• Korean Journal of Soil Science and Fertilizer
• /
• v.46 no.2
• /
• pp.122-128
• /
• 2013

This study was carried out to evaluate the soil dehydrogenase activity and microbial biomass C with soil type and land use in cropland of JeJu region. Soil chemical properties, dehydrogenase activity, and microbial biomass C were analyzed after sampling from upland (50 sites), orchard (50 sites), paddy (30 sites), horticultural facility (30 sites) in March. Average pH values was at 6.3 in upland soil, however soil chemical properties showed a large spatial variations in both orchard and horticultural facility soil. The Zn and Cu contents increased by the continuous application of pig manure compost in some citrus orchard soil. Soil dehydrogenase activity and microbial biomass C were higher in non-volcanic ash than in volcanic ash soil regardless of land use type. Soil dehydrogenase activity was two to four times higher in upland than in the others. It was at 38.7 ug TPF $24^{h-1}g^{-1}$ in non-volcanic ash of upland soil. Microbial biomass C content was very high in horticultural facility soil and it showed at 216.8 $mg\;kg^{-1}$ in non-volcanic ash. Soil dehydrogenase activity showed a positive correlation with organic matter ($r^2$=0.59), Zn ($r^2$=0.65), and Cu ($r^2$=0.66) in non-volcanic ash horticultural facility soil. There was a negative correlation ($r^2$=0.57) between soil organic matter and dehydrogenase activity in volcanic ash upland soil.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.23 no.1
• /
• pp.143-149
• /
• 1994

Carotenoids isolated from orange peels were determined physicocohemical properties with TLC, UV-spectrophotometer and HPLC etc., and the results were as follows . Maximum absorption wavelength of the isolated carotenoids was 415nm when the result was similar to $\beta$-carotene as 423nm. Eight spots were obtianed from TLC, and identified lutein, lycopene, $\alpha$-carotene and $\beta$-carotene with HPLC. The effect pH during the storage period of isolate carotenoids, the period when the amount of pigment retention was over 50% in pH 5, 6 and 7 , after 10 days . The amount of pigment retention was lower in control than in treatment of sugars such as fructose, glucose and sorbitol , but sucrose was similar to the control, Isolated carotenoids were stable to ascorbic acid, and the amount of pigment retention was over 70% after 10 days. The amount of pigment retention in the effect oforganic acid was higher in treated citric acid , lactic acid and tartaric acid than in control, but lower in treated maleic acid and succinic acid. Isolated carotenoids were stable at 50 $^{\circ}C$, and the amount of pigment retention was over 50% at 10$0^{\circ}C$.

• Journal of Food Hygiene and Safety
• /
• v.34 no.1
• /
• pp.30-39
• /
• 2019

An analytical method was developed for the determination of sedaxane in agricultural products using liquid chromatograph-tandem mass spectrometry (LC-MS/MS). The samples were extracted with acetonitrile and partitioned with dichloromethane to remove the interference, and then purified by using silica SPE cartridges to clean up. The analytes were quantified and confirmed by using LC-MS/MS in positive ion mode using multiple reaction monitoring (MRM). The matrix-matched calibration curves were linear over the calibration ranges ($0.001-0.25{\mu}g/mL$) into a blank extract with $r^2$>0.99. For validation, recovery tests were carried out at three different concentration levels (LOQ, 10LOQ, and 50LOQ, n=5) with five replicates performed at each level. The recoveries were ranged between 74.5 to 100.8% with relative standard deviations (RSDs) of less than 12.1% for all analytes. All values were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for sedaxane determination in agricultural commodities.

• Journal of Food Hygiene and Safety
• /
• v.34 no.3
• /
• pp.235-241
• /
• 2019

An analytical method was developed for the determination of an antibiotic fungicide, kasugamycin, in agricultural products (hulled rice, potato, soybean, mandarin and green pepper) using liquid chromatographytandem mass spectrometry (LC-MS/MS). Samples were extracted with methanol adjusted to pH 13 using 1 N sodium hydroxide, and purified with a HLB (hydrophilic lipophilic balance) cartridge. Linearity of a matrix-matched calibration curve using seven concentration levels, from 0.001 to 0.1 mg/kg, was excellent with a correlation coefficient ($R^2$) of more than 0.9998. The limits of detection (LOD) and quantification (LOQ) of instrument were 0.0005 and $0.001{\mu}g/mL$, respectively, and the LOQ of analytical method calculated as 0.01 mg/kg. The average recoveries at three spiking levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) were in the range of 71.2~95.4% with relative standard deviation of less than 12.1%. The developed method was simple and all optimized results was satisfied with the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. The present study could be served as a reference for the establishment of maximum residue limits (MRL) of kasugamycin and be used as basic data for safety management relative to kasugamycin residues in imported and domestic agricultural products.

• Journal of Food Hygiene and Safety
• /
• v.34 no.2
• /
• pp.140-147
• /
• 2019

An analytical method was developed for the determination of quinoxyfen in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted with 1% acetic acid in acetonitrile and water was removed by liquid-liquid partitioning with $MgSO_4$ (anhydrous magnesium sulfate) and sodium acetate. Dispersive solid-phase extraction (d-SPE) cleanup was carried out using $MgSO_4$, PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed by using LC-MS/MS in positive mode with MRM (multiple reaction monitoring). The matrix-matched calibration curves were constructed using six levels ($0.001-0.25{\mu}g/mL$) and the coefficient of determination ($R^2$) was above 0.99. Recovery results at three concentrations (LOQ, 10 LOQ, and 50 LOQ, n=5) were in the range of 73.5-86.7% with RSDs (relative standard deviations) of less than 8.9%. For inter-laboratory validation, the average recovery was 77.2-95.4% and the CV (coefficient of variation) was below 14.5%. All results were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for quinoxyfen determination in agricultural commodities. This study could be useful for the safe management of quinoxyfen residues in agricultural products.

• Journal of Food Hygiene and Safety
• /
• v.34 no.2
• /
• pp.115-123
• /
• 2019

An analytical method was developed for the determination of fenpropimorph, a morpholine fungicide, in hulled rice, potato, soybean, mandarin and green pepper using QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) sample preparation and LC-MS/MS (liquid chromatography-tandem mass spectrometry). The QuEChERS extraction was performed with acetonitrile followed by addition of anhydrous magnesium sulfate and sodium chloride. After centrifugation, d-SPE (dispersive solid phase extraction) cleanup was conducted using anhydrous magnesium sulfate, primary secondary amine sorbents and graphitized carbon black. The matrix-matched calibration curves were constructed using seven concentration levels, from 0.0025 to 0.25 mg/kg, and their correlation coefficient ($R^2$) of five agricultural products were higher than 0.9899. The limits of detection (LOD) and quantification (LOQ) were 0.001 and 0.0025 mg/kg, respectively, and the limits of quantification for the analytical method were 0.01 mg/kg. Average recoveries spiked at three levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) and were in the range of 90.9~110.5% with associated relative standard deviation values less than 5.7%. As a result of the inter-laboratory validation, the average recoveries between the two laboratories were 88.6~101.4% and the coefficient of variation was also below 15%. All optimized results were satisfied the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. This study could serve as a reference for safety management relative to fenpropimorph residues in imported and domestic agricultural products.

• Journal of Food Hygiene and Safety
• /
• v.38 no.3
• /
• pp.79-88
• /
• 2023

Trifludimoxazin is a triazinone herbicide that inhibits the synthesis of protoporphyrinogen oxidase (PPO). The lack of PPO damages the cell membranes, leading to plant cell death. An official analytical method for the safety management of trifludimoxazin is necessary because it is a newly registered herbicide in Korea. Therefore, this study aimed to develop a residual analysis method to detect trifludimoxazin in five representative agricultural products. The EN method was established as the final extraction method by comparing the recovery test and matrix effect with those of the QuEChERS method. Various sorbent agents were used to establish the clean-up method, and no differences were observed among them. MgSO₄ and PSA were selected as the final clean-up conditions. We used LC-MS/MS considering the selectivity and sensitivity of the target pesticide and analyzed the samples in the MRM mode. The recovery test results using the established analysis method and inter-laboratory validation showed a valid range of 73.5-100.7%, with a relative standard deviation and coefficient of variation less than 12.6% and 14.5%, respectively. Therefore, the presence of trifludimoxazin can be analyzed using a modified QuEChERS method, which is widely available in Korea to ensure the safety of residual insecticides.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.1
• /
• pp.725-731
• /
• 2020

This study analyzed the impact of increasing orange imports on the domestic fruit markets, focusing on the period January to May when oranges were imported and sold intensively after implementation of the Korea-US FTA. In this study, only citrus fruits that compete with U.S. oranges were limited to domestic fruits; of these, Hallabong, which is consistent with consumption of U.S. oranges, was selected as an analysis target. A dynamic recursive simulation model was established to evaluate the ex-post effects of the Korea-U.S. FTA, and to conduct mid and long-term forecasts for the Hallabong market. In addition, major policy simulations were performed on the Hallabong market to assess the effect of each scenario. The ex-post impact evaluation reveals that between December and February, Hallabong had no effect on the seasonal tariff of oranges. However, from 2012 to 2017, the actual import decreased by 21.9 billion won annually due to the TRQ, with the accumulated 6-year decrease being 131.5 billion won. Major policy simulation analysis shows that the change in the unit cost of import due to the U.S orange crop and the increase of Hallabong export will help in expanding the market, and thus effectively increase income.

• Journal of Food Hygiene and Safety
• /
• v.38 no.3
• /
• pp.131-139
• /
• 2023

In this study, we investigated pesticide residue levels in 535 domestically distributed agricultural products in South Korea using multi-residue analysis. Agricultural products from 13 regions, including Seoul, were pretreated using QuEChERS and d-SPE, and subsequently analyzed using LC-MS/MS and GC-MS/MS. Residual pesticides were detected in 288 (53.8%) out of the 535 samples, including 40 of apples, 40 of peppers, 33 of mandarins, 31 of peaches, and 144 other commodities. Furthermore, one sample of Korean cabbage exceeded the permitted maximum residue limit (MRL), diniconazole (0.18 mg/kg), detected at about twice the MRL. In total, 91 types of residual pesticides were detected, including fungicides (42), insecticides (48), and a nematicide. The most frequently detected pesticides were dinotefuran (91), carbendazim (75), tebuconazole (61), and pyraclostrobin (59). Our results showed that continuous monitoring of agricultural products is necessary.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.3
• /
• pp.262-276
• /
• 2018

Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.