Document Type : Research Article
Authors
1 Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan, Iran.
2 Department of Food Science, Faculty of Animal and Food Science, Ramin Agriculture and Natural Resources University of Khuzestan, Iran.
Abstract
Introduction: Nutritional quality of food during storage has become increasingly an important problem. The loss of some nutrients such as ascorbic acid (vitamin C) might be a critical factor for the shelf life of some products as citrus juice concentrates, since vitamin C content of citrus juices undergoes destruction during storage (Plaza et al., 2011a). Ascorbic acid is an important component of our nutrition and used as additive in many foods because of its antioxidant capacity. Thus, it increases quality and technological properties of food as well as nutritional value (Larisch et al., 1998). However, ascorbic acid is an unstable compound and even under minor desirable conditions it decomposes easily. Degradation of ascorbic acid proceeds both aerobic and anaerobic pathways and depends upon many factors such as oxygen, heat, light, storage temperature and storage time. Oxidation of ascorbic acid occurs mainly during the processing of citrus juices, whereas, anaerobic degradation of ascorbic acid mainly appears during storage which is especially observed in thermally preserved citrus juices (Lee & Coates, 1999). It was reported that several decomposition reactive products occur via the degradation of vitamin C and these compounds may combine with amino acids, thus result in formation of brown pigments (Wibowo et al., 2015). In recent years, several nondestructive methods such as computer vision, spectroscopy, ultrasonic have been developed to objectively evaluate different agricultural materials (Abdanan Mehdizadeh et al., 2014; Wang and Paliwal, 2007). However, due to the physical properties of fruit, machine vision has not been discussed much in the literature (Fernanzed-Vazquez et al., 2011). One disadvantage of using spectroscopic methods is that these methods require expensive equipment and also carrying these instruments are difficult. On the contrary, the combining of a digital camera and its image processing software that replaces the traditional measuring instruments have been widely used to provide a cheaper and versatile form to measure some internal quality of many foods. Therefore, the goal of this research is to determine the best features of surface texture (entropy, homogeneity, contrast, correlation and prominence) in order to predict quality factors (pH, acidity, soluble solids and ascorbic acid) of citrus juice.
Materials and methods: Orange, sour lemon, sour orange and tangerine fruit were obtained from one of local marker in Ahvaz, Iran. All samples were washed and the juice was extracted using a Pars-Khazar rotary extractor. The citrus juice, (sour orange, orange, lemon and tangerine) immediately after pasteurization process, were kept at a temperature of refrigerators (4º C) for 60 days in darkness. After taking images of the citrus juice, pH, acidity, ascorbic acid and soluble solids were measured on days 0, 20, 40 and 60.
Physicochemical analysis:
The pH of samples was determined with a pH meter (Methrohm, 827 pH lab, Switzerland). The soluble solids content of concentrates was determined as o Bx using a refractometer (Atago Co, Ltd. Carnation, WA). Total titrable acidity was assessed by titration with sodium hydroxide (0.1 N) and expressed as % citric acid (Kimball, 1999). Ascorbic acid was determined using 2,6-dichlorophenolindophenol by visual titration (Kabasakalis, 2000).
Imaging and color analysis:
Samples were placed under the camera (Canon PowerShot SX60 HS, Japan) of a computer vision system at the distance of 300 mm inside a black box with the size of 100 ×100 ×100 cm3. The samples were illuminated using four fluorescent lamps at the angle of 45o in relation with the sample.
After taking images, color images were transformed to L*a*b* color space. The L* parameter (luminosity) is an attribute by which a surface emits more or less light and can take values between 0 (absolute black) to 100 (absolute white). The parameters a* and b* represent the chromaticity, where a* defines the red-green component (red for positive values and green for negative values) and the b* parameter defines the yellow-blue component (yellow for positive values and blue for negative values) (Quevedo et al., 2009a). Following color transformation, the well-known textural parameter called the Gray-Level Co-Occurrence Matrix (GLCM function) was applied to the images and six features through Eq. 1-6 were extracted (Table 1).
Results and discussion: Color changes during storage in three color channels L*,a*,b* showed that the variation of channel L* could illustrate deterioration of citrus juice better than other channels. In the Figure 1, a gallery of four selected images (taken at different times in the experiment) corresponding to one sour orange sample and their corresponding surface intensity (based on L* value) are showed.
The results of statistical analysis depicted that acidity and ascorbic acid, in four citrus juices, significantly (P
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