominal fit) and the difference (Ricc) was calculated using Eq. (3).

X

icc ¼

X

iXRPD raw data 

X

ipolynomial fit

ð3Þ

The Ricc values were plotted against the sucrose content [%] of the measured carbohydrate samples. A linear fit was obtained for the quantification of the crystalline content cc [%] with a coefficient of determination (R2) of 0.9994. The three preblended powder mixtures and the obtained samples were processed in the same way, but only performed once. cc values of 23.3%, 47.7% and 71.9% were determined for the preblended powder mixtures.

2.5. Glass transition temperature Approx. 5 mg of the plasticized carbohydrate mixtures were weighed in 40 lL aluminium pans and hermetically sealed. To investigate the glass transition temperature (Tg), these samples were analyzed with a differential scanning calorimeter (DSC 1, Mettler-Toledo, Giessen, Germany). Starting from 30 °C or 50 °C the samples were heated with 10 °C/min to 100 °C. The glass transition range was determined and Tgmidpoint was taken as the characteristic value. An average for every Tgmidpoint was calculated out of at least two DSC measurements and used as response variable Tg. 2.6. Experimental design A 33 screening design with two repetitions at the centre point was used. The rotation speed (RS), the added water content (AWC) and the sucrose content (SUC) of the powder blend were varied systematically (Table 1). Sampling of approx. 1 g after 4, 6 and 11 min led to three 33 screening designs. Neglecting the loss of approx. 2 g and the time needed for sampling the three 33 designs were analyzed as a 34 design with the process time (t) as fourth factor. As response variables served the specific mechanical energy (SME) [Wh/kg], the product temperature (PT) [°C], sample water content (WC) [%], the glass transition temperature (Tg) [°C], the fraction of crystalline sucrose in the processed samples (cc) [%], and the part of amorphous sucrose within the amorphous fraction of the samples (AS) [%], calculated with (4):

AS ½% ¼ 100

SUC  cc 100  cc

ð4Þ

In continuous processes as the one of interest here (extrusion), the SME is used to calculate the mean energy input by the screw(s) into the product mass. It is determined by the power consumption of the motor less the no-load power, divided by the material mass flow. Since decades the SME is used in extrusion literature in order to characterize the overall energy input and its influence on product characteristics (Meuser et al., 1982, 1984). Physical and chemical processes during extrusion as e.g. degradation and water solubility are influenced and often controlled by this value (Meuser et al., 1984, and Schuchmann, 2008). In a batch process like the mixing process investigated here, a constant amount of material is exposed to the mechanical energy of the rotating blades over a fixed range of time. Thus we calculated the SME according to Eq. (5).

  t¼end X Wh aRSpðstþa þ st Þ ¼ SME kg 3600ðmpowder þ mwater Þ t¼start

ð5Þ

where t = process time [s], a = time interval [s] of the recording rate for torque, RS = rotation speed [1/s], s = measured torque [Nm] and m = weighed-in mass [kg] of the used powder mixture and injected water, respectively. The derivation of (5) is specified in the Supplementary Data.

Table 1 Factor levels for the parameters varied in the batch mixing process. RS: rotation speed; SUC: sucrose in the preblended powder mixture; AWC: added water content; t: process time.

Fig. 1. Peaks, and peak free fragments of the XRPD measurement of a blend containing 20% sucrose and 80% maltodextrin and the polynomial fit of the peak free fragments in the power of sixth.

RS (min1) SUC (%) AWC (%) t (min)

1

0

+1

70 23.3 2.9 4

100 47.7 4.3 6

130 71.9 5.7 11

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Four different parameters were obtained regarding the power of the model: the coefficient of determination (R2), the coefficient of prediction (Q2), the lack of fit (p) and the repeatability (RP) (Eriksson et al., 2008).

3. Results and discussion 29 Batch mixing processes were performed and 87 samples were collected. Any process condition led to a homogeneous carbohydrate mixture. The viscosity of the matrices increased after sampling during cooling to room temperature, but not all matrices turned into a solid and brittle state. Some process conditions led to discolouration of the carbohydrates. The obtained yellow/brown colour indicated a caramelization process. The levels of the investigated factors RS, SUC, and AWC as well as the obtained values of the response variables WC, SME, PT, Tg, cc and AS are listed in Table A.1 for sampling time 4 min, A.2 for sampling time 6 min and A.3 for sampling time 11 min in the Supplementary Data.

3.1. Water content (WC) Added water induced a plasticization process of the carbohydrate blends. The measured sample water content (WC) consisted of the added water content (AWC), the combined water in the powder blends, and the loss of water due to evaporation during the process. Values between 0.2% and 9.0% WC were obtained (Tables A.1– A.3 of the Supplementary Data). The power of the model was high (Table 2). WC increased with increasing AWC. It decreased with increasing process time and rotation speed (Table 2). This was due to the open mixing chamber during sampling and due to the unavailable hermetically sealing of the batch mixer during the process. The batch mixer is closed, but water evaporation occurred with an increase of mechanical energy input, temperature and time. The coefficient for factor SUC was not significant, but the square and interaction terms had influence on WC (Table 2). This is due to two contrary effects and shown in Fig. 2. WC decreased with increasing SUC (from factor level 0 to +1) due to the lower water content of sucrose (0.6%) in comparison with the maltodextrin (5.1%). Below a maximum value of WC at SUC factor level 0 (SUC: 47.7%), it decreased with decreasing SUC (from factor level 0 to 1). This was related to the increased mechanical energy, which was necessary for processing of the

Fig. 2. Influence of the factors added water content AWC and sucrose content SUC on the response variable sample water content WC.

carbohydrate matrix. This led to increased product temperature PT, water evaporation and finally to a decreased WC. Regarding an appropriate statistical analysis of the other response variables the response variable WC was considered as a factor instead of the AWC (Table 2). 3.2. Specific mechanical energy (SME) A broad range of values between 13.4 and 779 Wh/kg were obtained depending on the process parameters (Tables A.1–A.3 of the Supplementary Data). The power of the model is high (Table 2). All factors investigated had significant influence on the SME (Table 2). Regarding Eq. (5) it was likely that increasing RS and t increased the SME. Increasing WC and SUC decreased the SME, which is due to the plasticizing effect of these substances (Roos and Karel, 1991a). Values of 50–320 Wh/kg are common SME values of HMWC like starch in food extrusion processes (DellaValle et al., 1995; Leeb and Schuchmann, 2008). Increasing SME led to increasing product temperature PT, which resulted in a colour change of the matrices at SME values P300 Wh/kg (Fig. 3). The formation of the yellow/brown colour can be linked to a caramelization process of the maltodextrin sucrose matrix (Claude and Ubbink, 2006). Before caramelization was visually detected the plasticization process had turned into a melting process. Melting in batch mixing

Table 2 Results from the DoE – power of the model (R2, Q2, p and RP) and coefficients for factors to the response variables (coefficient ±95% confidence interval). SME: specific mechanical energy; PT: product temperature; Tg: glass transition temperature; cc: crystalline content; AS: part of amorphous sucrose within the amorphous fraction. WC

*

SME

PT

PT*

Tg

Tg*

cc

AS

R Q2 Lack of fit (p) RP

0.814 0.776 0.745 0.738

R Q2 Lack of fit (p) RP

0.929 0.907 0.998 0.811

0.925 0.913 0.000 0.991

0.913 0.894 0.066 0.962

0.856 0.838 0.053 0.933

0.908 0.889 0.402 0.917

0.986 0.983 0.445 0.987

0.863 0.833 0.777 0.809

Constant RS AWC SUC t SUC*RS SUC*SUC SUC*AWC – – –

5.3 ± 0.4% 0.8 ± 0.3% 2.2 ± 0.3% 0.1 ± 0.3%+ 0.8 ± 0.3% 0.8 ± 0.3% 1.2 ± 0.5% 0.5 ± 0.4% – – –

Constant RS WC SUC t WC*WC SUC*SUC SUC*WC SUC*t RS*t WC*t

163.1 ± 17.4 Wh/kg 31.9 ± 14.6 Wh/kg 193.5 ± 24.1 Wh/kg 96.8 ± 15.8 Wh/kg 58.1 ± 13.3 Wh/kg 70.7 ± 49.2 Wh/kg – 31.9 ± 31.2 Wh/kg 36.5 ± 17.0 Wh/kg 20.7 ± 16.7 Wh/kg 83.1 ± 26.7 Wh/kg

126.7 ± 2.5 °C 3.6 ± 2.1 °C 36.8 ± 3.2 °C 14.6 ± 2.2 °C 2.3 ± 1.9 °C 13.3 ± 7.0 °C – – – – –

125.1 ± 1.9 °C 1.6 ± 1.2 °C 31.4 ± 3.0 °C 14.4 ± 1.6 °C – 13.4 ± 5.8 °C 2.5 ± 2.2 °C 6.7 ± 4.5 °C – – –

44.1 ± 3.0 °C – 30.5 ± 3.9 °C 18.6 ± 2.3 °C – – 15.6 ± 3.8 °C 28.3 ± 4.9 °C – – –

47.6 ± 3.5 °C – 26.0 ± 5.5 °C 18.0 ± 2.9 °C – 14.1 ± 10.5 °C 20.8 ± 3.9 °C 36.2 ± 8.1 °C – – –

21.0 ± 1.2% 1.3 ± 0.8% 3.2 ± 1.3% 26.0 ± 0.8% 1.4 ± 0.7% 4.8 ± 2.5% 7.6 ± 1.2% 4.3 ± 1.6% – – –

33.7 ± 1.4% 1.2 ± 0.9% 3.9 ± 1.5% 8.2 ± 0.9% 1.2 ± 0.8% 4.1 ± 2.9% 4.4 ± 1.4% 5.5 ± 1.8% – – –

2

2

Samples with SME P 300 Wh/kg were excluded from the statistical analysis. + Non-significant coefficient, but necessary for the model because of the significant interaction terms: SUC*RS and SUC*AWC and the square term SUC*SUC.

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Fig. 3. Product temperature PT as function of specific mechanical energy SME in batch mixing. SME values P300 Wh/kg led to colourimetrically detectable caramelization.

process is characterised by an increasing torque as described by Bousmina et al. (1999) on the example of polymers. Sample 27 was chosen as a highly representative example to characterize the different stages plasticization, melting and caramelization with the recorded torque and temperature data. In Fig. 4 the increasing and decreasing torque within the first 2 min of the process indicated the plasticization of the matrix. From 2:30 min to 5:50 min the torque increased continuously, interrupted by peaks indicating the beginning and ending of sampling 1. Increasing torque led to increasing product temperature (PT), indicating melting of the matrix. After reaching the maximum, torque decreased again, interrupted by peaks indicating the beginning and ending of sampling 2. However PT increased further until a steady state was reached. This indicated the transition from melting to caramelization within the matrix. Kroh (1994) recommended temperatures >120 °C to obtain caramelization of sugars. In this batch mixing process PT higher than 150 °C were needed that caramelization occurred (Fig. 3). 3.3. Product temperature (PT) PT values between 98 and 187 °C were obtained during the batch mixing process (Tables A.1–A.3 of the Supplementary Data; Fig. 3). Increasing RS and t led to an increase in SME and PT. An

increase in WC and SUC led to a decrease in PT (Table 2). The coefficient of determination (R2), the coefficient of prediction (Q2) and the repeatability (RP) were on the same high level as for SME (Table 2). However, there was a lack of fit (p) in this model. This could be attributed to the caramelization process at elevated PT. The PT was increasing with the process time until the end of the process if no caramelization occurred. However PT stayed in a steady state if caramelization appeared (Figs. 3 and 4). This can be explained by two effects: Firstly the decreasing torque, due to a completely molten matrix (Bousmina et al., 1999). Due to the decreased energy input the PT could not rise further. Secondly the caramelization is characterised as a process with many stages, whereby thermal decomposition occurs (Claude and Ubbink, 2006, and Kroh, 1994). In combination with the remained mechanical and thermal energy input the caramelization is a self-stabilizing process at a constant product temperature. This could not be predicted with the chosen factors and led to a lack of fit in the model. Due to this fact all samples with a SME value 300 Wh/kg were excluded from the statistical analysis. Also sample 1 at sampling time 2 with a SME value of 261 Wh/kg and a PT of 159 °C was excluded as an outlier from the statistical analysis. The resulting values are marked by an *. The power of the model for response variable PT* was comparable to PT, but the lack of fit had disappeared (Table 2).

3.4. Glass transition temperature (Tg) The glass transition temperatures (Tg) could be determined with the described DSC method with a high reproducibility (Table 2). Midpoint glass transition temperatures between 23 °C and 63 °C were obtained (Tables A.1–A.3 of the Supplementary Data). R2 and Q2 showed high values. The single factors WC and SUC just like their interaction term and the quadratic term of SUC decreased Tg, due to their plasticizing properties which were described in literature (Roos and Karel, 1991a, 1991b, 1991c). For the calculation of plasticizing effects on the Tg in carbohydrate systems the GT Eq. (1) was used. GT constant k was used as fitting parameter (Palzer, 2010). The GT-model is valid for a homogenous amorphous binary system. The system investigated however contained amorphous maltodextrin, amorphous and crystalline sucrose and water. Ghorab et al. (2013) applied successfully the GT equation for a carbohydrate system containing a physical mixture of amorphous

Fig. 4. Torque and product temperature PT as function of process time t of sample 27.

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maltodextrin and crystalline sucrose. They showed that the content of the crystalline sucrose could be disregarded if the water content of the system is lower than 30%. As in this study a processed maltodextrin sucrose matrix was used and the GT equation was applied after a three step calculation. The temperature scale in Kelvin was used for each calculation step. (1) Calculation of the Tgdry of maltodextrin DE 12. The DE values between 5 and 40 of different maltodextrins (MD) were plotted against their Tg value, reported by Roos and Karel (1991a) and Ghorab et al. (2013), and fitted using Eq. (6) with an R2 of 0.979.

Tg dry MD ½K ¼ 2:730 DEMD þ 466:951

ð6Þ

The obtained Tgdry MD of 434.18 K of the DE 12 maltodextrin was used for the next calculation step. (2) Calculation of the Tgmix-dry of amorphous MD-sucrose matrix. At first the GT model (Eq. (1)) was used to obtain theoretical Tg values of a dry amorphous maltodextrin sucrose system (Tgdry mix), disregarding the crystalline sucrose content as well as the water content. Tg1 = Tgdry MD = 434.18 K; Tg2 = Tgdry sucrose = 340.15 K (Roos, 1993a) and k = 3 (Roos and Karel, 1991a) were used. The part of amorphous sucrose (AS) within the amorphous fraction of each sample was determined using Eq. (4) and the fraction of maltodextrin (MDamorph) in the amorphous fraction of each sample was determined by Eq. (7).

MDamorph ½% ¼ 100  AS

ð7Þ

(3) Calculation of the constant k required for the GT model. Due to the assumption that the WC was completely bound within the amorphous fraction of the samples the water content of the amorphous part (WCA) was calculated with (8).

WCA ½% ¼ 100

WC 100  cc

ð8Þ

The calculated WCA, Tgdry mix, the Tg of water = 144 K (Johari et al., 1987) and the measured average Tgmidpoint (Tgmeasured) were used to calculate the GT constant k for each sample, see Eq. (9):

k¼

ð100  WCAÞðTg drymix  Tg measured Þ WCAðTg measured  Tg water Þ

ð9Þ

Fig. 5. Measured Tg data compared to the Tg fits calculated via GT equation.

were obtained. Secondly caramelization led to various thermal decomposition products, depending on PT and t (Kroh, 1994). The fraction of maltodextrin and amorphous sucrose decreased and thus a calculation with (1) was not possible. At WCA higher than 4% the fitted data are approximately in accordance with the measured Tg values. The differences resulted from the various ratios of MDamorph and AS. The calculated Tg data with k = 5.87 ± 1.42 were fitted via polynomial equations with R2 > 0.95 (10, 11, 12):

Tg mixðk¼4:45Þ ½ C ¼ 0:226WCA2  10:463WCA þ 109:43

ð10Þ

Tg mixðk¼5:87Þ ½ C ¼ 0:315WCA2  12:764WCA þ 108:23

ð11Þ

Tg mixðk¼7:29Þ ½ C ¼ 0:400WCA2  14:730WCA þ 106:73

ð12Þ

Thus the obtained coefficients for the response variable Tg (Table 2) fit with the calculation model using the GT equation. The power of the model is high regarding R2, Q2 and RP (Table 2). The model has no lack of fit, but the lack of fit (p) value was just above 0.05. Excluding the coloured samples with a SME value P300 Wh/kg and the known outlier from the statistical analysis, the lack of fit (p) value increased to 0.4 (Table 2). However five samples (sample 19 at sampling time 4 min; sample 4, 6, and 8 at sampling time 6 min; sample 5 at sampling time 11 min) with SME value 6300 Wh/kg contained WCA <4%, correlating with a water loss >55% (Figs. 5 and 6). These matrices had turned from

k values between 2.9 and 143.2 were obtained. Values between 1.5 and 11.2 were reported for carbohydrate-water or food systems (Ghorab et al., 2013; Roos, 1993a, 1993b). Referring to the obtained k values >11.8 a correlation with the caramelization was found. Excluding these samples from the calculation, a range of values between 3.1 and 11.8 for k were obtained. The average (5.87 ± 1.42) was calculated and used for the GT-model (1). 3.4.1. GT fit of the processed maltodextrin-sucrose matrix The measured Tg values of the samples were plotted against the WCA (Fig. 5). A decrease of the Tg with increasing WCA was expected due the plasticization effect of water on carbohydrates (Roos and Karel, 1991c) and due to the results of the DoE (Table 2). The obtained Tg values were compared to the calculated Tg data using GT equation with k = 5.87. The fitted Tg values had much higher Tg values at lower water contents in comparison to the measured data. Differences up to 60 °C were obtained. This was due to two effects during caramelization. Firstly the low water content was linked to the water liberation from the matrix during caramelization (Claude and Ubbink, 2006). Due to the high PT the evaporation of the liberated water increased and low WCA

Fig. 6. Water loss as a function of process time t. At water loss >55% thermal decomposition appeared depending on melting and caramelization.

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plasticization to melting, while sampling. The melting led to an increase of PT and evaporation of water. As an example served sample 4 which was collected in a fully plasticized state at sampling time 4 min, during melting at sampling time 6 min, and during caramelization at sampling time 11 min. By obtaining a water loss >55%, depending on caramelization and melting, GT equation must be discarded. In this state thermal decomposition led to lower Tg values, as calculated with GT equation.

samples. With increasing SUC the maltodextrin content decreased to remain a constant amount of 80 g of the powder mixtures. Thus, the part of amorphous sucrose within the amorphous fraction of the samples (AS), calculated by (4) was the relevant response variable regarding the determination of the increasing or decreasing fraction of amorphous sucrose.

3.5. Crystalline content (cc)

The power of the model was high (Table 2) depending on values between 20 and 52.5% amorphous sucrose within the amorphous fraction of the samples (Tables A.1–A.3 of the Supplementary Data). Most values of the coefficients for AS were inverse to the values of the coefficients for cc. Thus RS and t increased AS. A wide difference was obtained regarding the coefficient for factor SUC in comparison to response variable cc. AS increased with increasing SUC (Fig. 7b). This can be explained by the different maltodextrin sucrose ratios. Increasing factor SUC decreased the amount of maltodextrin. With a lower fraction of maltodextrin (SUC factor level +1) more AWC is available for the dissolution of sucrose, which resulted in an increased fraction of amorphous sucrose. But due to no or low water evaporation during the process the WC of the obtained samples remained high, resulting in a low Tg of the amorphous fraction, recrystallization and values between 31% and 34.5% of AS (Fig. 7b). Thus a maximum of >45% amorphous sucrose was stabilized in the amorphous carbohydrate matrix at SUC factor level +1 containing a minimum of WC. As crystalline sucrose is also found in the sample, a recrystallization over a long storage time cannot be excluded. At SUC factor level 1 the factor WC had not this significant impact. Due to the high fraction of maltodextrin, a fully amorphous matrix contained a maximum level of 23.3% AS, if the complete fraction of crystalline sucrose is transferred to the amorphous state. This was observed for 14 of 29 factor combinations. Increasing RS and t led to a fully amorphous matrix. A lower fraction of AS between 20.3% and 22.8%, corresponding with cc <4%, were obtained for the other 15 factor combinations. Taking into consideration, that differences between samples with a cc <4% were detectable with the developed XRPD quantification method, the WC had a low, but verifiable, influence. At a WC lower than 2% (Tables A.1–A.3 of the Supplementary Data), the obtained high energy input led to melting and caramelization of the crystalline sucrose and finally to a fully amorphous matrix. Increasing WC to values of 4%, led to a small but detectable crystalline content, because melting was

The crystalline content (cc) of each sample was investigated via XRPD, resulting in a model with high power (Table 2). Values between 0 and 60.5% of a crystalline fraction in the samples were obtained (Tables A.1–A.3 of the Supplementary Data). Thus a fraction of the crystalline sucrose of each sample was transferred during the process into the amorphous state. Due to the sampling, the cooling rate of each sample and the sample preparation for the XRPD measurement, a recrystallization could not be excluded. A lower cc of each sample during the process was possible, but due to the analytical methods not detectable. Increasing t and RS decreased cc by a value of 1.4% and 1.3% (Table 2), which can be explained by the higher energy input. The influence of SUC and WC on cc is displayed in Fig. 7a. The highest cc was determined with high sucrose fraction (Table 1) and a high WC. Also these samples appeared at storage temperature (25 °C) in the rubbery state with a Tg lower than 25 °C. In this state a quantitative stabilization of amorphous sucrose is not possible and recrystallization occurred, as also described by (Roos and Karel, 1991b). At low WC (<2%) a decreased cc and thus an increased amorphous sucrose fraction was obtained in comparison to WC between 4 and 5%. The increased mechanical energy input associated with the higher PT at low WC led to an increased dissolution and / or melting of the crystalline sucrose in the plasticized carbohydrate matrix, resulting in a decreased cc. Also the Tg values of the amorphous fractions of these samples were above storage temperature, which reduced the recrystallization to a minimum. In comparison to the other coefficients, the coefficient for factor SUC is disproportionately high (Table 2). With the increasing factor SUC from 23.3% to 47.7% to 71.9% the cc in the samples increased with each factor level by a coefficient of 26% (Table 2, Fig. 7a). This suggested that the cc was nearly independent from the process and increased with the same level as factor SUC. But this can be misleading as the content of the maltodextrin is not equal in all

3.6. Part of amorphous sucrose (AS) within the amorphous fraction

Fig. 7. Influence of the factors sucrose content SUC and sample water content WC on the response variables (a) crystalline content cc and (b) part of amorphous sucrose within the amorphous fraction AS.

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not observed. At higher WC, again a fully amorphous matrix was found. This is due to the described fact that more AWC is available for the dissolution of sucrose. The high WC at SUC factor level 1 led to no detectable recrystallization due the Tg values >25 °C. 4. Conclusion This study has shown that the processes during batch mixing of sucrose maltodextrin mixtures could be related to plasticization, melting, and caramelization. Plasticization occurred independently of the process parameters. However, the correlation between process parameters and composition of the preblended powder mixture on SME, product temperature and water content and thus on melting and caramelization could be described sufficiently. Hence, this findings could be linked to the solid state properties as glass transition temperature, crystalline fraction, and amount of amorphous sucrose. Using a preblended powder mixture containing less than 25% sucrose, sample water contents lower than 2% and higher than 6% led to a fully amorphous matrix due to melting and plasticization, respectively. Regarding further studies using a batch mixing process the fraction of crystalline sucrose within the processed matrix could easily be adjusted. Therefore, this study makes it suitable to investigate the encapsulation properties of defined structured carbohydrate matrices. Acknowledgements The authors thank the Federal Ministry of Economics and Technology (BMWi) of the Federal Republic of Germany for its financial support of this AiF Central Innovation Programme (ZIM KF2256805WZ1), Karin Matthée, Heinrich-Heine-University for the DSC and Karl-Fischer measurements and the company Roquette Frères for donation of the maltodextrin. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jfoodeng.2014.01. 003. References Attwool, P., Blake, A., 1996. Particulate Flavour Compositions and Process to Prepare Same. Patent WO 1996011589A1. Bousmina, M., Ait-Kadi, A., Faisant, J.B., 1999. Determination of shear rate and viscosity from batch mixer data. J. Rheol. 43 (2), 415–433. Brahimi, B., Ait-Kadi, A., Ajji, A., Jérôme, R., Fayt, R., 1991. Rheological properties of copolymer modified polyethylene/polystyrene blends. J. Rheol. 35 (6), 1069– 1091. Brown, G.M., Levy, H.A., 1973. Further refinement of the structure of sucrose based on neutron-diffraction data. Acta Crystall. Sect. B – Struct. Sci. B29, 790–797. Carolina, B.C., Carolina, S., Zamora, M.C., Jorge, C., 2007. Glass transition temperatures and some physical and sensory changes in stored spray-dried encapsulated flavors. LWT – Food Sci. Technol. 40 (10), 1792–1797. Claude, J., Ubbink, J., 2006. Thermal degradation of carbohydrate polymers in amorphous states: a physical study including colorimetry. Food Chem. 96 (3), 402–410. DellaValle, G., Boché, Y., Colonna, P., Vergnes, B., 1995. The extrusion behaviour of potato starch. Carbohydr. Polym. 28 (3), 255–264. Eriksson, L., Johansson, E., Kettaneh-Wold, N., Wikström, C., Wold, S., 2008. Design of Experiments: Principles and Applications, third revised and enlarged ed. Umetrics, Sweden, Umeå. Ferry, J.D., 1980. Viscoelastic Properties of Polymers, third ed. John Wiley and Sons, New York.

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