• Journal of Bio-Environment Control
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• v.31 no.2
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• pp.114-124
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• 2022

The Saemangeum has a dry surface characteristic with a low moisture content ratio due to the saline and silt soil, so the vegetation cover is low compared to other areas. In areas with low vegetation cover, wind erosion has a high probability of scattering dust. If the vegetation cover is increased by cultivating crops that can withstand the Saemangeum reclaimed environment, scattering dust can be reduced by reducing the flow rate at the bottom. Thus, the purpose of this study is to analyze the effect of suppressing the generation of fine dust and scattering dust by cultivating winter forage crops on the Saemangeum reclaimed land. While growing 0.5 ha of barley and 0.5 ha of triticale in Saemangeum reclaimed land, the concentration of fine dust was monitored according to agricultural work and growth stage. Changes in the concentrations of PM-10, PM-2.5, and PM-1.0 were monitored on the leeward, the windward and centering on the crop field. As a result of monitoring, PM-1.0 had little effect on crop cultivation. the concentration of PM-10 and PM-2.5 increased according to tillage and harvesting, and tillage had a higher increasing the concentration of PM-10 and PM-2.5 than that of harvesting. According to the growth stage of crops, the effect of suppressing scattering dust was shown, and the effect of suppressing scattering dust was higher in the heading stage than in the seedling stage. So, it was found that there was an effect of suppressing scattering dust other than the effect of land covering. Through this study, it was possible to know about the generation and suppression effect of scattering dust according to crop cultivation.

• Microbiology and Biotechnology Letters
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• v.44 no.4
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• pp.432-441
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• 2016

Machaerium cuspidatum, a canopy liana, is a species of genus legume in the Fabaceae family and contributes to the total species richness in the tropical rain forests. In the present study, we investigated the antioxidative and anti-cancer effects of M. cuspidatum and its mode of action. The methanol extract of M. cuspidatum (MEMC) exhibited anti-oxidative activity with an $IC_{50}$ value of $1.66{\mu}g/ml$, and this was attributable to its 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity. MEMC also exhibited a cytotoxic effect and induced morphological changes in a dose-dependent manner in several cancer cell lines including human lung adenocarcinoma A549 cells, human hepatocellular carcinoma HepG2 cells, and human colon carcinoma HT29 cells. Moreover, MEMC treatment induced the accumulation of subG1 population, which is indicative of apoptosis in A549 and HepG2 cells. MEMC-induced apoptosis was confirmed by the increase in Annexin V-positive apoptotic cells and apoptotic bodies using Annexin-V staining and DAPI staining, respectively. Further investigation showed that MEMC-induced apoptosis was associated with the increase in p53 and Bax expression, and the decrease in Bcl-2 expression. In addition, MEMC treatment led to proteolytic activation of caspase-3, 8, and 9 and degradation of poly-ADP ribose polymerase (PARP). Taken together, these results suggest that MEMC may exert a beneficial anti-cancer effect by inducing apoptosis via both the extrinsic and intrinsic pathways in A549 and HepG2 cells.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.317-326
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• 2019

Salinity which is often detected on reclaimed land is a major detrimental factor to crop growth. It would be advantageous to develop an approach for assessment of salinity and drought damages using a non-destructive method in a large landfills area. The objective of this study was to examine applicability of the decision tree classifier using imagery for classifying for spring potatoes (Solanum tuberosum) damaged by salinity or drought at vegetation growth stages. We focused on comparing the accuracies of OA (Overall accuracy) and KC (Kappa coefficient) between the simple reflectance and the band ratios minimizing the effect on the light unevenness. Spectral merging based on the commercial band width with full width at half maximum (FWHM) such as 10 nm, 25 nm, and 50 nm was also considered to invent the multispectral image sensor. In the case of the classification based on original simple reflectance with 5 nm of FWHM, the selected bands ranged from 3-13 bands with the accuracy of less than 66.7% of OA and 40.8% of KC in all FWHMs. The maximum values of OA and KC values were 78.7% and 57.7%, respectively, with 10 nm of FWHM to classify salinity and drought damages of spring potato. When the classifier was built based on the band ratios, the accuracy was more than 95% of OA and KC regardless of growth stages and FWHMs. If the multispectral image sensor is made with the six bands (the ratios of three bands) with 10 nm of FWHM, it is possible to classify the damaged spring potato by salinity or drought using the reflectance of images with 91.3% of OA and 85.0% of KC.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.954-961
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• 2010

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for quantifying yield, biomass, and nitrogen (N) stress during growing season. This study was conducted to assess biomass and nitrogen (N) status of paddy rice (Oryza sativa L.) plants under N stress using passive and active ground-based remote sensors. Nitrogen application rates were 0, 70, 100, and 130 kg N $ha^{-1}$. At each growth stage, reflectance indices measured with active sensor showed higher correlation with DW, N uptake and N concentration than those with the passive sensor. NIR/Red and NIR/Amber indices measured with Crop Circle active sensors generally had a better correlation with dry weight (DW), N uptake and N content than vegetation indices from Crop Circle passive sensor and NDVIs from active sensors. Especially NIR/Red and NIR/amber ratios at the panicle initiation stage were most closely correlated with DW, N content, and N uptake. Rice grain yield, DW, N content and N uptake at harvest were highly positively correlated with canopy reflectance indices measured with active sensors at all sampling dates. N application rate explains about 91~92% of the variability in the SI calculated from NIR/Red or NIR/Amber indices measured with Crop Circle active sensors on 12 July. Therefore, the in-season sufficiency index (SI) by NIR/Red or NIR/Amber index from Crop Circle active sensors can be used for determination of N application rate.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.51-60
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• 2019

The major purpose of this study is to construct an in-situ soil moisture verification network employing Frequency Domain Reflectometry (FDR) sensors for Cosmic-ray soil moisture observation system operation as well as long-term field-scale soil moisture monitoring. The test bed of Cosmic-ray and FDR verification network system was established at the Sulma Catchment, in connection with the existing instrumentations for integrated data provision of various hydrologic variables. This test bed includes one Cosmic-ray Neutron Probe (CRNP) and ten FDR stations with four different measurement depths (10 cm, 20 cm, 30 cm, and 40 cm) at each station, and has been operating since July 2018. Furthermore, to assess the reliability of the in-situ verification network, the volumetric water content data measured by FDR sensors were compared to those calculated through the core sampling method. The evaluation results of FDR sensors- measured soil moisture against sampling method during the study period indicated a reasonable agreement, with average values of $bias=-0.03m^3/m^3$ and RMSE $0.03m^3/m^3$, revealing that this FDR network is adequate to provide long-term reliable field-scale soil moisture monitoring at Sulmacheon basin. In addition, soil moisture time series observed at all FDR stations during the study period generally respond well to the rainfall events; and at some locations, the characteristics of rainfall water intercepted by canopy were also identified. The Temporal Stability Analysis (TSA) was performed for all FDR stations located within the CRNP footprint at each measurement depth to determine the representative locations for field-average soil moisture at different soil profiles of the verification network. The TSA results showed that superior performances were obtained at FDR 5 for 10 cm depth, FDR 8 for 20 cm depth, FDR2 for 30 cm depth, and FDR1 for 40 cm depth, respectively; demonstrating that those aforementioned stations can be regarded as temporal stable locations to represent field mean soil moisture measurements at their corresponding measurement depths. Although the limit on study duration has been presented, the analysis results of this study can provide useful knowledge on soil moisture variability and stability at the test bed, as well as supporting the utilization of the Cosmic-ray observation system for long-term field-scale soil moisture monitoring.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.106-114
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• 2023

With rising concerns about pesticide spray drift by aerial application, this study attempt to evaluate aerodynamic property and collection efficiency of spray drift according to the leaf area index (LAI) of crop for preventing undesirable pesticide contamination by the spray-drift tunnel experiment. The collection efficiency of the plant with 'Low' LAI was measured at 16.13% at a wind speed of 1 m·s^-1. As the wind speed increased to 2 m·s^-1, the collection efficiency of plant with the same LAI level increased 1.80 times higher to 29.06%. For the 'Medium' level LAI, the collection efficiency was 24.42% and 43.06% at wind speed of 1 m·s^-1 and 2 m·s^-1, respectively. For the 'High' level LAI, it also increased 1.24 times higher as the wind speed increased. The measured results indicated that the collection of spray droplets by leaves were increased with LAI and wind speed. This also implied that dense leaves would have more advantages for preventing the drift of airborne spray droplets. Aerodynamic properties also tended to increase as the LAI increased, and the regression analysis of quadric equation and power law equation showed high explanatory of 0.96-0.99.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.