optimisation and modelling green bean's ultrasound blanching

Original article

Optimisation and modelling green bean’s ultrasound blanching

Mahmoud Yolmeh1* & Mahmoud Najafzadeh2

1 Department of Food Science and Technology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

2 Iranian Academic Center for Education, Culture and Research, IACECR, Mashhad branch, Iran

(Received 7 March 2014; Accepted in revised form 19 May 2014)

Summary Using of ultrasound in food processing is a novel and interesting technique, which is often complementary

to classical methods. This study reports on the ultrasound blanching (USB) of green bean. Response sur-

face methodology (RSM) was used to study the effect of process variables on the USB. Three independent

variables including temperature (50–90 °C), time (45–225 s) and duty cycle (0.2–0.8 s) were examined.

The optimal USB conditions were obtained with a temperature of 90 °C, USB time of 58.27 s and duty

cycle of 0.79 s. At these conditions, the residual peroxidase activity (RPA) determined as 9.64% and the

vitamin C loss as 8.92%. The experimental values under optimal condition were in good consistent with

the predicted values. According to the results, the USB process is more efficient process and as well as less

damage to the product compared to the conventional blanching method.

Keywords Green bean, optimisation, peroxidase, ultrasound blanching, vitamin C.

Introduction

Green bean (Phaseolus vulgaris L.) is considered oneof the vegetables whose consumption has increasedover the past years due not only to the nutritional andhealth benefits this vegetable provides, but also to theintroduction of new green-bean-derived products(Akyol et al., 2006).

Blanching is a heat treatment widely applied in theagro-food sector and especially important in the pro-cessing of green vegetables. Its main goal is to inacti-vate the enzymes involved in the spoilage of freshvegetables (Garrote et al., 2004). Other objectives ofblanching are to reduce the microbial load of productsto improve its conservation, to soften tissues for aneasier canning step and a shorter cooking time, and toeliminate intracellular air to prevent oxidation (Ra-mesh et al., 2002). Typically, blanching is carried outby treating the vegetable with steam or hot water for1–10 min at 75–95 °C, and the time and temperatureselection is dependent on the type of vegetable. In thecase of green bean, low-temperature/long-time andhigh-temperature/short-time blanching methods havebeen applied (Akyol et al., 2006). Commercial blan-chers used in the vegetable canning industry are rela-tively intensive in water and energy consumption.

Given the possible detrimental effect of blanchingon the nutritional quality of some products, there isa need to develop alternative pretreatment methodsthat have minimal impact on nutritional and organo-leptic properties of food (Gachovska et al., 2009).Ultrasound waves are promising and emerging alter-native technology for food-processing applicationsthat has been recognised as a possible pretreatmentto substitute conventional blanching (Zheng & Sun,2006). Ultrasound waves as pretreatment processhave been carried out on different vegetables andfruits, for example mushrooms, Brussels sprouts andcauliflower (Jambrak et al., 2007), carrot (Rawsonet al., 2011), banana (Azoubel et al., 2010) and apple(Opalic et al., 2009). However, no study has beencarried out on optimising of ultrasound blanching(USB). Optimising the blanching condition canreduce energy and time consumption and can resultin more desirable product quality (Afoakwa et al.,2006).The presence of peroxidase (POD) has been found

to have an empirical relationship to off-colours andoff-flavours in raw and unblanched frozen vegetables(Lopez et al., 1994). Therefore, the inactivation of thisenzyme increases the shelf life of vegetables during fro-zen storage and is often used as an index for blanchingsuitability (Polata et al., 2009). Generally, 90% orhigher reductions of POD activity are required in vege-tables to obtain the optimum vegetable quality duringfrozen storage (Akyol et al., 2006).

*Correspondent: Fax: +981735228573;

e-mail: [email protected]

International Journal of Food Science and Technology 2014, 49, 2678–2684

doi:10.1111/ijfs.12605

© 2014 Institute of Food Science and Technology

2678

Vitamin C is easily destroyed during processing andstorage, and it is the least stable of all vitamins (Cruzet al., 2008). The rate of destruction is intensified bythe action of metals, particularly iron and copper, andenzymes, presence of oxygen, lengthened heating inthe exposed to air and exposure to light are all harm-ful factors to vitamin C content of foods (Deman,1990).

There is no study available in the literature concern-ing the use of USB for green bean. Therefore, the firstgoal of present study was to blanch green bean byUSB and optimise the USB process through responsesurface methodology (RSM). The second goal was tostudy the interactive effects of the process. Indepen-dent variables were investigated on the USB of greenbean.

Materials and methods

Material

Fresh green beans (Phaseolus vulgaris L.) were purcha-sed from a local market. The green beans were 5–8 cmin length and were put five per in beaker. Guaiacol,o-dianisidine and hydrogen peroxide were preparedfrom Sigma-Aldrich Chmie GmbH, Germany. Thecommon reagents performed were all reagent grade(Merck, Germany).

Conventional blanching (Water blanching)

Green beans were blanched by a constant-temperaturewater bath with shaker at 60–90 °C for 5, 10, 15 and20 min.

Ultrasound blanching

The green beans were 5–8 cm in length and wereput five per in beaker (contain 50 cc distilled water),then immersed in a water bath contains distilledwater. Thermal treatment was carrying out in 50–90 °C and times of 45–225 s by water bath. Initialtemperature of distilled water was room temperature(24 °C). The processing time was counted after thewater reached treatment temperature. The distilledwater temperature reached the treatment temperatureafter 1–3 min.

The blanching vessel temperature was monitoredwith a thermocouple to control the blanching water atthe desired temperature.

A 1.5-kW ultrasonic processor (XL2020, Misonix,Germany) operating at 20 kHz with a 19-mm-diameterprobe was used for sonication. The ultrasound probewas submerged, and tip of it was 1 cm above greenbeans. All the experiments and measurements werereplicated thrice.

Preparation of crude enzyme extracts

To obtain vegetable extracts, samples were cut tosmaller size. Samples were then mixed with the cold(4 °C) sodium phosphate buffer (pH = 6.5). The sam-ple–buffer mixture in a hand blender for 2 min washomogenised. The suspensions were filtered throughcheesecloth to remove solid particles (Akyol et al.,2006).

Peroxidase assay

Presence of peroxidase substrate solution was prepareddaily by mixing 0.5 mL guaiacol (99.5%, Sigma,USA), 0.5 mL hydrogen peroxide (30%, Sigma) and99 mL sodium phosphate buffer (pH 6.5). POD assaywas conducted by mixing 0.1 mL enzyme extract with3.5 mL substrate solution. POD activity was measuredat 25 °C as the initial increase in absorbance at470 nm (UV-160A spectrophotometer, Shimadzu,Japan). The blank was prepared with 0.1 mL water and3.5 mL substrate solution (Akyol et al., 2006; Polataet al., 2009).The residual POD activity (RPA) was measured as a

percentage of the initial activity of POD in untreatedsamples, according to the following formula:Residual peroxidase activity (RPA)% = A/A0 9 100A: POD activity after the treatment.A0: POD activity in untreated samples.

Vitamin C content

Vitamin C contents of the crude and treated extractswere determined by indophenol titration method (Er-can & Soysal, 2011). In this method, ascorbic acidcontents of the samples were determined by stabilisingwith metaphosphoric acid and then titrating with 2, 6-dichlorophenolindophenol sodium salt solution. Vita-min C content was expressed as milligrams of ascorbicacid per 100 g green bean (wet basis).

Experimental design

A five-level, three-variable central composite designwas employed for optimisation with respect to threeimportant reaction variables: the process temperature,sonication time and duty cycle. Off time for the ultra-sound device considered to burst of the bubbles, so theduty cycle (on time/off time) and total time were 0.2–0.8 and 1 s, respectively. To analyse the obtainedresult, namely residual POD activity (RPA) and vita-min C loss%, Minitab� version 16.1.1 (Minitab Inc.,USA, 2010) was used. The factorial design composedof three factors, three replicates, twenty base run, sixtytotal run. This design has eight cube points, one centrepoint in cube, six axial points, 0 centre point in axial

© 2014 Institute of Food Science and Technology International Journal of Food Science and Technology 2014

Optimisation and modelling green bean M. Yolmeh and M. Najafzadeh 2679

and totally fifteen treatments without considering repe-tition. The centre points in cube, cube points and axialpoints were repeated 18, 3 and 3 times, respectively.Regression analysis was performed on the data ofresponse variables including the residual POD activityand the residual vitamin C content obtained.

Statistical analysis

The least-square multiple regression methodology wasperformed to investigate the relationship between theindependent and dependent variables. The multipleregression equation was used to fit the second-orderpolynomial equation based on the experimental dataas follows:

Y ¼ b0 þ b1X1 þ b2X2 þ b3X3 þ b4X4 þ b11X1X1

þ b22X2X2 þ b33X3X3 þ b44X4X4 þ b12X1X2

þ b13X1X3 þ b14X1X4 þ b23X2X3 þ b24X2X4

þ b34X3X4

where Y represents the predicted response, b0, is themodel intercept, b1, b2, b3, b4, b11, b22, b33, b44 andb12, b13, b14, b23, b24, b34 are linear quadratic andinteraction coefficients, respectively, and X1, X2, X3

and X4 are the independent.The models were compared based on the coefficient of

determination (R2), adjusted coefficient of determina-tion (R2-adj) and predicted coefficient of determination(R2-pred). The R2 ranges from 0 to 1. R2 values closer to1 means the model is more accurate (Badwaik et al.,2012). After selecting the most accurate model, theanalysis of variance (ANOVA) was used to enquire the sta-tistical significance of the regression coefficients by con-ducting the Fisher’s F-test at 95% confidence level. Theinteractive effects of the factors were observed using sur-face plots, derived from the chosen model.

Finally, the entire process was optimised. The aim ofthe optimisation was to minimise the RPA and the vita-min C loss with the same weight (w = 1), and the credi-bility of the optimum conditions was diagnosed throughthe desirability values of the responses which range from0 to 1. The closer values of desirability to 1 showed themore desirable and credible optimal conditions.

Results and discussion

Fitting the response surface models

According to the created design, fifteen treatmentswere performed in thrice and the obtained results aredepicted in Table 1.

From Table 2, the values of R2, R2-adj and R2-predrevealed that the linear-square models were the moresuitable than other models for the residual POD activ-ity and vitamin C loss.

The two models are as follows:

Vitamin C loss% ¼ �0:4576X1 þ 0:1800X2 þ 0:0055X21

� 0:0003X22:

RPA% ¼ 103:621� 0:986X1 � 0:141X2 � 37:355X3

þ 0:000X22 � 29:643X2

3:

The analysis of variance (ANOVA) was performed toevaluate the significance of the models (Yuan et al.,2008). For each terms in the models, a small P-valueand a large F-value would show a more significant

Table 1 The central composite design matrix and the experimental

data for the responses

Treatment

Temperature

(°C)

Time

(s)

Duty

cycle

(s)

Residual

POD

activity

(RPA) (%)

Vitamin C

loss (%)

1 58 188 0.30 28.41 � 0.63 11.75 � 0.25

2 70 135 0.50 18.11 � 0.59 11.07 � 0.39

3 82 81 0.65 11.50 � 0.50 8.33 � 0.52

4 70 135 0.20 23.50 � 0.75 14.16 � 0.52

5 70 135 0.80 19.61 � 0.38 9.75 � 0.25

6 58 188 0.65 25.05 � 0.50 8.5 � 0.50

7 81 188 0.30 10.00 � 0.75 17.91 � 0.38

8 81 188 0.65 7.25 � 0.51 16 � 0.50

9 70 45 0.50 27.08 � 0.52 0.66 � 0.28

10 81 81 0.30 14.75 � 0.50 9.5 � 0.50

11 50 135 0.50 34.75 � 0.75 6.83 � 0.16

12 58 81 0.65 30.08 � 0.52 2 � 0.28

13 58 81 0.30 32.16 � 0.63 3.66 � 0.26

14 70 225 0.50 15.66 � 0.62 18.66 � 0.28

15 90 135 0.50 3.85 � 0.90 22.75 � 0.24

POD, presence of peroxidase; RPA, residual peroxidase activity.

Table 2 The statistics of the four fitted models

Models Statistics

Responses

Residual POD activity

(RPA) (%)

Vitamin C loss

(%)

Linear R2 97.15 88.13

R2-adj 97.02 87.49

R2-pred 96.75 85.80

Linear squares R2 99.10 93.00

R2-adj 98.94 92.20

R2-pred 98.65 90.09

Linear

interactions

R2 97.08 88.38

R2-adj 96.80 87.06

R2-pred 96.60 84.76

Full quadratic R2 99.01 93.24

R2-adj 98.84 92.03

R2-pred 98.46 89.21


© 2014 Institute of Food Science and TechnologyInternational Journal of Food Science and Technology 2014

Optimisation and modelling green bean M. Yolmeh and M. Najafzadeh2680

effect on the respective response variable (Quanhong &Caili, 2005). Therefore, all of the linear terms of resid-ual POD activity show a significant effect (P < 0.05).The quadric term of time and duty cycle also had asignificant effect (P < 0.05) on the residual POD activ-ity. But, the effect quadric term of temperature wasinsignificant (P > 0.05; Table 3).

From Table 3, for the vitamin C loss, the linear andquadric terms of temperature and time show a signifi-cant effect unlike the linear and quadric terms of dutycycle (P < 0.05).

P-value for lack of fit was obtained 0.24 and 0.36for RPA and vitamin C loss, respectively, both ofwhich were shown to be insignificant at probabilitylevel of 0.5%, conforming model accuracy.

Effects of USB conditions on the RPA

Figure 1 indicates the interactive effects of time andduty cycle on the RPA when the temperature was keptat 70 °C. The RPA was declined by increasing theduty cycle to 0.7, whereas much increasing the dutycycle leads to be raised the RPA. This phenomenon isdue to lack of enough time to burst the bubbles thatare made by ultrasound waves, in high duty cycle. TheRPA was diminished by rising the time of USB.

Figure 2 presents the interaction between the tem-perature and duty cycle. The RPA reduced by increasing

the temperature. This is because of denaturation ofPOD in high temperature (Ercan & Soysal, 2011). Ini-tially, the RPA decreased by increasing the duty cyclebut subsequently increased, this is probably due toreduction thermal conductivity. High duty cycle leadsto accumulation of the bubbles and thereby decreasesthermal conductivity.

Effects of USB conditions on the vitamin C loss

Figure 3 shows the interaction between the USB tem-perature and time when the duty cycle was kept in0.5 s. According to the figure, the vitamin C loss wasraised by increasing the time of USB. This fact hap-pened in high temperature particularly. This is due tovitamin C is a vulnerable compound to high tempera-ture and using from it to evaluation quality ofblanched product (Gamboa-Santos et al., 2013). Thevitamin C loss was increased by temperature especiallyin the long USB. This could be due to the formationof sound chemical components in high extraction time.These components might have oxidative effectsthrough producing free radicals (Ghafoor & Choi,2009; Zhang et al., 2010) and destroying vitamin C, sothe vitamin C loss was raised.According to Fig. 4, the vitamin C loss was dimin-

ished by increasing the duty cycle. This is because ofsound chemical components have not enough time to

Table 3 ANOVA of the linear-square models for the residual POD activity (RPA) (%) and vitamin C loss (%)

Source Degrees of freedom Sum of squares Mean of squares F P

RPA% Regression 6 3834.97 639.162 878.96 0.000

Linear 3 164.39 54.795 75.35 0.000

Temperature (X1) 1 42.60 42.601 58.58 0.000

Time (X2) 1 92.84 92.836 127.67 0.000

Duty cycle (X3) 1 59.10 59.098 81.27 0.000

Square 3 71.20 23.735 32.64 0.000

X 21 1 2.18 2.176 2.99 0.089

X 22 1 39.68 39.675 54.56 0.000

X 23 1 38.46 38.464 52.89 0.000

Residual error 53 38.54 0.727

Pure error 45 14.66 0.326

Total 59

Vitamin C loss Regression 6 1557.34 259.556 172.27 0.000

Linear 3 169.47 56.490 25.52 0.000

Temperature (X1) 1 9.17 9.168 4.14 0.047

Time (X2) 1 150.96 150.961 68.21 0.000

Duty cycle (X3) 1 0.00 0.005 0.00 0.963

Square 3 81.48 27.159 12.27 0.000

X 21 1 26.94 26.942 12.17 0.001

X 22 1 45.21 45.206 20.43 0.000

X 23 1 1.95 1.949 0.88 0.352

Residual error 53 117.30 2.213

Pure error 45 6.89 0.153

Total 59




destruction of vitamin C in high duty cycle unlike theshort duty cycle. The vitamin C loss was raised byincreasing the temperature dramatically in low dutycycle. As shown in Fig. 4, it can be concluded that the

vitamin C was minimum when duty cycle and USBtemperature were approximately 0.8 s and 52 °C,respectively.Figure 5 describes the interactive effect of the USB

time and duty cycle on the vitamin C loss when theduty cycle was kept at 70 °C. The increasing dutycycle reduced the vitamin C loss particularly in longUSB times. The leaching phenomenon of vitamin Cwas intensified by prolongation of USB that this leadsto increasing the vitamin C loss in long USB (Cruzet al., 2008). The vitamin C loss was raised by increas-ing the USB time especially in short duty cycles. FromFig. 5, it can be concluded that the vitamin C wasminimum when duty cycle and USB time were approx-imately 0.8 and 50 s, respectively.

Optimisation of the USB process

Optimising the USB process was performed by thenumerical optimisation technique when weight andimportant values for both responses were consideredequal (Li et al., 2013). The temperature of 90 °C, USB

Figure 1 The interactive effect of the ultrasound blanching (USB)

time and duty cycle on the residual peroxidase activity (RPA) of

green bean.


temperature and duty cycle on the residual peroxidase activity

(RPA) of green bean.


temperature and time on the vitamin C loss of green bean.


temperature and duty cycle on the vitamin C loss of green bean.


time and duty cycle on the vitamin C loss of green bean.



time of 58.22 s and duty cycle of 0.79 s were found asthe optimal conditions of the USB process. The RPAof 9.64% and the vitamin C loss of 8.9% wereacquired as the predicted results whose desirability val-ues were equal to 1.

The experimental results of the RPA and vitamin Closs were 9.79% and 9.38%, respectively, in optimumconditions. This proximity of the experimental resultsto theoretical results revealed that the RSM algorithmcould estimate the results precisely. Stamatopouloset al. (2012) and Sharma et al. (2006) also optimisedblanching of olive leaf extraction and pretreatment ofcarrot by RSM, respectively.

Comparison of USB and conventional blanching

A constant-temperature water bath with shaker wasused as the water blanching equipment. Green beanswere blanched in water at 60–90 °C for 5, 10, 15 and20 min. The RPA was reduced to 28% and 8.5% at60 and 75 °C, respectively, after 20 min water blanch-ing. The RPA was diminished to 4% at 90 °C after4-min water blanching (Fig. 6). The vitamin C losswas increased to 34% and 76% at 60 and 75 °C,respectively, after 20-min water blanching. The vitaminC loss was intensified to 81% at 90 °C after 4-minwater blanching (Fig. 7). Giving to the result of con-ventional blanching, the quality of green bean reducedduring the blanching due to the high temperature inlong time.

Mechanism of peroxidase inactivation and vitaminC loss by US waves is through rapid increasing tem-perature by bursting the bubbles. Therefore, time ofgreen bean’s USB much reduced and quality of theproduct is preserved better than green bean’s conven-tional blanching. Reduced blanching time is importantfor the industry by decreasing energy cost and alsowould result in more desirable product quality. It was

reported that POD in green beans is completely inacti-vated by 2-min blanching at 93.3 °C (Barrett & The-erakulkait, 1995). In the study of Bahc�eci et al. (2004),the retention of POD was approximately 80% at70 °C for 20-min blanching, and 90% of POD inacti-vation could be achieved by a blanching treatment at90 °C for 3 min. However, in the conditions, the qual-ity of green beans was declined dramatically. The USBprocess decreased the POD activity sufficiently in shorttime. Thus, the green bean blanched by USB damagein very low level and it could substitute the conven-tional blanching. Jabbar et al. (2014), Gamboa-Santoset al. (2013) and Rawson et al. (2011) also achievedsimilar observation for carrot juice, carrot and carrotdiscs, and reported that USB is better thanconventional blanching for the vegetables.

Conclusion

The results from this research demonstrated that USBis an effective technique for green bean blanching, andquality of the product is better preserved in compari-son with the conventional method. The advantage ofthis technique includes less vitamin C damage com-pared to the conventional method.

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0

10

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5 10 15 20

RPA

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Figure 6 The residual peroxidase activity (RPA) in green beans

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optimisation and modelling green bean's ultrasound blanching

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