• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.1-7
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• 2003

Internal defects such as browning of the flesh and blackening and rot of the ovary of pear can be easily developed because of the inadequate environmental conditions during the storage and distribution of fruit. The quality assurance system for the agricultural product is to be settled in Korea. All defected agricultural products should be excluded prior to the distribution to enhance the commercial values. However, early stage on-line defect detection of agricultural product is very difficult and even more difficult in a case of the internal defects. The goal of this research is to develop a system that can detect and classify internal defects of agricultural produce on-line using VIS/NIR transmittance spectroscopy. And Shingo pear, which is one of the famous species of Korean pear, was used for the experiment. Soft independence modeling of class analogy (SIMCA) algorithm was employed to analyze the transmittance spectroscopic data qualitatively. On-line classification system was constructed and classification model was developed and validated. As a result, the correct classification rate (CCR) using the developed classification model was 96.1 ％.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.55-67
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• 2021

Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.200-210
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• 2023

Background: Cambaroides similis is an endangered candidate species living in the stream of South Korea. Freshwater crayfish is known to decline rapidly not only domestically, but also internationally. Its decline is projected to be further exacerbated due to climate change. Understanding physical characteristics of the habitat is crucial for the conservation of an organism. However, comprehensive data regarding the distribution and physical habitat characteristics of C. similis are currently unavailable in South Korea. Thus, the objective of this study was to ascertain preferred ranges for water depth, current velocity, and streambed substrate of C. similis using Weibull model. Results: In this study, C. similis was found at 59 sites across 12 regions in South Korea. Its optimal water depth preferences ranged from 11.9 cm to 30.1 cm. Its current velocity preferences ranged from 9.8 cm s^-1 to 29.1 cm s^-1. Its substrate preferences ranged from -5.1 𝜱_m to -2.5 𝜱_m. Median values of central tendency were determined as follows: water depth of 21.4 cm, current velocity of 21.2 cm s^-1, and substrate of -4.1 𝜱_m. Mean values of central tendency were determined as follows: water depth of 21.8 cm, current velocity of 22.0 cm s^-1, and substrate of -4.4 𝜱_m. Mode values of central tendency were determined as follows: water depth of 21.7 cm, current velocity of 20.1 cm s^-1, and substrate of -3.7 𝜱_m. Conclusions: Based on habitat suitability analysis, physical microhabitat characteristics of C. similis within a stream were identified as Run section with coarse particle substrate, low water depth, and slow current velocity. Due to high sensitivity of these habitats to environmental changes, prioritized selection and assessment of threats should be carried out as a primary step.

• Korean Journal of Environmental Biology
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• v.37 no.4
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• pp.759-768
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• 2019

This study was conducted to estimate the mean annual extreme minimum temperature raster and predict the potential distribution of the invasive plant, Ipomoea triloba, on the Korean peninsula. We collected annual extreme minimum temperature and mean coldest month minimum temperature data from 129 weather stations on the Korean peninsula from 1990-2019 and used this data to create a linear regression model. The min temperature of the coldest month raster from Worldclim V2 were used to estimate a 30 second spatial resolution, mean annual extreme minimum temperature raster of the Korean peninsula using a regression model. We created three climatic rasters of the Korean peninsula for use with the Proto3 species distribution model and input the estimated mean annual extreme minimum temperature raster, a Köppen-Geiger climate class raster from Beck et al. (2018), and we also used the mean annual precipitation from Worldclim V2. The potential distribution of I. triloba was estimated using the Proto3 model with 117 occurrence points. As a result, the estimated area for a potential distribution of I. triloba was found to be 50.7% (111,969 ㎢) of the Korean peninsula.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.163-173
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• 2022

Climate change is a key factor that greatly influences changes in the biological seasons and geographical distribution of species. In the ecological field, the BioClimatic predictor (BioClim), which is most related to the physiological characteristics of organisms, is used for vulnerability assessment. However, BioClim values are not provided other than the future period climate average values for each GCM for the Shared Socio-economic Pathways (SSPs) scenario. In this study, BioClim data suitable for domestic conditions was produced using 1 km resolution SSPs scenario detailed data produced by Rural Development Administration, and based on the data, a species distribution model was applied to mainly grow in southern, Gyeongsangbuk-do, Gangwon-do and humid regions. Appropriate habitat distributions were predicted every 30 years for the base years (1981 - 2010) and future years (2011 - 2100) of the Acer pictum subsp. mono. Acer pictum subsp. mono appearance data were collected from a total of 819 points through the national natural environment survey data. In order to improve the performance of the MaxEnt model, the parameters of the model (LQH-1.5) were optimized, and 7 detailed biolicm indices and 5 topographical indices were applied to the MaxEnt model. Drainage, Annual Precipitation (Bio12), and Slope significantly contributed to the distribution of Acer pictum subsp. mono in Korea. As a result of reflecting the growth characteristics that favor moist and fertile soil, the influence of climatic factors was not significant. Accordingly, in the base year, the suitable habitat for a high level of Acer pictum subsp. mono is 3.41% of the area of Korea, and in the near future (2011 - 2040) and far future (2071 - 2100), SSP1-2.6 accounts for 0.01% and 0.02%, gradually decreasing. However, in SSP5-8.5, it was 0.01% and 0.72%, respectively, showing a tendency to decrease in the near future compared to the base year, but to gradually increase toward the far future. This study confirms the future distribution of vegetation that is more easily adapted to climate change, and has significance as a basic study that can be used for future forest restoration of climate change-adapted species.

• Korean Journal of Environment and Ecology
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• v.22 no.4
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• pp.347-355
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• 2008

This study analyzed and modeled the relationships between the species richness of fish, plant, and bird and environmental factors such as climatic and geographical variables based on data collected from 109 major drainage systems in Japan from 1990 until 2005. As a result, the most parts of the distributions of the fish, plant, and bird species richness were clarified by the average annual atmospheric temperature, dimension of drainage areas, and annual rainfall, respectively. In addition, this study predicted the value of each organism species distributed in national drainage areas in Japan using GAMs(Generalized Additive Models) for each organism model created by environmental factors on a wide-ranging scale, and also mapped out the value. Mapping out the predicted value could make it easier for its managers to newly set up the areas needing to be protected to obtain diversity of the organism species and to assess their availability of conservation for bio-diversity.

• Ecology and Resilient Infrastructure
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• v.10 no.1
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• pp.11-19
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• 2023

Alien species are known to threaten regional biodiversity globally, which has increased global interest regarding introduction of alien species. The Ministry of Environment of Korea designated species that have not yet been introduced into the country with potential threat as alert alien species to prevent damage to the ecosystem. In this study, potential habitats of Esox lucius and Maccullochella peelii, which are predatory and designated as alert alien fish, were predicted on a national basis. Habitat suitability was evaluated using EHSM (Ecological Habitat Suitability Model), and water temperature data were input to calculate Physiological Habitat Suitability (PHS). The prediction results have shown that PHS of the two fishes were mainly controlled by heat or cold stress, which resulted in biased habitat distribution. E. lucius was predicted to prefer the basins at high latitudes (Han and Geum River), while M. peelii preferred metropolitan areas. Through these differences, it was expected that the invasion pattern of each alien fish can be different due to thermal preference. Further studies are required to enhance the model's predictive power, and future predictions under climate change scenarios are required to aid establishing sustainable management plans.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.2
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• pp.111-118
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• 2013

The Norwegian coastal area is the most efficient region for fishery production in the world's oceans, the Norway is the world's top 10 fisheries countries through efficient fishing and fishing aquaculture technology and its scientific management of fisheries bio-resources, with Norwegian salmon having attained the world's highest level. In the late 1980s, fisheries resources were depleted due to overfishing and fish diseases, resulting in a crisis in the fishing industry that lasted until the early 1990s. Since the national fishery emergency, people involved in the fishing industry, including fishermen, research scientists, and government officers, have tried to overcome the challenges facing the industry and identify an appropriate management model for fisheries bio-resources in the Norwegian coastal area. First, research vessels were used to monitor water and sediment conditions and fishery species, with the long-term aim of predicting fishery resources in real time and collecting information on species diversity, abundance, and distribution. Second, a "Healthy Fish Project" was promoted to counter natural disasters and fish disease problems with the development of vaccines against viruses and bacteria, eventually allowing for a decrease in the use of antibiotics and the production of notably healthier fish in the 2000s. Third, a systematic management model was developed to help with preparations for decreases in the total number of fishermen and increases in the proportion of elderly fishermen in the fishery industry using the development of automatic fishing aquaculture systems and short-chain systems. We could learn from the Norwegian model of fisheries bio-resources, management and could adopt it for the preparation of fishery bio-resources management policy for South Korean coastal areas in the near future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.370-378
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• 2017

A fluid model of 2D axis-symmetry based on inductively coupled plasma (ICP) reactor using $N_2/NH_3/SiH_4$ gas mixture has been developed for hydrogenated silicon nitride ($SiN_x:H$) deposition. The model was comprised of 62 species (electron, neutral, ions, and excitation species), 218 chemical reactions, and 45 surface reactions. The pressure (10~40 mTorr) and gas mixture ratio ($N_2$ 80~96 %, $NH_3$ 2~10 %, $SiH_4$ 2~10 %) were considered simulation variables and the input power fixed at 1000 W. Different distributions of electron, ions, and molecules density were observed with pressure. Although ionization rate of $SiH_2{^+}$ is higher than $SiH_3{^+}$ by electron direct reaction with $SiH_4$, the number density of $SiH_3{^+}$ is higher than $SiH_2{^+}$ in over 30 mTorr. Also, number density of $NH^+$ and $NH_4{^+}$ dramatically increased by pressure increase because these species are dominantly generated by gas phase reactions. The change of gas mixture ratio not affected electron density and temperature. With $NH_3$ and $SiH_4$ gases ratio increased, $SiH_x$ and $NH_x$ (except $NH^+$ and $NH_4{^+}$) ions and molecules are linearly increased. Number density of amino-silane molecules ($SiH_x(NH_2)_y$) were detected higher in conditions of high $SiH_x$ and $NH_x$ molecules density.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.972-980
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• 2022

The butterfly species recognition technology based on machine learning using images has the effect of reducing a lot of time and cost of those involved in the related field to understand the diversity, number, and habitat distribution of butterfly species. In order to improve the accuracy and time efficiency of butterfly species classification, various features used as the inputs of machine learning models have been studied. Among them, branch length similarity(BLS) entropy or color intensity entropy methods using the concept of entropy showed higher accuracy and shorter learning time than other features such as Fourier transform or wavelet. This paper proposes a feature extraction algorithm using RGB color intensity entropy for butterfly color images. In addition, we develop butterfly recognition systems that combines the proposed feature extraction method with representative ensemble models and evaluate their performance.