• Journal of Biosystems Engineering
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• 제30권6호통권113호
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• pp.340-346
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• 2005

Major quality features of the beef carcass in most countries including Korea are size, marbling state of the lean tissue, color of the fat and lean tissue, and thickness of back fat of the 13th rib. To evaluate the beef quality, extracting loin parts from the sectional image of the 13th beef rib is crucial and is the first step. However, because of the inhomogeneous distribution and fuzzy pattern of the fat and lean tissues on the beef cut, it is difficult to extract automatically the proper contour of the lean tissue. In this paper, a prototype mobile beef quality measurement system, which can be implemented practically at the beef processing site was developed. The developed system was composed of the hand held image acquisition unit and mobile processing unit mounted with touch-pad screen. Algorithms to extract the boundary of the lean tissue and a proper tool to evaluate the marbling status have been developed using color image processing. The boundary extraction algorithm showed successful results for the beef cuts with simple and moderate patterns of the lean tissue and fat. However, it had some difficulty in eliminating complex pattern of the extraneous tissues adhered to the lean tissue in the boundary extraction. The developed algorithms were implemented to the prototype mobile processing unit.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.715-721
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• 2000

In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

• Journal of Biosystems Engineering
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• 제39권3호
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• pp.174-183
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• 2014

Purpose: A robust, efficient auto-grading computer vision system for meat carcasses is in high demand by researchers all over the world. In this paper, we discuss our study, in which we developed a system to speed up line processing and provide reliable results for pork grading, comparing the results of our algorithms with visual human subjectivity measurements. Methods: We differentiated fat and lean using an entropic correlation algorithm. We also developed a self-designed robust segmentation algorithm that successfully segmented several porkcut samples; this algorithm can help to eliminate the current issues associated with autothresholding. Results: In this study, we carefully considered the key step of autoextracting lean tissue. We introduced a self-proposed scheme and implemented it in over 200 pork-cut samples. The accuracy and computation time were acceptable, showing excellent potential for use in online commercial systems. Conclusions: This paper summarizes the main results reported in recent application studies, which include modifying and smoothing the lean area of pork-cut sections of commercial fresh pork by human experts for an auto-grading process. The developed algorithms were implemented in a prototype mobile processing unit, which can be implemented at the pork processing site.

• 동의신경정신과학회지
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• 제21권4호
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• pp.53-68
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• 2010

Objectives : We investigated the effects of Sopungsungj-won(Shufengshunqjvuan) (SSEx1, SSEx2) on the metabolic syndrome in high-fat diet induced obese mice. Methods: 8 weeks old, high fat diet induced obese male mice were divided into 4 groups: C57BL/6 lean control, obese vehicle control, SSEx1, SSEx2. After mice were treated with SSExl, SSEx2 for 12 weeks, we measured body weight gain, food intake, feeding efficiency ratio, fat weight, plasma leptin, insulin, glucose and lipid levels. We also observe the morphology and count for the numbers of Adipocyte and evaluate the weight of organs and it's function. Results: 1. Compared to Obese Control Group, SSEx1 gained significantly lower body weight and showed lower Feeding Efficiency Ratio. 2. Compared to Obese Control Group, SSEx1 showed lower weights of epididymal adipose tissue, troperitoneal adipose tissue, inguinal adipose tissue, brown adipose tissue. SSEx2 showed higher weights of epididymal adipose tissue, troperitoneal adipose tissue, inguinal adipose tissue, brown adipose tissue. 3. Compared to Obese Control Group, the size of adipocytes was significantly decreased by SSEx1, whereas the number of adipocites per unit was significantly increased. Hepatic lipid accumulation was decreased significantly by SSEx1. 4. Concerning the weights of Liver, Heart, Spleen, Kidney and Pancreas, SSEx1, SSEx2 showed little differences with those of Lean Control, Obese Control. 5. Compared to Obese Control Group, SSEX1, SSEx2 showed lower level of plasma triglyceride, but SSEx1 had significance only. SSEx1, SSEx2 showed little lower level of plasma HDL-cholesterol. LDL-cholesterol, total cholesterol, but had no significances. 6. Concerning the levels of plasma glucose, insulin and leptin, SSEx1 and SSEx2 showed littele changes with those of Lean Control, Obese Control. 7. The leves of Plasma AST, AST, ALT, free fatty acid, BUN, creatinine were in the physiological range at 4 groups all: Lean Control, Obese Control, SSEx1, SSEx2. Conclusions : These results showed SSEx1 can be used as therapeutic agent for Obesity and metabolic syndrome caused by long-period high fat diet.

• Asian-Australasian Journal of Animal Sciences
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• 제18권5호
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• pp.692-698
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• 2005

Two experiments were conducted to examine the effect of graded levels of dietary chromium and leucine, and different fat sources on performance and body composition of broiler chickens. The results showed that chromium picolinate at 0.5 ppm significantly (p<0.05) lowered the carcass fat level. Gut weight and carcass water content were increased as a result of chromium treatment. Body weight, plucked weight, carcass weight, abdominal fat pad weight, breast yield and feed efficiency were unaffected by chromium treatment. Leucine did not interact with chromium to effect lean growth. Dietary leucine above the recommended maintenance level (1.2% of diet) markedly (p<0.001) reduced the breast muscle yield. The addition of fish oil to broiler diets reduced (p<0.05) the abdominal fat pad weights compared to birds on linseed diets. Fish oil is believed to improve lean growth through the effects of long chain polyunsaturated fatty acids in lowering the very low-density lipoprotein levels and triglyceride in the blood, in the meantime increasing glucose uptake into the muscle tissue in blood and by minimizing the negative impact of the immune system on protein breakdown. The amount of fat in the diet (2% or 4%) did not affect body composition.

• Clinical and Experimental Pediatrics
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• 제56권4호
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• pp.151-158
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• 2013

Purpose: We investigated the mRNA levels of peroxisome proliferator-activated receptor (PPAR)-${\alpha}$, PPAR-${\gamma}$, adipokines, and cytokines in the lung tissue of lean and obese mice with and without ovalbumin (OVA) challenge, and the effect of rosiglitazone, a PPAR-${\gamma}$ agonist. Methods: We developed 6 mice models: OVA-challenged lean mice with and without rosiglitazone; obese mice with and without rosiglitazone; and OVA-challenged obese mice with and without rosiglitazone. We performed real-time polymerase chain reaction for leptin, leptin receptor, adiponectin, vascular endothelial growth factor (VEGF), tumor necrosis factor (TNF)-${\alpha}$, transforming growth factor (TGF)-${\beta}$, PPAR-${\alpha}$ and PPAR-${\gamma}$ from the lung tissue and determined the cell counts and cytokine levels in the bronchoalveolar lavage fluid. Results: Mice with OVA challenge showed airway hyperresponsiveness. The lung mRNA levels of PPAR${\alpha}$ and PPAR-${\gamma}$ increased significantly in obese mice with OVA challenge compared to that in other types of mice and decreased after rosiglitazone administeration. Leptin and leptin receptor expression increased in obese mice with and without OVA challenge and decreased following rosiglitazone treatment. Adiponectin mRNA level increased in lean mice with OVA challenge. Lung VEGF, TNF-${\alpha}$, and TGF-${\beta}$ mRNA levels increased in obese mice with and without OVA challenge compared to that in the control mice. However, rosiglitazone reduced only TGF-${\beta}$ expression in obese mice, and even augmented VEGF expression in all types of mice. Rosiglitazone treatment did not reduce airway responsiveness, but increased neutrophils and macrophages in the bronchoalveolar lavage fluid. Conclusion: PPAR-${\alpha}$ and PPAR-${\gamma}$ expressions were upregulated in the lung tissue of OVA-challenged obese mice however, rosiglitazone treatment did not downregulate airway inflammation in these mice.

• Asian-Australasian Journal of Animal Sciences
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• 제22권10호
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• pp.1420-1428
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• 2009

In this study we cloned and characterized a novel lipid-accumulating gene, the oxidized low-density lipoprotein receptor 1 (OLR1), which is associated with lipogenesis. We analyzed the gene structure and detected the mRNA transcriptional expression levels in pig adipose tissues at different months of age (MA) and in different economic types (lean type and obese type) using real-time fluorescence quantitative PCR. OLR1 expression profile in different tissues of pig was analyzed. Finally, we studied the correlation between OLR1 and lipid metabolism related genes including peroxisome proliferator-activated $receptor{\gamma}2$ ($PPAR{\gamma}2$), fatty acid synthetase (FAS), triacylglycerol hydrolase (TGH), CAAT/enhancer binding protein $\alpha$ ($C/EBP{\alpha}$) and sterol regulatory element binding protein-1c (SREBP-1c). Results indicated that the OLR1 gene of the pig exhibited the highest homology with the cattle (84%), and the lowest with the mouse (27%). The signal peptide located from amino acid 38 to 60 and the domain from amino acid 144 to 256 were shared by the C-type lectin family. The expression level of OLR1 in pig lung was exceedingly higher than other tested tissues (p<0.01). In pig adipose tissue, the expression level of OLR1 mRNA increased significantly with growth (p<0.01). The expression level of OLR1 mRNA in obese-type pigs was significantly higher than that of lean-type pigs of the same monthly age (p<0.05). In adipose tissue, the expression of OLR1 correlated with $PPAR{\gamma}2$, FAS and SREBP-1c, but not TGH or C/EBP${\alpha}$. In conclusion, OLR1 was highly associated with fat deposition and its transcription, as suggested by high correlations, was possibly regulated by $PPAR{\gamma}2$ and SREBP-1c.

• Journal of mucopolysaccharidosis and rare diseases
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• 제1권2호
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• pp.44-48
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• 2015

Body fat distribution in patients with Prader-Willi syndrome (PWS) is characterized by reduce lean body mass (LBM), increased total body fat mass (FM), and lower percentage of visceral adipose tissue (VAT). Individuals with PWS seem to have a lower risk for insulin resistance with high levels of adiponectin, an anti-atherogenic adipocytokine that is decreased in visceral fat hypertrophy subjects compared to simple obese subjects, both in children and in adults. The mechanism of the reduction in visceral adiposity in PWS is still unclear. It might be related to qualitative intrinsic characteristics of adipocyte or novel genetic influences on the control of fat distribution. However, obesity remains a critical problem, and obesity status plays a crucial role in individual metabolic risk clustering and development of metabolic syndrome (Mets) in PWS children and adults. Long-term growth hormone (GH) treatment after cessation of skeletal growth improved body composition, with an increase in lean body mass and a reduction in total body fat and subcutaneous and visceral fat in PWS adults. Thus, the role of GH is important after childhood because it might attenuate obesity and Mets in PWS adult by adipocyte modification.

• Agricultural and Biosystems Engineering
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• 제4권1호
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• pp.16-21
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• 2003

In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.