• Korean Journal of Poultry Science
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• v.42 no.2
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• pp.147-156
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• 2015

This study was conducted to investigate the effects of dietary resveratrol on growth performance, blood biochemical parameters, immunoglobulin, and blood antioxidant activity in broiler chicks. Three hundred twenty one-day old broiler chicks were divided 8 treatments (C(-), basal diet; C(+), basal diet with antibiotics; DL-${\alpha}$-tocopherol 20 IU; DL-${\alpha}$-tocopherol 200 IU; resveratrol 20 ppm; resveratrol 200 ppm; methylated resveratrol 20 ppm; methylated resveratrol 200 ppm) with 4 replicates and 10 birds per replicate. Birds were reared for 35 days, and, at the age of 35 days, eight birds of average weight from each replicate were selected for blood samples collection. There were no significant differences on feed intake and feed conversion ratio. But final body weight and weight gain in antibiotics, resveratrol and methylated resveratrol treatments were significantly higher than no-antibiotics and ${\alpha}$-tocopherol treatments (P<0.05). There were no significant differences on carcass rate and relative organ weights among treatments, however, weights of liver and bursa of februcius in antibiotics, resveratrol and methylated resveratrol treatment were lower than other treatments. Weight of pancreas was high in resveratrol and methylated treatment. On the cecal microflora (total microbes, Coliform bacteria, Salmonella spp., and lactic acid bacteria), these in resveratrol and methylated resveratrol treatments didn't show the differences compared with those in no-antibiotics, antibiotics, and ${\alpha}$-tocopherol treatments. In the serum, there were no significant differences on creatinine, blood urea nitrogen (BUN), total protein, albumin, globulin, alanine aminotransferase (ALT) and aspartate aminotransferase (AST) among treatments, though globulin contents of reseveratrol 200 ppm and methylated resveratrol 20 ppm treatments decreased compared to those of other treatments. Immunoglobulin (IgA, IgG and IgM) were significantly decreased in antibiotics and resveratrol treatments compared to that of no-antibiotics and ${\alpha}$-tocopherol treatments (P<0.05). Superoxide dismutase (SOD) like activity tended to increase in resveratrol groups (P<0.05), however, there was no significant difference on malondiakdehyde (MDA) content among treatments. In conclusion, these results showed that resveratrol derived from mulberry can be used as alternative of antibiotics through improvement of broiler's performance and maintain of health.

• Korean Journal of Poultry Science
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• v.42 no.2
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• pp.139-145
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• 2015

The objective of this experiment was to investigate the effects of dietary supplementation of Lycii fructus (LF) and Glycyrrhiza uralensis (GU) mixture on growth performance, blood parameter, immune response and intestinal microflora in broiler. A total 750 1-d old ROSS 308 was randomly allotted to 1 of 3 dietary treatments with 5 replicates during d 35 of the feeding trial. Two additional diets were prepared by adding 0.5 or 1.0% of LF and GU mixture to the basal diet. The experimental diets were fed on an ad libitum basis to the birds during 35 d. Results indicated that increasing inclusion level of LF and GU mixture in diets improved BW gain (quadratic, P<0.05) and improved feed conversion ratio (quadratic, P<0.05) of birds during to 0 to 21 d. Increasing inclusion level of LF and GU mixture in diets improved BW gain (linear and quadratic, P<0.05) of birds during to 0 to 35 d. The leukocyte concentrations were not affected by increasing inclusion level of LF and GU mixture in diets. Plasma IgG concentration was increased (linear, P<0.05) as the concentrations of LF and GU mixture in diets increased. The concentrations of Lactobacillus spp. in the ileal content of birds increased (linear, P<0.05), but those of Escherichia coli decreased (quadratic, P<0.01). These results suggest that dietary LF and GU mixture may be used as a functional ingredient to improve growth performance, plasma IgG and intestinal health of birds.

• Korean Journal of Poultry Science
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• v.41 no.4
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• pp.323-329
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• 2014

The objective of this experiment was to investigate the effect of dietary supplementation of copper-soy proteinate (Cu-SP) and herbal mixture (HBM) on growth performance, blood parameter, and immune response in laying hens. A total 800 Hy-Line Brown laying hens (60 weeks old) were randomly allotted to 1 of 4 dietary treatments : (1) Control : control diet, (2) Cu-SP : control diet + 100 mg/kg Cu-soy proteinate, (3) HBM : control diet + 0.15% herbal mixture, and (4) Cu-SP + HBM : control diet + 100 mg/kg Cu-soy proteinate + 0.15% herbal mixture. Each treatment was replicated 5 times with forty birds units were arranged according to randomized block design. Feeding trial lasted 5 weeks under 16L : 8D lighting regimen. The diet and water were available ad libitum. Result indicated that during feeding trial of the experiment, hen-day egg production was significantly (P<0.05) higher in Cu-SP and HBM treated groups than control. However, feed intake, feed conversion ratio, egg weight, broken and shell less egg production were not significantly influenced by treatments. Eggshell strength was significantly (P<0.05) higher in Cu-SP than control. Eggshell thickness, eggshell color, egg yolk color, Haugh unit were not significantly influenced by treatments. The level of WBC and stress index (heterophil : lymphocyte) were higher in supplemented groups than the control. The concentration of plasma IgG was higher in supplemented groups than the control. The result of this experiment showed that dietary copper-soy proteinate or herbal mixture tended to improve egg production and affect positively on immune response of laying hens.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.347-358
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• 2019

Lambertian cloud model (Lambertian Cloud Model) is the simplified cloud model which is used to effectively retrieve the vertical ozone distribution of the atmosphere where the clouds exist. By using the Lambertian cloud model, the optical characteristics of clouds required for radiative transfer simulation are parametrized by Optical Centroid Cloud Pressure (OCCP) and Effective Cloud Fraction (ECF), and the accuracy of each parameter greatly affects the radiation simulation accuracy. However, it is very difficult to generalize the vertical ozone error due to the OCCP error because it varies depending on the radiation environment and algorithm setting. In addition, it is also difficult to analyze the effect of OCCP error because it is mixed with other errors that occur in the vertical ozone calculation process. This study analyzed the ozone retrieval error due to OCCP error using two methods. First, we simulated the impact of OCCP error on ozone retrieval based on Optimal Estimation. Using LIDORT radiation model, the radiation error due to the OCCP error is calculated. In order to convert the radiation error to the ozone calculation error, the radiation error is assigned to the conversion equation of the optimal estimation method. The results show that when the OCCP error occurs by 100 hPa, the total ozone is overestimated by 2.7%. Second, a case analysis is carried out to find the ozone retrieval error due to OCCP error. For the case analysis, the ozone retrieval error is simulated assuming OCCP error and compared with the ozone error in the case of PROFOZ 2005-2006, an OMI ozone profile product. In order to define the ozone error in the case, we assumed an ideal assumption. Considering albedo, and the horizontal change of ozone for satisfying the assumption, the 49 cases are selected. As a result, 27 out of 49 cases(about 55%)showed a correlation of 0.5 or more. This result show that the error of OCCP has a significant influence on the accuracy of ozone profile calculation.

• Journal of Animal Science and Technology
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• v.51 no.3
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• pp.207-216
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• 2009

This experiment was conducted to investigate the effects of dietary supplementation of organic acid mixture on growth performance, cecal microflora, blood characteristics and immune response in broiler chicks and to prove the possibility of organic acid mixture as an alternative to antibiotics growth promotor. A total of four hundred eighty, 1-day-old male broiler chicks (Ross$\times$Ross 308) were randomly divided into 4 groups with 4 replicates of 30 birds each. The treatments were NC (free antibiotics), PC (basal diet with virginiamycin 10 ppm and salinomycin 60 ppm), 0.3% organic acid, and 0.5% organic acid. The final body weight and body weight gain were significantly higher in organic acid 0.5% than NC (P<0.05). The feed conversion ratio in all treated groups were significantly improved as compared to that of NC (P<0.05). The carcass rate and relative organs weight were not significantly difference among the groups. The relative weight and length of small intestine in PC were significantly decreased than the other groups. The numbers of cecal coliform bacteria and Salmonella in all treated groups were significantly lower than NC (P<0.05). The number of cecal lactic acid bacteria was not different among the groups. No significant differences among the groups were observed in the contents of total cholesterol, triglyceride, blood urea nitrogen (BUN), albumin, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) in blood serum. The contents of total protein and globulin in blood serum of PC and organic acid treated groups were significantly increased as compared to those of NC (P<0.05). Therefore, albumin:globulin ratio of PC and organic acid treated groups was significantly lower than NC (P<0.05). The total white blood cell (WBC), heterophil, lymphocyte, and stress indicator (heterophil:lymphocyte ratio) were not significantly different among the groups. No significant difference was observed on the expression rate of splenic cytokines mRNA in organic acid treated groups compared to the control. Consequently, supplemental organic acid mixture improved the growth performance, and influenced positive effects on the intestinal microflora by inhibiting the growth of harmful bacteria without any adverse effects on relative weights of organs and blood biochemical parameters in broiler chicks.

• Journal of the Korean Applied Science and Technology
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• v.32 no.3
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• pp.427-438
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• 2015

The effects of different feeding times, using a diet containing 800 ppm betaine, on production, blood profile, and the short-chain fatty acid (SCFA), was investigated using 240 Cherry Valley (Anas platyrhynchos) meat ducks exposed to a scorching heat wave. The animals were randomly assigned to four groups, each of which was replicated three times with twenty ducks per replicate. The experimental period was 42 days for each group. Four groups were assigned into C (heat wave control group without betaine), T1 (ad libitum group fed a diet containing 800 ppm betaine), T2 (diet-restricted group fed twice daily between 05:00-10:00 and 17:00-20:00, using a diet containing 800 ppm betaine), and T3 (night-restricted group, fed from 17:00-10:00, with a diet containing 800 ppm betaine). At 42 days, body weight increased in order of T2, T1, T3 compared to the heat wave control group although. However, these differences were not found between the groups of T1 and T3. The heat wave control group, provided an ad libitum diet without betaine (C), showed an elevated feed conversion ratio compared to the groups fed a diet containing betaine. However, these differences were not found between the groups of T1, T2 and T3. RBC and platelet profiles except for PLT and MPV showed statistically significant differences between study groups fed a diet containing betaine. T2 presented significantly higher blood electrolytes $Na^+$ and $Cl^-$ than the other groups. T2 also showed a blood gas level that was generally higher than the other groups. Total SCFA, acetic acid and propionic acid concentration has been the increasing trend in T2, but butyric acid, isobutyric acid and valeric acid concentration has been the decreasing trend in T2 compared to the other groups. It is concluded that the feeding-restricted group, fed two times daily between 05:00-10:00 and 17:00-20:00, with a diet containing 800 ppm betaine may improve growth performance in meat ducks exposed to a scorching heat wave.

• Korean Journal of Poultry Science
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• v.48 no.3
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• pp.143-150
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• 2021

In this study, we investigated the effects of light intensity on broiler chick growth performance, blood parameters, and stress levels. A total of 240 one-day-old male Ross 308 broilers (47.97±0.166 g) were subjected to three different intensities of light (20, 30, and 50 lx), with each treatment being conducted with four replicates. On the seventh day, the growth performance (body weight, feed conversion ratio, and breast muscle and liver weights) and blood parameters were determined; the levels of serum corticosterone, interleukin-6 (IL-6), and tumor necrosis factor-α were also evaluated. The body weight, weight gain, liver weight, and breast muscle weight of chicks exposed to a light intensity of 50 lx were significantly increased compared with those of chicks subjected to 20 lx (P<0.05). No significant differences were observed in the leukocyte, erythrocyte, and platelet counts and the biochemical profile exceptions being the levels of glucose and inorganic phosphorus in the blood of the chicks in the three light intensity groups. However, serum corticosterone and IL-6 levels were the highest in chicks exposed to a light intensity of 20 lx (P<0.05). In conclusion, the findings of this study indicate that broiler chicks exposed to higher light intensity (50 lx) show significant improvements in terms of weight gain and corticosterone and IL-6 levels. Thus, high light intensities enhanced the growth performance, stress levels, and immune status of broiler chicks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.