Modeling and optimization of red currants vacuum drying process by response surface methodology (RSM)

Food Chemistry 203 (2016) 465–475

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Modeling and optimization of red currants vacuum drying process by response surface methodology (RSM) Zdravko Šumic´, Anita Vakula, Aleksandra Tepic´, Jelena Cˇakarevic´, Jasmina Vitas, Branimir Pavlic´ ⇑ Faculty of Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia

a r t i c l e

i n f o

Article history: Received 1 October 2015 Received in revised form 11 February 2016 Accepted 16 February 2016 Available online 16 February 2016 Keywords: Ribes rubrum L. Vacuum drying Physico-chemical properties Optimization Response surface methodology (RSM)

a b s t r a c t Fresh red currants were dried by vacuum drying process under different drying conditions. Box–Behnken experimental design with response surface methodology was used for optimization of drying process in terms of physical (moisture content, water activity, total color change, firmness and rehydratation power) and chemical (total phenols, total flavonoids, monomeric anthocyanins and ascorbic acid content and antioxidant activity) properties of dried samples. Temperature (48–78 °C), pressure (30–330 mbar) and drying time (8–16 h) were investigated as independent variables. Experimental results were fitted to a second-order polynomial model where regression analysis and analysis of variance were used to determine model fitness and optimal drying conditions. The optimal conditions of simultaneously optimized responses were temperature of 70.2 °C, pressure of 39 mbar and drying time of 8 h. It could be concluded that vacuum drying provides samples with good physico-chemical properties, similar to lyophilized sample and better than conventionally dried sample. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction Red currants in Serbia are mostly found in natural habitats, especially humid mountainous areas such as Kopaonik environment. Due to the winsome taste and antioxidant properties, currants are highly appreciated fruit both in Serbia and in almost all world regions. Currants have significant energy value and they contain high amount of biologically active components beneficial for human health. Main components of currant dry matter are carbohydrates 9.2%, dietary fiber 4.2%, fats 1.7% and proteins 1.3% (National Food Institute Denmark, 2009). Red currants have unique content of Vitamin C and they are also rich in anthocyanin and phenolic compounds. These components have an important impact in human nutrition since they have proved to possess antioxidant properties (Denev et al., 2010; Drach, Narkiewicz-Michałek, Sienkiewicz, Szymula, & Bravo-Díaz, 2011; Padayatty et al., 2003; Szymanowska, Złotek, Karas´, & Baraniak, 2015). Vitamin C has a great influence on the most damaging radical species that are produced in the human body during life and it also provides series of other very important health benefits (El-Gendy, Aly, Mahmoud, Kenawy, & El-Sebae, 2010). Valuable components of red currants made them prevalent raw materials of processing industry. Currants can be used fresh, frozen, dried or made into jams or syrups.

⇑ Corresponding author. E-mail address: [email protected] (B. Pavlic´). http://dx.doi.org/10.1016/j.foodchem.2016.02.109 0308-8146/Ó 2016 Elsevier Ltd. All rights reserved.

Dried fruits take much less storage space and also have longer shelf-life than fresh or frozen fruits. Dried fruits also provide a good alternative to fresh fruit in sense of allowing out of the season fruits to be available throughout the year (Jokic´ et al., 2009; Šumic´, Tepic´, Vidovic´, Jokic´, & Malbaša, 2013). Drying process has been applied since ancient times and today is widely used for fruits and vegetables conservation. During the drying process water from the raw material is removed, thus preventing the growth of microorganisms and subsequent decay (Lewicki, 2006). Commonly used type of drying is conventional drying process. However, high temperature and oxygen presence during conventional drying, accelerate chemical reactions, which negatively influence quality indicators of dried products. Drying can be carried out on lower temperatures and with lower content of oxygen using vacuum drying process (Das, 2005). Beside advantages in terms of lower temperature and lower content of oxygen, vacuum drying process is also characterized by high drying rate and less energy usage, which directly influence on reducing process costs (Alibas, 2007; Zhangjing & Fred, 2001). In accordance with all these advantages, vacuum-drying is suitable technique for materials that are sensitive to high temperatures and also offers a great potential for preserving bioactive compounds during dehydration process (Joshi, Rupasinghe, & Khanizadeh, 2011). Response surface methodology (RSM) represents a collection of statistical and mathematical techniques and it is often used for development, improvement and optimization of various processes, where certain response is influenced by several variables (Basß &

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Boyacı, 2007; Bezerra, Santelli, Oliveira, Villar, & Escaleira, 2008). The use of RSM has been successfully utilized for optimization of vacuum drying of berry fruit such as cherries (Šumic´ et al., 2013) and blueberries (Šumic´, Tepic´, Jokic´, & Malbaša, 2014). Previously used central-composite experimental design consisted of two independent variables (temperature and vacuum pressure), while drying time was determined by equilibrium point and varied for each experimental run. Drying time was in that case ‘‘hidden” independent variable and its influence on responses was not determined. Berries have recently gained huge attention due to their specific chemical profile and health benefit potential. Since vitamin C, anthocyanins and phenolic compounds contained in berries, have good influence on human health, food manufacturers strive for products with preserved composition of these components. Recently, various drying procedures have been utilized for preservation of chokeberries in similar domain of drying temperatures (50–70 °C) (Samoticha, Wojdyło, & Lech, 2016), while Stéger-Má té et al. (2011) investigated effects of vacuum drying of black currants in the range of 40–60 °C. Since there are no many reports about vacuum drying of red currants, the main goal of this study was to optimize vacuum drying process of widely used berry fruit, Ribes rubrum. RSM was used for optimization of vacuum drying parameters and new experimental design with three independent variables (temperature, vacuum pressure and drying time) was employed. In order to preserve good quality characteristics of the dried product, influence of vacuum drying parameters on moisture content, water activity, rehydratation power, total color change, firmness, total phenols content, total flavonoids content, monomeric anthocyanins, ascorbic acid and antioxidant activity, determined by DPPH assay, was determined. 2. Materials and methods 2.1. Sample Red currants (R. rubrum L.) were collected near Kopaonik (Serbia) between June and July (2014). To ensure the same starting material and prevent potential deterioration of the samples during the experiment, samples were frozen after being purchased, and stored at
20 °C until drying. 2.2. Chemicals 1,1-Diphenyl-2-picryl-hydrazyl-hydrate (DPPH) and (-)catechin were purchased from Sigma Aldrich (Germany); Folin– Ciocalteu reagent and gallic acid were purchased from Merck (Germany). Vitamin C (J.T. Baker, Holland) was used as a standard for HPLC analysis. Samples, as well as standard substance, were dissolved/extracted in the solution of 3% m-phosphoric acid (Alfa Aesar, Germany) in 8% acetic acid (J.T. Baker, Holland). Ammonium-acetate solution (Centrohem, Serbia) was used as a mobile phase (0.1 mol/L; pH 5.1). All solutions were prepared in redistilled water of suitable quality for HPLC analysis. All other chemicals and reagents were of analytical reagent grade. 2.3. Drying procedure 2.3.1. Vacuum drying Drying was performed in a vacuum dryer prototype, described in detail by Šumic´ et al. (2013). Samples were uniformly arranged on the tray as a thin layer. Sample size was kept constant (between 370 and 380 g) for each experiment. Weight loss was recorded in 5 min intervals. Drying runs were performed at different pressures (30, 180 and 330 mbar), temperatures (48, 63 and 78 °C), according

to the Box–Behnken design experimental design given in Table 1. Drying times were 8, 12 and 16 h, depending on working conditions (temperature and pressure). 2.3.2. Lyophilization Lyophilization was performed in a lyophiliser, constructed and installed at the Department of Food Preservation, Faculty of Technology Novi Sad (Serbia). This drying facility includes drying chamber, vacuum pump and condensate collector. Vacuum chamber contains three trays with heaters, one beneath the other. Vacuum pump provides pressure in the chamber of 0.01 mbar and chamber is equipped with the condensate collector that reaches temperature up to
50 °C. System is equipped with sensors in trays and products, sensor of condensate collector and sensor for pressure in vacuum chamber. Program is managed by drying procedure control system (PLC) that registers pressure in vacuum chamber and temperature on the heater surface. The most relevant technical features relating to the device are the following:
40 to 40 °C working temperature range; sensor sensitivity ±0.3 °C; 500 g balance maximum load; 0.1 g balance resolution; 0.01–1000 mbar working pressure range, sensor sensitivity ±1. Sample was dried on
30 °C and on the pressure of 0.01 mbar. Samples were arranged uniformly in thin layers and sample size used for experiment was 200 g. Pressure was kept constant during process. 2.3.3. Conventional drying Convectionally drying was performed in experimental convective laboratory dryer. Drying facility is consisted of convective chamber with one tray for placing the samples. Temperature sensors are placed in the trays and the temperature controller is located on the front side of dryer. Four trays (440  290 mm) were placed in drying chamber in thin layer and 0.5 kg of fresh red currants was placed on each tray. Drying temperature was provided by the electric heater (6.4 kW). Other characteristics of the dryer were: 760 m3/h maximal air flow and constant atmospheric pressure. 2.4. Experimental design and statistical analysis The RSM was applied for evaluation of the effects of drying parameters and their optimization for various responses. Box– Behnken experimental design with three numeric factors on three levels was used. Design consisted of seventeen experimental runs with five replicates at the central point. Various parameters could affect vacuum drying process, but temperature and pressure could be distinguished as the most influential. In this work, independent variables used in experimental design were temperature (T, 48– 78 °C), vacuum pressure (p, 30–330 mbar) and drying time (t, 8– 16 h). Drying parameters were normalized as coded variables, so they can affect the response more evenly and the units of the parameters are irrelevant (Basß & Boyacı, 2007). Variables were coded according to the following equation:

X¼

ðxi
x0 Þ Dx

ð1Þ

Table 1 Experimental domain with natural and coded values of independent variables used in Box–Behnken design (BBD). Variable

Coded levels
1

0

1

63 180 12

78 330 16

Natural levels Temperature [°C] Pressure [mbar] Drying time [h]

48 30 8

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where X is the coded value, xi is the corresponding actual value, x0 is the actual value in the center of domain, and Dx is the increment of xi corresponding to a variation of 1 unit of X. The natural and coded values of independent variables are presented in Table 1. The response variables were fitted to a second-order polynomial model (Eq. (2)) which is generally able to describe relationship between the responses and the independent variables.

Y ¼ b0 þ

2 2 2 X X X bi X i þ bii X 2i þ bij X i X j i¼1

i¼1

2.9. Rehydratation power Samples were rehydrated by immersion of 2.0 g of chopped dried red currants in 50 mL of distilled water for 24 h. Rehydratation power of samples was obtained by measuring volume of soaked samples and results were expressed as percentage (%). 2.10. Total phenols content

ð2Þ

i
where Y represents the response variable, Xi and Xj are the independent variables affecting the response and b0, bi, bii and bij, are the regression coefficients for intercept, linear, quadratic and interaction terms. Analysis of variance (ANOVA) was used in order to evaluate model adequacy and determine regression coefficients and statistical significance. Treatment of multiple responses and selection of optimal conditions were based on desirability function D (Derringer, 1980). Statistical analysis was performed using RSM software Design-Expert v.7 Trial (Stat-Ease, Minneapolis, MN, USA). The results were statistically tested at the significance level of p = 0.05. The adequacy of the model was evaluated by the coefficient of determination (R2), model p-value and lack of fit testing. A mathematical model was established to describe the influence of single process parameter and/or interaction of multiple parameters on each investigated response. 3-D response surface plots were generated with the same software and drawn by using the function of two factors, keeping the others constant. 2.5. Moisture content Moisture content was determined by drying the samples at 105 °C until constant weight. Experiments were replicated three times for statistical purpose, and results were expressed as mean values.

Dried red currant samples were ground in a blender before the extraction. 10.0 g of ground sample was transferred to a volumetric flask and 50 mL of methanol, as extraction solvent, was added. Extraction was carried out for 24 h at the room temperature. The obtained extract was filtered under vacuum. Prepared extracts were placed into a glass bottles and stored to prevent oxidative damage until analysis. The content of total phenolic compounds in methanolic extracts was determined by Folin–Ciocalteu procedure (Kähkönen et al., 1999; Singleton & Rossi, 1965), using gallic acid as a standard. Absorbance was measured at 750 nm (6300 Spectrophotometer, Jenway, UK). Content of total phenolic compounds has been expressed as mg of gallic acid equivalent per 100 g of dry weight of dried red currants (mg GAE/100 g DW). Experiments were replicated three times and results are expressed as mean values. 2.11. Total flavonoids content Total flavonoids content was determined using aluminum chloride colorimetric assay (Harborne, 1984). Catechin was used for preparation of standard diagram and absorbance was measured at 510 nm. Results were expressed as mg of catechin equivalents (CE) per 100 g DW. All experiments were performed in triplicate, and results are expressed as mean values. 2.12. Monomeric anthocyanins content

2.6. Water activity Water activity was determined by placing approximately 2.5 g of chopped and dried red currants in the sample holder of a TESTO 650 (Germany) aw-meter, at 25 °C. aw values were recorded after equilibration. 2.7. Total color change The CIE L⁄a⁄b⁄ color coordinates were measured using MINOLTA Chroma Meter CR-400 (Minolta Co., Ltd., Osaka, Japan). The apparent (surface) color of the samples was measured in terms of L (degree of darkness), a (degree of redness and greenness) and b (degree of yellowness and blueness). Finally, the total color change between blank white (L⁄0, a⁄0 and b⁄0) and dried red currant samples (L⁄, a⁄ and b⁄) was determined according to Eq. (4):

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2   2 DE ¼ ½ðL0
L Þ þ ða0
a Þ2 þ ðb0
b Þ 

467

ð3Þ

Monomeric anthocyanins content (MA) in the samples was estimated using a VIS-spectrophotometer by the pH differential method reported by Bakar, Mohamed, Rahmat, and Fry (2009) with slight modifications (Dzomba, 2013). Two buffer systems, potassium chloride buffer, pH 1.0 (0.0025 M) and sodium acetate buffer, pH 4.5 (0.4 M), were used. Briefly, 400 ll of sample (diluted liquid extract) was added in 3.6 ml of corresponding buffer solutions and absorbance was measured against a blank probe at 510 and 700 nm. Absorbance (Ad) was calculated as:

Ad ¼ ðA510
A700 ÞpH

1:0


ðA510
A700 ÞpH

4:5

ð4Þ

Anthocyanin concentration in the extract was calculated and expressed as cyanidin-3-glycoside equivalent (CGE):

MA ¼

Ad  MW  DF  1000 Ma

ð5Þ

Samples were placed on the measure head of Chroma Meter and measurements of color were performed for all prepared samples. A standard white color was used for calibration. Experiments were replicated five times for statistical purpose.

where, Ad is difference in absorbance, MW is a molecular weight for cyanidin-3-glucoside (449.2 g/mol), DF is the dilution factor of the samples and Ma is the molar absorptivity of cyanidin-3-glucoside (26.900 M/cm). Results were expressed as mg of cyanidin-3glucoside equivalents per 100 g of DW (mg CGE/100 g DW).

2.8. Texture analysis

2.13. Ascorbic acid determination

Instrumental texture measurements were performed using a Texture Analyzer (TE32, Stable Micro Systems, UK). The shearing force of dried red currant was measured, using a knife blade. Texture analysis settings were the following: test speed – 2.0 mm/s; distance – 30 mm; load cell – 250 kg.

Chopped dried currants samples (2.5 g) were transferred to a 25 mL volumetric flask. 3% m-phosphoric acid in 8% acetic acid was subsequently added and the mass was mixed for 5 min. The flask was filled up to the volume and filtered. Activated carbon was added to the filtered solution in order to remove the color

Z. Šumic´ et al. / Food Chemistry 203 (2016) 465–475

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and the whole was filtered through filter paper (blue label) and a membrane syringe filter with diameter pore of 0.45 lm. The filtrate was used for HPLC analysis of vitamin C in the HPLC system (Agilent 1100 Series, USA) equipped with degasser, binary pump, C-18 column (150  4.6 mm; 5 lm particle size) and UV-DAD detector. Analysis was performed in isocratic mode. Mobile phase (0.1 mol/L ammonium-acetate) flow rate was 0.4 mL/min. Column temperature was set at 37 °C, working pressure was 25 bar and detection wavelength was 254 nm. All analyses were performed in triplicate. Content of vitamin C was expressed as mg of vitamin C per 100 g of dry weight of dried currants (mg/100 g DW). 2.14. DPPH assay Free radical scavenging activity of samples was determined using DPPH assay, previously described by Espín, Soler-Rivas, and Wichers (2000). A certain volume of diluted sample was mixed with 95% methanol and 90 lM 1,1-diphenyl-2-picryl-hydrazyl (DPPH) in order to obtain different final concentrations. After incubation on room temperature for 60 min, the absorbance was measured at 515 nm and result was expressed as radical scavenging capacity (RSC, %) which was calculated using following equation:

% RSC ¼ 100


ðAsample  100Þ Ablank

ð6Þ

where Asample is the absorbance of sample solution and Ablank is the absorbance of blank probe. Antioxidant activity was further expressed as inhibition concentration at 50% of RSC value (IC50). IC50 represents the concentration of test solution required to obtain 50% of radical scavenging capacity, expressed as mg per mL. All experiments were performed in triplicate, and results are expressed as mean values. 3. Results and discussion It has been reported that vacuum drying process of berry fruits could be successfully optimized using rotatable central-composite design with two independent variables (temperature and vacuum pressure) (Šumic´ et al., 2013, 2014). In these experiments, drying time was determined by equilibrium point which was defined as a difference in mass, less than 1.0 g, in the duration of 30 min, meaning that all experimental runs had different drying time. In these cases, drying time was ‘‘hidden” independent variable which influenced measured responses, while its influence could not be measured and defined. Drying time could have significant effect on the process, particularly on the quality of the dried product due to interaction with other independent variables, e.g. some sensitive compounds could be preserved, even if they are treated with increased temperature, if the time of contact is reduced. Therefore, this work represents a step further from previous experiments since drying time is added in experimental design as independent variable together with temperature and vacuum pressure. This increased number of experiments from 13 to 17 (5 replicates in central point was used in both designs) and provided determination and quantification of influence of drying time on physicochemical properties of dried red currants. Therefore, influence of drying temperature (48–78 °C), vacuum pressure (30–330 mbar) and drying time (8–16 h) on investigated responses physical (moisture content, aw – value, total color change, firmness and rehydratation power) and chemical (total phenolic content (TP), total flavonoids content (TF), monomeric anthocyanins content (MA), ascorbic acid content (AA) and antioxidant activity) properties was optimized using response surface methodology (RSM). Choosing of drying temperature and vacuum pressure levels was based on previous reports (Šumic´ et al., 2013), while middle level of drying

time was determined as time needed to reach equilibrium point by drying red currants on middle level of temperature and pressure. 3.1. Model fitting Experimental results of investigated responses (moisture content, aw – value, total color change, firmness, rehydratation power, total phenolic content (TP), total flavonoids content (TF), monomeric anthocyanins content (MA), ascorbic acid content and antioxidant activity) obtained under different vacuum drying conditions (temperature, pressure and drying time) using Box–Behnken experimental design, are presented in Table 2. Results were fitted to a second-order polynomial model (Eq. (2)) and multiple regression coefficients were generated for all responses, using method of least square approach (MLS). Regression coefficients and their statistical significance for each investigated response are summarized in Table 3, and analysis of variance (ANOVA) results are presented in Table 4. Model adequacy was estimated by descriptive statistics (coefficient of multiple determination and coefficient of variance) and Fisher’s test for the model and lack-of-fit. According to particularly high R2 for all models (R2 > 0.900), except total color change (0.890), rehydratation power (0.878), ascorbic acid (0.788) and IC50 value (0.896), all applied polynomial models were in accordance with experimental results (Table 4). Moreover, relatively low CV (10%) for most of the responses (Table 4), suggested good reproducibility of the investigated systems, since CV describes dispersion of the data and small values indicates low variation in the mean value. This was not the case with firmness (CV = 33.72%) and ascorbic acid content (CV = 36.20%), where particularly high CV indicated on high variation in the mean value. Complete information about the model adequacy could be provided by decision-making statistics for the model and lack-of-fit (Fisher’s test). According to statistically significant values of p-value (<0.05) for all investigated responses, except ascorbic acid content, it was possible to conclude that applied mathematical model provides proper representation of experimental results. Also, assumption of the constant variance was satisfied since lack-of-fit testing was insignificant (p > 0.05) for most of the responses (Table 4). However significant lack of fit for the firmness and ascorbic acid content indicated that variance is a model-dependent measure of the pure error (Myers, Montgomery, & Anderson-Cook, 2009) and mathematical models could not fit with the experimental results properly for these two responses. Since applied model could be satisfactorily applied to describe experimental data for majority of the responses, MLS was used for generation of regression equations and creation of 3-D response surface plots. However, equations obtained for firmness and ascorbic acid content could provide rather suspicious results and their usage is questionable (Myers et al., 2009). Therefore, step further of this work was integration of drying time as independent variable, since previous designs for vacuum drying of berry fruits used only temperature and vacuum pressure as independent variables, while drying time effect was hidden and could not be determined. On the other hand, design applied in this work provided determination and quantification of drying time effect on investigated responses. Since it significantly influenced responses by either linear, interaction or quadratic term, drying time should be investigated as independent variables in further vacuum drying experiments of fruit and vegetables. 3.2. Physical properties of dried red currants Moisture content (MC) in fresh red currant samples was 85.48%, which is similar with the results obtained by Djordjevic´, Rakonjac, Akšic´, Šavikin, and Vulic´ (2014), where it is reported that initial MC of the fresh red currants was 87.40%. Depending on drying condi-

Table 2 Box–Behnken experimental design with natural and coded vacuum drying conditions and experimentally obtained values of all investigated responses. Run

a b

Response

Temperature [°C]

Pressure [mbar]

Drying time [h]

Moisture content [%]

Water activity

DE [%]

Firmness [g]

Rehydratation power [%]

TP [mg GAE/100 g DW]

TF [mg CE/100 g DW]

MA [mg CGE/100 g DW]

AA [mg/100 g DW]

IC50 [mg/ mL]

63 (0) 63 (0) 78 (1) 63 (0) 63 (0) 48 (
1) 78 (1) 48 (
1) 63 (0) 48 (
1) 63 (0) 63 (0) 78 (1) 63 (0) 48 (
1) 78 (1) 63 (0)
30 78

180 (0) 30 (
1) 30 (
1) 180 (0) 330 (1) 330 (1) 180 (0) 30 (
1) 180 (0) 180 (0) 180 (0) 30 (
1) 180 (0) 330 (1) 180 (0) 330 (1) 180 (0) 0.01 1000

12 (0) 16 (1) 12 (0) 12 (0) 16 (1) 12 (0) 16 (1) 12 (0) 12 (0) 16 (1) 12 (0) 8 (
1) 8 (
1) 8 (
1) 8 (
1) 12 (0) 12 (0) 72 8

22.98 10.23 8.09 17.68 17.5 60.67 10.07 14.56 13.36 37.8 18.88 17.22 21.62 51.64 68.99 12.76 16.42 12.57 19.98

0.674 0.250 0.210 0.576 0.473 0.874 0.347 0.407 0.473 0.743 0.579 0.359 0.660 0.867 0.848 0.343 0.635 0.280 0.666

34.29 31.02 30.09 28.98 33.35 21.30 31.51 24.01 29.28 24.78 25.68 23.74 24.15 22.03 17.12 33.99 28.96 33.48 29.33

514.16 558.16 358.67 966.40 1943.23 89.15 1607.15 1165.91 1341.57 178.19 986.79 1066.28 741.29 78.22 113.51 3420.22 1082.77 2501.41 649.49

37.50 41.25 36.25 37.50 33.75 26.25 41.25 36.25 36.25 23.75 41.25 37.50 31.25 17.50 17.50 36.25 36.25 40.00 26.25

326.56 469.84 520.99 339.31 316.47 241.80 412.66 475.68 344.79 282.07 319.50 462.89 381.12 229.57 155.35 357.11 365.99 366.65 351.51

183.85 270.94 277.52 193.25 181.61 123.77 175.22 310.23 200.74 178.17 194.82 307.81 229.23 138.38 91.45 209.90 218.44 219.96 211.61

52.91 60.77 64.31 59.22 42.76 38.04 40.23 66.84 67.71 30.66 53.12 88.29 53.54 30.55 24.89 39.74 65.17 65.90 60.17

2.93 6.67 4.41 2.90 2.68 2.67 3.19 6.28 3.33 2.03 2.22 8.14 8.10 2.47 3.42 2.17 3.29 4.33 2.19

0.4398 0.2857 0.5217 0.4194 0.4979 0.4032 0.5946 0.3281 0.3758 0.3915 0.4243 0.3530 0.4601 0.4160 0.5183 0.6503 0.3836 0.6257 0.3758

Lyophilized sample. Conventionally dried sample.

Table 3 Estimated coefficients of the fitted second-order polynomial model for all response variables. Regression coefficient

Response Moisture content

a

a

Water activity a

b0

17.86

Linear b1 b2 b3


16.19a 11.56a
10.48a


0.164a 0.166a
0.115a

Cross product b12 b13 b23


10.36a 4.91a
6.79a

Quadratic b11 b22 b33

8.31a
2.16 8.44a

0.587

DE 29.44

Firmness a

a

Rehydratation power a

978.34

37.75

4.07a 0.23 4.20a

572.57a 297.72a 285.93a

5.16a
4.69a 4.53a


0.084a
0.052
0.071

1.65
0.07 1.01

1034.58a 200.29 593.29a

0.017
0.146a 0.045


2.62 0.53
2.43

14.36 265.79
332.66

Total phenolics content 339.23

a

Total flavonoids content a

Monomeric anthocyanins content a

Ascorbic acid

IC50

2.93

0.4086a

198.22

59.63

64.62a
98.06a 31.51a

23.53a
64.10a 4.88

4.67
16.14a
2.86

0.43
1.94a
0.95

0.0732a 0.0599a 0.0028

2.50 0.94 3.13

17.50
23.80 19.99

29.71a
35.18a 20.02a

1.06
4.77 9.93a

0.34
0.88 0.42

0.0134 0.0653a 0.0373


4.03 0.03
5.28a


1.12 60.78a
30.31


12.02 44.15a
17.69a


12.82a 5.43
9.47a

0.07 0.88 1.18

0.0851a
0.0178
0.0026

Z. Šumic´ et al. / Food Chemistry 203 (2016) 465–475

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 La Cb

Independent variable

Significant at 0.05 level.

469

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Table 4 Analysis of variance (ANOVA) of the fitted second-order polynomial model for TP, TF and IC50 value.

a b

Source

Sum of squares

DF

Mean square

F-value

p-Value

Moisture content Model Residual Lack of Fit Pure Error Cor Total R2,a = 0.979; CVb = 16.31%

5384.11 113.93 64.32 49.61 5498.03

9 7 3 4 16

598.23 16.28 21.44 12.40

36.76

<0.0001

1.73

0.2988

Water activity Model Residual Lack of Fit Pure Error Cor Total R2 = 0.961; CV = 11.68%

0.700 0.029 5.640  10
3 0.023 0.730

9 7 3 4 16

0.077 4.099  10
3 1.880  10
3 5.763  10
3

18.90

0.0004

0.33

0.8078

Total color change Model Residual Lack of Fit Pure Error Cor Total R2 = 0.890; CV = 9.06%

346.07 42.88 4.79 38.09 388.95

9 7 3 4 16

38.45 6.13 1.60 9.52

6.28

0.0121

0.17

0.9129

Firmness Model Residual Lack of Fit Pure Error Cor Total R2 = 0.936; CV = 33.72%

1.056  107 7.236  105 3.651  105 3.585  105 1.129  107

9 7 3 4 16

1.174  106 1.034  105 1.217  105 89629.72

11.35

0.0021

1.36

0.3752

Rehydratation power Model Residual Lack of Fit Pure Error Cor Total R2 = 0.878; CV = 12.05%

817.16 113.36 96.48 16.88 930.51

9 7 3 4 16

90.80 16.19 32.16 4.22

5.61

0.0166

7.62

0.0394

Total phenolics content Model Residual Lack of Fit Pure Error Cor Total R2 = 0.956; CV = 8.71%

1.420  105 6620.49 5323.65 1296.83 1.486  105

9 7 3 4 16

15780.41 945.78 1774.55 324.21

16.69

0.0006

5.47

0.0671

Total flavonoids content Model Residual Lack of Fit Pure Error Cor Total R2 = 0.973; CV = 7.32%

57256.49 1576.14 917.86 658.28 58832.63

9 7 3 4 16

6361.83 225.16 305.95 164.57

28.25

0.0001

1.86

0.2772

Monomeric anthocyanins content Model 4015.56 Residual 444.52 Lack of Fit 260.81 Pure Error 183.72 Cor Total 4460.09 2 R = 0.900; CV = 15.42%

9 7 3 4 16

446.17 63.50 86.94 45.93

7.03

0.0088

1.89

0.2720

Ascorbic acid content Model Residual Lack of Fit Pure Error Cor Total R2 = 0.788; CV = 36.20%

52.71 14.21 13.42 0.79 66.92

9 7 3 4 16

5.86 2.03 4.47 0.20

2.89

0.0881

22.51

0.0058

IC50 value Model Residual Lack of Fit Pure Error Cor Total R2 = 0.896; CV = 10.40%

0.130 0.015 0.012 3.032  10
3 0.140

9 7 3 4 16

0.014 2.085  10
3 3.855  10
3 7.580  10
4

6.73

0.0100

5.09

0.0751

Coefficient of multiple determination. Coefficient of variance [%].

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Fig. 1. Observed drying rate of red currants under vacuum on: (a) 30 mbar, (b) 180 mbar and (c) 330 mbar.

tions, MC in vacuum dried samples varied from 8.09 to 68.99%. Drying rates of red currants under vacuum on 30, 180 and 330 mbar are presented on Fig. 1. It could be seen that drying on increased vacuum pressure (330 mbar) results in rather slow drying kinetics and provides samples with rather high and unsatisfactory MC (Fig. 1c), while decrease of vacuum pressure (30 mbar) provides faster drying due to higher concentration gradient of water in red currants samples and atmosphere in the vacuum dryer (Fig. 1a). Drying rate on middle vacuum pressure level (180 mbar) highly depends on temperature and is still particularly high, when temperature is increased (Fig. 1b). The lowest MC was obtained at 78 °C, 30 mbar and 12 h, while the highest MC was obtained at 48 °C, 180 mbar and 8 h. MC was determined in red currant samples dried by lyophilization (
30 °C, 0.01 mbar and 72 h) and conventional drying (78 °C, atmospheric pressure and 8 h) and it could be seen that the lowest MC obtained by vacuum drying was significantly lower comparing to MC observed in lyophilized (12.57%) and conventionally dried red currants (19.98%) (Table 2). MC is responsible for the majority of deteriorative microbial reactions which influence directly on storage life of dried prod-

ucts. It is also very important quality indicator of dried products, so it is desirable to reduce the initial MC during drying. Influence of independent variables was expressed by p-values of the regression coefficients presented in Table 3. According to p-statistics, all linear, interaction and quadratic terms of independent variables exhibited significant influence on MC except quadratic term of vacuum pressure (Table 3). Linear terms of temperature and drying time exhibited negative influence on MC while linear term of vacuum pressure exhibited positive influence which is rather expected since mass transfer of water from fruit samples is increased on higher temperature and lower pressure, and more water evaporates on prolonged drying experiments. Positive influence of quadratic terms of temperature and drying indicates asymptotic behavior of decrease of MC with increase of these two variables, which could be seen on Fig. S-1 (Supplementary data). Interaction terms are particularly interesting, since it could be concluded that increase of temperature and decrease of pressure both causes decrease of MC, which is in accordance with mass transfer from fruit samples. This occurs because during vacuum drying, pressure is held so low that the water could be removed at considerably

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Table 5 Second-order polynomial equations with neglected insignificant coefficients for investigated response variables. Response

Second-order polynomial model equation

Mositure content Water activity Total color change Firmness Rehydratation power Total phenolics content Total flavonoids content Monomeric anthocyanins content Ascorbic acid content IC50

Y = 17.86
16.18X1 + 11.56X2
10.18X3
10.48X1X2 + 4.91X1X3
6.79X2X3 + 8.31X21 + 8.44X23 Y = 0.587
0.164X1 + 0.166X2
0.115X3
0.084X1X2
0.146X22 Y = 29.44 + 4.07X1 + 4.20X3 Y = 978.34 + 572.57X1 + 297.72X2 + 285.93X3 + 1034.58X1X2 + 593.29X2X3 Y = 37.75 + 5.16X1
4.69X2 + 4.53X3
5.28X23 Y = 339.23 + 64.62X1
98.06X2 + 31.51X3 + 60.78X22 Y = 198.22 + 23.53X1
64.10X2 + 29.71X1X2
35.18X1X3 + 20.02X2X3 + 44.15X22
17.69X23 Y = 59.63
16.14X2 + 9.93X2X3
12.82X21
9.47X23 Y = 2.93
1.94X2 Y = 0.4086 + 0.0732X1 + 0.0599X2 + 0.0653X1X3 + 0.0851X21

lower temperatures. Rapid warming and mass transfer provided by lower pressure and temperatures, allows quick water evaporation. The reduced boiling point at low pressure finds considerable practical application in the field of vacuum evaporation (evaporation under low pressure) (McCleary, 1987). This interaction of temperature and pressure with drying time could not be seen on previously used experimental designs for vacuum drying of berry fruits, since drying time was not used as independent variable (Šumic´ et al., 2013, 2014). Determination of regression coefficients in Eq. (3) using the MLS provided empirical model equation with neglected insignificant coefficients, which is able to describe effects of vacuum drying conditions on MC and predict its value on investigated experimental domain (Table 5). Microorganisms are the main causes of food spoilage. Their growth and development depend on the amount of available water. So, water removing during drying process influences directly and positively on microbiological stability of dried products. Water activity (aw) presents the key parameter of dried product sustainability. Knowledge of aw is very useful because of the fact that specific changes in aroma, color, flavor, texture, and acceptability of dried products have been related with relatively narrow aw ranges (Rockland & Nishi, 1980). The relationship between the moisture content of food and the relative water vapor pressure (p/p0) of the atmosphere in equilibrium with the material, can be used to compute the corresponding equilibrium relative humidity [ERH = 100(p/p0) = 100 aw] (Barbosa-Cánovas, Fontana, Schmidt, & Labuza, 2007). The dried fruits should, therefore, be kept in a aw range of 0.45–0.54 for freeze-, and 0.46–0.63 for convectively dried material (Šumic´ et al., 2013). Water activity of fresh red currants amounts 0.99 (Barbosa-Cánovas et al., 2007). Microorganisms usually grow best between aw values 0.98–0.99, while most microbes stop growing at aw < 0.90. Some fungi stop growing only at aw values as low as 0.62 (Raimbault, 1998). Water activity of fresh red currants was 0.905, while aw in vacuum dried samples varied from 0.210, obtained on 78 °C, 30 mbar and 12 h, and 0.874 obtained on 48 °C, 330 mbar and 12 h. The lowest aw was observed on same experimental point as the lowest moisture content, which is rather expected, since these parameters are in direct correlation. Sample obtained by lyophilization had similar aw (0.280), as the lowest aw observed in vacuum dried samples. However, conventionally dried sample had unsatisfactory aw (0.666), meaning that quality of this sample was rather low and would reduce its shelflife. According to statistical analysis all linear terms of vacuum drying parameters had significant influence on aw, which was negative for temperature and drying time, and positive for vacuum pressure (Table 3). Same phenomenon occurred in moisture content, confirming correlation of these two values. Negative effect of temperature-pressure interaction indicated that aw in dried samples will decrease if temperature and pressure both increase. Moreover, these effects could be observed on Fig. S-2 (Supplementary data), particularly that aw could be low even on increased

pressure, only if temperature is on higher level (78 °C). Mathematical model which could predict behavior of the aw value in investigated experimental domain is presented in Table 5. Color is one of the most important quality indicators of dried products. Out of all sensory properties of dried products, color has a major impact on customer acceptance and thus on the commercial value of products. Color affects the overall impression and it is considered as synonym of quality. It is desirable that dried products have specific, intensive and uniform color (NietoSandoval, Fernández-López, Almela, & Muñoz, 1999). However, color changing of products during a drying process is imminent. Reducing color changes at the same time means reducing undesirable enzymatic changes in dried products (Ahmed, Kaur, & Shivhare, 2002). Therefore, basic task is reducing total color change (DE) on minimum in order to obtain product with minimal color changes. In dried red currants, DE was between 17.12% and 34.29%. The lowest DE was observed on mild vacuum drying conditions (48 °C, 180 mbar and 8 h), however, this sample had rather low quality due to particularly high moisture content (68.99%). DE for most of the vacuum dried samples was lower than DE observed in lyophilized and conventionally dried sample (33.48% and 29.33%, respectively). According to statistical indicators (Table 3), only linear terms of temperature and vacuum pressure exhibited significant influence on DE which was positive in both cases. This could be explained that prolonged high temperature treatment causes degradation and change in red currant pigments (anthocyanins) (Fig. S-3) (Supplementary data). Therefore, in order to minimalize color change, vacuum dying must be performed on milder conditions (lower temperature and drying time) which is limited with unsatisfactory moisture content and aw in samples obtained on lower level of temperature and drying time and higher level of pressure. External stress, such as influence of temperature, during drying process causes solubilization of the cell walls, destruction of cell integrity and loss of firmness (Kunzen, Kabbert, & Gloyna, 1999). This affects negatively on physical and chemical properties of dried products. Since firmness is important physical characteristics of dried products that affects a lot on consumer acceptability, it is desirable for dried products not to be too fragile and firm (Šumic´ et al., 2013). Experimentally observed firmness in vacuum dried red currants varied between 78.22 and 3420.22 g. Lower firmness of dried fruit is often desirable, therefore, the lowest firmness was observed in sample dried on 63 °C, 330 mbar and 8 h, which are relatively mild drying conditions. On the other hand, firm samples were obtained when temperature is increased (3420.22 g obtained on 78 °C, 330 mbar and 12 h) and when lyophilization was applied (2501.41 g). According to results from Table 4, all linear terms of independent variables exhibited positive linear influence on firmness, which is also visible on Fig. S-4 (Supplementary data), since all surfaces were inclined towards higher level of all drying parameters. Moreover, significant positive effect of

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temperature-drying time and pressure-drying time interaction confirms this claim meaning that firmness with significantly increase when all three variables are on their higher levels (78 °C, 330 mbar and 16 h). Ability of the dried products for subsequent absorption of water i.e. rehydratation, is one of the important characteristics of these products. If the product is dried properly, it will be able to receive a significant amount of water during rehydration. Most of the dried products are rehydrated before usage, so it is recommended that dried product have good rehydration power, precisely because of consumer acceptability. Rehydratation power was only physical property of dried red currants which results did not fit well with second-order polynomial model due to significant lack-of-fit testing (Table 4). Since regression equations could be successfully used as predictors of these responses in investigated experimental domain only for responses with good model fitting, equation obtained for rehydratation power (Table 5) could provide rather suspicious results (Myers et al., 2009). Rehydratation power of vacuum dried red currants samples was between 17.50% and 41.25% (Table 2). Since higher rehydratation power of dried sample is desirable, it was experimentally obtained on 63 °C, 30 mbar and 12 h, 78 °C, 180 mbar and 16 h and 63 °C, 180 mbar and 12 h (central point). Rehydratation power of these vacuum dried samples (41.25%) was similar to rehydratation power of lyophilized red currants (40.00%), while rehydratation power of conventionally dried sample was rather unsatisfactory (26.25%). 3.3. Chemical properties of dried red currants Phenolic compounds are very important bioactive compounds with antioxidative properties. Because of these properties, their composition and content can define quality of dried fruit (Mikulic´-Petkovsek et al., 2014). Presence of phenolic compounds also influence on taste, flavor and color of dried product, and therefore, it is highly desirable to preserve their content as much as possible (Šumic´ et al., 2013). According to Pantelidis, Vasilakakis, Manganaris, and Diamantidis (2006) phenolic content of fresh red currants was in the range from 1115 to 1193 mg GAE/100 g DW, while phenolic content of fresh red currants obtained in the study by Djordjevic´ et al. (2014) was 137.3 mg GAE/100 g DW. Vacuum drying process presents good alternative for phenolic compounds preservation, since air-drying process causes significant loss of phenolic compounds such as: catechin, epicatechin and phlorizin (Joshi et al., 2011). Since, experimentally obtained total phenols content (TP) in vacuum dried red currants varied from 155.35 and 520.99 mg GAE/100 g DW, it could be concluded that dried red currants could be used as good source of polyphenol compounds. Results obtained by Mitic´, Obradovic´, Kostic´, Micic´, and Paunovic´ (2011) showed that phenols content of dried red currants was in the range from 305 to 1268 mg GAE/100 g DW. The highest TP (520.99 mg GAE/100 g DW was obtained on 78 °C, 30 mbar and 12 h, which indicated that polyphenols from red currants did not degrade on elevated temperature and that atmosphere with reduced oxygen (30 mbar vacuum) prevents them from oxidation. TP obtained in lyophilized and conventionally dried sample was significantly lower (366.65 and 351.51 mg GAE/100 g DW, respectively). According to results from Table 3, all linear terms of drying parameters exhibited significant influence on TP, which was positive for temperature and drying time and negative for vacuum pressure. This confirmed previous claim that polyphenols are preserved on elevated temperature (78 °C), if applied drying pressure is reduced (30 mbar). These effects could be visualized on Fig. S-5 (Supplementary data). Flavonoids are phytochemicals that are not essential for survival, but can be one of the factors that contribute to the protective effects of a fruit- and vegetable-rich diet (Borges, Degeneve,

473

Mullen, & Crozier, 2010). The main flavonoids of interest are anthocyanins, flavan-3-ols, and their polymeric condensation products, flavanones, flavonols, and flavones (Crozier et al., 2006). These compounds represent very important antioxidants. In this study, total flavonoids content (TF) was in the range of 91.45– 310.23 mg CE/100 g DW. In the study by Mitic´ et al. (2011) flavonoids content of dried red currants was reported to be in the range from 125 to 261 mg CE/100 g DW. The lowest TF was observed on the same experimental point as the lowest TP (48 °C, 180 mbar and 8 h), while the highest TF (310.23 mg CE/100 g DW) was observed on 48 °C, 30 mbar and 12 h, indicating that applied pressure dominantly affects TF. This was confirmed by statistical analysis, which showed that linear terms of temperature (positive) and pressure (negative) have impact on TF. Particularly interesting was that interaction effects of all combinations of variables affect this response (Table 3). Temperature-pressure and pressure-drying time interaction caused positive influence while temperaturedrying time exhibited negative influence on TF, meaning that flavonoid compounds degrade on prolonged vacuum drying when temperature is increased (Fig. S-6) (Supplementary data). Moreover, quadratic terms of pressure (positive) and drying time (negative), also significantly affected this response. Anthocyanin compounds are associated with red, violet or black color of fruit (Mikulic´-Petkovsek et al., 2014). High temperature influence on degradation of anthocyanins which can further disintegrate on aglycon, anthocyanidins, and sugar. If the high temperature is applied for longer time, anthocyanidins are further degraded, creating undesirable dark brown coloration (Šumic´ et al., 2014). Anthocyanins content in fresh red currants obtained in study by Pantelidis et al. (2006) was in the range from 7.5 to 7.8 (mg CGE/100 g FW), while in the study by Djordjevic´ et al. (2014) content of antocyanins was 36.4 mg/100 g FW. Monomeric anthocyanins content (MA) in dried red currants was between 24.89 and 88.29 mg CGE/100 g DW. Results obtained by Mitic´ et al. (2011) showed that MA in dried red currants was in the range from 21.5 to 111.75 mg CGE/100 g DW. Even though, lyophilization provides the mildest conditions and is particularly suitable for drying of samples with heat-sensitive compounds, such as anthocyanins, it could be concluded that it does not provide significant advantage comparing to vacuum drying since MA in lyophilized red currants was 65.90 mg CGE/100 g DW. According to statistical indicators (Table 3), linear term of pressure exhibited negative influence on MA, which means that anthocyanins are preserved on reduced pressure and oxygen concentration. Quadratic terms of temperature and drying time exhibited negative effect on MA, meaning that MA increases with their increase, reaches maximum and then starts to decrease with further increase of these variables (Fig. S-7) (Supplementary data). It could be seen that 3-D response surfaces for TP, TF and MA have similar shape,

Table 6 Simultaneously optimized vacuum drying conditions with target and predicted values of investigated responses. Response

Target

Predicted

Moisture content Water activity Total color change Firmness Rehydratation power Total phenols content Total flavonoids content Monomeric anthocyanins content Ascorbic acid content IC50 value

Minimized <0.600 Minimized Minimized Maximized Maximized Maximized Maximized Maximized Minimized

14.03% 0.382 24.65% 586.95 g 35.29% 477.34 mg GAE/100 g DW 306.34 mg CE/100 g DW 83.54 mg CGE/100 g DW 8.56 mg/100 g DW 0.3836 mg/mL

Optimized conditions: 70.2 °C, 39 mbar and 8 h, Da = 0.780. a Desirability function.

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which suggests that drying parameters affect these compounds similarly. Ascorbic acid (vitamin C) is essential nutrient for human health and because of its sensitivity on the brightness, high temperatures and the presence of oxygen, it is regarded as an important quality indicator of dried products (Santos & Silva, 2008). Vitamin C is also well known antioxidant which has an important role in the prevention of many diseases (Padayatty et al., 2003). Temperature and drying time have the most important influence on stability of vitamin C. This presents one of the advantages of vacuum drying process since the drying can be conducted at lower temperatures and for shorter time. Beside these two most significant parameters the concentration of oxygen in the drying atmosphere also influences the final content of vitamin C in dried product. Value of ascorbic acid of fresh dried currants was obtained in studies by Pantelidis et al. (2006) and it was in the range from 35.6 to 40 mg/100 g DW. In dried red currants, ascorbic acid content (AA) varied from 2.03 to 8.14 mg/100 g DW. The lowest AA was observed on 48 °C, 180 mbar and 16 h, which indicated that increased pressure, i.e. oxygen presence and increased drying time are crucial to its degradation. Moreover, the highest AA was observed on 63 °C, 30 mbar and 8 h, supporting this claim since reduction in pressure and drying time significantly increase AA. Due to rather unsatisfactory statistical parameters for the model and lack-of-fit testing, second-order polynomial model could not be applied for optimization of ascorbic acid content. Many bioactive components isolated from red currants possess antioxidative properties. However, various parameters, high temperature the most, influence negatively on antioxidant activity of dried product during drying process. This is caused by high thermal sensitivity of the main antioxidant components (vitamin C, phenolics and antocyanins compounds) of red currants. DPPH assay was used for quick screening of antioxidant activities of dried red currants and results, expressed as IC50 value (mg/mL), were between 0.2857 and 0.6257 mg/mL. The lowest antioxidant activity, i.e. the highest IC50, was obtained when higher level of temperature and pressure were applied (Table 2), suggesting that increased temperature and oxygen presence caused inactivation of antioxidants. On the other hand, the highest antioxidant activity was observed on 63 °C, 30 mbar and 16 h, showing that reduced pressure preserves antioxidants in dried red currants. According to statistical analysis, linear terms of temperature and pressure exhibited significant influence on antioxidant activity (Table 3). Temperature caused negative, while pressure caused positive influence on antioxidant activity which could be seen on Fig. S-8 (Supplementary data). Moreover, temperature-drying time interaction and quadratic term of temperature exhibited negative influence on antioxidant activity, suggesting that drying should be performed on reduced temperature in order to preserve antioxidants present in red currants. 3.4. Optimization of the vacuum drying process Optimization is crucial step of each industrial process since it directly affects product quality and economy of the process. Each of the investigated responses could be separately optimized on target value, however, each of the responses has its own optimized parameters and not all of them are in good correlation, which means that improving one response may have opposite effect on another one. On the other hand, RSM approach and desirability function (D) provide simultaneous optimization of multiple responses. Therefore, all physico-chemical properties of dried red currants were simultaneously optimized according to target value presented in Table 6. Application of desirability function provided optimal conditions for 10 response variables to be temperature of 70.2 °C, vacuum pressure of 39 mbar and drying time of 8 h, while

D function was still reasonably high (0.780), considering large number of optimized responses. Applied mathematical models predicted that red currants dried on optimized conditions will have rather good physico-chemical properties and quality (Table 6). 4. Conclusions Due to satisfactory parameters of descriptive statistics (R2 and CV) and analysis of variance (ANOVA) for the model and lack of fit testing, it could be concluded that second-order polynomial model provided adequate mathematical description of red currants vacuum drying process. Statistical parameters were only inappropriate for rehydratation power and ascorbic acid content. Therefore, RSM could be successfully used for simultaneous optimization of all physico-chemical properties. Optimal conditions for all response variables were temperature of 70.2 °C, vacuum pressure of 39 mbar and drying time of 8 h, while generated model predicted obtaining of dried red currants with following physico-chemical properties: moisture content 14.03%, water activity 0.382, DE 24.65%, firmness 586.95 g, rehydratation power 35.29%, total phenols content 477.34 mg GAE/100 g DW, total flavonoids content 306.34 mg CE/100 g DW, monomeric anthocyanins content 83.54 mg CGE/100 g DW, ascorbic acid content 8.56 mg/100 g DW and IC50 value 0.3836 mg/mL. Acknowledgements Authors wish to thank ‘‘Kovacˇevic´ inzˇenjering” DOO from Banatski Karlovac (Serbia) for installation and development of the vacuum drying device. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.foodchem.2016. 02.109. References Ahmed, J., Kaur, A., & Shivhare, U. (2002). Color degradation kinetics of spinach, mustard leaves, and mixed puree. Journal of Food Science, 67(3), 1088–1091. Alibas, I. (2007). Energy consumption and colour characteristics of nettle leaves during microwave, vacuum and convective drying. Biosystems Engineering, 96 (4), 495–502. Bakar, M. F. A., Mohamed, M., Rahmat, A., & Fry, J. (2009). Phytochemicals and antioxidant activity of different parts of bambangan (Mangifera pajang) and tarap (Artocarpus odoratissimus). Food Chemistry, 113(2), 479–483. Barbosa-Cánovas, V. G., Fontana, J. A., Jr., Schmidt, J. S., & Labuza, P. T. (2007). Water activity in foods – Fundamentals and applications. Iowa: John Wiley & Sons. Basß, D., & Boyacı, I. H. (2007). Modeling and optimization I: Usability of response surface methodology. Journal of Food Engineering, 78(3), 836–845. Bezerra, M. A., Santelli, R. E., Oliveira, E. P., Villar, L. S., & Escaleira, L. A. (2008). Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta, 76(5), 965–977. Borges, G., Degeneve, A., Mullen, W., & Crozier, A. (2010). Identification of flavonoid and phenolic antioxidants in black currants, blueberries, raspberries, red currants, and cranberries. Journal of Agricultural and Food Chemistry, 58, 3901–3909. Crozier, A., Yokota, T., Jaganath, I. B., Marks, S. C., Saltmarsh, M., & Clifford, M. N. (2006). Secondary metabolites in fruits, vegetables, beverages and other plant based dietary components. In A. Crozier, M. N. Clifford, & H. Ashihara (Eds.), Plant secondary metabolites: Occurrence, structure and role in the human diet (pp. 208–302). Oxford: Blackwell. Das, H. (2005). Food processing operations analysis. Asian Books, p 287. Denev, P., Ciz, M., Ambrozova, G., Lojek, A., Yanakieva, I., & Kratchanova, M. (2010). Solid-phase extraction of berries’ anthocyanins and evaluation of their antioxidative properties. Food Chemistry, 123, 1055–1061. Derringer, G. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12, 214–219. Djordjevic´, B., Rakonjac, V., Akšic´, M. F., Šavikin, K., & Vulic´, T. (2014). Pomological and biochemical characterization of European currant berry (Ribes sp.) cultivars. Scientia Horticulturae, 165, 156–162. Drach, M., Narkiewicz-Michałek, J., Sienkiewicz, A., Szymula, M., & Bravo-Díaz, C. (2011). Antioxidative properties of vitamins C and E in micellar systems and in

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