• Journal of Bio-Environment Control
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• v.31 no.2
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• pp.98-103
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• 2022

Non-destructive estimation of leaf area is a more efficient and convenient method than leaf excision. Thus, several models predicting leaf area have been developed for various horticultural crops. However, there are limited studies on estimating the leaf area of strawberry plants. In this study, we predicted the leaf areas via nonlinear regression analysis using the leaf lengths and widths of three-compound leaves in five domestic strawberry cultivars ('Arihyang', 'Jukhyang', 'Keumsil', 'Maehyang', and 'Seollhyang'). The coefficient of determination (R²) between the actual and estimated leaf areas varied from 0.923 to 0.973. The R² value varied for each cultivar; thus, leaf area estimation models must be developed for each cultivar. The leaf areas of the three cultivars 'Jukhyang', 'Seolhyang', and 'Maehyang' could be non-destructively predicted using the model developed in this study, as they had R² values over 0.96. The cultivars 'Arihyang' and 'Geumsil' had slightly low R² values, 0.938 and 0.923, respectively. The leaf area estimation model for each cultivar was coded in Python and is provided in this manuscript. The estimation models developed in this study could be used extensively in other strawberry-related studies.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• Ecology and Resilient Infrastructure
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• v.4 no.1
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• pp.63-70
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• 2017

Tetracycline (TC) groups, widely used veterinary antibiotics, can enter into environment through animal manure application. TC forms a ligand complex with multivalent metal cations via chelation that can affect sorption and mobility of TC in soil. So far, however, it has been confirmed through the reaction of the soil outside in the aqueous solution and the evaluation of the performance in the soil cultivation process is insufficient. The purpose of this study was to examine effects of copper on TC toxicity to lettuce growth. In this research, $750mg\;kg^{-1}$ of TC and 2.5, 7.5, $17.5mg\;kg^{-1}$ of Cu are treated in soil and lettuce was cultivated in the treated soil. Growth difference of lettuce by treatment was observed. As a result, $750mg\;kg^{-1}$ of TC treated soil showed toxic effect to lettuce and the effect is alleviated by copper treatment.

• Journal of Bio-Environment Control
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• v.26 no.1
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• pp.13-18
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• 2017

This study was conducted to investigate optimal temperature of garlic and develop bulb weight model in harvest time. Day and night temperature in chambers was set to $11/7^{\circ}C$, $14/10^{\circ}C$, $17/12^{\circ}C$, $20/15^{\circ}C$, $23/18^{\circ}C$, $28/23^{\circ}C$(16/8h). Bulb fresh and dry weight was heaviest on $20/15^{\circ}C$. In $11/7^{\circ}C$ and $14/10^{\circ}C$, leaf number and total leaf area increased slowly. But in the harvest, leaf number and total leaf area were not significant, except $28/23^{\circ}C$. Models were developed with fresh bulb weight. As a result of analyzing the model, $18{\sim}20^{\circ}C$ certified optimal mean temperature. And the growing degree day base temperature estimated $7.1^{\circ}C$, upper temperature threshold estimated $31.7^{\circ}C$. To verify the model, mean temperature on temperature gradient tunnel applied to the growth rate model. Lineal function model, quadric model, and logistic distribution model showed 79.0~95.0%, 77.2~92.3% and 85.0~95.8% accuracy, respectively. Logistic distribution model has the highest accuracy and good for explaining moderate temperature, growing degree day base temperature and upper temperature threshold.

• Korean Journal of Ecology and Environment
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• v.48 no.4
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• pp.229-237
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• 2015

This study aims to offer basic data to effectively preserve and manage pine forests using more precise pine forests' distribution status. In this regard, this study predicts the geographical distribution change of pine forests growing in South Korea, due to climate change, and evaluates the spatial distribution characteristics of pine forests by age. To this end, this study predicts the potential distribution change of pine forests by applying the MaxEnt model useful for species distribution change to the present and future climate change scenarios, and analyzes the effects of bioclimatic variables on the distribution area and change by age. Concerning the potential distribution regions of pine forests, the pine forests, aged 10 to 30 years in South Korea, relatively decreased more. As the area of the region suitable for pine forest by age was bigger, the decreased regions tend to become bigger, and the expanded regions tend to become smaller. Such phenomena is conjectured to be derived from changing of the interaction of pine forests by age from mutual promotional relations to competitive relations in the similar climate environment, while the regions suitable for pine forests' growth are mostly overlap regions. This study has found that precipitation affects more on the distribution of pine forests, compared to temperature change, and that pine trees' geographical distribution change is more affected by climate's extremities including precipitation of driest season and temperature of the coldest season than average climate characteristics. Especially, the effects of precipitation during the driest season on the distribution change of pine forests are irrelevant of pine forest's age class. Such results are expected to result in a reduction of the pine forest as the regions with the increase of moisture deficiency, where climate environment influencing growth and physiological responses related with drought is shaped, gradually increase according to future temperature rise. The findings in this study can be applied as a useful method for the prediction of geographical change according to climate change by using various biological resources information already accumulated. In addition, those findings are expected to be utilized as basic data for the establishment of climate change adaptation policies related to forest vegetation preservation in the natural ecosystem field.

• Korean Journal of Environment and Ecology
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• v.32 no.2
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• pp.215-224
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• 2018

The climate change is expected to weaken the habitat of Pinus densiflora and P. thunbergii, but they are still in high demand for planting. This study aims to suggest the rational community planting design based on natural forests' community structure in the southeastern region of Korea (warm temperate zone). For this study, we surveyed 22 plots of Pinus densiflora community and 60 plots of P. thunbergii community in Busan Metropolitan City which is located in the southeastern part of the Korean peninsula. We investigated the diameter of breath hight (DBH) and population of each tree layer in a $100m^2$ quadrat and used a regression analysis to derive a regression equation for estimating the mean number of planting individuals in each DBH. The coefficient between canopy layer's DBH and growth individuals per unit area ($100m^2$) was 0.700 for P. thunbergii communities and 0.533 for P. densiflora communities, indicating very high explanatory power by single factor. The predicted regression equation of between DBH and growth density was $Y=31.176e^{-0.055x}$ (X=DBH, Υ=growth individuals per $100m^2$) for P. thunbergii communities and $Y=38.351e^{-0.059x}$ for P. densiflora communities. Planting densities of P. densiflora communities and P. thunbergii communities in southeast region were higher than the central region.

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.1-7
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• 2023

Understanding the light environment in greenhouse cultivation and the light utilization characteristics of crops is important in the study of photosynthesis and transpiration. Also, as the plant grows, the form of light utilization changes. Therefore, this study aims to develop a light extinction coefficient model reflecting the plant growth. To measure the extinction coefficient, five pyranometers were installed vertically according to the height of the plant, and the light intensity by height was collected every second during the entire growing season. According to each growth stage in the early, middle, and late stages, the difference between the top and bottom light intensity tended to increase to 69%, 72%, and 81%. When leaf area index and plant height increased, the extinction coefficient decreased, and it showed an exponential decay relationship. Three-dimensional model reflecting the two growth indexes, the paraboloid had the lowest RMSE of 1.340 and the highest regression constant of 0.968. Through this study, it was possible to predict the more precise light extinction coefficient during the growing period of plants. Furthermore, it is judged that this can be utilized for predicting and analyzing photosynthesis and transpiration according to the plant height.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.50-61
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• 2020

Street trees are very important to urban environments as they can alleviate air pollution. However, when ozone is absorbed through the stomata, it can induce the formation of free radicals inside the tree, negatively affecting the vegetation. The present study investigated the Air Pollution Tolerance Index (APTI) of four major street tree species: Prunus yedoensis, Zelkova serrata, Chionanthus retusus, and Pinus densiflora. Two-year-old seedlings were placed in a phytotron and fumigated with 100 nL·L^-1 (ppb) ozone for 4 weeks, following which the ascorbic acid contents, chlorophyll contents, leaf pHs, and relative water contents were measured. There was no significant difference in the APTI of Prunus yedoensis and Zelkova serrata between the ozone and control treatments. By contrast, the ozone treatment caused the APTI of Chionanthus retusus to increase and that of Pinus densiflora to decrease compared with the respective controls. These results suggest that the APTI of these tree species exhibit very different responses to ozone. Therefore, more detailed research should be conducted on a range of species in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.41-63
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• 2022

The purpose of this study is to secure objective and precise data through ecosystem monitoring, to reveal ecological characteristics through comparison and analysis with past survey data, and to accumulate basic data for diagnosing the current situation and predicting changes in the ecosystem. The target site is the 'Quercus mongolica forest on the Buksa-myeon of Namsan', which was designated as an Ecological Landscape Conservation Area (ELCA) of Seoul in July 2006. The research contents are analysis of soil environment change (1986~2016), change of actual vegetation (1978~2016), and change of plant community structure (1994~2016). A total of 8 fixed surveys (400~1,200m²) were established in 1994 and 2000. Analysis items are importance value, species and population, and Shannon's species diversity. The soil environment of Namsan is acidic (pH 4.40 in 2016), which is expected to have a negative impact on tree growth and vegetation structure due to its low capacity for exchangeable cations. Quercus mongolica forest in Namsan is mainly distributed on the northern slopes. The actual vegetation area changed from 49.4% in 1978 → 80.7% in 1986 → 82.4% in 2000 → 88.3% in 2005 → 88.3% in 2009 → 70.3% in 2016. In 2016, the forest decreased by 18% compared to 2009. While there was increased growth of Quercus mongolica in the tree layer from 2009 to 2016, the overall decline in vegetation area was due to logging and fumigation management following the spread of oak wilt in 2012. As for the changes in the plant community structure, Quercus mongolica of the tree layer was damaged by oak wilt, and the potential vegetation that can form the next generation was ambiguous. In the subtree layer, the force of urbanization tree species such as Styrax japonicus, Sorbus alnifolia, and Acer palmatum. was maintained or increased. In the shrub layer, the number of trees and species increased significantly due to the open tree crown, and accordingly, the species diversity of Shannon for woody plants also increased. In Quercus mongolica forest of Namsan, various ecological changes are occurring due to the effects of urban environments such as air pollution and acid rain, the limitation of Quercus mongolica pure forest due to oak wilt, and the introduction of exotic species, thus, it is necessary to establish a management plan through continuous monitoring.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.115-121
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• 2023

The leopard plant has the characteristic of being used for ornamental purposes when there are yellow spots on the leaves, and is widely used as a bed plant for viewing flowers. To set several indicators to predict the growth of crops with ornamental value, and to quantitatively express the relationship between the indicators are necessary. In this study, we determine a model that estimates the leaf area and the number of flower of Farfugium japonicum Kitam. using leaf length and width, and conducting a regression analysis on some regression models. As an indicator for estimating the leaf area and the number of flower, the leaf length and width of F. japonicum were measured and applied to 8 regression models. As a result of regression analysis of 8 models that estimated leaf area and the number of flower, R² values of the linear models were all higher than 0.84 and 0.80. As a result of validation, using the most reliable model among the models for estimating the leaf area and the number of flowering, R² was 0.90 and 0.82, respectively. Using a model that estimates various indicators that can be used for quality evaluation from easy-to-measure morphological factors, the evaluation of ornamental plants will be facilitated.