Mehran Nouri; Behzad Nasehi; Vahid Samavati; Saman Abdanan
Abstract
Introduction: Fried foods such as donuts enjoyed worldwide for their taste, distinctive flavor, aroma and crunchy texture. There is, however, grave health concern over large fat content of fried foods (Melito and Farkas, 2013). There are several ways to lower fat content in deep-fried foods. One method ...
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Introduction: Fried foods such as donuts enjoyed worldwide for their taste, distinctive flavor, aroma and crunchy texture. There is, however, grave health concern over large fat content of fried foods (Melito and Farkas, 2013). There are several ways to lower fat content in deep-fried foods. One method is to reformulate the product by adding hydrophilic ingredients such as dietary fibers to reduce oil uptake during frying. Another method to reduce fat content is to partially cook the food using another heating method (Melito and Farkas, 2012). There is an increasing interest in microwaving foods for several reasons: it is faster than conventional methods, the energy consumption is often lower and foods cooked by microwaving maintain nutritional integrity.vIn foods, the appearance is a main criterion in making purchasing decisions. Appearance is used throughout the production –storage-marketing-utilization chain as the key means of judging the quality of individual units of product. The appearance of unities of products could be assessed by considering their color and surface texture. The use of computer-vision technology has quickly increased in the fields of quality inspection, classification and evaluation in processing a large number of food products (Brosnan and Sun, 2004). Therefore the aim of this study was to study the effects of microwave pre-treatment on sensory and appearance properties of donut.
Materials and methods: Response surface methodology and Box- Behnken design were applied to evaluate the effects of independent variable include microwave power (300-900 W), microwave time (30-90 s) and frying time (70-130 s) on sensory and appearance properties of donuts. Donuts were prepared according to the formulation by Melito and Farkas (2012) with some modifications. Ingredients used in donuts formulation were consisted of 100 g of wheat flour (9 g/100g), 52 g of water, 9.75 g of Shortening, 14 g of Egg, 14 g of water for yeast, 6.80 g of sugar, 6.80 g of nonfat dried milk powder, 3.25 g of active dried yeast, 1.70 g of Vanilla extract, 1.7 g of baking powder, 1.70 g of Salt, 1.3 g of Persian gum and 7.00 g of carrot pomace powder. The dough was cut into squares approximately 50 mm on each side. Then, the dough pieces were allowed to proof for 30 min at 27 ºC. The proofed samples were pre-treated using a microwave oven at different levels of microwave power and microwave time in accordance with the experimental design. Formerly, the per-treated donuts were deep-fat fried in a Moulinex deep-fat fryer (model F18-RA, France) filled with 1.5 L of vegetable frying oil (A mixture of Sunflower, palm, and soybean oil; Behshahr CO., Tehran, Iran) at different levels of frying time in accordance with the experimental design. The oil was preheated for 30 min prior to frying and replaced with fresh oil after every frying process. After frying, donuts were removed from the fryer and allowed to cool for 30 min on paper towels. They were then stored in coded sealed polyethylene bags.The evaluation of the crumb grain and crust color of donuts was performed using an image analysis system consisted of a Canon digital camera (model SX60 HS, Japan) and a personal computer with a Pentium(R) Dual-Core processor and Windows 7 Ultimate. The samples were photographed at a fixed distance of 30 cm from the crumb of samples, which were sitting inside a black box. The captured images were analyzed using the MATLAB R2014a software (The MathWorks Inc., Natick, Mass, USA).The CIE L*a*b* (or CIELAB) color model was used for determination of the crust color of donuts. Crumb grain features of the donut samples were obtained with described digital image analysis system. After imaging, each image was converted from RGB format to 8 bits (grey level) using the MATLAB software. In this format, an area of 3 × 3 cm2 was selected at the center of the captured image. After contrast enhancement of image, the image segmented using the Otsu algorithm, which produces highly uniform binary images (Otsu, 1979). Finally, crumb grain properties of donuts were studied by determination of cells densities and area of cells. Sensory evaluation of donut samples was carried out by assigning scores for crust appearance, crumb appearance, crust color, aroma, texture, taste and overall acceptance parameters based on a nine-point hedonic scale. (Stone et al., 2012).
Results and discussion: Results showed that roughness of the donuts surface increased significantly (p
Mehran Nouri; Behzad Nasehi; Vahid Samavati; Saman Abdanan
Abstract
Introduction: Increased awareness of diet-health association has led to the growth of health food industry. Deep-fat fried foods such as donuts enjoy wide popularity owing to their taste, distinctive flavor, aroma and crunchy texture. There is, however, a great health concern over large fat content of ...
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Introduction: Increased awareness of diet-health association has led to the growth of health food industry. Deep-fat fried foods such as donuts enjoy wide popularity owing to their taste, distinctive flavor, aroma and crunchy texture. There is, however, a great health concern over large fat content of fried foods. Incorporating the dietary fiber such as hydrocolloids into the food substrate in the batter formulation is one of the most effective strategies to decrease fat uptake in fried foods. Dietary fibers act as water binders in a coating or batter formulation through which reduce fat uptake of fried foods. That is, an increase of water content of food could lead to a decrease of oil penetration during the frying process. Persian gum (PG), as a novel gum, is exudates of the wild or mountain almond trees (the main source is Amygdalus scoparia Spach). Carrot pomace is a fibre-rich by-product of carrot juice industries which contains approximately 80% of carrot carotenes. Carrot juice yield is reported to be only 60-70% and the remaining pomace is usually disposed of as feed or fertilizer. There is an increasing interest in microwaving foods for several reasons: it is faster than conventional methods, the energy consumption is often lower and foods cooked by microwaving maintain nutritional integrity. Therefore, the aim of this study was to examine the effect of microwave pre-treatment on physico-chemical properties of donut containing Persian gum and carrot pomace powder sources of dietary fiber.
Materials and methods: Donuts were prepared according to the formulation reported by Melito and Farkas (2012). Ingredients used in control donut formulation were consisted of 100 g of wheat flour (9 g/100g), 38 g of water, 9g of Shortening, 13g of Egg, 13g of water for yeast, 6.3g of sugar, 6.3g of nonfat dried milk powder, 3g of active dried yeast, 1.6g of Vanilla extract, 1.6g of baking powder, and 1.6g of Salt. For the making of donuts, the flour blends were prepared by replacing wheat flour with 1.2 g/100g PG and 645 g/100g CPP. As well, water was added at 48.16 g/100g based on flour weight. The exudate gums of mountain almond trees were collected in Lorestan province. In order to eliminate foreign matters such as dust and dirt, the PG was washed three times with its threefold weight of ethanol (96% w/v) for 15 min under constant stirring. After removing ethanol by drying in an oven (at 60º C for 6 h) the PG was ground using a coffee grinder (model 320, Spain), sieved (180 µm) and packaged in polyethylene packs and then stored in 4ºC. Fresh carrots were purchased from a local market. Carrots were washed and then pressed with a juice extractor and the resultant pomace was collected. The carrot pomace was blanched in water (80 ± 2°C for 3 min) and then cooled in cold water (4º C). The pomace water was drained with cheese-cloth prior to drying. Finally, the carrot pomace was dried in an oven (60º C for 12 h). The dried pomace was ground using a coffee grinder to fine powder. The carrot pomace powder was sieved (180 µm) and packed in polyethylene packs and then stored in 4ºC. Specific volume of donuts was determined using the rapeseed displacement AACC method. Moisture content of donuts crumb was measured using a oven at 105 ºC for 3. The fat content of dried donuts was determined by Soxhlet extraction with petroleum ether for 5 h. Firmness and springiness were measured in triplicate using a TA.XT2i Texture Analyzer equipped with a 5 kg load cell and a P/35 mm aluminum cylindrical probe. Crumb grain (total number of cells and porosity) and crumb color of donuts were evaluated using an image analysis system consisted of a digital camera, a personal computer and MATLAB R2014a software. The control and optimized donuts were evaluated for acceptance of their appearance, crust color, crumb color, aroma, texture, taste and overall acceptance based on a nine-point hedonic scale. Response Surface Methodology (RSM) and Box-Behnken design with 3 factors were applied to obtain optimal levels of independent variables including microwave power (300-900 W), microwave time (30-90 s) and frying time (70-130 s).
Results and discussion: The results indicatedthat moisture content significantly (p
Saman Abdanan; Mehran Nouri; Maryam Soltani Kazemi; Somaye Amraei
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 ...
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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
