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The effect of different frying conditions on the color parameters of purple sweet potato (Ipomoea Batatas Poiret) slices
Article in Carpathian Journal of Food Science and Technology · June 2017
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35
THE EFFECT OF DIFFERENT FRYING CONDITIONS ON THE COLOR PARAMETERS OF PURPLE SWEET POTATO (Ipomoea batatas Poiret)
SLICES
Rahmat Fadhil1*, Diswandi Nurba2, Kiki Ikhwanto2
1 Department of Agricultural Engineering, Syiah Kuala University, Jalan Teungku Hasan Krueng Kalee No.3 Darussalam 23111, Banda Aceh, Indonesia
2 Laboratory of Postharvest Technology, Syiah Kuala University, Darussalam 23111, Banda Aceh, Indonesia
Article history:
Received :
26 April 2016 Accepted :
6 June 2017
ABSTRACT
The aim of the research was to analyze of the surface color measurement to the pre-frying and post-frying purple sweet potato (Ipomea batatas Poiret) slices by using a combining device i.e. the digital camera and the graphic software. It is believe that such analysis method able to observe colors and an average in a value of L*a*b* units of food ingredient surfaces. The digital images of purple sweet potato slices could be displayed on the computer screen or printed on a certain piece of paper their colors and structures can be analyzed. To do so, the method of digital image application is used, namely a digital camera Canon Ixus 145 without using the camera light and with the distance focus of 10 cm from the object.
Following that, the resulted images, were plotted against colors on the Adobe Photoshop CS5. The results show that the use of the Adobe Photoshop CS5 software is extremely helpful in measuring colors of purple sweet potato chips due to the fact that it could bring a consistency when defining colors of pre-frying and post-frying slices with the system model of L*a*b* units. Overall, this study found that there is no difference in colors between pre-frying purple sweet potatoes and the post-frying ones in various treatments by the variance analysis and continued to the Duncan Multiple Range Test (DMRT) at a confidence level of 95 percent (p<0.05), except those in a fractional number of treatments.
Keywords:
Color;
Purple sweet potato;
L*a*b* model;
Frying;
Adobe Photoshop CS5.
1. Introduction
A food visual appearance is still a primary consideration for consumers to assess and decide to buy a food product. The food color is relatively one important parameter for consumers to select foods that would be consumed. This, at once, becomes a decision in accepting those food ingredients, whether it is proper to be accepted by consumers. The visual on colors sometimes is more preferred by consumers rather than observation on other quality parameters and it provides a clue regarding chemical changes in food ingredients (Winarno, 2002). The digital image is a
process aiming to manipulate and analyze color images in which involves many visual perceptions and supported by a computer. The image processing aims to see the detail of image qualities in order to be interpreted easily by humans or machines (Wijaya et al., 2007).
Overall, there are three measurement models of a color space, those are the RGB (red, green, blue) model (for televisions, computer screens, scanners, and digital cameras), the CYMK (cyan, magenta, yellow, black) model (for printing industries) and the CIE Lab model or also called as the L*a*b*
color m o d e l (used in laboratories of
Fadhil et al. Carpathian Journal of Food Science and Technology 2017, 9(2), 35-42
36 color
measurement) (Fernandez et al., 2005). The color model most commonly used is the L*a*b*
color model since it has a homogenous color distribution (Leon et al., 2005, Zhang et al., 2010). The homogeneity of color perceptions carries an appropriate guarantee of color differences and is essential for the process of segmentation (Dong & Xie, 2005). This color space is able to depict all colors that could be seen by human eyes and is often used as a reference of color spaces (Yam & Papadakis, 2004).
The color measurement of food ingredients in L*a*b units is an international standard of a color measurement developed by the Commission Internationale d’Eclairage (CIE) in 1976. The L*a*b color model comprises 3 components, those are the L* dimension as luminance (color brightness) whose the value ranges from 0 to 100, in which 0 is for black and 100 is for white; the a* dimension describing the color types of green-red, in which a negative indicates a green color and the reverse indicates a red color; and the b*
dimension for the color types of blue-yellow, in which a negative indicates a green color and the reverse indicates a yellow color. The a* and b* dimensions are color dimensions opposite to each other ranging from -120 to +120. The L*a*b is an independent device that provides consistent colors regardless of the inputs or outputs. It is specifically devices of digital cameras, scanners, monitors, and printers (Widiasri, 2013; Lukinac et al., 2009; Yam and Papadakis, 2004).
Soaking in the sodium bicarbonate (NaHCO3) solution aims for crisping and would produce the CO2 gas. As the concentration of NaHCO3 improves, more gas will be generated in food ingredients when the frying process is conducted. This gas builds some pores in the food ingredients. Due to a large number of pores in the ingredients, their mass becomes lower and will be friable to loads or outer forces exposed to them. As more pores are built, the texture of chips produced will be much crispier (Shinta et al., 1995; Putranto et
al., 2013). The NaHCO3 is one of cake improvers and a firming agent of fried foods in the form of white powder. As the concentration of NaHCO3 and the frying temperature increase, the hardness value of chips will decline (Winarno, 2002).
2.Materials and methods 2.1. Tools and material
The tools used in this study were knifes, peel removers, stoves, pans, plastic washbasins, food jars, plastic bags, manual chip slicers, digital scales, thermometers, a digital camera Canon Ixus 145 (DIGIC 4, 16.0 MP, 28-224 mm, 8x optical, 16x zoom plus, 1600 max. ISO value, ½.3 type CCD, 2.7- i n c h LCD), and the Adobe Photoshop CS5 program (Adobe System, 2010).
The main material used in this research was the purple sweet potato obtained from famers in the Sare area, Aceh Besar Regency, Aceh Province, Indonesia. Purple sweet potatoes used in this study were cropped in approximately 4-5 months of age after planting. In addition, supporting materials included in this research were sodium bicarbonate (NaHCO3), salt (NaCl), water, and Bimoli brand cooking oil produced by PT. Salim Ivomas Pratama Tbk.
2.2. Research procedures
The fresh purple sweet potatoes were washed to get rid of any dirt, then they were weighed in 500 grams and sliced in various thicknesses of 1 mm, 2 mm, and 3 mm. After slicing, each of them were weighed before soaking in a solution of 2% salt and 1 L of water within 10 minutes. Following that, the next soaking used a solution of NaHCO3 at concentrations of 1 gram/liter water, 3 grams/liter water, and 5 grams/liter water within 30 minutes respectively in order to enable chips to be crispy. Then, the analysis of pre-frying purple sweet potatoes was conducted.
The purple sweet potato slices were fried on the stove at the temperatures ranging from 145oC to 150oC for 2-3 minutes. The volume of cooking oil was 2 L for 500 grams of sweet
37 potato s l i c e s from various thicknesses and
NaHCO3 concentrations. The cooking oil was replaced in each completed frying so as each treatment was conducted with the new cooking oil. A thermometer was inserted directly into the oil in order to keep the temperature range desired. Since the temperature stability of frying purple sweet potato chips would determine colors and crispness of chips produced, the chips from each treatment, after frying, were weighed and putted into jars. Finally, the color measurement of post-frying sweet potato slices was carried out.
2.3. The color measurement
The method of digital image taking was conducted with a Canon Ixus 145 digital camera having a resolution of 16 megapixels without the camera light and with the focus distance of 10 cm from objects in light rooms.
The digital image taking was performed in two times of repetitions in each treatment of ingredients. The digital images obtained were saved in the SanDisk Ultra 30 MB/s memory
card at a capacity of 8 GB in the PNG (Portable Network Graphics) format. Those images, then, were transferred to a PC to be plotted against colors on Adobe Photoshop CS5, thereby obtaining the RGB (Red, Green, Blue) values at a color intensity ranging from 0 to 225 (Magdić and Dobričević, 2007; Lukinac et al., 2009).
Hue angles were obtained using the method described by Precil (1953), that is:
Where R0, G0 and B0 indicate the color parameters of sweet potato slices. The calculation of R, G, and B values were shown by the 0o (red), 60o (yellow), 120o (green), 180o (cyan), 240o (blue), 300o (magenta) degrees.
The average values of each color of purple sweet potato slices were presented as the final result of the color determination plotted along R, G, B axises (Figure 1).
Figure 1. The graphic representation of color spaces along R, G and B axis (White, 2003).
Accordingly, the values of X, Y, Z could be calculated using an
equation from the Commission on Illumination (CIE) (White, 2003) as follows:
X = 0,607R+0,174G+0,201B Y = 0,299R+0,587G+0,114B Z = 0.066G+1.117B
Fadhil et al. Carpathian Journal of Food Science and Technology 2017, 9(2), 35-42
38 Subsequently, by using the system of Hunter-Lab, the values of a* and b* that would be plotted into the L*a*b* (Hunter-Lab, 2008) units were gained; therefore digital images of purple sweet potato chips were obtained.
L* = 25(100Y/100)1/3-16
a* = 500[(X/98.071)1/3-(Y/100)]1/3 b* = 200[(Y/100)1/3-
(Z/118.225)]1/3
2.4. The experiment design
This research used the Randomized Completely Design with 3 treatments and 2 repetitions. Factors that were tested included the purple sweet potato thicknesses of 1 mm, 2 mm, and 3 mm as well as the sodium bicarbonate (NaHCO3) concentrations of 1 gram/liter, 3 grams/liter and 5 grams/liter.
Hence, there were 9 combinations of the treatment and 2 repetitions so as the total was 18 experimental units. Data obtained, then, was subjected to Analysis of Variance (ANOVA) using a SAS software, version 9.1.3 (SAS Institute Inc., 2006) and was tested further by the Duncan Multiple Range Test (DMRT) at the uncertainty of 5% (Gomez and Gomez, 1984; Sastrosupadi, 2000; Steel and Torie, 1980).
3.Results and discussions
There are several reasons to select the Adobe Photoshop as a color measurement method. Firstly, this software has numerous features of picture editing and an analysis capability comparable to other more expensive softwares. Secondly, this software also provides a more advance capability to manage colors and create consistent colors rather than other graphic softwares. Furthermore, it is available in many computer laboratories and also supported by the manufacturer and users (Yam et al., 2004).
The average values of pre-frying and post- frying color measurements from various treatments and thicknesses of purples sweet potato slices were obtained using the Adobe Photoshop CS5. The L*, a*, and b* values from purple sweet potato slices could be seen
in Table 1. The L* average values of purple sweet potato slices gained range from 48.01 (the lowest) to 74.10 (the highest). The former was obtained from a treatment of 3 grams/1 L water NaHCO3 concentration and a slice thickness of 2 mm (K2S2) and the latter was obtained from a treatment of 5 grams/1 L water NaHCO3 concentration and a slice thickness of 3 mm (K3S3). Whereas, the a* average values of purple sweet potato slices gained range from -8.28 (the lowest) to 27.04 (the highest). The former was obtained from a treatment of 3 grams/1 L water NaHCO3 concentration and a slice thickness of 3 mm (K2S3) and the latter was obtained from a treatment of 1 gram/1 L water NaHCO3 concentration (K1S1) and a slice thickness of 1 mm (K1S1). Whilst, the b*
average values of purple sweet potato slices gained range from 3.59 (the lowest) to 64.49 (the highest). The former was obtained from a treatment of 3 gram/1 L water NaHCO3
concentration and a slice thickness of 1 mm (K2S1) and the latter was obtained from a treatment of 5 grams/1 L water NaHCO3
concentration and a slice thickness of 1 mm (K3S1).
This color measurement is extremely important in food industries since a large amount of information, nowadays, could be received from measurements at the level of pixels that would enable better characterizations of food color images. The measurement in identifying food colors commonly used is the one with the model of L*a*b* units, due to the homogenous distributions so as the results resemble colors perceived by humans (Leon et al., 2006;
Papadakis et al., 2000; Segnini et al., 1999).
In brief, the results show that there is no significant difference among colors created from the treatment of various NaHCO3
concentrations and the different thicknesses of purple sweet potato slices (L*: K1S1, K2S1, K3S1; a*: K1S1, K2S1, K1S2, K2S2, K3S2, K1S3, K2S3, K3S3; b*: K1S1, K2S1, K2S2, K3S2, K1S3, K2S3, K3S3).
39
Table 1. The L*a*b* unit values of pre-frying and post-frying purple sweet potato slices
3S3
The notification of same words in each column shows that there is no statistically significant difference (P>0.05)
Descriptions:
K1S1 = the NaHCO3 concentration of 1 gram and the thickness of 1 mm K2S1 = the NaHCO3 concentration of 3 grams and the thickness of 1 mm K3S1 = the NaHCO3 concentration of 5 grams and the thickness of 1 mm K1S2 = the NaHCO3 concentration of 1 gram and the thickness of 2 mm K2S2 = the NaHCO3 concentration of 3 grams and the thickness of 2 mm K3S2 = the NaHCO3 concentration of 5 grams and the thickness of 2 mm K1S3 = the NaHCO3 concentration of 1 gram and the thickness of 3 mm K2S3 = the NaHCO3 concentration of 3 grams and the thickness of 3 mm K3S3 = the NaHCO3 concentration of 5 grams and the thickness of 3 mm
Initial K1S1 K2S1 K3S1 K1S2 K2S2 K3S2 K1S3 K2S3
K
L* Pre 62.73 + 3.48 a 66.66 + 5.15 a 63,39 + 2.48 a 65,5 0 + 7.19 a 67,8 7 + 2.50 a 70,5 4 + 1.30 a 70,33 + 11.73 a 68,69 + 7.39 74,1 0 + 3.59 a Post 62,43 + 5.03 a 57.25 + 14.08 a 55,27 + 1.81 a 51,4 3 + 0.00 b 48,0 1 + 0.00 b 57,0 8 + 8.02 b 60,25 + 0.79 a 65,55 + 4.99 60,4 7 + 9.72 a
a* Pre 27,04 + 16.14 a 10,59 + 13.37 a 13,45 + 1.97 a 8,7 3 + 6.18 a 3,0 0 + 4.16 a 6,76 + 12.77 a 3,51 + 6.21 a 4,04 + 14.58 a -2,4 2 + 0.13 a Post 7,41 + 4.76 a 6,31 + 10.87 a 6,26 + 1.44 b 2,84 + 11.15 a 6,2 5 + 2.25 a 3,0 9 + 2.97 a 5,97 + 4.37 a -8,28 + 8.45 a -3,5 4 + 7.96 a b* Pre 12,44 + 1.86 a 3,59 + 1.05 a 8,56 + 5.55 a 11,6 4 + 0.13 a 5,8 4 + 8.46 a 13,1 6 + 4.68 a 12,50 + 4.37 a 11,22 + 1.35 a 10,8 7 + 1.08 a Post 6,55 + 1.35 a 6,85 + 4.51 a 64,49 + 17.90 b 4,8 2 + 0.91 b 14,2 2 + 9.59 a 11,4 5 + 6.48 a 4,07 + 9.48 a 12,94 + 12.55 a 13,4 1 + 1.89 a
Fadhil et al. Carpathian Journal of Food Science and Technology 2017, 9(2), 35-42
40
Figure 2. The graph of Pre-frying L*a*b values (Adopted from Konicaminolta, 2003)
Figure 3. The graph of Post-frying L*a*b values (Adopted from Konicaminolta, 2003)
41 Hoever, several other treatments show a significant difference between those of pre- frying and post-frying (L*: K1S2, K2S2, K3S2; a*: K3S1; b*: K3S1,
K1S2) (Table 1). Figure 2 and Figure 3 also show the different L*a*b* values gained.
Apparently, it is due to the inhomogeneous color of those purple sweet potato slices resulting in the different L*a*b* values of each thickness and NaHCO3 concentration.
4.Conclusions
The use of the Adobe Photoshop CS5 software is very helpful in analyzing colors of purple sweet potatoes as it could provide a consistency in defining colors of pre-frying and post-frying slices with the system model of L*a*b* units. Overall, there is no significant difference among several treatments of pre- frying and post-frying purple sweet potatoes by the Duncan Multiple Range Test (DMRT) at the confidence level of 95 percent (P<0.05), except in a fractional number of treatments.
Consumer decision on food products, particularly is based on the visual perception and this becomes commonly the only one immediate decision of the food product acceptance. This coverage eventually suggests that an analysis model of this system could be used in analyzing colors of a food product, particularly in observing the color distribution of food ingredient surfaces having the average values within L*a*b* units. Later on, it is necessary to conduct a further research, in particular for the application on different food ingredients and products.
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