• Journal of Soil and Groundwater Environment
• /
• v.28 no.6
• /
• pp.71-89
• /
• 2023

A groundwater potential map (GPM) was built for the Nakdonggang River Basin based on ten variables, including hydrogeologic unit, fault-line density, depth to groundwater, distance to surface water, lineament density, slope, stream drainage density, soil drainage, land cover, and annual rainfall. To integrate the thematic layers for GPM, the criteria were first weighted using the Analytic Hierarchical Process (AHP) and then overlaid using the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) model. Finally, the groundwater potential was categorized into five classes (very high (VH), high (H), moderate (M), low (L), very low (VL)) and verified by examining the specific capacity of individual wells on each class. The wells in the area categorized as VH showed the highest median specific capacity (5.2 m³/day/m), while the wells with specific capacity < 1.39 m³/day/m were distributed in the areas categorized as L or VL. The accuracy of GPM generated in the work looked acceptable, although the specific capacity data were not enough to verify GPM in the studied large watershed. To create GPMs for the determination of high-yield well locations, the resolution and reliability of thematic maps should be improved. Criterion values for groundwater potential should be established when machine learning or statistical models are used in the GPM evaluation process.

• Journal of IKEEE
• /
• v.28 no.2
• /
• pp.150-157
• /
• 2024

In this paper, we propose a novel algorithm for predicting the number of apples on an apple tree using a deep learning-based object detection model and a polynomial regression model. Measuring the number of apples on an apple tree can be used to predict apple yield and to assess losses for determining agricultural disaster insurance payouts. To measure apple fruit load, we photographed the front and back sides of apple trees. We manually labeled the apples in the captured images to construct a dataset, which was then used to train a one-stage object detection CNN model. However, when apples on an apple tree are obscured by leaves, branches, or other parts of the tree, they may not be captured in images. Consequently, it becomes difficult for image recognition-based deep learning models to detect or infer the presence of these apples. To address this issue, we propose a two-stage inference process. In the first stage, we utilize an image-based deep learning model to count the number of apples in photos taken from both sides of the apple tree. In the second stage, we conduct a polynomial regression analysis, using the total apple count from the deep learning model as the independent variable, and the actual number of apples manually counted during an on-site visit to the orchard as the dependent variable. The performance evaluation of the two-stage inference system proposed in this paper showed an average accuracy of 90.98% in counting the number of apples on each apple tree. Therefore, the proposed method can significantly reduce the time and cost associated with manually counting apples. Furthermore, this approach has the potential to be widely adopted as a new foundational technology for fruit load estimation in related fields using deep learning.

• Journal of Life Science
• /
• v.19 no.5
• /
• pp.652-658
• /
• 2009

The comparative activities of aqueous, ethanol, and methanol extracts from Aralia elata shoot (AES) and leaf (AEL) were tested by in vitro experimental models of linoleic acid peroxidation by thiocyanate and thiobarbituric acid (TBA) methods and scavenging activities of free radicals by DPPH (${\alpha}$,${\alpha}$'-diphenyl-${\beta}$-picrylhydrazyl). In addition, bio-active materials (phenolic compounds and minerals) were also measured. The extract yield of each solvent extracted from AES and AEL was 3.08% and 3.13% in aqueous, 0.58% and 0.66% in ethanol, and 0.81% and 1.73% in methanol, respectively. The highest extract yield was found in the aqueous extract from AEL. Major mineral contents (mg%) of AES and AEL were 575.7 and 759.3 in Ca, 353.5 and 330.0 in K, and 31.3 and 31.0 in Mg, respectively. The highest free radical scavenging activity was found in the aqueous extract by 28.69% at 0.1% additional level from AES and in the methanol extract by 92.36% at 0.1% additional level from AEL. Free radical scavenging activity was stronger in AEL than in AES. In antioxidative activities determined by thiocyanate and TBA methods against lipid peroxidation using linoleic acid, ethanol extracts from AEL showed the highest antioxidative activity at all treatment concentrations. These results may provide the basic data to understand the biological activities of bio-active materials derived from AES and AEL.

• Korean Journal of Soil Science and Fertilizer
• /
• v.33 no.4
• /
• pp.221-233
• /
• 2000

Evaluation method of soil fertility by application of geographic information system (GIS) which includes landscape characteristics and soil map data was investigated from productivities of red pepper and tobacco grown on the fields with no fertilization. Total 131 fields experiments, 64 fields of red pepper and 67 fields of tobacco were conducted from 22 and 23 fields for red pepper and tobacco, respectively, located at Cheangweon and Eumseong counties in 1996, from 20 and 25 fields at Boeun and Goesan counties in 1997, and 22 and 19 fields at Jincheon and Chungju counties in 1998. All the experimental sites were selected on the basis of wide range of distribution in landscape and soil attributes. Dry weights and nutrients (N, P and K) uptakes by red pepper plant and tobacco leaves were considered as basic fertility of the soil (BFS). The BFS was estimated by twenty-five independent variables including 13 chemical properties and 12 GIS data. Twenty-five independent variables were classified by two groups, 15 quantitative variables and 10 qualitative variables, and were analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Dry weight of red pepper (DWRP) and dry weight of tobacco leaves (DWTL) every year showed high variations by five times in difference plots with minimum yield and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including independent variables was better than that by simple regression showing gradual improvement by adding chemical properties, quantitative variables, and qualitative variables of the GIS. However the evaluation for the BFS by the MLR showed the better result for tobacco than red pepper. For example the variability in the DWTL by MLR was explained 34.2% by only chemical properties, 35.0% by adding quantitative variables, and 72.5% by adding both the quantitative and qualitative variables of the GIS compared with 21.7% by simple regression with $NO_3-N$ content in soil. Consequently, it is assumed that this approach by the MLR including both the quantitative and qualitative variables was available as an evaluation model of soil fertility for upland field.

• Korean Journal of Food Science and Technology
• /
• v.47 no.2
• /
• pp.233-239
• /
• 2015

This study determined the optimum extraction conditions based on five response variables (yield, total phenolics, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical scavanging activity, oxygen radical absorbance capacity (ORAC), and ${\beta}$-1,3-glucan content) in chaga mushroom (Inonotus obliquus) using the response surface methodology, where three independent variables (ethanol concentration, extraction temperature, and extraction time) were optimized using a central composite design. The optimum ethanol concentration, extraction temperature, and extraction time were 50% (w/w), $88.7^{\circ}C$, and 14.5 h; 9.2%, $92.7^{\circ}C$, and 14.5 h; 50.8%, $92.7^{\circ}C$, and 14.5 h; 9.2%, $92.7^{\circ}C$, and 1.5 h; and 90.8%, $92.7^{\circ}C$, and 1.5 h for yield, total phenolics, ABTS, ORAC, and ${\beta}$-1,3-glucan content, respectively. The predicted values of the response variables were compared with those of the extracts under the optimal extraction conditions to verify the models. The optimum extraction condition for the five response variables was predicted to be 81.4% ethanol at $92.7^{\circ}C$ for 14.5 h.

• Clean Technology
• /
• v.25 no.2
• /
• pp.129-139
• /
• 2019

Bamboo is an evergreen perennial plant, and it is known as one of the most productive and fastest-growing plants in the world. It grows quickly in moderate climates with only moderate water and fertilizer. Traditionally in Asia, bamboo is used for building materials, as a food source, and as versatile raw materials. Bamboo as a biomass feedstock can be transformed to prepare activated carbon using the thermal treatment of pyrolysis. The effect of process variables such as carbonization temperature, activation temperature, activation time, the amount of steam, and the mixing ratio of phosphoric acid and bamboo were systematically investigated to optimize the preparation conditions. Steam activation was proceeded after carbonization with a vapor flow rate of $0.8{\sim}1.8mL-H_2O\;g-char^{-1}\;h^{-1}$ and activation time of 1 ~ 3 h at $700{\sim}900^{\circ}C$. Carbon yield and surface area reached 2.04 ~ 20.59 wt% and $499.17{\sim}1074.04m^2\;g^{-1}$, respectively, with a steam flow rate of $1.4mL-H_2O\;g-char^{-1}\;h^{-1}$ for 2 h. Also, the carbon yield and surface area were 24.67 wt% and $1389.59m^2\;g^{-1}$, respectively, when the bamboo and phosphoric acid were mixed in a 1:1 weight ratio ($700^{\circ}C$, 2 h, $1.4mL-H_2O\;g-char^{-1}\;h^{-1}$). The adsorption of methylene blue into the bamboo activated carbon was studied based on pseudo first order and second order kinetics models. The adsorption kinetics were found to follow the pseudo second order model, which is governed by chemisorption.

• Journal of Korean Society of Forest Science
• /
• v.112 no.1
• /
• pp.71-82
• /
• 2023

Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO₂ absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO₂ concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.

• Journal of Animal Science and Technology
• /
• v.55 no.5
• /
• pp.373-380
• /
• 2013

The study aimed to develop prediction models of primal cut yield using body measurements of Hanwoo steers in Korea. The progeny of 874 steers at Hanwoo Improvement Main Center from 2008 to 2010 were recorded. Pearson's correlation coefficients for primal cuts and other traits were estimated. Primal cuts were adjusted for slaughter date and age using the SAS GLM procedure. Afterwards, a stepwise regression was performed on each primal cut by fitting body measurement traits. An independent covariable was selected at the highest coefficient of determination with the greater fitness model using Mallows's Cp statistic. Results showed that primal cuts were significantly influenced by slaughter date (P<0.01). The age at slaughter, however, was only significant for the top round (P<0.05). There was a moderate to high correlation between chest girth and tenderloin (0.54), loin (0.74), and rib (0.80). Most primal cut percentages were negatively related to BFT. Similar negative to low positive correlations were observed for primal cut percentage and body size traits. In addition, a correlation of 0.21 was observed between rib percentage and chest girth. The regression of body measurements on the adjusted primal cuts were significant for later traits. Regression estimates revealed that wither height, body length, rump length, hip bone width, and chest girth are important for primal cut weight and percentage determination. In particular, chest girth was always important for primal cut weight estimates.

• Korean Journal of Soil Science and Fertilizer
• /
• v.9 no.3
• /
• pp.165-181
• /
• 1976

Fertilizer(N,P,K) demand for crop production in 1980, 1990 and 2000 was estimated according to the two proposed models, one of which is fertilizer use efficiency model expressed in $Fn=(Y/E){\cdot}(1-Cs)Eu$, where Fn:fertilizer demand, Y:Crop production estimated, E:nutrient efficiency, Cs:fraction of natural resource nutrient in plant, Eu:fertilizer use efficiency and the other fertilization efficiency model expressed in Fn=Y(1-Cys)/Fe, where Cys:fraction of yield without fertilizer, Fe:fertilization efficiency. Total crop uptake of nutrient and its noncycling portion were estimated as criteria for fertilizer demand and nutrient maintenance. Total crop uptake of N,P,K was 600,000 M/T in 1965 700,000 M/T in 1974 and estimated to 880,000 M/T in 1980, 1,170,000 M/T in 1990 and 1,410,000 M/T in 2000. Fertilizer demand appeares to be about 90% of total crop uptake according to fertilizer use efficiency model and about 87% according to fertilization efficiency model. The noncycling nutrient was about 29% of total crop uptake. Fertilizer demand was almost same to the uptake amount in nitrogen, 1.5 times of uptake in phosphorus and half of uptake in potassium. Varietal development, improvement of soil fertility and cultivation method and development of fertilizer forms appears to decrease fertilizer demand by increasing efficiency term in two models while environmental stress such as low temperature appears to give reverse effect resulting in higher fertilizer demand. Fertilizer consumption in 1974 seemed to be unreasonably high especially in nitrogen and phosphorus and thus the effective use of fertilizer appeared as an urgent problem considering that large fields are still remained in lower fertility.

• Journal of Bio-Environment Control
• /
• v.9 no.3
• /
• pp.171-178
• /
• 2000

Gross photosynthetic rats of leaves of hydroponically grown cucumber plants(Cucumis sativus L. cv. Guwoosalichungjang) were measured under various conditions of photosynthetic photon flux(PPF), ambient $CO_2$ concentration, air temperature and leaf nitrogen contents. Light compensation point of leaf photosynthesis appeared to be in the range of 10~20$\mu$mol.m$^{-2}$ .s$^{-1}$ and light saturation point be above 1000$\mu$mol.m$^{-2}$ .s$^{-1}$ . Gross photosynthetic rates increased persistently and asymptotically as air temperature rose from 12$^{\circ}C$ to 32$^{\circ}C$. However, there were only small differences in gross photosynthetic rates in the range of 24-32$^{\circ}C$, so that the range seemed to be optimal for photosynthesis of cucumber plants at the condition of $CO_2$ concentration of 400$\mu$mol.mol$^{-1}$ and PPF of around 400$\mu$mol.m$^{-2}$ .s$^{-1}$ . $CO_2$ compensation point of leaf photosynthesis appeared to be in the range of 20-40$\mu$mol.mol$^{-1}$ and $CO_2$ saturation point be above 1200$\mu$mol.mol$^{-1}$ . Gross photosynthetic rates increased sigmoidally as leaf nitrogen content increased. These environmental factors interacted synergistically to enhance gross photosynthetic rate, so that the rate increased multiplicatively s level of one factor increased progressively with higher levels of he other factors. Mathematical models wer developed to estimate the gross photosynthetic rate in accordance with the variations of these environmental factors. These modes can be used not only to explain he variation of growth or yield of cucumber plants under different environmental conditions but also as building blocks of plant growth model or expert system of cucumber plants.