• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.158-163
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• 2014

In this study, two commercial PCR and ELISA test kits were examined for identification of eight animal species (beef, pork, chicken, duck, turkey, goat, lamb, and horse) from raw meat and meat products in Korea. The detection limit in RAW meat ELISA kit$^{(R)}$ on three types of meat samples blended with beef, pork and chicken, demonstrated that all meat species were differentiable down to 0.2%. RAW meat ELISA kit$^{(R)}$ on animal species resulted in differentiation rate of 94.5% for beef, 93.3% for pork, 90% for lamb, and 100% for chicken, duck, turkey, goat, and horse. In contrast, Powercheck Animal Species ID PCR kit$^{TM}$ resulted in 100% specificity at 0.05% limit of detection for all meat species. The detection limit of Cooked Meat ELISA kit$^{(R)}$ on mixed meat samples heat-treated with different temperatures and times, resulted in 0.1% for all heat-treated mixed meat except for chicken at 1.0%. Additionally, ELISA kit on sixty meat products resulted in specificity of 31.8% for ham, 13.6% for sausages, and 12.5% for ground processed products, and relatively low rate for more than 2 types of mixed meats. On the contrary, meat species differentiation using PCR kit showed higher percentage than that using ELISA kit$^{(R)}$: 50.0% for ham, 41.7% for sausages, and 28.6% for ground processed meat. Futhermore, PCR kit on 54 dried beef meats detected pork genes in 13 products whereas ELISA kit showed negative results for all products. Hence, the possibility of cross-contamination during manufacturing process was investigated, and it was found that identical tumblers, straining trays, cutters and dryers were used in both beef and pork jerky production line, suggesting the inclusion of pork genes in beef products due to cross-contamination. In this study, PCR and ELISA test kits were found to be excellent methods for meat species differentiation in raw meat and heat-processed mixed meat. However, lower differentiation rate demonstrated in case of meat processed products raised the possibility of inclusion of other species due to cross-contamination during manufacturing process.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.26 no.3
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• pp.214-220
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• 1993

Browning of ascidian, Halocynthia roretzi, meat occurres very rapidly when skinned off or cut during processing and it resulted the quality loss of fresh frozen, dehydrated or fermented products. In this study, the causes of color development and prevention of browning were experimented. The browning of ascidian meat may be occurred enzymatically by a tyrosinase contained in meat and viscera which acted specifically on L-tyrosine as a substrate rather than on catechol. Activity of the enzyme in viscera was three times higher than in meat. The optimum pH and temperature on the tyrosinase activity of crude enzyme obtained from ascidian was 6.0 and $30{\sim}35^{\circ}C$, respectively. The enzyme was inactivated heating at $80^{\circ}C$ for 3 minutes or $90{\sim}100^{\circ}C$ for 1 minute and it was inhibited by $0.1{\sim}0.5mM$ solutions at ascorbic acid, sodium hydrogen sulfite, cystein, citric acid, cyanide but only sodium hydrogen sulfite treatment was effective to retard such a high content of enzyme as in case of viscera. In practical use for processing of ascidian meat browning was retarded by dipping the viscera removed ascidian meat in 0.2M citric acid for 5 minutes or $0.2\%$ sodium hydrogen sulfite solution for 1 minute resulting in sulfur dioxide residue less than 100 ppm.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.835-848
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• 2021

In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.1
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• pp.40-47
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• 2019

This study was conducted to investigate the effect of planting density on plant growth, yield, and quality in the sweet sorghum cultivar 'Chorong' (Sorghum bicolor (L.) Moench). Plants were cultivated at densities of 16.7, 11.1, 8.3, 6.7, and $5.6plants{\cdot}m^{-2}$. Factors related to yield and yield components were analyzed using correlation and multivariate analyses. There was no significant difference among plant densities in stem length from 20 to 110 days after sowing. But the stem diameter was thin, and a decrease in number of tillers occurred more rapidly as planting density increased. At harvest, juice and sugar yield were higher at densities of 16.7 (42.9, $4.16Mg{\cdot}ha^{-1}$, respectively) and 11.1 (37.1, $3.73Mg{\cdot}ha^{-1}$) $plants{\cdot}m^{-2}$ than at 8.3 (30.5, $2.96Mg{\cdot}ha^{-1}$), 6.7 (26.6, $2.41Mg{\cdot}ha^{-1}$), and 5.6 (24.7, $2.22Mg{\cdot}ha^{-1}$) $plants{\cdot}m^{-2}$. The soluble solids and total sugar contents were not different among treatments, but relatively high values were observed at the density of 11.1 and $8.3plants{\cdot}m^{-2}$. As plant density was increased from 5.6 to $11.1plants{\cdot}m^{-2}$, the lodging index (1 = no, 9 = lodging) increased rapidly from 2.00 to 6.33. To determine the optimal planting density, the number of typhoons and topographical characteristics should be considered. Correlation and principal components analyses revealed that plant density exhibited a positive relationship with fresh stem yield ($r=0.62^{**}$), dry stem yield ($r=0.58^{**}$), juice ($r=0.63^{**}$), and sugar yield ($r=0.66^{**}$), but a negative with stem diameter ($r=-0.65^{**}$). The yield factors were not statistically related to stem height, diameter, and number of nodes.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.20 no.1
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• pp.41-51
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• 1987

This study was carried out to prepare powdered smoked-dried mackerel which can be used as a soup base, and to examine storage stability and the taste compounds of Products. Raw mackerel are filleted, toiled for 10 minutes and pressed to remove lipids, and then soaked in extract solution of skipjack meat. This soaked mackerel are smoked 3 times to $10-12\%$ moisture content at $80^{\circ}C$ for 8 hours. And the smoked-dried mackerel were pulverized to 50 mesh. Finally, the powdered smoked-dried mackerel were packed in a laminated film $bag(PET/Al\;foil/CPP:\;5{\mu}m/15{\mu}m/70{\mu}m,\;15\times17cm)$ with air(product C), nitrogen(product N) and oxygen absorber(product O), and then stored at room temperature for 100 days. The moisture and crude lipid content of powdered smoked-dried mackerel was $11.3-12.3\%,\;12\%$, respectively, and water activity is 0.52-0.56. And these values showed little changes during storage. The pH, VBN and amino nitrogen content increased slowly during storage. Hydrophilic and lipophilic brown pigment formation showed a tendency of increase in product(C) and showed little change in product(N) and (O). The TBA value, peroxide value and carbonyl value of product(N) and (O) were lower than those of product (C). The major fatty acids of products were 16:0, 18:1, 22:6, 18:0 and 20:5, and polyenoic acids decreased, while saturated and monoenoic acids increased during processing and storage of products. The IMP content in products were 420.2-454.2 mg/100 g and decreased slightly with storage period. And major non-volatile organic acids in products were lactic acid, succinic acid and $\alpha-ketoglutaric$ acid. In free amino acids and related compounds, major ones are histidine, alanine, hydroxyproline, lysine, glutamic acid and anserine, which occupied $80.8\%$ of total free amino acids. The taste compounds of powdered smoked-dried mackerel were free amino acids and related compounds (1,279.4 mg/100 g), non-volatile organic acids(948.1 mg/100 g), nucleotides and their related compounds (672.8 mg/100 g), total creatinine(430.4 ntg/100 g), tetaine(86.6 mg/100 g) and small amount of TMAO. The extraction condition of powdered smoked-dried mackerel in preparing soup stock is appropriate at $100^{\circ}C$ for 1 minute. Judging from the results of taste and sensory evaluation, it is concluded that the powdered smoked-dried mackerel can be used as natural flavoring substance in preparing soups and broth.