Optimization of drying parameters and color changes of pretreated organic apple slices

STELA JOKIĆ*, JASMINA LUKINAC, DARKO VELIĆ, MATE BILIĆ, DAMIR MAGDIĆ,

MIRELA PLANINIĆ

Department of Process Engineering, Faculty of Food Technology, University J.J. Strossmayer of Osijek,

F. Kuhaca 18, P.O. Box 709, 31000 Osijek, Croatia

* Corresponding author. Tel.: +385 98 1666629, fax: +385 31 207 115, E-mail address: stela.jokic@ptfos.hr

ABSTRACT

The aim in this research was to determine the optimal drying parameters for the production of dried

apple slices of good texture, good rehydration ability and suitable color. Organic apple samples variety “Florina”

were pretreated and dried in laboratory tray drier at different temperatures. Different chemical pretreatments

were applied on samples (dipping in 0.5% ascorbic acid solution; 0.3% L–cysteine solution; 0.1% 4–hexyl

resorcinol solution and 1% sodium metabisulfite solution). Drying temperatures for nontreated samples were 50,

60, and 70 °C at airflow velocity of 1.5 ms-1

. Color changes were measured by chromameter and digital image

analysis. The Page’s mathematical model was used to calculate the drying kinetic parameters. The obtained

results showed a good agreement with experimental data. According to drying time, rehydration and color

characteristics the optimal drying temperature was found to be 60 °C. The best results were achieved when

samples were pretreated with 4–hexyl resorcinol.

Keywords: Drying kinetics; Color; Rehydration; Pretreatment; Organic apple; Image analysis

ABBREVIATIONS

a red-green

AK ascorbic acid solution

b yellow-blue

B blue

BL blanching in hot water

G green

k, n parameters in model (6)

L lightness-darkness

LC L–cysteine solution

1

m weight (g)

NaB sodium metabisulfite solution

NT non treated samples

R red

RR rehydration ratio

t drying time (min)

T temperature (C)

W weight (g)

X moisture (kgwkgdb-1

)

X´ dimensionless moisture

dX´/dt drying rate (min-1

)

4H 4–hexyl resorcinol solution

∆ELab color changes in CIE Lab color model

∆ERGB color changes in RGB color model

Subscripts

d dried sample

db dry basis

e equilibrium

r rehydrated sample

w water

0 initial

2

INTRODUCTION

During the last decade there is a strong tendency towards organic apple cultivation. Defining the

optimal preservation and storage conditions for fresh apples is beneficial since unsuitable preservation and

storage methods cause losses of fruits and vegetables that range from 10% to 30% (Yaldiz and Ertekin 2001).

The development of new, high quality and consumer attractive dried fruit products is necessary to widen product

availability and diversify markets, particularly since fresh fruit consumption is generally below the levels

recommended in normal diet (Contreras et al. 2008).

Color is an important fruit quality attribute of fruit which occurs in the interaction among light,

observed object and observer (Yam and Papadakis 2004). Color changes are mostly related to browning

reactions that take place during drying of fruits and vegetables. There are many studies about pretreatments of

fruit in order to minimize adverse changes occurring during drying and rehydration (Son et al. 2001; Guerrero-

Beltran et al. 2005; Doymaz, 2006 and 2007). The browning of fruits and vegetables during drying appears due

to both enzymatic and non-enzymatic reactions (Vadivambal and Jayas 2007). To define and display color it is

necessary to select a color space which is a mathematical representation of a set of colors. The three most

common color spaces are: RGB (used for television, computer screens, scanners and digital cameras), CMYK

(used by the printing industry) and the CIE Lab space (used in laboratory colorimeters). Colorimeters measure

color parameters on small rounded area and give nonobjective results on colored samples with different color

area. Most objective color assessment can be obtained using image analysis of all visible surface of analyzed

sample. These techniques can be applied on both sides of apple, reddish and greenish to ensure more objective

results because almost 100% of apple surface is captured in an image. Color changes measured in RGB color

model can be separated in color channels with intensity values for red, green and blue color from 0 to 255

(Magdić and Dobričević 2007).

For the food technologist properties such as color, shape (shrinkage) and rehydration capacity are

determinant for the quality of the dried product (Fernandez et al. 2005). Drying is probably one of the oldest

methods of food preservation and also well researched scientific area (Lewicki and Jakubczyk 2004; Velić et al.

2004; Lewicki 2006; Sacilik and Elicin 2006; Kaya et al. 2007; Margaris and Ghiaus 2007; Doymaz 2008;

Lertworasirikul 2008). Thousands of years of experience and trial-error methods as well as research done during

the last hundred years resulted in development of a variety of drying methods and drying equipment.

The aim of this research was to investigate the impact of drying kinetics and different chemical

pretreatments on color changes of organic apple slices during the drying process. The effect of temperatures and

3

pretreatments on the quality of dried apple samples was determined on the basis of color and rehydration

characteristics. For this purpose color changes were measured by two different methods and results were

compared.

4

MATERIAL AND METHODS

Material

Organically grown apples (var. Florina) were obtained from the local small family farm and stored at +4

°C. After stabilization at the ambient temperature, apples were hand peeled and cut into tube-shaped samples, 20

mm diameter and 5 mm height.

Drying method

Drying was performed in a pilot plant tray dryer (UOP 8 Tray Dryer, Armfield, UK). The dryer operates

on the thermogravimetric principle. The dryer (Fig. 1) is equipped with controllers for controlling the

temperature and airflow velocity. Air was drawn into the duct through a diffuser by a motor driven axial flow fan

impeller. In the tunnel of the dryer there were carriers for trays with samples, which were connected to a balance.

The balance was placed outside the dryer and continuously determined and displayed the sample weight.

FIG. 1.

The drying temperatures for nontreated apple samples had varied from 50 °C, 60 °C and 70 °C. The

dryer was operated at air velocity of 1.5 ms-1

. Prior to drying at temperature of 60 °C, apple samples were treated

for four groups of analysis as follows: dipping in 0.5% ascorbic acid solution; dipping in 0.3% L–cysteine

solution; dipping in 0.1% 4–hexyl resorcinol solution and dipping in 1 % sodium metabisulfite solution. The

apple samples on trays were placed into the tunnel of the dryer and the measurement started from this point.

“Testo 350” probes, placed into the drying chamber, were used to measure the drying air temperature. Sample

weight loss and airflow velocity were recorded in five minutes interval during the drying process using a digital

balance (Ohaus, Explorer, USA) and digital anemometer (Armfield, UK). Dehydration lasted until a moisture

content of about 12% (wet base) was achieved. Dried samples were kept in airtight glass jars until the beginning

of rehydration experiments.

Determination of the total solid/moisture content

The moisture content of the dried samples was determined using a standard laboratory method. Small

quantities of each sample were dried in a vacuum oven (24 hours at 105 °C). Time dependent moisture content

of the samples was calculated from the sample weight and dry basis weight. Weight loss data allowed the

moisture content to be calculated such as follows:

w

db

mX(t)=

m (1)

5

Color measurements

The color characteristics were used as quality parameter of the dried apple samples. Color measurement

was done using Minolta CR-400 Chromameter and image analysis system. Data were stored in CIE Lab and

RGB color models and color changes during this period were evaluated. The total color difference in CIE Lab

color model was calculated as follows:

( ) ( ) ( )2 2 2

Lab∆E = ∆L + ∆a + ∆b

(2)

Parameter L refers to the lightness of the samples, and ranges from black = 0 to white = 100. A negative value of

parameter a indicates green, while a positive one indicates red–purple color. Positive value of parameter b

indicates yellow while negative value indicates blue color. Samples were placed on the measure head of CR-400

and measurements of color were performed for all prepared samples. A standard white color was used for

calibration.

Color changes in RGB color model were followed by image analysis. Basic elements of image analysis

system shown in Fig 2. were lightening chamber with low voltage halogen lamps with reflector (provided

illumination of sample area of 760±5 Lux), digital camera (Panasonic Lumix DMC-FZ30) and software for

image preprocessing and analysis (IrfanView, Adobe Photoshop, Global Lab Image/2). Samples for imaging

were placed at 60 cm from camera.

FIG 2.

Images were stored in bitmap (BMP) graphic format with 8-bit pallet (28 = 256 colors) and after that were

processed and analyzed. This graphic format stores information about colors in RGB-triplets for every pixel on

the image where red (R), green (G) and blue (B) are intensities of mentioned colors in range from 0 to 255.

Program calculated average percentage of red (R), green (G) and blue (B) color on a sample area. An average

share of each color on sample surface was presented as the final result. Color changes in RGB color model were

defined as:

( ) ( ) ( )2 2 2

∆E = ∆R + ∆G + ∆BRGB

(3)

where ∆R, ∆G and ∆B were differences between color values of fresh apple samples and color values of dried

samples. Average values of color and color changes of apples were calculated for both color models.

6

Rehydration

Rehydration characteristics of the dried products were used as a quality index and they indicated the

physical and chemical changes that occurred during the drying and were influenced by processing conditions,

sample compositions, sample preparation and extent of structural and chemical disruptions induced by drying

(Krokida and Maroulis 2001).

Approximately 3 g (±0.01 g) of dried samples were placed in a 250 ml laboratory glass (two

measurements for each sample), 150 ml distilled water was added, the glass was covered and heated for 3 min up

to the boiling point. The content of the laboratory glass was then cooked for 10 min by mild boiling and cooled.

Cooled content was filtered for 5 min under vacuum and weighted. The rehydration ratio (RR) was used to

express ability of the dried material to absorb water. It was determined by the following equation:

r

d

WRR=

W (4)

Drying rate curve determination

Page's exponential model successfully describes the drying kinetics of food materials (Velić et al. 2004;

Simal et al. 2005; Bozkir 2006; Wang et al. 2007; Singh et al. 2008). The authors also used this model to

describe the changes of moisture content and drying rates. To avoid some ambiguity in results due to differences

in initial sample moisture, the sample moisture was expressed as dimensionless moisture ratio ( 0X'=X(t)/X ) .

The drying curve for each experiment was obtained by plotting the dimensionless moisture of the sample vs. the

drying time. For approximation of the experimental data and calculating drying curves (Eq. 5) and drying rate

curves (Eq. 6), the simplified model was used, as follows:

( ) )(-ktn

etX' = (5)

( ) ( )tX'tnk

dt

dX' 1n⋅⋅⋅=−

− (6)

The parameters k and n were calculated by non-linear regression method (Quasi-Newton) using

Statistica 6.0 computer program. The correlation coefficient (r2) was used as a measure of model adequacy.

7

RESULTS AND DISCUSSION

Fig. 3 shows experimental data of moisture contents at 50 °C, 60 °C and 70 °C and the fitting to Page's

model (mod_50, mod_60 and mod_70) versus drying time at different temperatures. It can be seen that a good

agreement exists between the experimental data and the chosen mathematical model (Page's model), which is

confirmed by high values of correlation coefficient in all runs (R2 = 0.99981 - 0.99989). Results show that the

temperatures had a significant effect on the drying rates of apple. The variation of moisture content and drying

time was obtained at each drying temperature. Drying of apple samples at higher temperature resulted in shorter

drying time, as it was expected.

FIG. 3.

Fig. 4 shows typical drying curves versus drying time for different drying temperatures. Apples did not

exhibit a constant rate period of drying. The entire drying took place in the falling rate period.

FIG. 4.

Fig. 5 shows experimental moisture content versus drying time for different pretreatments at air velocity

of 1.5 m s-1

and drying temperature at 60 °C.

FIG. 5.

Fig. 6 shows drying rate vs. drying time for different pretreatments at air velocity of 1.5 m s-1

and

drying temperature at 60 °C. It can be seen that different pretreatments decrease the drying time compared to

nontreated apple samples.

FIG. 6.

Fig. 7 shows total color difference in both color models CIE Lab and RGB versus different drying

temperatures for nontreated apple samples. ∆ELab values varied from 9.4 to 11.42, whereas ∆ERGB values varied

from 12.39 to 21.74. The smaller color changes were observed where apple samples were dried at 60 °C.

FIG. 7.

Fig. 8 shows total color changes in both color models CIE Lab and RGB of pretreated apple samples

versus different pretreatments at air velocity of 1.5 m s-1

and drying temperature at 60 °C. ∆ELab values for

pretreated apple samples varied from 5.72 to 9.38, whereas ∆ERGB values varied from 2.01 to 39.22. Chemical

pretreatment with 0.1% 4–hexyl resorcinol give the smaller change of color in both color models. It can be seen

the big difference in color changes between two chosen color models in the case of pretreatments with ascorbic

acid. It depends on chosen area of analyzed apple sample surface. Lab values differs because of small diameter

8

of measuring head of instrument Meanwhile, using image analysis in RGB color model all area of analyzed

apple sample is included.

FIG. 8.

Fig. 9 shows RGB color space in pixels vs. luminosity of dried apples for different pretreatments and

drying temperature at 60 °C. The biggest luminosity changes were observed on samples pretreated with ascorbic

acid. Color content is expressed in nuances from 0 to 255. Samples closer to nuance 255 were lighter and the

samples closer to 0 showed darker color.

FIG. 9.

Fig. 10 shows rehydration ratio versus different drying temperatures for drying of nontreated apple

samples. The rehydration ratio was affected significantly by the drying temperatures. Rehydration ratio for

nontreated apple samples decreased as the drying temperature increased. The results show that the longer the

exposure time of apple samples to certain temperature is the higher are the irreversible degradation changes.

FIG. 10.

Fig. 11 shows rehydration ratio versus different pretreatments of apple samples. It can be seen that

dipping in 0.1 % 4–hexyl resorcinol solution resulted in the highest rehydration, compared to other

pretreatments.

FIG. 11.

9

CONCLUSIONS

Air drying of apple samples could be modeled using Page’s equation. The results of the estimation

exhibited correspondence to the experimental results. Increase in the drying air temperature caused a decrease in

the drying time and an increase in the drying rate. Rehydration rates and color characteristic of apple samples

were found to be dependent on drying conditions. The rehydration ratio decreased as the drying temperature

increased. Also, rehydration ratio of all treated samples was higher as compared to nontreated samples. In view

of the color measurements for nontreated apple samples calculated correlation among used color models was

found to be 0.97, and for pretreated apple samples correlation was equal to 0.37.

According to drying time, rehydration and color characteristics the optimal drying temperature was

found to be 60 °C. The best results (reduced drying time, high rehydration ratio and minimum color change)

were achieved when samples were pretreated with 4–hexyl resorcinol.

Today’s consumer expectation for better food quality drives research and improvement of drying

technologies. The observed differences in the drying kinetics and pretreatments should be considered when

selecting the best drying condition in order to improve the final product quality. The investigation of economic

parameters of different drying pretreatments should be considered as well.

ACKNOWLEDGMENTS

This work was financially supported by Ministry of Science, Education and Sports of the Republic of Croatia,

projects 113-0000000-3497 and 113-1130471-0592.

10

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Figures

Fig. 1. Schematic diagram of the convection drying equipment

Air outlet Air inlet

Digital

anemometer Trays

Heat power control

Fan speed

control

Digital

balance

Heaters

Thermocouples to PC

Relative humidity couples

to «Testo 350»

Door

Thermocouples

to «Testo 350»

13

1. Lightning chamber

2. Light source

3. Digital camera

4. Background for sample

5. Sample for analysis

6. Computer

Fig. 2. Image analysis system

14

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 50 100 150 200 250 300 350 400

t [min]

X'

50 °C

60 °C

70 °C

mod_50 °C

mod_60 °C

mod_70 °C

Fig. 3. Experimental and approximated moisture content of nontreated dried apple samples

15

0.000

0.005

0.010

0.015

0 100 200 300 400

t [min]

-dX

'/dt [m

in -1

]

50 °C

60 °C

70 °C

Fig. 4. Drying rate dynamics of nontreated apple samples at different temperatures

16

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 50 100 150 200 250 300

t [min]

X'

NT

AK

LC

4H

NaB

Fig. 5. Changes of apple moisture content at 60 °C drying temperature after different pretreatments

17

0.000

0.003

0.006

0.009

0.012

0 40 80 120 160 200 240 280

t [min]

-dX

'/dt

[m

in -1

]

NT

AK

LC

4H

NaB

1

Fig. 6. Drying rate dynamics of pretreated apple samples at 60 °C drying temperature

18

0

5

10

15

20

25

50 ºC 60 ºC 70 ºC

∆E

Lab

RGB

Fig.7. Total color changes (∆ELab and ∆ERGB) of nontreated apple samples at different drying temperatures

19

0

5

10

15

20

25

30

35

40

45

NT AK LC 4H NaB

∆E

Lab

RGB

Fig. 8. Total color changes (∆ELab and ∆ERGB) of pretreated apple samples at 60 °C drying temperature

20

0

500

1000

1500

2000

2500

3000

3500

4000

4500

100 120 140 160 180 200 220 240

luminosity

pix

els

1_NT

2_4H

3_AK

4_LC

5_NaB

1

23

4

5

Fig. 9. Dried apples luminosity after different pretreatments at 60 °C drying temperature

21

5.20

5.40

5.60

5.80

6.00

6.20

6.40

6.60

6.80

50 °C 60 °C 70 °C

RR

Fig. 10. Rehydration ratio (RR) of nontreated apple samples at different drying temperatures

22

0

1

2

3

4

5

6

7

8

9

10

NT AK LC 4H NaB

RR

Fig. 11. Rehydration ratio (RR) of pretreated apple samples at 60 °C drying temperature