Journal of Food Engineering 105 (2011) 56–64 Contents lists available at ScienceDirect Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng Osmotic dehydration process for low temperature blanched pumpkin Keila de Souza Silva a,⇑, Lidimara Cássia Caetano a, Carolina Castilho Garcia a, Javier Telis Romero a, Adriana Barbosa Santos b, Maria Aparecida Mauro a a Department of Food Engineering and Technology, Institute of Biosciences, Language and Physical Sciences (IBILCE), UNESP – São Paulo State University Rua Cristóvão Colombo 2265, 15054-000 São José do Rio Preto, SP, Brazil b Departments of Computational Sciences and Statistics, Institute of Biosciences, Language and Physical Sciences (IBILCE), UNESP – São Paulo State University, Rua Cristóvão Colombo 2265, 15054-000 São José do Rio Preto, SP, Brazil a r t i c l e i n f o Article history: Received 20 October 2010 Received in revised form 19 January 2011 Accepted 21 January 2011 Available online 31 January 2011 Keywords: Low temperature blanching Pumpkin Osmotic dehydration Response surface Optimization a b s t r a c t This study investigated the influence of stepwise blanching over the kinetics of osmotic dehydration process and over the physical characteristics of pumpkin (Cucurbita moschata). The 23 factorial design and response surface methodology was used to optimize the blanching process. The independent variables for blanching were temperature, blanching time and holding time. These independent variables showed different effects on the two studied answers: texture and color. The kinetics of osmotic dehydration were investigated using 50% and 65% sucrose solutions, using samples previously blanched by both stepwise and conventional means. The diffusivity values for the water and sucrose were similar for the two components, showing greater gains of solute than loss of water in many samples. Blanching affected the color of the pumpkin, whereas osmotic dehydration did not change it significantly. The impregnation process maintained or even increased the tissue firmness when compared to the blanched samples. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Treatments applied before convective drying are generally used to reduce the moisture in food and the negative effects caused by air-dehydration. Some researchers have investigated the effect of blanching and osmotic dehydration treatments on the kinetics of air-dehydration of plant tissues such as strawberries (Alvarez et al., 1995) or apples (Nieto et al., 1998; González-Fésler et al., 2008). Thermal blanching is one of the most widely used treatments to decrease the initial microorganism load as well as to prevent off flavors and color changes resulting from enzymatic reactions that affect product quality. However, conventional thermal blanching can cause undesirable alterations in the structure and color of vegetables due to heat. A low temperature blanching treatment can reduce texture losses during subsequent heating (Bartolome and Hoff, 1972). This kind of treatment consists of an initial blanching at low temperatures, followed by a holding time at room temperature and finally rapid blanching at a high temperatures (Sanjúan et al., 2001). The firming effect is attributed to the activation temperature of the pectin methyl-esterase (PME) at temperatures between 50 and 70 °C (Van Buren, 1979). The enzyme hydrolyzes the methyl ester linkages in pectin molecules, producing free carboxyl groups. The de-esterified pectin, in turn, ⇑ Corresponding author. Tel.: +55 17 8139 5278. E-mail address: keilasouzas@yahoo.com.br (K. de Souza Silva). 0260-8774/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2011.01.025 can bind calcium ions present in the middle lamella, producing insoluble pectates that reinforces the cell wall and improves product texture. The subsequent high temperature blanching is performed to inactivate the enzyme (Bartolome and Hoff, 1972; Van Buren, 1979). Thereby stepwise blanching gives a firmer structure than conventional blanching at high temperature (Sanjúan et al., 2001). Concentrations of 10–30% of pectin can be found in the middle lamella of plants (Van Buren, 1991), which can substantially contribute to the success of this type of blanching. Dutta et al. (2006) showed the presence of PME in a study on the thermal treatment of Cucurbita moschata cv ‘Akra Chandan’ pumpkins. Many researchers have shown that stepwise blanching can ensure a firmer texture in canned vegetables such as carrot (Lee et al., 1979), green beans (Bourne, 1987), cauliflower (García-Reverter et al., 1994), sweet potato (Moreno-Perez et al., 1996) and broccoli (Sanjúan et al., 2001). However none of them evaluated the effect of this treatment combined with osmotic dehydration. Since it can reduce the moisture content of a plant by approximately 50%, osmotic dehydration (OD) is useful as a treatment for drying, preventing color changes due to enzymatic oxidation and the loss of volatile compounds, and reducing the acidity and damage caused by the heat (Ponting et al., 1966; Pan et al., 2003). Sucrose is considered to be a good osmotic substance, especially when the OD is applied as a treatment to drying, because it reduces enzymatic browning and provides a pleasant taste (Ponting et al., 1966; Lenart, 1996). Nascimento (2006) reported that although the osmotic dehydration of C. moschata pumpkin caused some K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 57 Nomenclature a,b,c a⁄ b⁄ °B °C Def DE H L⁄ M DM side of parallelepiped redness yellowness °Brix degrees Celsius effective diffusion coefficients (m2/s) total color variation hardness lightness mass (kg) total mass variation in relation to initial mass (dimensionless) determination coefficient (dimensionless) R2 RRMS mean relative error root square (dimensionless) SG sugar gain in relation to initial mass (dimensionless) wi average fraction of component i (water or sucrose) at time t, in wet basis (kg kg1 total mass) water content in wet basis (kg kg1 total mass) ww WL water loss in relation to initial mass (dimensionless) Y1 hardness relation total color difference Y2 b1, b1, Yi, b3, b12, b13, b23, b123 estimated regression coefficient of the Eq. (1) degradation of the carotenoids, the osmotic pre-treatment increased their retention during convective drying at 50 and 70 °C as compared to untreated samples, as well as improving their appearance. According to the author, this is due to the protective effect of this treatment, probably by decreasing the oxidative damage caused by exposure to oxygen. The objectives of this study were: to optimize the stepwise blanching of pumpkin (C. moschata) slices in order to minimize the color and texture changes; evaluate the influence of stepwise and conventional blanching, both followed by osmotic dehydration in sucrose solutions, on the color, texture and diffusivity of the water and sucrose. 2. Materials and methods 2.1. Materials Pumpkins (C. moschata), weighing between 40 and 50 kg, were cut into three portions in a direction transversal to their axis, and portion cut into four longitudinal pieces. Two opposing sides of each pumpkin were combined and used in the same experiment. In each trials was used a different pumpkin. In the experiment, the pieces were peeled, seeded and sliced (1 ± 0.1 cm thick), the slices being cut with dimensions of length (5 cm) and width (4 cm). The samples were placed in plastic bags, homogenized and selected at random. 2.2. Procedures 2.2.1. Stepwise blanching For the first stage of stepwise blanching, the samples were immersed in beakers containing water, previously placed in a thermostatically controlled water bath (Marconi, model MA-184 – Brazil) at low temperatures (55, 60 or 65 °C) for a blanching time of 30, 45 and 60 min. The slices were then removed from the beakers and left at room temperature for a holding time (30, 45 or 60 min). After this period of time, the slices were submitted to the second stage of blanching, which consisted of immersion in water at 97 °C (boiling) for 5 min, followed by cooling for 2 min Bt, Ht, T: variáveis indenpendentes não codificadas: Bt time of first stage of blanching for the response i (s) Ht holding time for the response i (s) T temperature of first stage of blanching for the response i (°C) x1i; x2i; x3i Variáveis independents codificadas: Subscripts and superscript b blanched calc calculated eq equilibrium exp experimental f fresh OD osmotically dehydrated s sucrose S1 stepwise blanched samples under the conditions optimized for texture S2 stepwise blanched samples under the conditions optimized for color w water 0 initial state under running water. This second stage also ensured the inactivation of peroxidases, detrimental to the quality of the product. 2.2.2. Conventional blanching In order to perform the conventional blanching, the samples were placed in boiling water (97 °C) for 5 min. This treatment was carried out in order to compare its effect with that of stepwise blanching. 2.2.3. Osmotic dehydration Samples submitted to stepwise blanching under conditions selected to maintain the best texture and color, and conventionally blanched samples, were osmotically dehydrated in sucrose solutions. The pumpkin slices were arranged in four baskets made of nylon with a division down the middle and stainless steel lids on each side, with approximately 300 g of pumpkin slices in each basket. The baskets were immersed in 20 kg of sucrose solution, continuously stirred using a 1.6 kW mechanical stirrer (Marconi, model MA-261 – Brazil) with a 10 cm diameter propeller and rotation at1000 rpm. The temperature of the solution was maintained at 27 °C and syrup-to-fruit ratio was approximately 20:1. The sucrose concentrations studied were 50° and 65 °Brix and the process was carried out for 0.5, 1, 2 and 3 h. At the end of each process time, one basket was removed from the osmotic bath and the samples immersed in distilled water at room temperature in order to remove the osmotic solution from the surface. They were then blotted with absorbing paper and weighted. The total solids, color and texture were analyzed before and after each treatment, and the total and reducing sugars in the samples determined before each treatment. The results obtained for each type of blanching were compared to investigate their effects on osmotic dehydration and on the product. 3. Analytical methods The TPA method (Texture Profile Analysis) was used to determine the texture of the samples (eight replicates) using the universal texturometer (TA-XT2i Texture Analyser, Stable Micro System, 58 K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 Surrey, UK) and the response expressed as hardness (H). The samples, cut in the shape of a cylinder with a cross sectional area of 2.87  104 m2, were individually compressed by a 35 mm acrylic cylinder. The hardness of the samples was defined by a peak representing 30% of the total strain and the strain rate was 1 mm/s for 5 s. The color of the samples was obtained using methodology proposed by Luzuriaga et al. (1997). For this, a digital camera 7.0MP (DC7325BR, MITSUCA, China) was installed in a lighted box and the recorded images were analyzed by the academic software V01 E&CS Programs (Gainesville, Florida, USA, version 9.7.6). The light box, with dimensions of 43 cm (w)  61 cm (l)  70 cm (h), was built with plywood and the inside walls were painted white to reflect light in all directions and to minimize shadow formation. The illumination was made with four fluorescent lamps (Sadokin T8/6400K, 15 W, 2007/4) and the lens of the digital camera was positioned 49.5 cm above the sample. The response was expressed in the form of the parameters L⁄ (lightness: 100 for white and 0 for black), a⁄ (green–red), b⁄ (yellow–blue) and the total color difference (DE), DE ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi   ðL  Lf Þ2 þ ða  af Þ2 þ ðb  bf Þ2 ð1Þ where the lower case letter ‘‘f’’ indicates the fresh sample. The values used for the standard parameters were: L⁄ = 62.661, a⁄ = 36.067 and b⁄ = 57.096 and color measurements were done in quadruplicate. The moisture content of the samples was measured gravimetrically in triplicate, drying to constant weight using a vacuum oven at 60 °C. The total and reducing sugar contents were determined in duplicate by the oxy-reduction titration (William, 1970; Rodrigues et al., 2003). 4. Experimental design and statistical analysis 4.1. Optimization of the stepwise blanching A 23 factorial design with three replications at the central point was used for this experiment. The coded independent variables studied were temperature (x1), blanching time for the first step (x2) and holding time (x3). The dependent variables (responses) evaluated were the color and texture. The experiments were processed in a random order. To minimize the influence of the initial conditions of the raw material on the tests, the results for texture were normalized by the ratio between the experimental measurement performed on the sample blanched and the corresponding fresh sample. To optimize the treatment, the hardness ratio (Hb/Hf) and total color difference (DE) (Eq. (1)) were selected as the dependent variables. The proximity of the blanched samples to the fresh ones was considered as the optimization criterion. Thus for texture, the relationships that came closer to the optimum were those with the highest values. For color, the variations in DE that came closer to the optimum were the lowest ones. The following general form of a first-order model that was used in this study: Y i ¼ b0 þ b1 x1i þ b2 x2i þ b3 x3i þ b12 x1i x2i þ b13 x1i x3i þ b23 x2i x3i þ b123 x1i x2i x3i ð2Þ where Yi represents the ith response variable (Y1 = Hb/Hf; Y2 = DE); x1i, x2i, x3i are the linear terms; and x1ix2i, x1ix3i, x2ix3i e x1ix2ix3i mean the cross product terms; b1, b1, b2, b3, b12, b13, b23, b123 are regression coefficients of the model being x1, x2, x3 the coded independent variables (Meyer, 1971; Montgomery, 1991). The coded values for using in the above equations can be obtained from the uncoded values using the following expression: x1 ¼ ðT  60Þ=5 ð3Þ x2 ¼ ðBt  45Þ=15 x3 ¼ ðHt  45Þ=15 ð4Þ ð5Þ where, T is the temperature (°C); Bt is the blanching time for the first stage (min) e Ht is the holding time after first stage of blanching (min). The regression coefficients were used to derive a mathematical model. From the analysis of variance it was possible to identify the coded variables that had significant effects on the responses of interest at the 95% confidence level (p < 0.05) and validate the mathematical models. The effects were estimated for each response with the objective to verify which dependent variable has greater influence on the response. After the optimization procedure, parameters that gave the best response for color and texture in the samples were chosen for use in the osmotic dehydration experiments. Blanching and osmotic dehydration combinations were evaluated. All statistical analyses were performed using Statistica 7.0 (StatSoft Inc., South America, Tulsa, OK, USA). 4.2. Osmotic dehydration The study of the kinetics of osmotic dehydration was carried out on samples treated with three different types of blanching methods: conventional blanching (97 °C/5 min), stepwise blanching with independent variables resulting in better product firmness (S1) and stepwise blanching with variables causing the least variation in color (S2). The choice of the latter two was based on responses obtained after optimizing the stepwise blanching. The mass balance was determined for each time of osmotic treatment and the influence of the kind of blanching, concentration of the sucrose solution and time of OD were compared. Thus the mass variation (DM), water loss (WL) and solute gain (SG) were calculated according to Eqs. (6)–(8). DM ¼ WL ¼ M  M0  100 M0 ðMwa Þ  ðM 0 w0a Þ M0 SG ¼ DM  DWL ð6Þ  100 ð7Þ ð8Þ To evaluate the effect of osmotic solution concentration and process time on the texture of the product, the results were normalized according to the ratio between the experimental measurements obtained from the osmotically treated sample and the corresponding fresh sample. The results for color and texture were statistically evaluated using the analysis of variance (ANOVA), with the sources of variation being the sample type and number of samples, and the Tukey Test being applied at the 5% level of significance. The results for color were also assessed by DE. The coefficients of diffusivity for water and sugar in the pumpkin slices were determined according to Fick’s Second Law as applied to a regular parallelepiped with sides 2a, 2b and 2c. The solution, when integrated along the distance, resulted in the mean concentration of the component, wi ðtÞ for a time t (Crank, 1975). The analytical solution was determined from the product of three integrated solutions for flat plates, considering the size of each one (a 6 x 6 a; b 6 x 6 b; c 6 x 6 c): 59 K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 wi ðtÞ  weq i ¼ w0i  weq i 8 3 X 1 X 1 X 1 1 ð 2l  1 Þ ð 2m  1Þð2n  1Þ l¼1 m¼1 n¼1 ( " 2  2   2 #) 2 p Def 2l  1 2m  1 2n  1  exp t þ þ a b c 4  p 2 ð9Þ where Def = the effective diffusion coefficient of water and sucrose; wi ðtÞ = average fraction of component i (water or sucrose on a wet basis) at time t, w0i = fraction of the component i at time zero (t = 0), weq i = fraction of the component i at equilibrium; l, m and n are the numbers of the series; a, b and c are characteristic lengths; t is the time. The Eq. (9) was fitted to the experimental results, using software Statistica 7.0 (StatSoft Inc., South America, Tulsa, OK, USA) that fits nonlinear functions. Four terms of the series were used, enough for convergence of the solution. For each setting the values for the Residual Root Mean Squares (RRMS) were calculated, defined by: ( RRMSð%Þ ¼ 100 1=ðn  p  1Þ n X  x exp x calc 1  exp 2 =x )1=2 ð10Þ where xexp  xcalc is the residual [the difference between the experimental (xexp) and calculated (xcalc)]; n is the number of observations, or residuals; p is the number of independent variables in the fitted equation and (n  p  1) defines the degrees of freedom. 5. Results and discussion 5.1. Stepwise blanching Table 1 shows the experimental results obtained in the optimization of the stepwise blanching using a third order factorial design, where Hf is hardness of the fresh sample, Hb is hardness of the blanched sample and DE is total color difference. The pumpkins were also blanched at 97 °C for 5 min and the hardness values were evaluated for comparison with the stepwise blanched. Table 2 shows these results. Observe that the some samples subjected to the stepwise blanching conditions (experiments 2, 3, 4, 7, 8 and 10 of Table 1) showed greater hardness ratios than the conventionally blanched ones (Table 2). Maximum firmness is attributed to the activity of pectin methyl esterase that produces free carboxyl groups which can bind calcium ions producing insoluble pectates that give a firmer texture (Bartolome and Hoff, 1972; Van Buren, 1979; Sanjúan et al., 2001). The analysis of variance (Table 3) showed that the blanching time had a significant effect (p = 0.0265) on the hardness of the sample. For DE, the analysis of variance and 95% confidence interval showed that the significant effects were the blanching time and any interactions between the variables (Table 4). The data were evaluated and the regression coefficients of the significant effects were used to determine a coded model, which described the behavior of the texture (Eq. (11)) and color (Eq. (12)) in the stepwise blanching of C. moschata. Y 1 ¼ 0:145 þ 0:033x2 ð11Þ Y 2 ¼ 10:036 þ 2:122x2  0:773x1 x2 þ 1:317x1 x3 þ 1:648x2 x3  1:516x1 x2 x3 ð12Þ The coded model proposed to represent the behavior of the response variables in the stepwise blanching treatment showed a good fit, with a correlation coefficient of 0.935 for the hardness ratio and 0.972 for the total color difference and lack of fit not significant for both responses (Tables 3 and 4). The positive effect of blanching time on the hardness ratio and on the DE (Tables 3 and 4) indicates samples firmer and stronger color changes when the processing is performed with high blanching times. A trend of increasing hardness ratio and DE with the highest holding times can also be observed. Similar results for the texture were observed by Quintero-Ramos et al. (1998) for the pumpkin Variety Grey Zucchini. The fact of treatments with smaller blanching time provide smaller variation color, when compared to the fresh samples, can be related to the higher retention of carotenoids. Milder thermal treatment affect less the isomerization and the oxidation of carotenoids (Rodriguez-Amaya et al., 2008). Table 4 shows, also, that the blanching time was the independent variable that showed the greatest effect on DE response. The results for the optimizations using color and texture were different, because in order to minimize the variation in color of the processed samples in relation to the fresh samples, they must be subjected to a milder thermal treatment, unlike what was necessary to get firmer textures. Thus the choice of the best treatment depends on whether you wish to prioritize the color or texture product. Table 2 Hardness of the samples blanched at 97 °C and their respective fresh samples. Samples 1 2 3 Hardness (Newton) Hb =Hf Fresh (Hf) Conventional blanching (97 °C for 5 min) (Hb) 153.20 ± 11.92 145.63 ± 13.88 137.84 ± 24.68 21.38 ± 4.69 17.57 ± 5.23 13.57 ± 2.33 0.14 0.12 0.10 Table 1 Experimental design in coded form of process variables, values of experimental data for optimization of osmotic dehydration process and values of calculated data from Eqs. (13) and (14). Trials 1 2 3 4 5 6 7 8 9 10 11 a Mean ± SD. Coded and (uncoded) variables Hardness Response variables (Y) x1 (T) x2 (Bt) x3 (Ht) Hfa (N) Hba (N) ðHb =Hf Þexp ðHb =Hf Þcalc (DE)exp (DE)calc 1 (55) 1 (65) 1 (55) 1 (65) 1 (55) 1 (65) 1 (55) 1 (65) 0 (60) 0 (60) 0 (60) 1 (30) 1 (30) 1 (60) 1 (60) 1 (30) 1 (30) 1 (60) 1 (60) 0 (45) 0 (45) 0 (45) 1 (30) 1 (30) 1 (30) 1 (30) 1 (60) 1 (60) 1 (60) 1 (60) 0 (45) 0 (45) 0 (45) 162.32 ± 22.82 148.55 ± 34.18 122.71 ± 29.47 157.11 ± 10.68 138.14 ± 14.94 148.13 ± 11.33 124.99 ± 43.25 155.41 ± 19.76 119.38 ± 12.20 139.78 ± 22.66 152.25 ± 12.55 12.82 ± 3.49 19.86 ± 3.88 25.41 ± 5.71 21.16 ± 6.67 22.68 ± 5.22 14.22 ± 2.50 27.89 ± 4.34 25.77 ± 5.54 15.96 ± 2.54 21.65 ± 2.52 18.48 ± 4.04 0.08 0.16 0.21 0.17 0.13 0.10 0.18 0.17 0.13 0.15 0.12 0.11 0.11 0.18 0.18 0.11 0.11 0.18 0.18 0.15 0.15 0.15 11.998 9.033 11.461 11.467 1.830 10.196 13.946 13.157 8.592 9.223 9.490 11.621 7.502 11.084 9.936 2.661 9.872 14.777 12.833 10.036 10.036 10.036 60 K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 Table 3 Analysis of variance and analysis of perturbation of the investigated variables on the response Hb =Hf . Source SS d.f. MS F p x1 x2 x3 x1x2 x1x3 x2x3 x1x2x3 Lack of fit Pure error Total SS 0.0000 0.0085 0.0002 0.0013 0.0008 0.0001 0.0024 0.0006 0.0005 0.014 1 1 1 1 1 1 1 1 2 10 0.0000 0.0085 0.0002 0.0013 0.0008 0.0001 0.0024 0.0006 0.0002 – 0.0000 36.2143* 0.8571 5.3571 3.4286 0.2143 10.5000 2.5974 – – 1.0000 0.0265 0.4523 0.1467 0.2053 0.6889 0.0835 0.2484 – – Factor Effect Std. Err. 95% Cnf. limt +95% Cnf. limt p Mean/intercept x1 x2 x3 x1x2 x1x3 x2x3 x1x2x3 0.145 0.000000 0.0650 0.0100 0.0250 0.0200 0.0050 0.0350 0.0046 0.01080 0.01080 0.01080 0.01080 0.01080 0.01080 0.01080 0.1256 0.0465 0.0185 0.0565 0.0715 0.0665 0.0515 0.0115 0.1653 0.0465 0.1115 0.0365 0.0215 0.0265 0.0415 0.0815 0.0010* 1.0000 0.0265* 0.4523 0.1467 0.2053 0.6889 0.0835 R2 = 0.9248. Significant at 5% level. * Table 4 Analysis of variance and analysis of perturbation of the investigated variables on the response DE. Source SS d.f. MS F p x1 x2 x3 x1x2 x1x3 x2x3 x1x2x3 Lack of fit Pure error Total SS 2.6657 36.0146 2.9161 4.7802 13.8759 21.7140 18.3800 3.5989 0.4253 104.3708 1 1 1 1 1 1 1 1 2 10 2.6657 36.0146 2.9161 4.7802 13.8759 21.7141 18.3800 3.5989 0.2126 – 12.5363 169.3670* 13.7137 22.4802* 65.2547* 102.1154* 86.4361* 16.9248 – – 0.0713 0.0058 0.0658 0.0417 0.0150 0.0097 0.0114 0.0543 – – Factor Effect Std. Err. 95% Cnf. limt +95% Cnf. limt p Mean/intercept x1 x2 x3 x1x2 x1x3 x2x3 x1x2x3 10.0357 1.1545 4.2435 1.2075 1.5460 2.6340 3.2950 3.0315 0.1390 0.3261 0.3261 0.3261 0.3261 0.3261 0.3261 0.3261 9.4375 0.2485 2.8405 2.6105 2.9490 1.2310 1.8920 4.4345 10.6340 2.5575 5.6465 0.1955 0.1430 4.0370 4.6980 1.6285 0.0002* 0.0713 0.0059* 0.06658 0.0417* 0.0150* 0.0097* 0.0114* R2 = 0.9614. * Significant at 5% level. The use of blanching before osmotic dehydration could increase the acceptance of the product after drying, once the sensory analysis of non-blanched pumpkins (C. moschata) osmotically dehydrated with sucrose and sodium chloride showed rejection of the taste of the raw vegetable by some tasters (Borin et al., 2008). In a more suitable way for application, the expressions 13 and 14 are showed in function of uncoded variables: Hb ¼ 0:046 þ 2:2  103 Bt Hf ð13Þ DE ¼ 3:055T  3:176Bt  4:971Ht þ 0:05TBt þ 0:077THt þ 0:0864BtHt  1:320  103 TBtHt  201:814 ð14Þ 5.2. Osmotic dehydration To study the effect of blanching on the osmotic treatment, the kinetic of the osmotic dehydration was determined in the stepwise blanched samples under the conditions optimized for texture (S1) and for color (S2) and in the conventionally blanched samples (97 °C/5 min). The blanching temperature of the central point (60 °C) was used because the temperature of the stepwise blanching did not exert any significant influence on sample texture, and only a slightly significant influence on the color. The independent variables for stepwise blanching optimized for texture (S1) were 60 min of blanching and 30 min of holding time, and for color (S2) were 30 min of blanching and 60 min of holding time, both with subsequent enzyme inactivation at 97 °C for 5 min. The mass transfer during the OD and the texture of the samples after each treatment was studied in the samples previously blanched by S1, S2 and conventionally. The values for moisture content, weight variation (Eq. (6)), water loss (Eq. (7)), sucrose gain (Eq. (8)), hardness (H) and DE (Eq. (1)) are shown in Tables 5 and 6. The relatively large standard deviations among the replicates in hardness analysis, especially in fresh samples (Tables 1, 2, 5 and 6) showed heterogeneity in a same pumpkin (standard deviation between 12% and 43%). In addition, each experiment was conducted 61 K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 Table 5 Moisture content, water loss, sucrose gain, mass variation (all with respect to the initial mass), hardness of blanched samples (conventional or stepwise) and osmotically dehydrated in a 50% (w/w) sucrose solution for different times, and the ratio with the hardness of the initial sample. Experiment Time of osmotic dehydration (h) wa (%) WL (%) SG (%) DM (%) H (N) Hf/Hf DE Fresh Conventional blanching Conventional blanch + OD (50%) 0 0 0.5 1 2 3 0 0 0.5 1 2 3 0 0 0.5 1 2 3 94.85 ± 0.14 96.45 ± 0.12 83.53 ± 0.28 78.99 ± 0.52 73.09 ± 0.49 68.47 ± 0.17 94.55 ± 2.39 95.04 ± 0.05 78.76 ± 0.20 74.52 ± 0.40 70.17 ± 0.39 65.87 ± 0.15 93.97 ± 0.04 95.48 ± 0.20 82.68 ± 0.24 78.47 ± 0.70 72.20 ± 0.23 70.17 ± 0.02 0 0 13.27 13.3 15.11 20.65 0 0 16.65 17.63 20.34 22.70 0 0 19.37 21.33 26.65 22.37 0 0 11.69 17.35 25.08 29.95 0 0 16.17 23.05 26.8 32.52 0 0 11.43 15.83 21.99 26.57 0 0 1.58 4.04 9.98 9.29 0 0 0.48 5.42 6.46 9.82 0 0 7.94 5.50 4.66 4.20 111.48 ± 20.48 20.07 ± 5.68 26.73 ± 5.19 30.59 ± 3.19 38.39 ± 5.82 45.10 ± 5.80 204.49 ± 24.08 8.58 ± 2.87 9.64 ± 3.67 11.06 ± 2.04 12.23 ± 2.41 12.88 ± 3.77 155.84 ± 14.23 18.7 ± 4.41 21.52 ± 3.24 17.49 ± 1.66 20.24 ± 2.63 18.81 ± 5.50 – 0.18 0.24 0.27 0.34 0.40 – 0.04 0.05 0.05 0.06 0.06 – 0.12 0.14 0.11 0.13 0.12 – 13.81 13.42 12.93 12.72 13.74 – 10.25 8.66 8.06 10.28 8.87 – 7.53 9.54 8.10 9.00 9.44 Fresh S1 S1 + OD (50%) Fresh S2 S2 + OD (50%) Table 6 Moisture content, water loss, sucrose gain, mass variation (all with respect to the initial mass), hardness of blanched samples (conventional or stepwise) and osmotically dehydrated in a 65% (w/w) sucrose solution for different times, and the ratio with the hardness of the initial sample. Experiment Time of osmotic dehydration (h) wa (%) WL (%) SG (%) DM (%) H (N) Hf/Hf DE Fresh Conventional blanching Conventional blanch + OD (65%) 0 0 0.5 1 2 3 0 0 0.5 1 2 3 0 0 0.5 1 2 3 94.83 ± 0.01 96.46 ± 0.20 81.40 ± 0.17 76.85 ± 0.28 69.69 ± 0.73 65.71 ± 0.13 95.76 ± 0.05 97.42 ± 0.96 83.94 ± 0.34 78.64 ± 0.15 69.47 ± 0.17 63.33 ± 0.13 94.34 ± 0.03 95.79 ± 0.03 83.23 ± 0.06 77.50 ± 0.06 72.24 ± 0.08 67.50 ± 0.68 0 0 12.64 17.42 20.85 27.29 0 0 22.14 25.06 36.57 47.22 0 0 14.35 20.64 25.08 27.82 0 0 14.42 19.00 27.95 31.06 0 0 11.83 17.07 24.16 26.49 0 0 11.83 17.21 22.54 28.06 0 0 1.78 1.58 7.10 3.78 0 0 10.31 7.99 12.41 20.73 0 0 2.52 3.43 2.53 0.24 131.41 ± 17.38 28.91 ± 2.31 28.80 ± 4.84 34.78 ± 5.36 37.40 ± 3.34 47.31 ± 4.60 151.76 ± 12.33 9.97 ± 1.54 10.86 ± 3.34 11.76 ± 2.28 12.58 ± 4.72 11.10 ± 2.71 139.87 ± 19.38 25.84 ± 3.84 28.29 ± 2.76 30.01 ± 4.23 32.80 ± 2.53 38.31 ± 5.99 – 0.22 0.22 0.26 0.28 0.36 – 0.07 0.07 0.08 0.08 0.07 – 0.18 0.20 0.21 0.23 0.27 – 12.92 13.77 13.20 14.70 13.87 – 16.01 15.61 15.21 17.08 14.99 – 9.12 9.65 10.18 7.94 11.20 Fresh S1 S1 + OD (65%) Fresh S2 S2 + OD (65%) with a different pumpkin and the hardness of the fresh samples showed a variation between 111.48 and 204.5 (Tables 1, 5 and 6), probably due to different times of harvest. Large deviations in the measurements of hardness due to variability of the raw material were also observed in studies carried out with guavas (Pereira et al., 2004), apples (Castelló et al., 2009), melon (Ferrari, 2009) and grapefruits (Moraga et al., 2009). Tables 5 and 6 show that the conventionally blanched samples were significantly firmer (p < 0.05) than the stepwise blanched ones, and that a longer OD time resulted in greater firmness in the case of samples submitted to the conventional treatment. Nevertheless, these results differed from those found in the optimization of the stepwise blanching (Table 1) and in the conventional blanching tests (Table 2), optimization of the blanching was carried out in 2008 March and April while the OD was studied in October and November of the same year. Significant changes in calcium and pectin in West Indian cherry fruits with maturation and harvesting time was found by França and Narain (2003). Hence, these results could be associated to the pectin and calcium contents, once these factors are directly related to the firmness production during stepwise blanching. Further investigations about pectin and calcium contents are needed in order to identify other relevant variables that affect firmness production. It is also verified on Tables 5 and 6 that the blanching and osmotic dehydration treatments did not affect the texture of fresh pumpkin in a consistent way although the impregnation process maintained or even increased the tissue firmness when compared to the blanched samples. It was noted that longer periods of OD provided greater firmness to the samples submitted to conventional treatment (Tables 5 and 6). The samples subjected to conventional blanching and treated in 50% sucrose solutions showed a greater hardness ratio than those treated in 65% solutions. However this effect was small and only significant when the samples were compared after 2 and 3 h of treatment. For this, Tukey’s test was applied for each type of blanching and each hardness ratio was measured in the same osmotic dehydration time being compared at both sucrose solution concentration. Table 5 shows that for up to 0.5 h of OD at 50 °Brix, all the blanching studies showed mass reduction. After this time, conventional blanching and S1 showed mass gains with the osmotic treatment, which means greater gains in solute than water loss. The S2 treatment showed little mass reduction when compared to the other blanching studies for up to 2 h of OD (50 °Brix) (Table 5). The mass gain observed for conventionally blanched samples and samples subjected to S1 is a result of the thermal treatments, 62 K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 once these cause damage to the cell membranes resulting in more space for the diffusion of sucrose, since cell membranes, when intact, are not permeable to sucrose molecules. According to Bidweel (1979), cell membranes show selective permeability, since they allow the passage of small molecules like water, but restrict the passage of larger molecular weight molecules such as sucrose. When these membranes lose this property, part of the cell contents diffuse to the osmotic solution and the intercellular spaces become available, resulting in greater impregnation of the tissue with solutes from the solution, in this case, sucrose. Kowalska et al. (2008) also observed mass gain in osmotic dehydration of blanched pumpkin vs. Justynka. At 65 °Brix (Table 6) the stepwise treatments provided mass reduction during the OD, a result not found with the conventionally blanched samples. The S2 treatment showed a small mass reduction up to 2 h, whereas the S1 treatment resulted in 20% mass reduction relative to the initial mass after 3 h of OD. Of all the treatments carried out in both solution concentrations (50% and 65%), S1 was the only one to show such a decrease (Tables 5 and 6). A comparison of the effects of the two osmotic concentrations on the variation in mass also showed that in general, the 50% sucrose solution provided greater mass gains for conventionally blanched samples and those treated by S1, and greater mass losses for the samples treated by S2 (Tables 5 and 6). The fresh pumpkin sample was considered as the standard in the analysis of the color changes in the stepwise blanched samples (S1 and S2) and conventionally blanched samples, with subsequent osmotic treatments in 50% and 65% sucrose solutions for different times. The same trends in the color parameters observed in the optimization of the stepwise blanching were found when these samples were osmotically dehydrated, and therefore the samples showed less variation in color when treated by S2 (Tables 5 and 6). A trend for higher values for L⁄ in samples conventionally blanched and submitted to S2 can be seen, as shown in Fig. 1. Analyzing the influence of the three blanching methods investigated under different conditions for OD, it was found that the samples pre-treated by S1 showed lower values for lightness (p < 0.05) as compared to the fresh sample, for all times of osmotic treatment (Figs. 1 and 2). However, when analyzing the change in L⁄ with time of osmotic treatment, it can be seen that the OD did not significantly (p > 0.05) change the lightness of the product. A comparison of the parameter a⁄ between the fresh and blanched samples (Figs. 3 and 4), showed that only the conventionally blanched samples did not present significant differences (p 6 0.05) in parameter a⁄ after blanching. It was found that the changes were not significant during the osmotic dehydration for all treatments at both concentrations. At 95% of reliability, the conventionally blanched samples were more yellow (higher b⁄) than those treated by S1 and S2, but for all the blanched samples the OD times showed no changes in the value of parameter b⁄ at 5% level of significance (Figs. 5 and 6). All the significant changes, for both b⁄ and a⁄, could be attributed to the type of blanching used, showing no relationship with the osmotic treatment. Table 7 shows the diffusion coefficients for water (Defw) and sucrose (Defs) calculated according to Eq. (9), for the different types of blanching subjected to osmotic treatment at 50 and 65 °Brix. The data showed a good fit to Eq. (9), the R2 values being above 0.930 and the values for RRMS below 13%. For each treatment the coefficients tended to decrease when the concentration of the osmotic solution increased, as expected for pure sucrose solutions. Solute gains higher than the water loss were observed for many samples, especially those subjected to 50 °Brix solutions, which could be attributed to the low selectivity of the tissue due to the thermal treatment, combined with the higher diffusivity found at this concentration. The diffusion coefficients were higher for the samples treated with S1 and subsequently subjected to a 50 °Brix sucrose solution. Moreover, it was observed that the diffusion coefficients of water and sucrose provided by this treatment were very similar at the two concentrations, which can be attributed to greater damage to the tissue and a greater loss of selectivity. These changes, combined with the higher diffusivity in more dilute solutions, resulted in greater impregnation by sucrose, as noted in the SG for this treatment in Table 5. Fig. 1. Values for the parameter L⁄ plus standard deviation for conventionally blanched pumpkin samples, those treated by S1 and those treated by S2, all subsequently dehydrated in a 50% sucrose solution for different times. Fig. 2. Values for the parameter L⁄ plus standard deviation for conventionally blanched pumpkin samples, those treated by S1 and those treated by S2, all subsequently dehydrated in a 65% sucrose solution for different times. K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 Fig. 3. Values for the parameter a⁄ plus standard deviation for conventionally blanched pumpkin samples, those treated by S1 and those treated by S2, all subsequently dehydrated in a 50% sucrose solution for different times. Fig. 4. Values for the parameter a⁄ plus standard deviation for conventionally blanched pumpkin samples, those treated by S1 and those treated by S2, all subsequently dehydrated in a 65% sucrose solution for different times. 63 Fig. 5. Values for the parameter b⁄ plus standard deviation for conventionally blanched pumpkin samples, those treated by S1 and those treated by S2, all subsequently dehydrated in a 50% sucrose solution for different times. Fig. 6. Values for the parameter b⁄ plus standard deviation for conventionally blanched pumpkin samples, those treated by S1 and those treated by S2, all subsequently dehydrated in a 65% sucrose solution for different times. 6. Conclusions The lowest diffusivity values were found for the S2 treatment, although at 50 °Brix, the values differed little from those of the conventional treatment. The diffusion coefficients obtained for water and sucrose (Table 7) were higher than those obtained by Garcia et al. (2007) for slices of C. moschata osmotically dehydrated in 50% and 60% sucrose solutions, which is related to the effect of the temperature used in the blanching studies, which caused damage to the tissue and facilitated diffusion of the species during the osmotic dehydration. Higher values for the diffusion coefficients were also reported by Rodrigues et al. (2003) in papaya osmotically dehydrated at 50 °C. Stepwise blanching was optimized by evaluating the effect of blanching time, temperature and the holding time on the color and texture of pumpkin. The blanching time significantly influenced the texture, although the effect was very small, and showed a much larger and negative effect on the color, reducing the color intensity of the samples. The conditions of the raw material used in the experiments showed heterogeneity amongst the pumpkins of the same variety, and this had a greater influence on the hardness than the stepwise or conventional blanching. The diffusion coefficients obtained for water and sucrose were similar for all the treatments at both concentrations, and were very 64 K. de Souza Silva et al. / Journal of Food Engineering 105 (2011) 56–64 Table 7 Diffusion coefficients for water and sucrose in the conventionally and stepwise (S1 and S2) blanched samples, all submitted to 50% and 65% sucrose solutions. Treatment Water Sucrose 2 Defw (m /s) (10 Conventional blanch + OD (50 °Brix) Conventional blanch + OD (65 °Brix) S1 + OD (50 °Brix) S1 + OD (65 °Brix) S2 + OD (50 °Brix) S2 + OD (65 °Brix) 6.6 4.9 8.0 4.4 6.4 3.8 10 ) 2 R RRMS (%) Defs (m2/s) (1010) R2 RRMS (%) 0.987 0.981 0.973 0.981 0.981 0.977 3.70 4.47 12.68 6.70 7.47 3.37 6.1 4.5 8.0 4.6 5.9 3.4 0.987 0.980 0.973 0.981 0.982 0.976 2.67 3.92 11.00 2.57 6.29 3.01 high, reflecting the low selectivity of the tissue. The diffusivity decreased with increase in concentration. 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