Thermal characteristics and state diagram of extruded instant artificial rice

Thermochimica Acta 593 (2014) 50–57

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Thermal characteristics and state diagram of extruded instant artificial rice Heny Herawat a,b , Feri Kusnandar b , Dede R. Adawiyah b , Slamet Budijanto b , Mohammad Shafiur Rahman c, * a b c

Indonesia Center for Agricultural Post Harvest Research and Development, Tentara Pelajar Road No. 12, Cimanggu, Bogor, Indonesia Department of Food Science and Technology, Faculty of Agricultural Engineering and Technology, Bogor Agricultural University, Bogor, Indonesia Department of Food Science and Nutrition, College of Agricultural and Marine Sciences, Sultan Qaboos University, P. O. Box 34, Al-Khod 123, Oman

A R T I C L E I N F O

A B S T R A C T

Article history: Received 28 April 2014 Received in revised form 12 August 2014 Accepted 14 August 2014 Available online 17 August 2014

Instant artificial rice was developed by extrusion method using corn flour, glycerol monostearate (GSM), and glucomannan and guar gum. Moisture sorption isotherm and thermal characteristics of the artificial rice with glucomannan and guar gum were measured and modeled to develop different regions of a state diagram. The freezing point, glass transition, and solids-melting were measured and modeled by Chen’s model, modified Gordon–Taylor model, and Flory–Huggins model, respectively. The ultimate maximal-freeze-concentration conditions were found as (Tm0 )u (i.e., annealed end glass transition temperature for the sample with moisture 0.40 g/g sample) equal to 8.3  C and (Tg000 )u (i.e., annealed onset glass transition temperature for the sample with moisture 0.40 g/g sample) equal to 8.4  C, and the characteristic solids content, Xs0 as 0.76 g/g sample (i.e., un-freezable water, Xw0 equal to 0.24 g/g sample). Similarly the characteristic glass transition temperature, Tgiv (i.e., intersection of vertical line passing through Tm0 and glass transition line above Xs0 ) was estimated as 29.8  C. ã 2014 Elsevier B.V. All rights reserved.

Keywords: Artificial rice Freezing point Glass transition Solids-melting Maximal-freeze-concentration Relaxation

1. Introduction Artificial rice could be developed as a new value added product using different types of grains with added nutrients and functionalities. The terms of artificial rice, enriched rice, rice analogs or reformed rice were introduced by several authors [1–4]. The developed products could avoid deficiency in nutrients as compared to the natural rice without major changes in consumers’ dietary habits. The main advantages could be the easy process of developing instant rice and the possibility of incorporating different nutrients with desired textural characteristics. In addition, it could be developed using wastes or byproducts with low cost and utilizing energy efficient process, such as extrusion [5]. A number of studies are reported on the development of artificial rice [4–13]. Instant rice can be prepared quickly within 2–15 min with simple procedures or steps. Luh et al. [14] stated that quick cooking could take only 5–15 min, however good ones should take only 5 min. Roberts [15] stated that a quick cooking rice is expected to

* Corresponding author. Tel.: +968 241 41273; fax: +968 244 13418. E-mail addresses: shafi[email protected], shafi[email protected] (M.S. Rahman). http://dx.doi.org/10.1016/j.tca.2014.08.017 0040-6031/ ã 2014 Elsevier B.V. All rights reserved.

be ready to serve within 5–15 min. Once prepared (i.e., cooked) the rice must comply with the characteristics of paddy rice in terms of its taste, aroma, and texture. Wang et al. [5] developed extrusion-cooked instant rice with emulsifiers (glycerol monostearate, soybean lecithin, sodium stearoyl lactylate), gums (gum Arabic, sodium alginate) and sticky rice. They assessed their quality parameters (i.e., bulk density, water soluble index, a-amylase sensitivity, water hydration rate and water soluble carbohydrate) in order to optimize the processing conditions. Mishra et al. [6] reviewed formulations (i.e., ingredients) of instant artificial rice and their processing methods. The important aspect of formulation is the fortifications of color, flavors, vitamins, nutrients, and antioxidant in order to ensure its value addition; and it is important to determine the stability of fortified components in the artificial rice matrix during processing and its storage. Recently, a great deal of research has been reported on the utility of glass transition to determine foods’ stability and their ingredients [16–18]. The glass transition was also related to the molecular mobility, chemical reaction and shelf life of foods [16,17,19,20]. The possible regions of extrusion, drying and freezing process can be easily visualized in the state diagram (i.e., a map presents different phases and states as a function of solids or water content and temperature) [16]. The effect of aging on the glass transition and enthalpy relaxation of waxy rice starch [21,22] and native and

H. Herawat et al. / Thermochimica Acta 593 (2014) 50–57

gelatinized starch [23] was reported in the literature. Sablani et al. [18] measured the glass transition and freezing point of rice by modulated DSC and cooling curve methods, respectively. In the literature, relatively low information is available on the thermal characteristics of starch based products, such as rice and instant artificial rice. Thus the objectives of this research were to study thermal characteristics (i.e., freezing, glass transition, solids-melting and maximal-freeze-concentration condition) using different types of DSC as initial data to develop state diagram of extruded artificial rice. Finally different components of the state diagram were also developed in order to visualize different phases and states of the artificial instant rice as a function of temperature and solids contents (i.e., moisture) so that it could be used to determine the stability of artificial rice during its processing and storage. In addition the isothermal protocol proposed by Rahman and Al-Saidi [24] was also tested for measuring glass transition of biomaterial consisting stiff molecular polymer. 2. Materials and method 2.1. Materials Corn flour was made from corn (i.e., White Srikandi variety) released by IAARD (Indonesia Agency for Agricultural Research and Development, Bogor, Indonesia). In order to produce the artificial rice, corn flour, tapioca starch (Tapioca Gunung Agung Merck, Indonesia), guar gum (Type V-62, Spectrum, Pakistan), glycerol monostearate (GMS) (Type EN 38098, Danisco Malaysia, Penang, Malaysia) were used. Indonesian commercial rice (i.e., Purnama, Cianjur, Indonesia) were purchased from the local super market. Sodium hydroxide (NaOH), magnesium chloride (MgCl2), magnesium nitrate Mg(NO3)2, sodium chloride (NaCl), and potassium sulfate (K2SO4) were purchased from Merck, Darmstadt, Germany. Potassium chloride (KCl) was purchased from Cica Kanto Chemical Co., Tokyo, Japan and barium chloride (BaCl2) from Showa Chemical Co., Tokyo, Japan.

fraction and mass fractions of water, ash, fat and protein). The fiber was determined by enzymatic method as proposed by Asp et al. [27]. 2.4. Moisture sorption isotherm The moisture sorption isotherm was measured by isopiestic method [28–30]. The ground artificial rice flour and the commercial rice flour were placed in a desiccator maintained dry environment with calcium oxide. The samples were equilibrated for two weeks at 30  C. 2 g of dry samples were stored in different desiccators maintained at different relative humidity environments at 30  C. The specific relative humidity in the desiccators were created using saturated salt solution placed at the bottom of the desiccators (i.e., under the metal mesh). The saturated condition was created by maintaining a layer of salt crystals at the bottom. The salts used to prepare solution for maintaining relative humidity were: sodium hydroxide (NaOH), magnesium chloride (MgCl2), potassium carbonate (K2CO3), magnesium nitrate Mg(NO3)2, sodium chloride (NaCl), potassium chloride (KCl), barium chloride (BaCl2), and potassium sulfate (K2SO4). The water activity values of the above saturated salt solutions are presented in Table 1. Samples were equilibrated at 30  C until a constant mass was achieved. The moisture contents of the equilibrated samples were determined by gravimetrically using an oven at 105  C for at least 18 h of drying. The moisture sorption isotherms were modeled with Brunauer–Emme–Teller (BET) [31] and Guggenheim–Andersen–de Boer (GAB) [32]. BET equation is: Mw ¼

Corn flour was prepared by dry mill method according to Johnson [25]. In preparing artificial rice, 2 kg of dough was prepared with 1.74 kg corn flour, 200 g tapioca starch, 40 g GMS, 19.2 g glucomannan and 0.8 g guar gum. First dough was prepared by mixing 1 kg of distilled water to guar gum followed by addition of other ingredients and mixed for 5 min. The dough was then fed into twin screw extruder (Twin Screw Bex 225-6, Berto Industries, Jakarta, Indonesia) and run at 96  C and 168 rpm. The extruded rice was then treated with steam (Tea Steaming Machine, Terada Seisakusho, ED-4K-SP, Shizuoka, Japan) in a closed chamber (5 min) followed by convection air drying (Tea Drier Oven, Terada Seisakusho, Shizuoka, Japan) at 70  C for 6 h. In order to decrease the cooking time of artificial rice, the extruded rice was further treated with steam to increase the degree of gelatinization. The artificial rice was then ground into powder and desiccated over calcium chloride. The samples containing different levels of unfreezable water were prepared by adsorption over saturated salt solutions in desiccators. The samples with freezable water were prepared by adding predetermined amount of water into the dry powder and equilibrated at 4  C for 24 h. 2.3. Chemical analysis The chemical analysis of the samples for moisture, ash, fat and protein were performed according to the AOAC [26], while carbohydrate was determined by difference (i.e., total mass

Mb Baw ð1  aw Þ½1 þ ðB  1Þaw 

(1)

where Mb is the BET monolayer water content (g/100 g dry-solids), aw is the water activity, and B is a constant related to the net heat of sorption. Moisture sorption isotherm data within water activity of 0.05 and 0.55 were also fitted to the theoretical BET model to determine the monolayer moisture content [29]. GAB equation is: Mw ¼

2.2. Sample preparation

51

Mg CKaw ½ð1  Kaw Þð1  Kaw þ CKaw Þ

(2)

where Mg is GAB monolayer moisture content (g/100 g dry-solids), C is related to the heat of monolayer sorption, and K is related with the heat of multilayer sorption. 2.5. Thermal characteristics 2.5.1. DSC measurement for the samples containing unfreezable water Thermal characteristics were measured by DSC (Q20) and modulated DSC (Q1000) (TA Instruments, New Castle, DE, USA) attached with mechanical refrigerated cooling system capable to cool down to 90  C. The instrument was calibrated for heat flow and temperature using distilled water (melting point, mp = 0  C; DHm = 334 J/g) and indium (mp = 156.5  C; DHm = 28.5 J/g). Aluminum pans of 30 mL with lid were used in all experiments with an empty sealed pan as reference, and nitrogen at a flow rate of 50 mL/min was used as a carrier gas.

Table 1 Proximate analysis of artificial and commercial samples. Content (g/100 g sample)

Artificial rice

Commercial rice

Moisture Ash Fat Protein Carbohydrate Dietary fiber

10.82 0.52 0.59 6.34 81.75 6.66

13.21 0.56 3.41 11.66 71.16 0.13

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H. Herawat et al. / Thermochimica Acta 593 (2014) 50–57

In the case of linear heating in DSC, sample of 3–5 mg was placed in an aluminum pan and then sealed with lid. The sealed pan with samples were cooled to 90  C at 5  C/min, and then kept for 10 min. It was then scanned from 90 to 250  C at a heating rate of 10  C/min and 50  C/min, and thermal characteristics were determined from the heating thermogram. A shift in the thermogram line can be considered as glass transition. In the case of isothermal relaxation, sample was cooled to 90  C at a cooling rate 5  C/min and kept for 5 min [24]. The cooled sample was then heated at 20  C/min to different temperatures from 20 to 100  C at 10  C increment (i.e., each sample at a time) and kept at that temperature isothermally. The heat flow at isothermal condition was recorded as a function of time (i.e., thermal relaxation curve). Initial slope of the thermal relaxation curve (i.e., enthalpy versus time plot) was determined considering initial linear part, and then the slope was plotted as a function of temperature. A shift in the plot of slope versus temperature was considered as the glass transition [24]. In the case of modulated DSC, the sample preparation and calibration procedures were the same as described in the DSC. Samples of around 3–5 mg were cooled to 90  C at 5  C/min, and equilibrated for 10 min. Following equilibration, the samples were scanned from 90  C to 250  C at a constant rate within 5  C/minwith a modulation of 0.50  C amplitude and 40 s period of modulation. Thermograms were analyzed from their total, reversible and nonreversible heat flow. The glass transition could be identified as a shift in thermogram line (vertical) in the reversible heat flow line. For all experimental measurements, the average value and standard deviation of 3 replicates were obtained. The glass transition was predicted by Rahman [33] model, which was proposed based on the modified Gordon–Taylor (RGT) model as: T gm

X s T gs þ kc X w T c ¼ X s þ kc X w

(3)

where Tgm, and Tgs are the glass transition temperatures of the mixture and dry-solids, and Tc is extrapolated temperature of the glass line (i.e., glass transition versus solids mass fraction) intersecting at zero solids ( C), respectively; Xw and Xs are the mass fractions of water and solids, and kc is the RGT model parameter. In the original Gordon–Taylor model Tw (i.e., glass transition of water) is considered as Tc. In the above equation, Tc is considered as critical temperature, and it is related to Tgiv (i.e., glass transition at maximal-freeze-concentration, Xs0 as defined by Rahman [33]). The value of Tgiv was determined from the intersection point of the glass transition line and a vertical line through Xs0 . In the Eq. (3), the value of Tc can be estimated using Eq. (4) [34]: 0 T c ¼ T iv g ð1  X s Þ

(4)

This correction in Tgw was needed since intercept of the original Gordon–Taylor equation to the y-axis is now shifted from Tgw (i.e., glass transition of water) to Tc (i.e., critical temperature) [33,34].

2.5.2. DSC measurement for the sample containing freezable water A different procedure was used for high water content samples with freezable water (total water, freezable and unfreezable, Xwo: 0.20–0.98 g/g sample). A 3–5 mg sample was placed in a sealed aluminum pan then cooled to 90  C at 5  C/min, and then maintained at this temperature for 5 min. The sample was then scanned from 90  C to 250  C, at a rate of 10  C/min, in order to determine freezing point and apparent maximal-freeze-concentration temperature [(Tm0 )a and (Tg000 )a], and solids-melting point. Higher temperature used in this protocol caused leaks or broken pans, and it was observed at end of the experiments. However, it was noticed that the leaks were observed above or close to 100  C

(i.e., boiling point of water). For this reason, solids-melting endotherms were not considered or analyzed further, and only freezing endotherms were analyzed. Selected data points are replicated 3 to 4 times in order to see the variability in the experimental measurement. In the case of annealed maximal-freeze-concentration temperature [(Tm0 )n and (Tg000 )n], sample at moisture content 0.40 g/g sample (i.e., solids 0.6 g/g sample) was cooled as above and scanned from 90  C with annealing at [(Tm0 )a  1] for 30 min as recommended earlier by Al-Rawahi et al. [35], then annealed maximal-freeze-concentration temperatures (Tm0 )n and (Tg000 )n were determined. The use of annealing conditions allowed maximum formation of ice before the second heating cycle. The ultimate maximal-freeze-concentration (Xs0 ) was determined from the intersection point of the extended freezing curve by maintaining the same curvature as Chen’s model (as discussed later) and drawing a horizontal line passing through the ultimate (Tm0 )u (average value of (Tm0 )n from 3 replicates, determined from the samples with solids content 0.6 g/g sample). Finally Xs0 was determined from the x-axis by drawing a vertical line passing through the intersection point as mentioned above. The freezing endotherm was characterized by maximum slope, peak and enthalpy for melting of ice during heating cycle. The initial or equilibrium freezing point was considered as the maximum slope in the ice melting endotherm [36]. Chen’s [37] model based on the extended ideal Clausius–Clapeyron equation was used to predict the freezing point of artificial rice [34]: " # b 1  X 0s  BX 0s d ¼  ln (5) lw 1  X 0s  BX 0s þ EX 0s where d is the freezing point depression (Tw-TF), TF is the freezing point of food ( C), Tw is the freezing point of water ( C), b is the molar freezing point constant of water (1860 kg K/kg mole), lw is the molecular weight of water, Xs0 is the initial solids mass fraction before freezing (g/g sample), B is the unfreezable water (g/g dry-solid), and E is the molecular weight ratio of water and solids (lw/ls). The values of B and E were estimated directly from Eq. (5) by non-linear regression using experimental data for freezing points. The solids-melting peak was analyzed as onset, maximum slope, peak, end and enthalpy of the solids-melting endotherm. The latent heat of fusion of ice or solids-melting was determined from the area of the endotherm (i.e., peak). Each data point was replicated 3 times. The melting point of a polymer in diluent was modeled by Flory–Huggins equation as [17]:    1 1 R Vu  ¼ (6) ðe  xe2w Þ Tp Ts DH u V w w where, Tp and Ts are the peaks of melting temperature for the polymer with diluent, and pure polymer (i.e., only dry solids) (K), R is the gas constant (8.314 J/g mol K), DHu is the heat of fusion for repeated polymer units in the diluent (J/g), Vw is the molar volume of the diluent (m3/g mol), Vu is the molar volume of polymer unit (m3/g mol), ew is the volume fraction of the diluent, and x is the Flory–Huggins polymer-diluent interaction parameter, respectively. The volume fraction of water was calculated from the following equation [17]:

ew ¼

X w =rw X w =rw þ X s =rs

(7)

where, Xw is the mass fraction of water (wet basis, g/100 g sample), rw is the density of water (kg/m3), Xs is the solids content (g/100 g sample), and rs is the density of dry-solids (kg/m3), respectively. The density of dried artificial rice was considered as 1500 kg/m3 (i.e., density of starch) [30].

H. Herawat et al. / Thermochimica Acta 593 (2014) 50–57 Table 2 Moisture sorption isotherm data of artificial and commercial rice. Salt used for creating relative humidity

Sodium hydroxide Magnesium chloride Potassium carbonate Magnesium nitrate Mg(NO3)2 Sodium chloride Potassium chloride Barium chloride Potassium sulfate

Water activity at 30  C

0.076 0.324 0.432 0.514 0.751 0.836 0.897 0.971

for evaluating the amount of strongly bound water to the specific polar sites in dried foods. The BET monolayer values were 5.9 g/100 g dry solids for cassava starch [39] and 3.1–9.7 g/100 g dry-solids for different varieties of rice [18]. The values observed in this study are within the range of reported literature values. BET model is not valid for the complete moisture isotherm, thus GAB model could be used to predict the moisture sorption isotherm within the whole range.

Moisture content (g/100 g dry solids) Artificial rice

Commercial rice

2.3 6.6 8.6 9.8 12.4 15.2 18.8 27.7

5.3 9.7 11.5 12.7 15.8 18.1 20.9 28.8

53

3.2. Thermal characteristics Fig. 1A shows the DSC thermogram of the artificial rice containing moisture 2.0 g/100 g sample at heating rate of 10  C/min. A sharp decrease in the heat flow at lower temperature indicated a continuous disordering in the polymeric molecules with the increasing temperature, while an ordering in the molecule was observed at higher temperature instead of showing any endothermic melting. A small curvature could be due to the interactions of the phases at the end of disordering. However, thermogram for the samples with moisture contents at or above 5 g/100 g sample showed an endothermic peak for solids-melting without indicating glass transition (i.e., no shift or change in slope in the thermogram line) (Fig. 1B). The varied thermal characteristics, at moisture contents 2.0 and 5.0 g/100 g sample, indicated the molecular complexity of the composite artificial rice prepared by the extrusion process. This could be due to the complex time dependent thermal relaxation in the matrix. These types of complexity were also reported in the literature in the cases of complex carbohydrate (i.e., starch, fiber, and cellulose) and protein based foods as reviewed by Rahman and Al-Saidi [24]. In order to increase the sensitivity to trace the glass transition, samples were also scanned at 50  C/min. At higher heating rate 50  C/min, sample (moisture content: 2.0 g/100 g sample) showed a shift (as marked

2.6. Statistical analysis Average and standard deviations of selected data points are presented. The model parameters of sorption isotherm (Eqs. (1) and (2)), glass transition (Eq. (3)), freezing point (Eq. (5)), and solids-melting (Eq. (6)) were estimated using SAS non-linear regression [38]. 3. Result and discussions 3.1. Proximate analysis and moisture sorption Proximate compositions and moisture sorption isotherm data of the commercial and artificial rice are presented in Tables 1 and 2. The BET and GAB model parameters are presented in Table 3 with their mean square error. The BET monolayer values for the artificial and commercial rice were 4.45 and 6.54 g/100 g dry-solids, respectively. BET-monolayer is considered as an effective method

Table 3 BET and GAB model parameters for moisture sorption isotherm of artificial and commercial rice. Sample

BET model (aw rang: 0.076–0.514) B

Mb

p value

MSE

C

K

Mg

p value

MSE

Artificial rice Commercial rice

1.10  1067 2.32  1044

4.45 6.54

p < 0.005 p < 0.01

2.44 1.87

2.52  1065 5.53  101

0.86 0.76

4.45 7.14

p < 0.0001 p < 0.0001

2.20 2.16

GAB model (aw rang: 0.076–0.971)

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Table 4 Thermal transition measurements of samples containing unfreezable water of artificial rice by MDSC. Xs

Tgi ( C)

Tgp ( C)

Tge ( C)

DCp (J/kg K)

Tmi ( C)

Tmm ( C)

Tmp ( C)

Tme ( C)

DH (kJ/kg)

0.98a 0.98b 0.98 0.95 0.90 0.85 0.80

74.2 10.7 10.5 10.7 10.7 10.4

92.3 (7.4) 13.7 (0.2) 13.0 (0.1) 13.6 (0.2) 13.3 (0.2) 13.2 (0.5)

123.8 (7.3) 16.7 (0.1) 16.6 (0.1) 16.8 (0.1) 16.8 (0.0) 16.8 (0.4)

976 (84.9) 415 (9.3) 319 (9.1) 334 (31.6) 367 (16.1) 394 (22.2)

N 114 (16.6) 71 (2.9) 57 (7.5) 69 (21.0) 86 (26.7)

N 123 (15.2) 95 (4.2) 78 (11.0) 84 (18.5) 95 (21.8)

N 141 (10.5) 118 (0.9) 104 (12.1) 101 (10.1) 103 (9.5)

N 161 190 187 178 169

N 75 (57.9) 124 (17.6) 156 (34.1) 234 (41.3) 246 (22.9)

(4.9) (0.2) (0.1) (0.2) (0.1) (0.3)

(6.4) (3.7) (7.8) (11.8) (6.3)

N: Not detected. a DSC method (heating rate: 10  C/min). b DSC method (heating rate: 50  C/min).

G) without any endothermic peak, and this could be apparently considered as glass transition (Fig. 1C). However, there could be a possibility of spreading the solids-melting peak (i.e., slow relaxing stiff molecules) due to fast heating rate, since the solids-melting endothermic peak was absent. In addition, the higher (i.e., nearly double) specific heat change at this transition as compared to the modulated DSC data indicated the possibility of spreading enthalpy over the transition (Table 4). However, in the cases of the samples at or above moisture content 5.0 g/100 g sample, the shift for glass transition was absent even at higher heating rate, but an endothermic peak was observed due to solids-melting (i.e., fast relaxing flexible molecules at higher moisture) (Fig. 1D). This phenomenon could also be explained from the observation of Bulut and Schick [40] for waxy maize starch. Using modulated DSC, they observed an intermediate phase (i.e., rigid amorphous) between amorphous and crystalline structure. The absence of a shift (i.e., characteristic glass transition) in conventional DSC indicated the existence of a rigid amorphous fraction of starch (Fig. 1C). It was likely that the same phenomenon was present in Fig. 1D, but existence of excess plasticizer hided (i.e., override) the glass transition. Since it was difficult to trace the glass transition by conventional linear heating, isothermal relaxation technique and modulated MDSC were used. Fig. 2 shows the initial slope of the relaxation curve as a function of temperature at different moisture

contents. The glass transition temperatures were determined from the point G as shown in Fig. 2A–C. An improved sensitivity was observed since this method considered combined time dependent relaxation of thermal conductivity, porosity, and nature of contacts in the particles, instead of considering only instantaneous relaxation in specific heat in the case of conventional linear heating method. Fig. 2D shows that the onset of glass transition increased with the increase in solids contents (i.e., decreasing water content). The glass transition was modeled by Rahman’s model modified from Gordon–Taylor equation [34]. The characteristic temperature Tgiv was estimated from the intersection of the glass transition line and a vertical line passing through Xs0 = 0.76 (as discussed later) as proposed by Rahman [33]. From Fig. 2D, Tgiv was found as 29.8  C. The values of Tgiv was observed as 68.0  C for starch (Xs0 = 0.70) and 34.0  C (Xs0 = 0.80) for gelatin, respectively [34]. The characteristic temperature Tc was estimated as 7.0  C from Eq. (4). In the case of gelatin, Rahman et al. [34] observed Tc value as 6.8  C. The model parameters Tgs and kc of Eq. (3) were estimated as 75.5  C and 6.4 for artificial rice, whereas Rahman et al. [34] observed as 153.7  C and 17.3 for gelatin, respectively. The lower value of kc for artificial rice as compared to gelatin indicated lower plasticization by water (i.e., hydrogen bond did not interact with polymeric chain), which was also evident from the solids-melting as discussed later.

Fig. 2. Plot of the initial slopes of the isothermal relaxation curves for the artificial rice as a function of relaxation temperature. A: Moisture content: 2.0 g/100 g sample, B: moisture content: 10.0 g/100 g sample, C: moisture content: 20.0 g/100 g sample, D: glass transition temperature as a function of solids mass fraction (Series 1: experimental data, Series 2: modified Gordon–Taylor model).

H. Herawat et al. / Thermochimica Acta 593 (2014) 50–57

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Table 5 Thermal transition measurements of artificial rice containing freezable water. Xs

Tg0 ( C)

Tm0 ( C)

TF ( C)

(DH)i (kJ/kg)

Tmi ( C)

Tmm ( C)

Tmp ( C)

Tme ( C)

(DH)s (kJ/kg)

0.80 0.75 0.70 0.65 0.60a 0.60 0.55 0.50 0.40 0.30 0.20 0.10

5.2 (0.6) 9.2 (0.6) 9.3 9.1 (0.2) 8.3 (0.4) 9.0 (0.1) 9.5 (0.4) 9.6 (0.6) 9.1 7.2 (0.7) 5.7 6.1 (1.3)

4.7 (0.2) 7.0 (0.4) 6.9 7.9 (0.4) 8.4 (0.3) 7.4 (1.1) 8.4 (0.3) 9.1 (0.6) 6.7 5.8 (0.8) 5.7 4.9 (0.4)

4.2 (0.5) 5.5 (1.0) 4.8 5.3 (0.5) 5.6 (0.1) 3.5 (0.5) 3.1 (0.2) 1.4 (0.5) 0.5 0.5 (0.0) 0.5 0.4 (0.0)

0.25 (0.03) 4.3 (3.7) 5.0 38.3 (3.0) 56.1 (4.7) 58.6 (8.9) 74.2 (1.9) 92.7 (12.5) 118.0 168.3 (13.5) 144.0 136.3 (2.9)

82 (0.9) 87 (6.8) 88 96 (3.1) 96 (2.3) 96 (1.8) 98 (1.6) 99 (0.8) 100 110 (9.9) 105 106 (6.1)

95 (1.2) 97 (2.8) 96 102 (1.3) 102 (0.9) 101 (0.7) 101 (0.6) 103 (1.4) 102 113 (11.7) 111 100 (2.8)

103 (3.1) 103 (0.9) 103 107 (2.3) 107 (1.3) 105 (3.9) 106 (1.7) 109 (2.2) 105 112 (7.8) 117 104 (1.7)

137 (3.8) 129 (10.7) 129 135 (2.9) 123 (3.1) 119 (6.2) 129 (1.3) 124 (0.9) 117 126 (3.3) 127 119 (1.3)

286 (33.2) 320 (37.9) 344 413 (10.3) 428 (29.3) 452 (50.8) 602 (5.6) 611 (15.8) 716 750 (27.8) 724 854 (32.7)

Note: (DH)i: enthalpy change at ice-melting; (DH)s: enthalpy change at solids-melting. Values in the parentheses are standard deviation of 3 replicates. a Annealed at Tm0  1 for 30 min.

The samples were also scanned with sensitive modulated DSC for different moisture contents. A typical total heat flow, reversible heat flow and non-reversible heat flow are shown in Fig. 3A–C, respectively. The glass transition is marked as G, and solids-melting are marked as S. The glass transition temperature was determined from the shift (marked as G) in the reversible heat flow as 10.7  C (Table 5). Similarly in the case of waxy maize starch, Bulut and Schick [40] observed a glass transition for an amorphous part at around 40  C, which took place as soon as excess water was introduced at room temperature. They also observed another glass transition for rigid amorphous phase, which was parallel to the gelatinization. The rigid amorphous fraction was mobilized as crystallites melted. In addition, modulated DSC only traced lower glass transition, which did not plasticize with increasing water. In many food materials, two glass transitions were observed, one at lower temperature and another one at higher temperature close to the solids-melting [36,41]. As mentioned above, the observations of Bulut and Schick [40] for starch could explain the two stages of glass transition of artificial rice. However, in this study the glass transition for rigid amorphous phase could not be clearly traced by modulated DSC, but it was observed in the case of isothermal relaxation in conventional DSC. Solids-melting peak was characterized from the non-reversible

heat flow as shown in Fig. 3C. Table 5 shows solids-melting characteristics as a function of solids content. The solids-melting peak temperature decreased exponentially with decreasing solids (i.e., increasing moisture) and melting enthalpy increased with the decreasing solids (i.e., with increasing moisture) (Table 5 and Fig. 3D). Similar results were also observed in the case of starch [42], coarsely ground rice kernels [43] and date-pits [44]. Fig. 3D presents the experimental values and predicted line from Flory–Huggins equation. The melting peak temperature decreased with decreasing solids (i.e., increasing moisture content) due to water sorption and plasticization. Considering Eq. (6), the values of (RVu/DHuVw) and x were estimated as 3.42  103 and 0.0088, respectively. The values (RVu/ DHuVw) and x were estimated as 1.9  103 and 0.5 for starch [45], and 2.3  103 and 0.0068 for date-pits [44]. Similarly the values of x were estimated as 2.2 for gelatin [34] and 0.48 for starch [34], respectively. The low value of x for artificial rice as compared to starch and gelatin indicated very low water-solids interaction to change the crystalline structure (i.e., molecular ordered) or inability to plasticize the polymeric chain. Similar structural behavior was also observed in the case of very compact structure of date-pits [44].

Fig. 3. MDSC thermogram of artificial rice containing unfreezable water content (moisture: 2 g/100 g sample). A: Total heat flow, B: reversible heat flow, C: non-reversible heat flow) and D: solids-melting peak as a function of solids content (Series 1: experimental data, Series 2: Flory–Huggins model).

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Fig. 4. DSC thermogram of artificial rice containing freezable water (moisture: 40.0 g/100 sample) with annealed at [(Tm0 )a  1] for 30 min. A: Complete thermogram, B: details of the ice-melting thermogram, C: freezing point as a function of solids content (Series 1: freezing point, Series 2: Tm0 , Series 3: Tg000 , Series 4: Chen’s model).

A typical DSC thermogram for the sample containing freezable water are presented in the Fig. 4. Two endothermic peaks were identified during heating cycle: one for melting of ice (marked as M) and another one for the solids-melting (marked as M) (Fig. 4A). The endothermic peak was enlarged in Fig. 4B in order to visualize the characteristics points. These are freezing point (marked as m), Tm0 (marked as b) and Tg000 (marked as a). Table 5 shows these data as well as characteristics of the solids-melting. Fig. 4C shows the freezing point and ultimate maximal-freeze-concentrated temperature [(Tm0 )u = -8.3  C and (Tg000 )u = 8.4  C]. The freezing point decreased with the increase of solids content (Fig. 4C). The Chen’s model parameters E and B were estimated as 0.0229 and 0.0496 g/g dry-solids, respectively. In the case of rice, Sablani et al. [18] determined the values of E and B as 0.0117 and 0.329 g/g dry-solids, respectively. The value of Xs0 was determined from the intersection (i.e., point a in Fig. 4C) of the extended freezing curve ‘ba’ by maintaining the similar curvature as Chen’s model (Eq. (5)) and a horizontal line (ca) passing through (Tm0 )u = 8.3  C. Finally Xs0 was read on the x-axis by drawing a vertical line passing through point ‘a’, as 0.76 g/g sample. The unfreezable water content can be estimated as (Xw0 = 1  Xs0 = 0.24 g/g sample) and the water in the right side of the vertical line passing through point ‘a’ did not show any freezable water (i.e., unable to form ice even at very low temperature). 4. Conclusion Thermal characteristics (freezing point, glass transition, solidsmelting and maximal-freeze-concentration condition) were measured by DSC to develop state diagram of formulated rice. It was difficult to trace the glass transition using conventional linearheating in DSC, while isothermal relaxation in DSC was able to determine the glass transition temperature. However, modulated DSC determined another glass transition at lower temperature, which did not plasticize with the increase in moisture content. The modified

Gordon–Taylor model parameters for predicting glass transition were estimated as 75.5  C (i.e., Tgs) and 6.4 (i.e., kc), while Chen’s model parameters E and B for predicting freezing point were estimated as 0.0229 and 0.0496 g/g dry-solids, respectively. The Flory–Huggins interaction parameter, x was estimated as 0.0088 from the solids-melting peak as a function of water content. The developed state diagram of artificial rice can be used to determine its phase or state changes as a function of temperature and moisture content, thus it could be helpful in determining the stability or reactivity of the product during storage. However, further studies need to be conducted to determine the stability of functional components (i.e., color and flavor compounds, vitamins, nutrients and antioxidants) within different regions of the state diagram. Acknowledgments The authors would like to acknowledge the support of Sultan Qaboos University toward this research in characterizing artificial rice and the Literacy Professional Development Project (LPDP) of Indonesia, Ministry of Finance for Inner Dissertation Funding and Indonesia Agency for Agricultural Research and Development for awarding a visiting scholarship to conduct this project at Sultan Qaboos University. References [1] T. Yoshida, T. Ojima, Process for Producing Enriched Artificial Rice (1971). US Patent No. 3628966. [2] D.A. Harrow, J.W. Martin, Reformed Rice Product (1982). US Patent No. 4325976. [3] H. Kurachi, Process of Making Enriched Artificial Rice (1995). US Patent No. 5403606 A. [4] S. Budijanto, D. Yulianti, Studi persiapan tepung sorgum dan aplikasinya pada pembuatan beras analog, Jurnal Teknologi Pertanian 13 (3) (2012) 177–186. [5] J.P. Wang, H.Z. An, Z.Y. Jin, Z.J. Xie, H.N. Zhuang, J.M. Kim, Emulsifiers and thickeners on extrusion-cooked instant rice product, J. Food Sci. Technol. 50 (4) (2013) 655–666. [6] A. Mishra, H.N. Mishra, P.S. Rao, Preparation of rice analogues using extrusion technology, Int. J. Food Sci. Technol. 47 (9) (2012) 1789–1797.

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