• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.1-9
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• 2023

Arsenic (As), which is ubiquitous throughout the environment, represents a major environmental threat at higher concentration and poses a global public health concern in certain geographic areas. Most of the conventional arsenic remediation techniques that are currently in use have certain limitations. This situation necessitates a potential remediation strategy, and in this regard bioremediation technology is increasingly important. Being the oldest representativse of life on Earth, microbes have developed various strategies to cope with hostile environments containing different toxic metals or metalloids including As. Such conditions prompted the evolution of numerous genetic systems that have enabled many microbes to utilize this metalloid in their metabolic activities. Therefore, within a certain scope bacterial isolates could be helpful for sustainable management of As-contamination. Research interest in microbial As(III) oxidation has increased recently, as oxidation of As(III) to less hazardous As(V) is viewed as a strategy to ameliorate its adverse impact. In this review, the novelty of As(III) oxidation is highlighted and the implication of As(III)-oxidizing microbes in environmental management and their prospects are also discussed. Moreover, future exploitation of As(III)-oxidizing bacteria, as potential plant growth-promoting bacteria, may add agronomic importance to their widespread utilization in managing soil quality and yield output of major field crops, in addition to reducing As accumulation and toxicity in crops.

• Korean Journal of Environmental Agriculture
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• v.19 no.5
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• pp.375-381
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• 2000

Quantifying the changes of soil microbial biomass and activity of enzymes are important to understand the dynamics of active soil C and N pools. The dynamics of soil microbial biomass C and N and the activity of enzymes over entire growth period of soybean-(Glycine max (L) Merr.)-wheat (Triticum aestivum L.) sequence on a Typic Haplustert as influenced by organic manure and inorganic fertilizer N were investigated in a field experiment. The application of farmyard manure at 4 to 16 $Mg{\cdot}ha^{-1}\;y^{-1}r^{-1}$ along with fertilizer nitrogen at 50 or 180 $kg{\cdot}ha^{-1}$ increased the mean soil microbial biomass from 1.12 to 2.05 fold over unmanured soils under soybean-wheat system. Irrespective of organic and chemical fertilizer N application, the soil microbial biomass was maximum during the first two months at active growing stage of the crops and subsequently declined with crop maturity. The mean annual microbial activity was significantly increased when manure and chemical fertilizer at 8 $Mg{\cdot}ha^{-1}$ and 50/180 N $kg{\cdot}ha^{-1}$, respectively were applied. The C turnover rate decreased by 47 to 72 % when the level of farmyard manure was increased from 4 to 8 and 16 $Mg{\cdot}ha^{-1}$. There were significant correlations between biomass C, available N, dehydrogenase, phosphatase and yield of the crops.

• The Plant Pathology Journal
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• v.40 no.4
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• pp.408-413
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• 2024

The emergence of rice black-streaked dwarf virus (RBSDV) poses a significant threat to global cereal crop cultivation, necessitating the urgent development of reliable detection and quantification techniques. This study introduces a reliable approach for the precise and sensitive quantification of the RBSDV in cereal crop samples, employing a reverse transcription digital polymerase chain reaction (RT-dPCR) assay. We assessed the specificity and sensitivity of the RT-dPCR assay proposed for precise RBSDV detection and quantification. Our findings demonstrate that RT-dPCR was specific for detection of RBSDV, with no cross-reactivity observed with other viruses infecting cereal crops. The RT-dPCR sensitivity was over 10 times that of RT-quantitative PCR (RT-qPCR). The detection limit of RT-dPCR was 0.096 copies/㎕. In addition, evaluation of RT-dPCR assay with field samples was conducted on 60 different cereal crop samples revealed that RT-dPCR (45/60) exhibited superior accuracy compared with RT-qPCR (23/60). In this study, we present a specific and accurate RT-dPCR assay for the detection and quantification of RBSDV.

• Journal of Advanced Navigation Technology
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• v.12 no.4
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• pp.324-331
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• 2008

In this paper, we developed the crops monitoring system using wireless sensor networks. It can acquire the information about the cultivation environments from a temperature, humidity, illumination and soil sensor then use the detailed information for very useful. The acquisition about the cultivation environment information with wireless sensor networks can be made up an environment that an administrator is able to confirm the information and wherever in a remote place instead of conventional way visiting the cultivate place by investing a lot of money and time. Therefore, it could be saving money, time and effort, and reduced the damages from the natural disasters such as a cold-weather damage and drought. In addition, we could be possible preventing from the damages of blight and harmful insects according to the temperature by an analysis. In agriculture field, this system could be supported for making a foundation of the advanced technology developing endless, and, in IT field, it is look forward to preparing the opportunity which creates a new requirement on the new technology.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.463-468
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• 2013

The level of nitrous oxide ($N_2O$), a long-lived greenhouse gas, in atmosphere has increased mainly due to anthropogenic source, especially application of nitrogen fertilizers. Quantifying $N_2O$ emission from agricultural field is essential to develop national inventories of greenhouse gases (GHGs) emission. The objective of the study was to develop emission factor to estimate direct $N_2O$ emission from agricultural field in Gangwon-do, Korea by measuring $N_2O$ emissions from potato (Solanum tuberosum), red pepper (Capsicum annum L.), and Chinese cabbage (Brassica campestris L.) cultivation lands from 2009 to 2012. Accumulated $N_2O$ emission was $1.48{\pm}0.25kg$ $N_2O-N\;ha^{-1}$ for red pepper, $1.27{\pm}0.27kg$ $N_2O-N\;ha^{-1}$ for potato, $1.49{\pm}0.06kg$ $N_2O-N\;ha^{-1}$ for Chinese cabbage cultivated in spring, and $1.14{\pm}0.22kg$ $N_2O-N\;ha^{-1}$ for fall Chinese cabbage. Emission factor of $N_2O$ calculated from accumulated $N_2O$ emission, nitrogen fertilization rate, and background $N_2O$ emission was $0.0051{\pm}0.0016kg$ $N_2O-N\;ha^{-1}$ N for cropland in Gangwon province. More extensive study is deserved to be conducted to develop $N_2O$ emission factor for upland crops in Korea through examining the emission factors from various regions and crops because $N_2O$ emission is influenced by many factors including climate characteristics, soil properties, and agricultural practices.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.19-27
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• 2012

The objective of this study was to test the pollutant reduction effect by the silt fence and vegetated ridge through field monitoring. The experiment plots were established with two replication and three treatments. Each plot was designed with 5 m width, 22 m length, and 3 % slope. Flumes with the floating type stage gages were installed at the outlet of each plot to monitor the runoff. For a rainfall monitoring, tipping bucket rain gage was installed within the experiment site. Cultivated crops were spring daikon and autumn chinese cabbage. Analysis of variance (ANOVA) indicated that the water quality concentration from three experiment plots were not significantly different in 5 % of significant level. The monitoring results showed that the average pollution loads reduced by silt fence compared to control were SS 75.33 %, TN 40.87 %, TP 56.58 %, BOD 52.12 %, COD 36.07 %, TOC 34.99 %; by vegetated ridge compard to control were SS 65.27 %, TN 81.80 %, TP 54.26 %, BOD 67.09 %, COD 46.55 %, TOC 43.30 %. Analysis of Spearman's rank correlation coefficient showed that BOD-SS and SS-Turbidity were highly related at the silt fence and vegetated ridge plots. In all plots, SS-Turbidity and TP-TN relations were relatively high. The monitoring results showed that the silt fence and vegetated ridge were effect method to reduce the pollutant loads from the field runoff. Long-term monitoring is required to obtain more quantitative reduction effect for diverse crops and to increase the reliability of results.

• Journal of Agricultural Extension & Community Development
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• v.11 no.1
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• pp.191-207
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• 2004

This study was focused on the development of greenhouse management and environmental control system using internet. The essence of this system were remote automatic control unit connected with greenhouse environmental control according to the growth stages of crops, The specific objectives of the study were; 1) to analyze need of greenhouse environmental remote control system, 2) to investigate the important functions related to greenhouse management program, 3) to explore the possibility of diffusing the system using internet.The study was carried out through review of related literature and need assessment from the research and extension workers in charge of greenhouse management using questionnaire survey, interview and field study. The results of the study were summarized as fallows: 1) About 89% of respondents responded positively on the need to establish automatic control system using internet. 2) The greenhouse management and environmental control system using internet was possible to control the greenhouse in remote, automatic, and simultaneous manner, and additionally by cellular phone in emergent situation. 3) The system was possible to precisely control the greenhouse environment, and it was able to connect the environmental control data with information on growth of crops. 4) By networking the farmer, extension educator of agricultural technology center and researcher, web based farm consulting was possible through the system. Based on the results of the study recommendations were suggested as follows: 1) Thorough spot inspections and field trials should be performed before the diffusion of this system. 2) The costs of the system installation and maintenance should be moderate. 3) The operation of the system should be simple and easy for tamers to adopt. 4) National support should be made to build better internet infrastructure in rural areas.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.243-245
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• 2007

This study was begun to classify the paddy fields by the rice varieties and to monitor the temporal change in rice growth using SAR backscatter coefficients $({\sigma}^{circ})$. For nine fine-beam mode images of Radarsat-1 SAR, a growing period time-series of backscatter coefficients was set up from April to October in 2005, and was compared with the field-measured rice growth parameters such as LAI (leaf area index), plant height, fresh and dry biomass, and water content in grain and plant for 45 parcels in Dangjin-gun, Chungcheongnam Province, South Korea. The average backscatter coefficients for early-maturing rice varieties (13 parcels) were ranged from -18.17dB to -6.06dB and were lower than for medium-late maturing rice varieties during most of the growing season. At around the heading stage (July 30) for early-maturing rice, both rice crops showed the highest backscatter coefficient values and the difference was the greatest before harvesting early-maturing rice. The temporal difference in backscatter coefficients between rice varieties was expected to play a key role to identify early-maturing rice fields. On the other hand, comparison with field-measured rice growth parameters showed that the backscatter coefficients decreased or stayed on the plateau after heading stage even though the growth of rice canopy advanced.

• Journal of the Korean Geographical Society
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• v.37 no.1
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• pp.93-110
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• 2002

The purpose of this study is to analyse the change and characteristic of agricultural land use for the mountainous village which was linked to the development of arable land in the historic process as the case study on Yowon-village, Gyeongbuk province. The findings are summarized as fellows. First, most of arable land development had been developed from the late 16th century to the late 19th century and in the 1960s. A rice field was developed at the valley containing water resource and a dry field at the land close to a village before 1960 and at the gently sloped and wide hill after 1960. Second, the crops cultivated before the introduction of commercial agriculture were potato, foxtail millet, bean. After the 1970s, The vegetable, red pepper, tobacco were commercially cultivated. Third, the main group of land use change(choice of crops) result from effort of the inhabitant The significance of this study are as follows, explaining the change and characteristic of agriculture land use for the mountainous village which was linked to the development of arable land, studying as the case on small-scale village.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.88-88
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• 2022

Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.