• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.9-16
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• 2022

Rice is one of the most important staple foods in Wnju, Jeonbuk, South Korea. However, rice consumption has dramatically decreased as eating habits have diversified owing to rapid economic growth. Recently, floury endosperm rice varieties have been developed to invigorate the rice processing industry, because dry-milled rice flour is economically and environmentally suitable for massive rice flour distribution. The National Institute of Crop Science has developed 'AromaT', an early-maturing black rice with floury-endosperm, suitable for tea and dry milling. 'AromaT' was derived from a cross between 'Suweon542' as the floury endosperm source and 'Heugjinju' as the black and aromatic source. In this study, 'AromaT' and its parents, 'Suweon542' and 'Heugjinju', were analyzed for agronomic traits, anthocyanin content, and their major physicochemical properties by different planting date. The field experiment was conducted in Wanju, Jeollabuk-do Province, South Korea, in 2019. The transplanting dates were May 30 (ordinary season), June 25 (double-cropping season), and July 10 (late season). The yield performance of brown rice 'AromaT' was 330 kg/10 a in the double-cropping cultivation method and was the highest among the transplanting dates. The floury endosperm of 'AromaT' was derived from 'Suweon542' containing 'flo7', located on chromosome 5 and known to control floury endosperm. With the late planting date, the anthocyanin content of 'AromaT' was 570.5 mg/100 g, much higher than that of 'Heugjinju' (376.3 mg/100 mg). The brown rice of 'AromaT' also exhibited the pop-corn-flavoring 2-acetyl-1-pyrroline, exclusively detected in aroma rice varieties. The average particle sizes of 'AromaT' and 'Suweon542' were 67.12 ㎛ and 70.9 ㎛, respectively, lower than that of 'Heugjinju' (95.5 ㎛) with a black transparent endosperm. The average damaged starch content of 'AromaT' was 8.1%, lower than that of 'Heugjinju' (10.05%) and Suweon542 (9.5%). As a result, 'AromaT' with high anthocyanin content, fine particle size, and low damaged starch content is expected to provide a new rice material in various processing fields.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

• The Korea Journal of Herbology
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• v.37 no.5
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• pp.89-96
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• 2022

Objectives : This research was performed to analyze the components in the different parts of Lythrum salicaria L. and to compare which parts of L. salicaria L. are appropriate for food development. Methods : L. salicaria L. was extracted in 20% EtOH at 100 ℃ for 4 hours. Cytotoxicity was investigated in 3T3-L1 cells after treatment of 10-500 ㎍/ml L. salicaria L. for 24 hours. Total polyphenol content (TPC) was estimated using 1 N Folin-ciocateu reagent. 2,2-Diphenyl-1-picryhydrazyl (DPPH) radical scavenging activity was estimated using DPPH reagent and gallic acid. The chemical composition was analyzed by high-performance liquid chromatography (HPLC). 1) Results : The half maximal inhibitory concentration (IC50) in the extracts of the whole plant, aerial parts, and root parts was 350 ㎍/ml, over 500 ㎍/ml, and 150 ㎍/ml, respectively. The TPC in the extracts of the whole plant, aerial parts, and root parts was 527.1 mg/g, 422.6 mg/g, and 781.1 mg/g, respectively. The averages of vitexin contents in the aerial parts, and root parts were 256.7 ± 154.9 ㎍/g and 266.1 ± 63.2 ㎍/g, respectively. The averages of TPC in the leaves, roots, flower stalks and stems were 224.0 ± 53.7 tannin acid (TA) mg/g, 221.8 ± 70.2 TA mg/g, 249.8 ± 34.4 TA mg/g, and 67.7±8.9 TA mg/g, respectively. The averages of DPPH radical scavenging activity in the leaves, roots, flower stalks, and stems were 282.01 ± 43.3 gallic acid equivalent (GAE) 𝜇mole/g, 260.16 ± 44.1 GAE 𝜇mole/g, 288.0 ± 9.3 GAE 𝜇mole/g, and 97.6 ± 10.7 GAE 𝜇mole/g, respectively. Conclusions : There were no significant differences in the content of components or antioxidant activity in the aerial parts compared to those in the whole plant of L. salicaria L. Furthermore, the root parts had low extract yield, cytotoxicity, and quality control problems, therefore our results suggest that the use of the aerial part of L. salicaria L. would be the most appropriate for food development.

• Journal of Food Hygiene and Safety
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• v.37 no.4
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• pp.216-224
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• 2022

This study was aimed at validating the analysis methods for deacetylasperulosidic acid (DAA), total sugar, galacturonic acid, glucose, and galactose, which are the indicator components of fermented Morinda citrifolia polysaccharide extract (Vitalbos). We modified the previously reported methods for validating the analytical methods. The specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) were measured using phenol-sulfuric acid method and high-performance liquid chromatography (HPLC). The retention time and spectrum of the standard solution of Vitalbos coincided, confirming the specificity. The calibration curve correlation coefficient (R²), of five indicator components, ranged from 0.9995-0.9998, indicating excellent linearity of 0.99 or more. The intra-day and inter-day precision range of the assay was 0.14-3.01%, indicating a precision of less than 5%. The recovery rate was in the range of 95.13-105.59%, presenting excellent accuracy. The LOD ranged from 0.39 to 0.84 ㎍/mL and the LOQ ranged from 1.18 to 2.55 ㎍/mL. Therefore, the analytical method was validated for DAA, total sugar, galacturonic acid, glucose, and galactose, in Vitalbos. The indicator component content in Vitalbos was determined using a validated method. The contents of DAA, total sugar, galacturonic acid, glucose, and galactose were 2.31±0.06, 475.92±5.95, 72.83±1.05, 71.63±2.44, and 67.30±2.31 mg/g of dry weight, respectively. These results suggest that the developed analytical method is efficient and could contribute to the quality control of Vitalbos, as a healthy functional food material.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.57-78
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• 2023

COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Journal of Animal Science and Technology
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• v.65 no.2
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• pp.336-350
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• 2023

Two experiments were conducted in this research. Experiment 1 investigated the spatial expression characteristics of calcium (Ca) and phosphorus (P) transporters in the duodenum, jejunum, and ileum of 21-day-old broilers provided with adequate nutrient feed. Experiment 2 evaluated the effects of dietary vitamin D₃ (VD₃) concentration (0, 125, 250, 500, 1,000, and 2,000 IU/kg) on growth performance, bone development, and gene expression levels of intestinal Ca and P transporters in 1-21-day-old broilers provided with the negative control diet without supplemental VD₃. Results in experiment 1 showed that the mRNA levels of calcium-binding protein 28-kDa (CaBP-D28k), sodium-calcium exchanger 1 (NCX1), plasma membrane calcium ATPase 1b (PMCA1b), and IIb sodium-phosphate cotransporter (NaPi-IIb) were the highest in the broiler duodenum. By contrast, the mRNA levels of inorganic phosphate transporter 1 (PiT-1) and 2 (PiT-2) were the highest in the ileum. Results in experiment 2 showed that adding 125 IU/kg VD₃ increased body weight gain (BWG), feed intake (FI), bone weight, and percentage and weight of Ca and P in the tibia and femur of 1-21-day-old broilers compared with the negative control diet (p < 0.05). The rise in dietary VD₃ levels from 125 to 1,000 IU/kg further increased the BWG, FI, and weights of the bone, ash, Ca, and P (p < 0.05). No difference in growth rate and leg bone quality was noted in the broilers provided with 1,000 and 2,000 IU/kg VD₃ (p > 0.05). Supplementation with 125-2,000 IU/kg VD₃ increased the mRNA abundances of intestinal Ca and P transporters to varying degrees. The mRNA level of CaBP-D28k increased by 536, 1,161, and 28 folds in the duodenum, jejunum, and ileum, respectively, after adding 1,000 IU/kg VD₃. The mRNA levels of other Ca and P transporters (PMCA1b, NCX1, NaPi-IIb, PiT-1, and PiT-2) increased by 0.57-1.74 folds by adding 1,000-2,000 IU/kg VD₃. These data suggest that intestinal Ca and P transporters are mainly expressed in the duodenum of broilers. Moreover, the addition of VD₃ stimulates the two mineral transporter transcription in broiler intestines.