• Korean Journal of Breeding Science
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• v.50 no.4
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• pp.396-405
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• 2018

The areas of soybean (Glycine max (L.) Merrill) cultivation in Gangwon-do have increased due to the growing demand for well-being foods. The soybean barcode system is a useful tool for cultivar identification and diversity analysis, which could be used in the seed production system for soybean cultivars. We genotyped cultivars using 202 insertion and deletion (InDel) markers specific to dense variation blocks (dVBs), and examined their ability to identify cultivars and analyze diversity by comparison to the database in the soybean barcode system. The genetic homology of "Cheonga," "Gichan," "Daewang," "Haesal," and "Gangil" to the 147 accessions was lower than 81.2%, demonstrating that these barcodes have potentiality in cultivar identification. Diversity analysis of one hundred and fifty-three soybean cultivars revealed four subgroups and one admixture (major allele frequency <0.6). Among the accessions, "Heugcheong," "Hoban," and "Cheonga" were included in subgroup 1 and "Gichan," "Daewang," "Haesal," and "Gangil" in the admixture. The genetic regions of subgroups 3 and 4 in the admixture were reshuffled for early maturity and environmental tolerance, respectively, suggesting that soybean accessions with new dVB types should be developed to improve the value of soybean products to the end user. These results indicated that the two-dimensional barcodes of soybean cultivars enable not only genetic identification, but also management of genetic resources through diversity analysis.

• Korean Journal of Food Science and Technology
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• v.53 no.1
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• pp.46-54
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• 2021

The biological activities of non-edible extracts of asparagus stems and roots were investigated using hot water and ethanol. The highest contents of rutin and total polyphenol were 31.74 mg/g and 20.14 mg GAE/g, respectively, in the stem hot water extract. ABTS and DPPH radical scavenging activities were 541.1±21.0 and 649.5±6.6 ㎍/mL, respectively, in stem hot water extract. All extracts were non-cytotoxic in HepG2 cells, but 200 ㎍/mL stem extracts tended to decrease the viability of RAW 264.7 cells. The highest xanthine oxidase inhibitory activity was 43.68% in the root hot water extract at 200 ㎍/mL. The expression level of MMP-9 was significantly decreased in the asparagus extracts. The highest GGT, AST, and LDH activities showed a concentration-dependent decrease in the stem ethanol extract. In conclusion, the presence of bioactive substances in the non-edible extracts of asparagus was confirmed for the development of extracts with antioxidant, hepatoprotective and anti-gout activities.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.1
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• pp.59-70
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• 2011

The purpose of this study is to present raw data to systematically and rationally manage the protected trees located in Changwon-si, Korea. This study investigated about the present condition and the information of location, individual, management, health and soil. The results are as follows. The protected trees were located in 26 spots, and species of trees were 9 taxa; Zelkova serrata, Celtis sinensis, Aphananthe aspera, Ginkgo biloba, Carpinus tschonoskii, Pinus densiflora for. multicaulis, Quercus variabilis, Pinus densiflora and Salix glandulosa. In protected tree types, shade trees were the most, and the majority of theirs were 200 years or more in age. The range of altitude was 14~173m, and the number of trees located in flat fields was the most. For location types, village and field and mountain were presented in the order and, in land use, land for building was the most. The range of height was 8.0~30.0m, 0.6~5.1m in crown height, 240~700cm in diameter of breast and 210~800cm in diameter of root. In case of crown area, Zelkova serrata of No.5 was most large. The status boards were mostly installed except No.23 and No.26. The sites with fence were 9 spots, and the site with stonework were 14 spots. The sites with the support beam were 5 spots, and most sites were not covered up with soil. The materials of bottom were soil, gravel and vegetation in the order. The range of withering branch rate was 0~40%, and peeled bark rate was 0~60%. The sites made holes were 23 spots, and the hole size of Aphananthe aspera of No.12 was the largest. The sites disturbed by human trampling were 7 spots, the sites by disease and insects of 2 spots, the sites by injury of 23 spots and the sites by exposed roots of 13 spots. In the results of soil analysis, there showed that acidity was pH 4.5~8.0, organic matter content of 3.5~69.8g/kg, electrical conductivity(EC) of 0.11~2.87dS/m, available $P_2O_5$ of 3.0~490.6mg/kg, exchangeable K of 0.10~1.05cmol+/kg, exchangeable Ca of 1.41~16.45cmol+/kg, exchangeable Mg of 0.37~1.96cmol+/kg, exchangeable Na of 0.25~2.41cmol+/kg and cation exchange capacity(C.E.C) of 8.35~26.55cmol+/kg.

• Journal of agriculture & life science
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• v.51 no.2
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• pp.47-59
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• 2017

The objectives of this study were to select the seeds of Cucurbitaceae and Solanaceae genotypes in terms of superior with bioactive compounds content and to inform sophisticated data for developing the high value-added products. We evaluated to aspects of the antioxidant activity, polyphenol content, and flavonoid contents in seeds from two vegetable family. We used in the Cucurbitaceae(watermelon, squash, bitter gourd, and sponge gourd) and Solanaceae(hot pepper, sweet pepper, and egg plant) the total 408 genotypes. In Cucurbitaceae, polyphenol content of watermelon and squash genotypes were ranged 19.9-343.8 and $6.1-81.2mg{\cdot}100g^{-1}\;DW$, respectively. The polyphenol content of watermelon genotypes was 12% among all genotypes over $160mg{\cdot}100g^{-1}\;DW$. The mean of flavonoid content in watermelon and squash genotypes represented 80 and $41.3mg{\cdot}100g^{-1}\;DW$, respectively. In Solanaceae, flavonoid content of hot pepper genotypes was ranged $64.4-472.5mg{\cdot}100g^{-1}\;DW$, with an average of $165.0mg{\cdot}100g^{-1}$. The 23 hot pepper genotypes were classified over 90% antioxidant activity. The antioxidant activity of sweet pepper was ranged 35.9-90.3%, and 23% of all genotypes represented 82% antioxidant activity. The polyphenol and flavonoid content of egg plant was ranged $38.1-642.0mg{\cdot}100g^{-1}\;DW$ and $14.2-1217.0mg{\cdot}100g^{-1}\;DW$, respectively. In addition, we selected that 8 egg plant with the superior genotypes for antioxidant activity, polyphenol, and flavonoid content. Results revealed that there was significant variation of antioxidant activity and bioactive compounds contents in both vegetable famaily. In addition, we suggested that selected genotypes seeds with high contain bioactive compounds will be more efficiency to develop natural value-added products.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Food Hygiene and Safety
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• v.36 no.6
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• pp.493-503
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• 2021

The study was designed to analyze raw and auxiliary materials of Korean traditional cookies such as Yugwa and Gangjeong, equipment and tools, personal hygiene of workers and microbial contamination of materials by each manufacturing process. In addition, it looked at washing method for reducing microorganisms at the site and reduction effect of microorganisms by frequency in the manufacturing processes of Yugwa. In the process of producing Korean traditional cookies, the level of total aerobic bacteria (TAB) in popped rice was 1.2 Log CFU/g and the level of TAB in finished products increased to 3.7 Log CFU/g. In the process of producing Yugwa, the level of TAB increased to a maximum of 6.5 Log CFU/g in the soaking process but decreased to 1.3 Log CFU/g in the frying process. However, the level of TAB increased again to 1.3 Log CFU/g in finished products that proves its recontamination. It is estimated that he manufacturing process causes cross-contamination that comes from the work tools, equipment or workers. In particular, the spatula, one of the work tools, was found to have 4.4 Log CFU/g of aerobic bacteria and 4.2 Log CFU/g of colon bacillus that show they are highly contaminated. In the soaking process of Yugwa that lasts seven days, the level of TAB was a maximum of 10 Log CFU/g and the level of total colon bacillus was 6.8 Log CFU/g. When compared with washing methods, using hands and tools or running water, it is confirmed that the level of both TAB and total colon bacillus decreased to 5.0 Log CFU/g and 2.8 Log CFU/g respectively when hands were washed with running water 10 times. The above result shows that it's required for workers to wash their hands as well as wash and disinfect work tools and equipment in the process of producing Korean traditional cookies at small-scale companies. In addition, to reduce the level of microbial contamination in finished products, workers are required to apply their reduction method at the site.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.4
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• pp.287-294
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• 2021

The objective of this study was conducted to calculate the damage of whole crop maize in accordance with abnormal climate using the forage yield prediction model through machine learning. The forage yield prediction model was developed through 8 machine learning by processing after collecting whole crop maize and climate data, and the experimental area was selected as Gyeonggi-do. The forage yield prediction model was developed using the DeepCrossing (R²=0.5442, RMSE=0.1769) technique of the highest accuracy among machine learning techniques. The damage was calculated as the difference between the predicted dry matter yield of normal and abnormal climate. In normal climate, the predicted dry matter yield varies depending on the region, it was found in the range of 15,003~17,517 kg/ha. In abnormal temperature, precipitation, and wind speed, the predicted dry matter yield differed according to region and abnormal climate level, and ranged from 14,947 to 17,571, 14,986 to 17,525, and 14,920 to 17,557 kg/ha, respectively. In abnormal temperature, precipitation, and wind speed, the damage was in the range of -68 to 89 kg/ha, -17 to 17 kg/ha, and -112 to 121 kg/ha, respectively, which could not be judged as damage. In order to accurately calculate the damage of whole crop maize need to increase the number of abnormal climate data used in the forage yield prediction model.

• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.279-289
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• 2021

BACKGROUND: Recently, the golden apple snail, Pomacea canaliculata has been used as an environmentally-friendly weed-control agent in rice farming. Although effective for this particular style of farming, P. canaliculata can be destructive to other crops. The objective of this study was to identify overwintering as well as regional and seasonal distribution characteristics of P. canaliculata. Notably, winter is typically fatal for P. canaliculata. However, owing to increasing average global temperatures, we assessed the ability of P. canaliculata to survive through uncharacteristically warm winters. METHODS AND RESULTS: To examine the distribution and overwintering regions of P. canaliculata, We conducted a survey from April 2020 to May 2021 on environmentally-friendly rice fields, agricultural waterways, and streams in 23 cities belonging to 8 provinces. In addition, because air temperature may influence the distribution density of P. canaliculata, we analyzed the winter temperature data (http://weather.rda.go.kr). CONCLUSION(S): In 2021, overwintering of P. canaliculata (1-3 individuals/m²) was observed in the Goheung and Yeongam regions in Jeonnam. Overwintering of P. canaliculata was observed in fewer regions in 2021 than in 2020; this fact may be attributed to the lower minimum temperatures measured in 2021 (approximately 8℃ lower) than those in 2020. Our results suggest that overwintering occurs as long as overnight temperatures are ≥ -15℃, but can take place if temperatures are as low as -19℃.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.2
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• pp.17-28
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• 2022

The application of supplemental activated biochar pellet fertilizers (ABPFs) was evaluated by investigating key factors such as changes of surface paddy water and soil chemical properties and rice growth responses during the growing season. The treatments consisted of control, activated rice hull biochar pellet (ARHBP-40%), and activated palm biochar pellet (APBP-40%) applications. It was shown that the lowest NH₄⁺-N and PO₄^--P concentrations were observed in surface paddy water to the ARHBP-40%, while the NH₄⁺-N concentration in the control was abruptly decreased until 30 days after transplant in the soil. However, the lowest NH₄⁺-N concentration in the blended biochar application was 9.18 mg L^-1 at 1 day of transplant, but its ABPFs application was observed to be less than 1 mg L^-1 at 56 days after transplant. The lowest PO₄^--P concentration in paddy water treated ARHBP-40% ranged from 0.06 mg L^-1 to 0.08 mg L^-1 until 30 days after transplant among the treatments. For the paddy soil, the NH₄⁺-N concentration in the control was abruptly decreased from 177.7 mg kg^-1 to 49.4 mg kg^-1, while NO₃^--N concentration was highest, 13.2 mg kg^-1 in 14 days after transplant. The P₂O₅ concentrations in the soils increased from rice transplants until the harvesting period regardless of the treatments. The highest K₂O concentration was 252.8 mg kg^-1 in the APBP-40% at 84 days after transplant. For the rice growth responses, plant height in the control was relatively high compared to others, but grain yield was not significantly different between the control and ARHBP-40%. The application of ARHBP-40% can minimize nitrogen and phosphorous application rates into the agro-ecosystem.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.2
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• pp.115-125
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• 2022

The purpose of this study was to examine the effect of packaging on quality maintenance of paprika (Capsicum annuum L. cv. Nagano RZ) stored at three different temperatures. In Korea, paprika is stored and distributed under ambient conditions. To ensure the freshness maintenance, determining optimal storage temperature is necessary. Paprika were unpacked (control) or packed with polyamide film and stored at 5℃, 10℃ and 20℃ for 35 days. Quality characteristics such as weight loss and appearance were examined. Paprika packed with polyamide film showed less quality changes compared to unpacked paprika under all the storage temperatures. The commercial properties tended to decrease rapidly during storage at 20℃ regardless of packing. The degree of weight loss was significantly lower in packed paprika compared to unpacked paprika. It was found that soluble solids, pigments, hardness, etc. were complexly affected by storage temperature and film packaging. For paprika, the storage temperature of 5℃ or 10℃ was effective in maintaining freshness; paprika packed in polyamide film packing maintained greater freshness than unpacked paprika. Our results showed that, packaging is required to preserve the freshness and to improve the marketability of paprika in the domestic market. It seems that it is necessary to continuously search for an effective packaging method.