Determination of proximate composition, shelf life and fatty acid profiles of breaded kilka (Clupeonella cultriventris) during frozen storage

The present study aimed production of a new product with various texture and sensory properties in chase of the impetus for increasing human consumption considering suitable resources of Kilka fish in Caspian Sea. Following deheading, gutting, and brining, common Kilka were battered in two different formulations, i.e. simple batter and tempura batter, via automated predusting machinery and then, they were fried through flash frying for 30 seconds at 170°C in sunflower oil after they were breaded with bread crumbs flour. The products were subjected to continuous freezing at -40°C and were kept at -18°C in cold storage for four months once they were packed. Chemical composition (protein, fat, moisture, and ash), fatty acid profiles (29 fatty acids), chemical indices of spoilage (peroxide value, thiobarbituric acid, free fatty acids, and volatile nitrogen), and microbial properties (total bacteria count and coliform count) were compared in fresh and breaded Kilka at various times before frying (raw breaded Kilka), after frying (zero-phase), and in various months of frozen storage (phases 1, 2, 3, and 4). Organoleptic properties of breaded Kilka (i.e. odor, taste, texture, crispiness, cohesiveness of batter) and general acceptability in the phases 0, 1, 2, 3, and 4 were evaluated. The results obtained from chemical composition and fatty acid profiles in common Kilka denoted that MUFA, PUFA, and SFA were estimated to be 36.96, 32.85, and 29.12 g / 100g lipid, respectively. Levels of ù-3 and ù-6 were 7.6 and 1.12 g / 100 gr lipid, respectively. Docosahexaonoic acid (20.79%) was the highest fatty acid in PUFA group. ù-3/ù-6 and PUFA/SFA ratios were 7.6 and 1.12, respectively. The high rates of the indices and high percentage of ù-3 fatty acid in common Kilka showed that the fish can be considered as invaluable nutritional and fishery resources and commonsensical consumption of the species may reduce the risk of cardiovascular diseases. Frying breaded Kilka affected overall fat and moisture contents so that moisture content in fried breaded Kilka decreased significantly compared to raw breaded Kilka, while it was absolutely reverse for fat content. Overall fat content in tempura batter treatment was significantly lower than that of simple batter treatment (P≤0.05). Presence of hydrocolloids, namely proteins, starch, gum, and other polysaccharides, in tempura batter may prohibit moisture evaporation and placement with oil during frying process in addition to boosting water holding capacity through confining water molecules. During frying process, fatty acids composition of breaded Kilka with various batters changed so that rates of some fatty acids such as Palmitic acid (C16:0), Stearic acid (C18:0), Oleic acid (C18:1 ù-9cis), and linoleic acid (C18:3 ù-3) increased considerably following frying; however, ù-3/ù-6, PUFA/SFA, and EPA+DHA/C16:0 ratios (Polyan index) decreased significantly after frying. ù-3/ù-6, PUFA/SFA, and EPA+DHA/C16:0 ratios in tempura batter treatment were higher than those of simple batter treatment which is an indicator of higher nutritional value of breaded Kilka with tempura batter. Significant elevations were found in peroxide, thiobarbituric acid, and free fatty acids in fried breaded Kilka samples compared to raw samples which points to fat oxidation during cooking process. Overall microorganism count and coliform count decreased following heating process. Both breaded Kilka samples were of high sanitation quality at zero-phase according to ICMSF Standard. The results acquired from organoleptic evaluation declared that odor, cohesiveness, and general acceptability indices, among others, had significant differences between the treatments (P≤0.05). In all evaluated properties, breaded Kilka with tempura batter in different phases gained higher scores than breaded Kilka with simple batter. During cold storage of various treatments of breaded Kilka, total lipid content, PUFA, MUFA, ù-3, ù- 3/ù-6, PUFA/SFA, Polyen index decreased significantly. The mentioned reductions in addition to significant elevation of spoilage indices, namely peroxide, thiobarbituric acid, and free fatty acids, during frozen storage, indicate to oxidation and enzymatic mechanism activity during frozen storage of breaded Kilka. Considering sensory evaluation at the end of the fourth month and TVB-N contents exceeded eligible rate in the fourth month, shelf life of the products during frozen storage was set to be three months at -18°C. The results obtained from statistical tests indicate to better quality of breaded Kilka processed with tempura batter compared to simple batter in terms of organoleptic evaluation, spoilage indices, and high quality of fat in various sampling phases.

Different masking effects on "hole" and "no-hole" figures

Global information is considered the primitive of visual perception in Gestalt psychology. Further, L. Chen ( 2005) proposed a new theory of topological visual perception. According to this theory, the perception of topological difference is faster than o

Size distribution of heavy mineral grains in some modern Nile Delta coastal sands, Egypt

This study includes determination and discussion of the texture and heavy mineral compositions of some modem Nile Delta coastal sands (river, coastal dune, beach-face, and nearshore marine) in order to delineate the process and factors that regulate the size distribution of heavy mineral grains comprising these coastal sands. Textural analysis of unseparated bulk samples indicate that the examined four types of sands differ in their mean grain sizes and degree of sorting. However, analysis of size distribution curves of 10 heavy mineral species or group of species in the four environments having the same general shape and nearly similar in that general order of arrangement. However, these curves vary both in median sizes and sorting. The size distribution of a heavy mineral in the Nile Delta coastal sands appear to depend on: (1) range of grain size fractions in each sample, (2) relative availability of heavy mineral in each size grade of the sample, (3) specific gravity of minerals comprising these sands, and (4) some other unknown factor or factors. Results of size measurement of heavy minerals indicated that increasing specific gravity is accompanied by increasing fineness of the heavy minerals. This study may be useful in search for marine placers and understanding the processes of grain-sorting on the sea beaches.

Study of distribution, growth and reproduction polychaetes Nereidae in intertidal zone of Bandar Abbas and effect dominant species on white Indian shrimp brood stocks (Fenneropenaeus indicus)

Distribution of polychaetes worms Nereidae in intertidal zone of Bandar Abbass indicated that distribution rate of worms from the west to east for the reason status of seabed type, habitat and feeding substrate used to worms increased. Also investigation description that last-mentioned worms are belong to Nereididae family, Perinereis genus and species of Perinereis nuntia. By viewpoint seabed soil types experiments implement indicated Nereididae worms have higher survival with sandy clay loam soil texture. Statistical analysis showed positive relation coefficient correlation of Pearson between substrate type to frequency of worms and too substrate type with soil organic matter value (P<0.05). By viewpoint feeding also experiments with different feed treatment indicated that Nereid worms is Omnivore but in natural condition more utilized algae substrate special Entermorpha and survival rate had the worms last-mentioned in dietary treatments on this algae 93/3% different significant with other treatments (P<0.05). In this project pond-reared white Indian shrimp (Fenneropenaeus indicus) were used in four maturation and spawning trials lasting 60 days. one group of shrimps was fed a formulated pelleted special of broodstock diet only, a second group was fed squid meat diet; a third group of shrimps with mollusca (Solen vagina) meat diet and fourth group was fed polychaete worms Nereidae family, collected in intertidal zone of Bandar Abbass. Four types of dietary treatments (M1, M4) were given to separate batches that were run in three duplicate. Results of experiments demonstrate that more grew rate and maturation and spawning rate and we found that shrimps fed with polychaete worms have the best condition and then shrimps fed with solen. This is demonstrate furthermore environmental circumstance, endocrine hormone, types of feed important of maturation and spawning of shrimps and in polychaete worms used HUFA help to maturation ovarian in shrimp.

Development and shelf life evaluation of Tilapia (Orechromis spp.) marinades

Tilapia (Oreochromis spp.) consumption is limited due to its strong muddy odour and the difficulty of processing. In addition, consumption of tilapia is minimal in urban areas because of the low availability. There are no processed market products of tilapia available in Sri Lanka. Therefore, this study was designed to develop a new marinade for tilapia and to evaluate the shelf life of the product. Twelve different treatments of varying amounts of vinegar, salt, chili powder, white pepper and garlic powder were applied to filleted tilapia, and three best treatment combinations were selected using a sensory evaluation test. Processed tilapia was stored in the freezer at -4°C. Treated samples were subjected to evaluation of sensory profile: taste, odour, colour, texture and overall acceptability. Analysis of the shelf life was carried out by using the total plate count, faecal coliform test, acidity and pH at weekly intervals. Results revealed that the third treatment (vinegar 75 ml, salt 5 g, chili powder 5 g, white pepper 5 g and garlic powder 5 g) was best in terms of colour, texture, odour, taste and the overall acceptability according to the estimated medians (6, 6, 6 and 6.33 respectively). There was no significant difference between the first and the third treatment in terms of odour and overall acceptability. There was no significant difference between the three vacuum packed treatments for acidity and pH. Acidity and pH of the three treatments were at an acceptable level, which was below pH 5.3 and above 1.95% acidity. Average bacterial count was 10 colonies and 1.33x10 super(6) colonies respectively in vacuum packed treatments and bottled samples after one week. The acceptable level of bacterial colonies is 1.00x10 super(5). Vacuum packed treatments showed a one month shelf life. In conclusion, marinades can be developed from tilapia with a pleasant taste and acceptable texture.

Studies on diversity of Hara's Laft-Khamir and Sout Beaches of the Gheshm polychaete

One of the most important marine ecologic phenomenon , is the study of animal community among the bed or benthic fauna. Macrobenthoses are the graet part of the benthic faune , that are more biomasses than meiofauna and microfauna. To study polychaetes diversity of Mangroves, located in Khoore-Khooran , sampling was conducted on a bimonthly and carried out from December 2001 to October 2002. Bottom samples were collected by Van Veen grab (0.025 m2)at 6 station from 2 transect Insitu measurement of temperature , pH , Do and salinity were done . Atotal of polychaetes werw identified within study 32 Family and 43 Genus . Cirriphormia and Nephtys were the most dominant genus in the studies . The range fomumerical abundance of polychaets was between 3006 per m2 in the station A3 to 559individual per mein the station A1 and the variation was done to different bottom , texture the variable environment conditions govrtneng the different parts of each creeks as well as within creeks . Application of diversity indices (Shannon H') on the dominant polychates assambladges has higher H' in the Azar and lower 1-1/ in the Mehr . and the stations B3 has the highest H' and the station A2 has the lowest H' Application of diversity and Richness, Evennes were studied and showed that the station A3 has the lowest evenness and the most individual , and station A1 has the middle pollution.

Automatic object segmentation from calibrated images

This paper addresses the problem of automatically obtaining the object/background segmentation of a rigid 3D object observed in a set of images that have been calibrated for camera pose and intrinsics. Such segmentations can be used to obtain a shape representation of a potentially texture-less object by computing a visual hull. We propose an automatic approach where the object to be segmented is identified by the pose of the cameras instead of user input such as 2D bounding rectangles or brush-strokes. The key behind our method is a pairwise MRF framework that combines (a) foreground/background appearance models, (b) epipolar constraints and (c) weak stereo correspondence into a single segmentation cost function that can be efficiently solved by Graph-cuts. The segmentation thus obtained is further improved using silhouette coherency and then used to update the foreground/background appearance models which are fed into the next Graph-cut computation. These two steps are iterated until segmentation convergences. Our method can automatically provide a 3D surface representation even in texture-less scenes where MVS methods might fail. Furthermore, it confers improved performance in images where the object is not readily separable from the background in colour space, an area that previous segmentation approaches have found challenging. © 2011 IEEE.

Pothole detection in asphalt pavement images

Pavement condition assessment is essential when developing road network maintenance programs. In practice, the data collection process is to a large extent automated. However, pavement distress detection (cracks, potholes, etc.) is mostly performed manually, which is labor-intensive and time-consuming. Existing methods either rely on complete 3D surface reconstruction, which comes along with high equipment and computation costs, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In this paper we present a method for automated pothole detection in asphalt pavement images. In the proposed method an image is first segmented into defect and non-defect regions using histogram shape-based thresholding. Based on the geometric properties of a defect region the potential pothole shape is approximated utilizing morphological thinning and elliptic regression. Subsequently, the texture inside a potential defect shape is extracted and compared with the texture of the surrounding non-defect pavement in order to determine if the region of interest represents an actual pothole. This methodology has been implemented in a MATLAB prototype, trained and tested on 120 pavement images. The results show that this method can detect potholes in asphalt pavement images with reasonable accuracy.

Parameter optimization for automated concrete detection in image data

Several research studies have been recently initiated to investigate the use of construction site images for automated infrastructure inspection, progress monitoring, etc. In these studies, it is always necessary to extract material regions (concrete or steel) from the images. Existing methods made use of material's special color/texture ranges for material information retrieval, but they do not sufficiently discuss how to find these appropriate color/texture ranges. As a result, users have to define appropriate ones by themselves, which is difficult for those who do not have enough image processing background. This paper presents a novel method of identifying concrete material regions using machine learning techniques. Under the method, each construction site image is first divided into regions through image segmentation. Then, the visual features of each region are calculated and classified with a pre-trained classifier. The output value determines whether the region is composed of concrete or not. The method was implemented using C++ and tested over hundreds of construction site images. The results were compared with the manual classification ones to indicate the method's validity.

Concrete column recognition in images and videos

The automated detection of structural elements (e.g., columns and beams) from visual data can be used to facilitate many construction and maintenance applications. The research in this area is under initial investigation. The existing methods solely rely on color and texture information, which makes them unable to identify each structural element if these elements connect each other and are made of the same material. The paper presents a novel method of automated concrete column detection from visual data. The method overcomes the limitation by combining columns’ boundary information with their color and texture cues. It starts from recognizing long vertical lines in an image/video frame through edge detection and Hough transform. The bounding rectangle for each pair of lines is then constructed. When the rectangle resembles the shape of a column and the color and texture contained in the pair of lines are matched with one of the concrete samples in knowledge base, a concrete column surface is assumed to be located. This way, one concrete column in images/videos is detected. The method was tested using real images/videos. The results are compared with the manual detection ones to indicate the method’s validity.

Improving Pothole Recognition through Vision Tracking for Automated Pavement Assessment

Pavement condition assessment is essential when developing road network maintenance programs. In practice, pavement sensing is to a large extent automated when regarding highway networks. Municipal roads, however, are predominantly surveyed manually due to the limited amount of expensive inspection vehicles. As part of a research project that proposes an omnipresent passenger vehicle network for comprehensive and cheap condition surveying of municipal road networks this paper deals with pothole recognition. Existing methods either rely on expensive and high-maintenance range sensors, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In our previous work we created a pothole detection method for pavement images. In this paper we present an improved recognition method for pavement videos that incrementally updates the texture signature for intact pavement regions and uses vision tracking to track detected potholes. The method is tested and results demonstrate its reasonable efficiency.

Alternative methods for surface texturing

Surface texturing has a great potential to improve tribological performance. First, possible texturing methods were identified and classified according to their physical principles. In sequence, some alternative texturing methods are presented. Some of them are already currently used either in industry or in laboratory, and innovations or simplifications are described for them. Others are innovative techniques. Some were explored only tentatively, where basic ideas and simple experimental investigations were developed to check their validity. Others were explored in more detail, so that their practical applicability could be identified. The first texturing method was photochemical texturing using a simple and cheap apparatus. Masking with inkjet printing before chemical etching was also successful to texture metallic samples. A new method involving electrochemical texturing, without the need to previously mask the samples to be textured have been studied in terms of voltage, current, mechanical configuration of the apparatus and electrolyte flushing. Another method aims to generate randomly distributed circular pockets on steel surfaces and involves dispersion of small acid droplets in oil. The final method involves the selective formation of hard areas on a steel surface by locallised diffusion, which should then develop into a texture during wear.

The parameter space of graphene chemical vapor deposition on polycrystalline Cu

A systematic study of the parameter space of graphene chemical vapor deposition (CVD) on polycrystalline Cu foils is presented, aiming at a more fundamental process rationale in particular regarding the choice of carbon precursor and mitigation of Cu sublimation. CH 4 as precursor requires H 2 dilution and temperatures ≥1000 °C to keep the Cu surface reduced and yield a high-quality, complete monolayer graphene coverage. The H 2 atmosphere etches as-grown graphene; hence, maintaining a balanced CH 4/H 2 ratio is critical. Such balance is more easily achieved at low-pressure conditions, at which however Cu sublimation reaches deleterious levels. In contrast, C 6H 6 as precursor requires no reactive diluent and consistently gives similar graphene quality at 100-150 °C lower temperatures. The lower process temperature and more robust processing conditions allow the problem of Cu sublimation to be effectively addressed. Graphene formation is not inherently self-limited to a monolayer for any of the precursors. Rather, the higher the supplied carbon chemical potential, the higher the likelihood of film inhomogeneity and primary and secondary multilayer graphene nucleation. For the latter, domain boundaries of the inherently polycrystalline CVD graphene offer pathways for a continued carbon supply to the catalyst. Graphene formation is significantly affected by the Cu crystallography; i.e., the evolution of microstructure and texture of the catalyst template form an integral part of the CVD process. © 2012 American Chemical Society.

Learning based automatic face annotation for arbitrary poses and expressions from frontal images only

Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based approach for the automatic annotation of visually deformable objects from a single annotated frontal image is presented and demonstrated on the example of automatically annotating face images that can be used for building AAMs for fitting and tracking. This approach employs the idea of initially learning the correspondences between landmarks in a frontal image and a set of training images with a face in arbitrary poses. Using this learner, virtual images of unseen faces at any arbitrary pose for which the learner was trained can be reconstructed by predicting the new landmark locations and warping the texture from the frontal image. View-based AAMs are then built from the virtual images and used for automatically annotating unseen images, including images of different facial expressions, at any random pose within the maximum range spanned by the virtually reconstructed images. The approach is experimentally validated by automatically annotating face images from three different databases. © 2009 IEEE.

A performance evaluation of volumetric 3D interest point detectors

This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (i.e. 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied; 3D shape less so. However, the increasing prevalence of 3D shape acquisition techniques and the diminishing returns to be had from appearance alone have seen a surge in 3D shape-based methods. In this work, we investigate the performance of several state of the art interest points detectors in volumetric data, in terms of repeatability, number and nature of interest points. Such methods form the first step in many shape-based applications. Our detailed comparison, with both quantitative and qualitative measures on synthetic and real 3D data, both point-based and volumetric, aids readers in selecting a method suitable for their application. © 2012 Springer Science+Business Media, LLC.