• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.194-203
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• 2022

Cultivation of tomatoes in Korea grown in soil covers 89% of the total area for tomato cultivation. Tomatoes grown in soil often encounter various environment stresses including not only salt stress and soil-borne diseases but also cold stress in the winter season. This study was conducted to comparatively analyze the performance of rootstocks with cold stress by measuring the growth, yield, and photosynthetic efficiency in tomatoes grown in soil. The rootstocks were used 'Powerguard', 'IT173773', and '20LM' for the domestic rootstock cultivars and 'B-blocking' for a control cultivar. The tomato cultivar 'Red250' was used as the scion and the non-grafted tomatoes. Stem diameter, flowering position, leaf length, and leaf width were investigated for the growth parameters. The stem diameter of the non-grafted tomatoes decreased by 15% compared to the grafted tomatoes at 80 days after transplanting when exposed to low temperatures of 9-14℃ for 14 days. The leaf length and width of the non-grafted tomatoes were the lowest with 42.4 cm and 41.8 cm at 80 days after transplanting. The total yield per plant was the highest in tomato plants grafted on 'Powerguard' with 1,615 g and lowest in non-grafted tomatoes with 1,299 g. As the result of measuring the chlorophyll fluorescence parameters, PI_ABS and DI₀/RC, which mean the performance index and dissipated energy flux, 'Powerguard' was the highest with 3.73 in PI_ABS and the lowest with 0.34 in DI₀/RC, whereas non-grafted tomatoes was the lowest with 2.62 in PI_ABS and the highest with 0.41 in DI₀/RC at 80 days after transplanting. The stem diameter has positive correlation with PI_ABS, while it has negative correlation with DI₀/RC. The results indicate that can be analyzed by chlorophyll fluorescence parameters can be used for analyzing the differences in the growth of tomato plants grafted on different rootstocks when exposed to cold stress.

• Research in Plant Disease
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• v.28 no.2
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• pp.69-81
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• 2022

This study was performed to screen the efficacy of antagonistic bacterial isolates from various sources against the bacterial fruit blotch (BFB) causing pathogen (Acidovorax citrulli) in cucurbit crops. In addition, plant growth promoting traits of these antagonistic bacterial isolates were characterized. Two thousand seven hundred ninety-four microorganisms were isolated from the collected samples. Molecular identification revealed two A. citrulli out of 2,794 isolates. In vitro antagonistic results showed that, among the 28 antagonistic bacterial isolates, 24 and 14 bacterial isolates exhibited antagonism against HPP-3-3B and HPP-9-4B, respectively. Antagonistic and growth promotion characterization of the antagonistic bacterial isolates were further studied. Results suggested that, 4 antagonistic bacteria commonly showed both antagonism and growth promotion phenotypes. Moreover, 3 isolates possessed growth promoting activities. Overall results from this study suggests that BFB causing bacterial pathogen (A. citrulli) was suppressed in in vitro antagonism assay by antagonistic bacterial isolates. Furthermore, these antagonistic bacterial isolates possessed growth promotion and antagonistic enzyme production ability. Therefore, data from this study can provide useful basic data for the in vivo experiments which ultimately helps to develop the eco-friendly agricultural materials to control fruit rot disease in cucurbit crops in near future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.253-264
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• 2022

In this study, we investigated the occurrence of viral diseases in the early growth stage of soybean to establish management practices. We collected 83 soybean samples showing abnormal symptoms, approximately 3-4 weeks after seeding in the breeding field of the National Institute of Crop Science. Viruses were detected in the collected samples using reverse transcription polymerase chain reaction (RT-PCR) and metatranscriptome analysis of all those samples. The incidence of viral diseases in the field was less than 1% overall and up to 50% in certain cultivars and lines. RT-PCR and metatranscriptome analysis detected Soybean yellow mottle mosaic virus (SYMMV), Soybean mosaic virus (SMV), Soybean yellow common mosaic virus, Peanut stunt virus, and soybean geminivirus A (SGVA). Among these detected viruses, SYMMV and SMV were identified as major viruses causing infection in the early growth stage of soybean, with detection rates of 53.7% and 42.6%, respectively. Soybeans infected with SYMMV showed typical mosaic symptoms, whereas those infected with SMV showed a variety of symptoms such as mosaic, mottle, stunt, and chlorotic spots. Transmission characteristics of these viruses are variable, such that SMV is primarily transmitted by seeds, whereas SYMMV could be transmitted by insects, soil, and seeds. In this study, SGVA was detected in the early growth stage of soybean, and research on the current status and its effects on soybean after the early growth stage should be conducted.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.325-338
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• 2023

Korean fir (Abies koreana Wilson) is one of the most important environmental indicator tree species for assessing climate change impacts on coniferous forests in the Korean Peninsula. However, due to the nature of alpine and subalpine regions, it is difficult to conduct regular field surveys of Korean fir, which is mainly distributed in regions with altitudes greater than 1,000 m. Therefore, this study analyzed the vegetation change trend of Korean fir using regularly observed remote sensing data. Specifically, normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), land surface temperature (LST), and precipitation data from Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievalsfor GPM from September 2003 to 2020 for Hallasan and Jirisan were used to analyze vegetation changes and their association with environmental variables. We identified a decrease in NDVI in 2020 compared to 2003 for both sites. Based on the NDVI difference maps, areas for healthy vegetation and high mortality of Korean fir were selected. Long-term NDVI time-series analysis demonstrated that both Hallasan and Jirisan had a decrease in NDVI at the high mortality areas (Hallasan: -0.46, Jirisan: -0.43). Furthermore, when analyzing the long-term fluctuations of Korean fir vegetation through the Hodrick-Prescott filter-applied NDVI, LST, and precipitation, the NDVI difference between the Korean fir healthy vegetation and high mortality sitesincreased with the increasing LST and decreasing precipitation in Hallasan. Thissuggests that the increase in LST and the decrease in precipitation contribute to the decline of Korean fir in Hallasan. In contrast, Jirisan confirmed a long-term trend of declining NDVI in the areas of Korean fir mortality but did not find a significant correlation between the changes in NDVI and environmental variables (LST and precipitation). Further analyses of environmental factors, such as soil moisture, insolation, and wind that have been identified to be related to Korean fir habitats in previous studies should be conducted. This study demonstrated the feasibility of using satellite data for long-term monitoring of Korean fir ecosystems and investigating their changes in conjunction with environmental conditions. Thisstudy provided the potential forsatellite-based monitoring to improve our understanding of the ecology of Korean fir.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.103-103
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• 2022

다복찰은 전라북도농업 기술원에서 2012~2020년에 신명흑찰과 익산488호를 교배하여 육성한 찰벼이며, 중대립, 단간, 내도복, 다수성의 특징을 보인다. 동진찰은 1998년도에 육성되었으며, 우리나라에서 가장 인기 있는 찰벼이다(재배면적 25,161ha/2021년 기준). 드문모심기 재배 기술은 2017년부터 도입되었으며, 밀파 육묘하여 재식밀도 및 재식주수를 감소함으로써 소요되는 재료비 등 경비 및 투입되는 노동력을 절감하는 경제성 있는 기술이다. 따라서 본 연구는 전라북도농업기술원에서 육성한 다복찰 보급 확대 및 가장 인기 높은 동진찰의 드문모심기 재배기술 확립 일환으로 시작되었으며, 2024년까지 3년간 실시할 계획이다. 시험은 기술원 논 포장에서 실시하였으며, 시험품종은 다복찰, 동진찰, 시험요인은 이앙시기(3처리) 및 재식밀도(4처리)를 두었다. 이앙시기별로 이앙 17일 전에 온탕소독(62℃, 10분), 종자소독(32℃, 1일), 침종(32℃, 1일), 간이출하(30℃, 3일) 과정을 거쳐 부직포 육묘(12일 정도)를 실시하였다. 5월20일(이앙520)부터 5월30일(이앙530), 6월9일(이앙609)까지 10일 간격으로 드문모심기 전용 이앙기로 이앙하였으며, 주당 본수는 5.7개 정도였다. 이앙 시기별로 시험포장을 구분하였고 포장내에 2품종, 각각 3.3m2당 80주, 60주, 50주, 37주 등 재식밀도 처리구를 두었으며, 처리구마다 3반복 조사구(10주/반복, 5본/주) 설치하였다. 10a당 9-4.5-5.7kg(N-P₂O₅-K₂O)를 밑거름(50%)-분얼거름(20)-이삭거름(30) 등 3회 거쳐 시비하였다. 중간물떼기는 이앙32일째부터 10일간 실시하였으며, 예상 출수 30일 전에 충분하게 담수하였다. 이앙20일째부터 10일 간격으로 경수, 초장, 엽색도 등 생육 조사, 그리고 출수기, 후기 생육 및 병해충을 조사하였다. 향후 수확기에 수량, 수량구성요소, 미질 및 품위를 분석할 계획이다. 시험토양은 pH 6.0~6.3, EC는0.68~0.85dS/m, 유기물함량은 52~57g/kg 수준으로 높았다. 동진찰 발아율(94.0~98.1%)이 다복찰(89.9~94.9%)보다 우수하였다(3~6%P ↑). 다복찰 묘 충실도(102~106mg/주)가 동진찰(79~101mg/주)보다 다소 좋았으며, 이앙530 묘소질이 가장 좋았다. 동진찰 초장은 다복찰에 비해 다소 길었으나 이앙시기 및 재식밀도별 초장의 변화 유형은 비슷하였다. 이앙520구의 80주에서 초장이 가장 작았고 이앙609구에서는 80주에서 다소 길었으나, 처리구간의 유의성은 없었다. 동진찰 및 다복찰 경수는 37주에서 이앙 후 40일째, 50주, 60주, 80주에서는 30일째 가장 컸다. 출수기는 다복찰에 비해 동진찰이 3~7일 정도 빨랐으며, 특히 이앙520 동진찰에서는 재식밀도가 높을수록 출수기가 빠른 경향을 보였으며, 이앙530 이후에는 재식밀도간 차이가 거의 없었다. 동진찰에 비해 다복찰 간장이 3~6cm 작았으며, 2품종 모두 이앙609구에서 가장 낮은 값을 보였다. 수장도 간장과 비슷한 경향을 보였다. 수수는 2품종 모두 이앙이 늦을수록 증가하였으며, 37주에서 가장 높았으며, 80주에 비해 다복찰, 동진찰 각각 73.8%, 77.4% 높았다. 다복찰의 경우 3.3m²당 수수는 이앙시기별과 관계없이 상대적으로 80주에서 가장 많았고 이앙520에서 재식밀도간 차이는 감소하였지만 이앙시기가 늦을수록 수수는 증가하는 경향을 보였다. 동진찰도 비슷한 경향을 보였으며, 이앙520과 이앙609 사이에 수수 차이는 적었다. 병 발생은 잎집무늬마름병, 세균성벼알마름병, 이삭누룩병이 주로 관찰되었으며, 세균성 벼알마름병은 출수기와 맞물린 이앙530에서 가장 크게 발생하였으며, 이앙520도 비슷한 경향을 보였다. 이삭누룩병 발생이 심하였는데 재식밀도간 차이보다는 이앙시기별 차이가 더 크게 발생하였으며 품종 간의 병 발생 차이는 없었다. 이상의 결과로 수수 측면에서 조기 이앙할 경우에는 50~60주, 늦은 이앙 시에는 80주가 유리할 것으로 보이며, 추후주당 립수, 등숙률, 천립중 등을 조사하고 경영비 등을 고려하여 합리적인 이앙시기 및 재식밀도를 판단할 수 있을 것으로 판단된다.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.