• Journal of Bio-Environment Control
• /
• v.31 no.4
• /
• pp.444-451
• /
• 2022

Recently, long-term cultivation is becoming more common with the increase in tomato hydroponics. In hydroponics, it is very important to supply an appropriate nutrient solution considering the nutrient and moisture requirements of crops, in terms of productivity, resource use, and environmental conservation. Since seasonal environmental changes appear severely in long-term cultivation, it is so critical to manage irrigation control considering these changes. Therefore, this study was carried out to investigate the effect of irrigation volume on growth and yield in tomato long-term cultivation using coir substrate. The irrigation volume was adjusted at 4 levels (high, medium high, medium low and low) by different irrigation frequency. Irrigation scheduling (frequency) was controlled based on solar radiation which measured by radiation sensor installed outside the greenhouse and performed whenever accumulated solar radiation energy reached set value. Set value of integrated solar radiation was changed by the growing season. The results revealed that the higher irrigation volume caused the higher drainage rate, which could prevent the EC of drainage from rising excessively. As the cultivation period elapsed, the EC of the drainage increased. And the lower irrigation volume supplied, the more the increase in EC of the drainage. Plant length was shorter in the low irrigation volume treatment compared to the other treatments. But irrigation volume did not affect the number of nodes and fruit clusters. The number of fruit settings was not significantly affected by the irrigation volume in general, but high irrigation volume significantly decreased fruit setting and yield of the 12-15th cluster developed during low temperature period. Blossom-end rot occurred early with a high incidence rate in the low irrigation volume treatment group. The highest weight fruits was obtained from the high irrigation treatment group, while the medium high treatment group had the highest total yield. As a result of the experiment, it could be confirmed the effect of irrigation amount on the nutrient and moisture stabilization in the root zone and yield, in addition to the importance of proper irrigation control when cultivating tomato plants hydroponically using coir substrate. Therefore, it is necessary to continue the research on this topic, as it is judged that the precise irrigation control algorithm based on root zone-information applied to the integrated environmental control system, will contribute to the improvement of crop productivity as well as the development of hydroponics control techniques.

• Journal of Bio-Environment Control
• /
• v.31 no.3
• /
• pp.246-254
• /
• 2022

Domestic facility agriculture grows rapidly, such as modernization and large-scale. And the production scale increases significantly compared to the area, accounting for about 60% of the total agricultural production. Greenhouses require energy input to create an appropriate environment for stable mass production throughout the year, but the energy load per unit area is large because of low insulation properties. Through the rooftop greenhouse, one of the types of urban agriculture, energy that is not discarded or utilized in the building can be used in the rooftop greenhouse. And the cooling and heating load of the building can be reduced through optimal greenhouse operation. Dynamic energy analysis for various environmental conditions should be preceded for efficient operation of rooftop greenhouses, and about 40% of the solar energy introduced in the greenhouse is energy exchange for crops, so it should be considered essential. A major analysis is needed for each sensible heat and latent heat load by leaf surface temperature and evapotranspiration, dominant in energy flow. Therefore, an experiment was conducted in a rooftop greenhouse located at the Korea Institute of Machinery and Materials to analyze the energy exchange according to the growth stage of crops. A micro-meteorological and nutrient solution environment and growth survey were conducted around the crops. Finally, a regression model of leaf temperature and evapotranspiration according to the growth stage of leafy vegetables was developed, and using this, the dynamic energy model of the rooftop greenhouse considering heat transfer between crops and the surrounding air can be analyzed.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.57 no.2
• /
• pp.171-181
• /
• 2012

Lysine is the first limiting essential amino acid in cereals for humans and monogastric animals, although its content is generally low. A chemically induced high-lysine barley mutant, M98, has an agronomically undesirable shrunken endosperm trait. In order to obtain detailed insight into the atypical traits of M98 grains, we characterized amino acid composition and protein profiles of M98 and its parent cultivar Chalssalbori. Among a total of 16 amino acids, the percentage of each of the 7 amino acids, including lysine, was 1.2~1.8 times higher in M98, comparing to Chalssalbori. The percentage of proline and its precursor, glutamic acid, in M98 was about the half of that of the amino acids in Chalssalbori, but arginine synthesized from glutamic acid was 1.8 times higher in M98, compared that in the parent cultivar. Theses results indicated that the mutation in M98 grains might alter the proportion of amino acids linked to each other in a biosynthetic pathway. A comparison of grain proteome profiles between Chalssalbori and M98 revealed 70 differentially expressed protein spots, where 45 protein spots were up-regulated and 25 protein spots down-regulated in M98 compared to those in Chalssalbori. Of these changed protein spots, 53 were identified using nano-electrospray ionization liquid chromatography mass spectrometry. Most of these identified proteins were involved in various biological processes. In particular, 28 protein spots such as ${\beta}$-amylase, serpins and B3-hordein were identified as proteins associated with the atypical traits of M98. It was thought that a genetic study on the unique protein profile of M98 would be needed to develop an agronomically feasible barley cultivar with high-lysine trait.

• Journal of Life Science
• /
• v.25 no.3
• /
• pp.349-356
• /
• 2015

Thanks to recent advances in next-generation sequencing (NGS) technology, diverse livestock species have been dissected at the genome-wide sequence level. As for cattle, there are currently four Korean indigenous breeds registered with the Domestic Animal Diversity Information System of the Food and Agricultural Organization of the United Nations: Hanwoo, Chikso, Heugu, and Jeju Heugu. These native genetic resources were recently whole-genome resequenced using various NGS technologies, providing enormous single nucleotide polymorphism information across the genomes. The NGS application further provided biological such that Korean native cattle are genetically distant from some cattle breeds of European origins. In addition, the NGS technology was successfully applied to detect structural variations, particularly copy number variations that were usually difficult to identify at the genome-wide level with reasonable accuracy. Despite the success, those recent studies also showed an inherent limitation in sequencing only a representative individual of each breed. To elucidate the biological implications of the sequenced data, further confirmatory studies should be followed by sequencing or validating the population of each breed. Because NGS sequencing prices have consistently dropped, various population genomic theories can now be applied to the sequencing data obtained from the population of each breed of interest. There are still few such population studies available for the Korean native cattle breeds, but this situation will soon be improved with the recent initiative for NGS sequencing of diverse native livestock resources, including the Korean native cattle breeds.

• Journal of The Korean Association For Science Education
• /
• v.29 no.8
• /
• pp.990-1010
• /
• 2009

To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.55-63
• /
• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• Korean Chemical Engineering Research
• /
• v.46 no.3
• /
• pp.451-464
• /
• 2008

Three-phase inverse fluidized bed has been widely adopted with its increasing demand in the fields of bioreactor, fermentation process, wastewater treatment process, absorption and adsorption processes, where the fluidized or suspended particles are small or lower density comparing with that of continuous liquid phase, since the particles are frequently substrate, contacting medium or catalyst carrier. However, there has been little attention on the three-phase inverse fluidized beds even on the hydrodynamics. Needless to say, the information on the hydrodynamics and transport phenomena such as heat and mass transfer in the inverse fluidized beds has been essential for the operation, design and scale-up of various reactors and processes which are employing the three-phase inverse beds. In the present article, thus, the information on the three-phase inverse fluidized beds has been summarized and reorganized to suggest a pre-requisite knowledge for the field work in a sense of engineering point of view. The article is composed of three parts; hydrodynamics, heat and mass transfer characteristics of three-phase inverse fluidized beds. Effects of operating variables on the phase holdup, bubble properties and particle fluctuating frequency and dispersion were discussed in the section of hydrodynamics; effects of operating variables on the heat transfer coefficient and on the heat transfer model were discussed in the section of heat transfer characteristics ; and in the section of mass transfer characteristics, effects of operating variables on the liquid axial dispersion and volumetric liquid phase mass transfer coefficient were examined. In each section, correlations to predict the hydrodynamic characteristics such as minimum fluidization velocity, phase holdup, bubble properties and particle fluctuating frequency and dispersion and heat and mass transfer coefficients were suggested. And finally suggestions have been made for the future study for the application of three-phase inverse fluidized bed in several available fields to meet the increasing demands of this system.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.16 no.4
• /
• pp.79-90
• /
• 2013

The altitude range of habitats in which Fairy Pitta inhabited in 1960s is different from the present in Jeju Island. We studied on the habitat environment to understand the causes of difference through the comparison of satellite image data(Landsat) between 1975 and 2002, the literature review in relation to habitats, vegetations, and forest landscapes. The area of below 600m asl.(above sea level) where is mainly Fairy Pitta inhabited at the present with a lot of forests, was massive pasture with small isolated forests nearby valley. The forests were broad-leaved evergreen forests, and second forests with poor condition in the size and forest structure. The forests around 700m asl. were also second forests with approximately 3m height trees. The forests from 800m to 1300m asl. were also disturbed by mushroom cultivation by local people. The authors believe that Fairy Pitta could not inhabited in the area above 1300m because of the poor forest conditions in the size and structure in which consist of Ilex crenata, Rhododendron mucronulatum var. ciliatum and coppice forests. Therefore it might be possible that the best forests for the Fairy Pitta habitat were located in the area of 1,000m to 1,300m above sea level in 1960s. Compared to present habitats, forests at 100m up to 800m above sea level, the authors believe that the size of habitats were smaller with less population of Fairy Pitta. Since 1960s the forest landscape of Jeju Island has been improved successfully, and because of that the population of Fairy Pitta also has been increased. To protect the Fairy Pitta and habitats in Jeju Island, it is suggested that sustainable forest management focusing on the species composition and stand structure maintain or enhance the biodiversity.

• Journal of The Korean Association For Science Education
• /
• v.18 no.4
• /
• pp.463-472
• /
• 1998

Biotechnology is the process of using biological system for the production of materials. Genetic engineering, a subset of biotechnology, is the process of altering biological systems by the purposeful manipulation of DNA It is a new field in biology and no topic in biology is more likely to impact our personal lives and is therefore more worthy of our attention and understanding. The purpose of this study was to investigate students' understanding of the concepts of biotechnology, and a test tool which is made up of 20 basic questions was developed for the study. The subject of this study was high school students and the sample size was 486. In order to find out the source of students' misunderstanding, we also analysed high school textbooks and teachers were given the same tool applied to students. Two-way ANOVA was used for the analysis. Major findings of this study are as following; 1. Mean score of students was 41, and there was a significant difference between the scores of boys and girls(p<0.05). Female students scored higher than male students. The variables "region" and "major" had no significant influence. 2. Students' the most misunderstood concepts were "monoclonal antibody" and "gene cloning". Many students thought that a plamid DNA originally has a useful DNA in it, which is apparently wrong. 3. Mean score of teachers was 82, and the variabes of gender and career did not have statistically significant influence on the result(p>0.05). 4. Teachers got the lowest scores on the concepts of "gene therapy", "the accomplishment of biotechnology in agriculture and medicine", and "plasmid DNA". The results of item analysis implied that teachers' misunderstanding might be a part of the sources of students' misunderstaning. 5. Out of 18 basic concepts selected in the study, only 10 concepts were explained well enough in most textbooks. The results of item analysis indicated that textbooks also could be a part of the source of students' misunderstanding.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.1
• /
• pp.29-41
• /
• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.