• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.321-329
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• 2014

This experiment was conducted to establish an analytical method for residues of amisulbrom, as recently developed an oomycete-specific fungicide showing inhibition of fungal respiration, in crops using HPLC-UVD/MS. Amisulbrom residue was extracted with acetonitrile from representative samples of five raw products which comprised apple, green pepper, kimchi cabbage, potato and hulled rice. The extract was diluted with 50 mL of saline water and directly partitioned into dichloromethane to remove polar co-extractives in the aqueous phase. For the hulled rice sample, n-hexane/acetonitrile partition was additionally employed to remove non-polar lipids. The extract was finally purified by optimized Florisil column chromatography. On an octadecylsilyl column in HPLC, amisulbrom was successfully separated from sample co-extractives and sensitively quantitated by ultraviolet absorption at 255 nm with no interference. Accuracy and precision of the proposed method was validated by the recovery test on every crop samples fortified with amisulbrom at 3 concentration levels per crop in each triplication. Mean recoveries ranged from 85.3% to 105.6% in five representative agricultural commodities. The coefficients of variation were all less than 10%, irrespective of sample types and fortification levels. Limit of quantitation (LOQ) of amisulbrom was 0.04 mg/kg as verified by the recovery experiment. A confirmatory method using LC/MS with selected-ion monitoring technique was also provided to clearly identify the suspected residue. The proposed method was sensitive, reproducible and easy-to-operate enough to routinely determine the residue of amisulbrom in agricultural commodities.

• Analytical Science and Technology
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• v.26 no.2
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• pp.142-153
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• 2013

A new, rapid, and simple analytical method was developed and validated using high performance liquid chromatograph-photodiode array detector (HPLC-PAD) for the determination of lepimectin residues in agricultural commodities. The lepimectin residues in samples were extracted with methanol, partitioned with dichloromethane, and then purified with glass column filled with subsequently to aminopropyl ($NH_2$) solid phase extraction (SPE) cartridge. The purified samples were detected using HPLC-PAD. Correlation coefficient ($R^2$) of both lepimectin $A_3$ and $A_4$ solutions were 0.9999. The method was validated using cucumber spiked with lepimectin at 0.02 and 0.2 mg/kg and pepper, mandarin, hulled rice, potato, soybean at 0.02 and 0.5 mg/kg. Average recoveries were 76.0~114.8% with relative standard deviation less than 10%, and limit of detection (LOD) and limit of quantification (LOQ) were 0.005 and 0.01 mg/kg, respectively. The result of recoveries and overall coefficient of variation of a laboratory results in Gwangju regional KFDA and Daejeon regional KFDA was followed with Codex guideline (CAC/GL 40). Therefore, developed method in this study is accurate, rapid, and appropriate for lepimectin determination and will be used to keep safety of lepimectin residues in agricultural products.

• The Korean Journal of Pesticide Science
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• v.15 no.2
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• pp.149-159
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• 2011

Bentazone is benzothiadiazole group herbicide, and used to foliage treatment. This herbicide have already been widely used for cereals and vegetables planting in worldwide. This experiment was conducted to establish a determination method for bentazone residue in crops using HPLC-UVD/MS. Bentazone residue was extracted with acetone (adjusted pH 1 with phosphoric acid) from representative samples of five raw products which comprised hulled rice, soybean, apple, green pepper, and Chinese cabbage. The extract was diluted with saline water, and dichloromethane partition was followed to recover bentazone from the aqueous phase. Florisil column chromatography was additionally employed for final clean up of the extract. The bentazone was quantitated by HPLC with UVD, using a YMC ODS AM 303 ($4.6{\times}250$ mm) column. The crops were fortified with bentazone at 3 levels per crop. Mean recovery ratio were ranged from 82.0% for a 0.2 mg/kg in apple to 97.9% for a 0.02 mg/kg in Chinese cabbage. The coefficients of variation were ranged from 0.5% for a 0.02 mg/kg in soybean to 9.7% for a 0.02 mg/kg in Chinese cabbage. Quantitative limit of bentazone was 0.02 mg/kg in representative five crop samples. A LC/MS with selected-ion monitoring was also provided to confirm the suspected residue. Therefore, this analytical method was reproducible and sensitive enough to determine the residue of bentazone in agricultural commodities.

• The Korean Journal of Pesticide Science
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• v.15 no.2
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• pp.125-133
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• 2011

Ametryn is used in USA, China, and Japan, but not introduced in Korea yet. So, MRL (Maximum Residue Level), and analytical method of ametryn were not establishment in Korea. Therefore, this experiment was conducted to establish a determination method for ametryn residue in crops using HPLC-UVD/MS. Ametryn residue was extracted with acetone from representative samples of five raw products which comprised hulled rice, soybean, apple, green pepper, and Chinese cabbage. The extract was diluted with saline water, and dichloromethane partition was followed to recover ametryn from the aqueous phase. Florisil column chromatography was additionally employed for final clean up of the extract. The ametryn was quantitated by HPLC with UVD, using a Tosoh ODS 120T ($4.6{\times}250$ mm) column. The crops were fortified with ametryn at 2 levels per crop. Mean recovery ratio were ranged from 83.7% for a 0.2 mg/kg in soybean to 91.1% for a 1.0 mg/kg in hulled rice. The coefficients of variation were ranged from 1.2% for a 1.0 mg/kg in hulled rice to 3.6% for a 1.0 mg/kg in soybean. Quantitative limit of amatryn was 0.02 mg/kg in representative 5 crop samples. A LC/MS with selected-ion monitoring was also provided to confirm the suspected residue. Therefore, this analytical method was reproducible and sensitive enough to determine the residue of ametryne in agricultural commodities.

• Journal of Korean Society of Forest Science
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• v.105 no.2
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• pp.238-246
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• 2016

The study aims to examine Japan's National REDD+ Strategies prepared for Post-2020 and the status of its implementation by organizations in Japan, and then to suggest the potential REDD+ countermeasures against Joint Credit Mechanism (JCM) for Republic of Korea and their implications. As for the technical limitations of the guidelines of REDD+ under the JCM, it is pointed out that forests located at the place with less potential safeguard intervention tend to be selected as the target area for a project and that, as reference emission trend changes depending on the basic year of the baseline, differences could occur among the amounts of greenhouse gas emission. In addition, it is pointed out that the result of the calculation of the displacement of emissions, or leakeage, in REDD+, can have an uncertainty, since the calculation is done by just multiplying leakage area by certain coefficients, without considering the size of the leakage area. Furthermore, the lack of implementation guideline or methodologies for a project level is also pointed out as a limitation, considering that there are only some national and sub-national monitoring guidelines at present. Finally, internationally accepted guidelines for safeguard and its sub-items needed to be prepared, as current safeguard policy only includes lists without detailed items. Such things mentioned above are all related to, and can lead to the problem of double counting of items in Nested Approach etc., as well as of the distribution of credits. Therefore, Republic of Korea should take these into consideration when implementing its REDD+ projects.

• Korean Journal of Environmental Agriculture
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• v.37 no.1
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• pp.57-65
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• 2018

BACKGROUND: An analytical method was developed using HPLC-UVD/MS to precisely determine the residue of flusulfamide, a benzenesulfonamide fungicide used to inhibit spore germination. METHODS AND RESULTS: Flusulfamide residue was extracted with acetone from representative samples of five raw products which comprised apple, green pepper, Kimchi cabbage, hulled rice, and soybean. The extract was diluted with large volume of saline water and directly partitioned into dichloromethane to remove polar co-extractives in the aqueous phase. For the hulled rice and soybean samples, n-hexane/acetonitrile partition was additionally employed to remove non-polar lipids. The extract was finally purified by optimized Florisil column chromatography. On an octadecylsilyl column in HPLC, flusulfamide was successfully separated from co-extractives of sample, and sensitively quantitated by ultraviolet absorption at 280 nm with no interference. Accuracy and precision of the proposed method was validated by the recovery experiment on every crop sample fortified with flusulfamide at 3 concentration levels per crop in each triplication. CONCLUSION: Mean recoveries ranged from 82.3 to 98.2% in five representative agricultural commodities. The coefficients of variation were all less than 10%, irrespective of sample types and fortification levels. Limit of quantitation (LOQ) of flusulfamide was 0.02 mg/kg as verified by the recovery experiment. A confirmatory method using LC/MS with selected-ion monitoring technique was also provided to clearly identify the suspected residue.

• The Korean Journal of Pesticide Science
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• v.14 no.1
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• pp.37-48
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• 2010

The diacylhydrazine insecticides, methoxyfenozide, chromafenozide and tebufenozide are new-generation insecticides. These insecticides induce premature molting and cause the death of insects by mimicking their hormone. Also, these insecticides have already been widely used for vegetables planting in worldwide. Highperformance liquid chromatography (HPLC) is the most widely used procedure for determination of each compound residues in crops. However, simultaneous analysis method of these diacylhydrazine insecticides was not reported. The purpose of this study is to develop a simultaneous determination procedure of methoxyfenozide, chromafenozide and tebufenozide residue in crops using HPLC-UVD/MS method. These insecticide residues were extracted with acetone from representative samples of five raw products which comprised hulled rice, soybean, apple, pepper, and Chinese cabbage. The extract was diluted with saline water, and dichloromethane partition was followed to recover these insecticides from the aqueous phase. Florisil column chromatography was additionally employed for final cleanup of the extracts. The analytes were quantitated by HPLCUVD/MS, using a $C_{18}$ column. The crops were fortified with each insecticide at two levels per crop. Mean recoveries ranged from 89.0 to 104.8% in five representative agricultural commodities. The coefficients of variation were less than 3.9%. Quantitative limits of methoxyfenozide, chromafenozide and tebufenozide were 0.04 mg/kg in crop samples. A HPLC-UVD/MS with selected-ion monitoring was also provided to confirm the suspected residues. The proposed simultaneous analysis method was reproducible and sensitive enough to determine the residues of methoxyfenozide, chromafenozide and tebufenozide in agricultural commodities.

• Korean Journal of Environmental Agriculture
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• v.34 no.4
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• pp.309-317
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• 2015

BACKGROUND: An analytical method was developed using GC-ECD/MS to precisely determine the residue of fipronil, a phenylpyrazole insecticide used to control a wide range of foliar and soil-borne pests.METHOD AND RESULTS: Fipronil residue was extracted with acetone from representative samples of five raw products which comprised hulled rice, soybean, Kimchi cabbage, green pepper, and apple. The extract was diluted with saline water, and fipronil was partitioned into n-hexane/dichloromethane (20/80, v/v) to remove polar co-extractives in the aqueous phase. Florisil column chromatography was additionally employed for final purification of the extract. Fipronil was separated and quantitated by GC-ECD using a DB-17 capillary column. Accuracy of the proposed method was validated by the recovery from crop samples fortified with fipronil at 3 levels per crop in each triplication.CONCLUSION: Mean recoveries ranged from 86.6% to 106.0% in five representative agricultural commodities. The coefficients of variation were less than 10%. Limit of quantitation of fipronil was 0.004 mg/kg as verified by the recovery experiment. A confirmatory technique using GC/MS with selected-ion monitoring was also provided to clearly identify the suspected residue. Therefore, this analytical method was reproducible and sensitive enough to determine the residue of fipronil in agricultural commodities.

• Korean Journal of Medicinal Crop Science
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• v.7 no.1
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• pp.45-50
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• 1999

Timosaponin A III, an active and major compound, was isolated from rhizomes of Anemarrhena asphodeloides. The quantitative analysis of timosaponin AIII was performed by a high performance liquid chromatographic(HPLC) method using ELSD and the useful extraction method for HPLC analysis was examined as well. This HPLC method can be utilized as the standard analytical method for the evaluation of the quality of Anemarrhena rhizoma in the steps of breeding and cultivation. Additionally, the HPLC analysis method can be useful for the evaluation of the quality of Anemarrhena rhizoma sold as a traditional medicine in current markets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.36-43
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• 2005

This paper suggests a method to effectively apply an application model of fuzzy-neural network to the optimal load distribution algorithm, considering the complication and non-linearity of the web server environment. We use the clustering web server in the linux system and it consists of a load balancer that distributes the network loads and some of real servers that processes the load and responses to the client. The previous works considered only with the scrappy decision information such as the connections. That is, since the distribution algorithm depends on the input of the whole network throughput, it was proved inefficient in terms of performance improvement of the web server. With the proposed algorithm, it monitors the whole states of both network input and output. Then, it infers CPU and memory states of each real server and effectively distributes the requests of the clients. In this paper, the proposed model is compared with the previous method through simulations and we analysis the results to develop the optimal and intelligent load balancing model.