• Korean journal of applied entomology
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• v.60 no.1
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• pp.1-13
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• 2021

The concept of integrated pest management (IPM) first developed in the 1950s, and the concept of economic control via pest management was established in the 1960s. Research on IPM began in the United States and Europe, and IPM studies in Korea started with citrus insects and paddy field pests following the distribution of high-yield varieties of rice. Apple IPM in Korea began with research on pest control using chemical pesticides and pesticides resistant to insect pests, studies on the ecology of insect pests and their natural enemies, and the exploitation of sex pheromones on insect pests. Since the 1990s, IPM research and field projects have been carried out simultaneously for farming households. In the 2000s, the development of pest monitoring and forecasting models centered on mating disturbances, database programs for pests, and networks for sharing information. IPM technology has expanded via the development of unmanned forecasting systems and automation technologies in the 2010s.

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.57-63
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• 2023

The external weather conditions including temperature and wind speed in the Saemangeum reclaimed land is different from that of the inland, affecting the internal environment of the greenhouse. Therefore, it is important to select an appropriate covering material considering the insulation effect according to the type and characteristics of the covering material considering the weather condition in the Saemangeum reclaimed land. A hexahedral insulation chamber was designed to evaluate the insulation efficiency of each glass-clad material in the outside weather condition in reclaimed land. In order to evaluate the insulation effect of each covering material, a radiator was installed and real-time power consumption was monitored. 16-mm PC (polycarbonate), 16-mm PMMA (polymethyl methacrylate), 4-mm greenhouse glass, and 16-mm double-layered glass were used as the covering materials of the chamber. In order to understand the effect of the external wind directions, the windward and downwind insulation properties were evaluated. As a result of comparing the thermal insulation effect of each greenhouse cover material to single-layer glass, the thermal insulation effect of double-layer glass was 16.9% higher, while PMMA and PC were 62.5% and 131.2% higher respectively. On average the wind speed on the windward side was 53.1% higher than that on the lee-wind side, and the temperature difference between the inside and outside of the chamber at the wind ward side was found to be 52.0% larger than that on the lee ward side. During the experiment period, the overall heating operation time for PC was 39.2% lower compared to other insulation materials. Showing highest energy efficiency, and compared to PC, single-layer glass power consumption was 37.4% higher.

• Research in Plant Disease
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• v.28 no.4
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• pp.179-194
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• 2022

In this review, the mycotoxin contamination of Korean cereals and their products is analyzed by crop based on scientific publications since 2000. Barley, rice, and corn were investigated heavier than the others. The common mycotoxins occurred in all cereals and their products were deoxynivalenol and zearalenone. Nivalenol was detected in all samples analyzed but more frequently or mainly in barley, rice, and oat. Fumonisin was commonly detected in corn and sorghum but also in adlay, millet, and rice. Adlay and millet were similar in the contamination pattern that fumonisin and zearalenone were the most frequently detected mycotoxins. Zearalenone was the most commonly detected mycotoxin with concentrations higher than the national standards (maximum limit), followed by deoxynivalenol, and aflatoxin. However, most occurrence levels were below the maximum limits for respective mycotoxins. This result shows that barley, rice, corn, sorghum, millet, and adlay are more vulnerable to mycotoxin contamination than other cereals and therefore continuous monitoring and safety management are necessary.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1085-1095
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• 2023

Time-series data generated from satellite data are crucial resources for change detection and monitoring across various fields. Existing research in time-series data generation primarily relies on single-image analysis to maintain data uniformity, with ongoing efforts to enhance spatial and temporal resolutions by utilizing diverse image sources. Despite the emphasized significance of time-series data, there is a notable absence of automated data collection and preprocessing for research purposes. In this paper, to address this limitation, we propose a system that automates the collection of satellite information in user-specified areas to generate time-series data. This research aims to collect data from various satellite sources in a specific region and convert them into time-series data, developing an automatic satellite image collection system for this purpose. By utilizing this system, users can collect and extract data for their specific regions of interest, making the data immediately usable. Experimental results have shown the feasibility of automatically acquiring freely available Landsat and Sentinel images from the web and incorporating manually inputted high-resolution satellite images. Comparisons between automatically collected and edited images based on high-resolution satellite data demonstrated minimal discrepancies, with no significant errors in the generated output.

• The Korean Journal of Pesticide Science
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• v.14 no.2
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• pp.95-103
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• 2010

Fomesafen is a selective herbicide, and used to control annual and perennial broad-leaf grass on soybean and fruit fields in USA and China, but not introduced in Korea yet. So, MRL (Maximum Residue Level), and analytical method of fomesafen were not establishment in Korea. Therefore, this experiment was conducted to establish a determination method for fomesafen residue in crops using HPLC-UVD/MS. Fomesafen 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 fomesafen from the aqueous phase. Florisil column chromatography was additionally employed for final clean up of the extract. The fomesafen was quantitated by HPLC with UVD, using a Shiseido CAPCELL-PAK UG C18 column. The crops were fortified with fomesafen at 3 levels per crop. Mean recovery ratio were ranged from 87.5% for a 0.4 ppm in hulled rice to 102.5% for a 0.4 ppm in apple. The coefficients of variation were ranged from 0.6% for a 2.0 ppm in hulled rice to 7.7% for a 0.04 ppm in green pepper. Quantitative limit of fomesafen was 0.04 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 fomesafen in agricultural commodities.

• Korean Journal of Environmental Agriculture
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• v.37 no.2
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• pp.104-116
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• 2018

BACKGROUND: This experiment was conducted to establish a simultaneous analysis method for 7 kinds of herbicides in 3 different classes having similar physicochemical property as diphenyl ether(bifenox and oxyfluorfen), dinitroaniline (ethalfluralin and trifluralin), and chloroacetamide (metolachlor, pretilachlor, and thenylchlor) in crops using GC-ECD/MS. METHODS AND RESULTS: All the 7 pesticide residues were 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 saline water and directly partitioned into n-hexane/dichloromethane(80/20, v/v) 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. The analytes were separated and quantitated by GLC with ECD using a DB-1 capillary column. Accuracy and precision of the proposed method was validated by the recovery experiment on every crop samples fortified with bifenox, ethalfluralin, metolachlor, oxyfluorfen, pretilachlor, thenylchlor, and trifluralin at 3 concentration levels per crop in each triplication. CONCLUSION: Mean recoveries of the 7 pesticide residues ranged from 75.7 to 114.8% 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 the analytes were 0.004 (etahlfluralin and trifluralin), 0.008 (metolachlor and pretilachlor), 0.006 (thenylchlor), 0.002 (oxyfluorfen), and 0.02 (bifenox) 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 residues. Therefore, this analytical method was reproducible and sensitive enough to determine the residues of bifenox, ethalfluralin, metolachlor, oxyfluorfen, pretilachlor, thenylchlor, and trifluralin in agricultural commodities.

• The Korean Journal of Pesticide Science
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• v.20 no.4
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• pp.319-325
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• 2016

This study was conducted to investigate residual organochlorine pesticides in green house soil and oriental melon, green pepper, and lettuce. The majority of them were designated as persistent organic pollutants (POPs) by the international community at the Stockholm Convention on Persistent Organic Pollutant. Extraction and clean-up method were developed using the QuEChERS method for residual organochlorine pesticides (OCPs) in soil and oriental melon, green pepper and lettuce. Recovery of OCPs in greenhouse soil and oriental melon, green pepper, and lettuce ranged from 73.3-110.6%. Limit of detection (LOD) of OCPs in soil and 3 crops were 0.01-0.08 and $0.11-0.17{\mu}g/kg$. The residues of OCPs in oriental melon, green pepper and lettuce greenhouse soil were analyzed by the developed method, and dieldrin, ${\beta}-endosulfan$ and endosulfan sulfate were detected at 1.4-72.5, 0.1-78.7 and $0.0-214.1{\mu}g/kg$, respectively. The detection frequency of 3 compounds in soils were 52 (29.7%), 34 (19.4%) and 57 (32.6%) among 175 samples, respectively. However, these compounds were not detected in all crop samples. The residue level in 3 crops were lower than 1/58.8 of maximum residue level of them. These results showed that the OCPs residue in oriental melon, green pepper, and lettuce greenhouse soil were not as high as crop safety threatening.

• The Korean Journal of Pesticide Science
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• v.15 no.3
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• pp.254-268
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• 2011

Fenoxycarb, pyriproxyfen and methoprene are juvenile hormone mimic insecticide. These insecticides have been widely used for mosquito, fly, scale insects, and Lepidoptera. The purpose of this study was to develop a simultaneous determination procedure of fenoxycarb, pyriproxyfen and methoprene residues in crops using HPLC-UVD/MS. These insecticide residues were extracted with acetone from representative samples of four raw products which comprised brown rice, apple, green pepper, and Chinese cabbage. The extract was diluted with saline water, and then n-hexane/dichloromethane partition was followed to recover these insecticides from the aqueous phase. Florisil column chromatography was additionally employed for final clean up of the extract. The analytes were quantitated by HPLC-UVD/MS, using a $C_{18}$ column. The crops were fortified with each insecticide at 3 levels per crop. Mean recovery ratios were ranged from 80.0 to 104.3% in four representative agricultural commodities. The coefficients of variation were less than 4.8%. Quantitative limit of fenoxycarb, pyriproxyfen, and methoprene was 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 fenoxycarb, pyriproxyfen and methoprene in the agricultural commodities.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.1
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• pp.23-31
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• 2013

Microwave remote sensing can help monitor the land surface water cycle and crop growth. This type of remote sensing has great potential over conventional remote sensing using the visible and infrared regions due to its all-weather day-and-night imaging capabilities. In this paper, a ground-based multi-frequency (L-, C-, and X-band) polarimetric scatterometer system capable of making observations every 10 min was developed. This system was used to monitor the wheat over an entire growth cycle. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. Backscattering coefficients for the crop growing season were compared with biophysical measurements. Backscattering coefficients for all frequencies and polarizations increased until dat of year 137 and then decreased along with fresh weight, dry weight, plant height, and vegetation water content (VWC). The range of backscatter for X-band was lower than for L- and C-band. We examined the relationship between the backscattering coefficients of each band (frequency/polarization) and the various wheat growth parameters. The correlation between the different vegetation parameters and backscatter decreased with increasing frequency. L-band HH-polarization (L-HH) is best suited for the monitoring of fresh weight (r=0.98), dry weight (r=0.96), VWC (r=0.98), and plant height (r=0.96). The correlation coefficients were highest for L-band observations and lowest for X-band. Also, HH-polarization had the highest correlations among the polarization channels (HH, VV and HV). Based on the correlation analysis between backscattering coefficients in each band and wheat growth parameters, we developed prediction equations using the L-HH based on the observed relationships between L-HH and fresh weight, dry weight, VWC and plant height. The results of these analyses will be useful in determining the optimum microwave frequency and polarizations necessary for estimating vegetation parameters in the wheat.