• Journal of the Korean Society of Food Science and Nutrition
• /
• v.43 no.6
• /
• pp.955-961
• /
• 2014

This study was carried out to investigate the amounts of vitamin C in 22 sweet potato cultivars cultivated in Korea as well as evaluate the effects of cooking methods on vitamin C contents. Methods for determining vitamin C was validated by determining linearity, specificity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy using HPLC. Results showed high linearity in the calibration curve with a coefficient of correlation ($R^2$) of 0.9999. The LOD and LOQ values for ascorbic acid (AA) were 0.03 and $0.10{\mu}g/mL$, respectively. The relative standard deviations (RSDs) for intra- and inter-day precision of AA were less than 5%. The recovery rates of AA and dehydroascorbic acid (DHA) were in the range from 98.21~98.64 and 98.28~100.68%, respectively. Depending on cultivar, contents of AA, DHA, and total ascorbic acid (TA) in sweet potatoes varied in the range from 37.76 (Sinyulmi)~89.25 (Juhwangmin), 23.37 (Sinjami)~63.94 (Sinyulmi), and 68.52 (Sinjami)~115.95 (Juhwangmin) mg/100 g, respectively, and their average levels were $56.98{\pm}12.53$, $36.46{\pm}9.03$, and $93.44{\pm}12.00mg/100g$, respectively. The average TA levels were also dependent on flesh color, whish was significantly higher in general sweet potato and orange sweet potato than in purple sweet potato. Steaming, baking, and frying processes significantly reduced AA (10.61~58.41%), DHA (2.57~52.81%), and TA (14.54~49.92%) contents in sweet potatoes. The highest reduction of AA, DHA, and TA contents was observed after baking, followed by steaming and frying. We expect that the basic information provided by this study will be useful to plant breeders and food scientists.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.1
• /
• pp.35-45
• /
• 2018

Image data collected by an airborne hyperspectral camera system have a great usability in coastal line mapping, detection of facilities composed of specific materials, detailed land use analysis, change monitoring and so forh in a complex coastal area because the system provides almost complete spectral and spatial information for each image pixel of tens to hundreds of spectral bands. A few approaches after classifying by a few approaches based on SAM(Spectral Angle Mapper) supervised classification were applied for extracting optimal land cover information from hyperspectral images acquired by CASI-1500 airborne hyperspectral camera on the object of a coastal area which includes both land and sea water areas. We applied three different approaches, that is to say firstly the classification approach of combined land and sea areas, secondly the reclassification approach after decompostion of land and sea areas from classification result of combined land and sea areas, and thirdly the land area-only classification approach using atmospheric correction images and compared classification results and accuracies. Land cover classification was conducted respectively by selecting not only four band images with the same wavelength range as IKONOS, QuickBird, KOMPSAT and GeoEye satelllite images but also eight band images with the same wavelength range as WorldView-2 from 48 band hyperspectral images and then compared with the classification result conducted with all of 48 band images. As a result, the reclassification approach after decompostion of land and sea areas from classification result of combined land and sea areas is more effective than classification approach of combined land and sea areas. It is showed the bigger the number of bands, the higher accuracy and reliability in the reclassification approach referred above. The results of higher spectral resolution showed asphalt or concrete roads was able to be classified more accurately.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.13 no.3
• /
• pp.165-173
• /
• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of Food Hygiene and Safety
• /
• v.33 no.3
• /
• pp.176-184
• /
• 2018

The aim of the present work was to develop simultaneous methods of quantification of carazolol, azaperone, and azaperol residues in livestock and fishery products using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Samples were extracted from beef, pork, chicken, egg, milk and shrimp using acetonitrile (ACN); while flat fish and eel were extracted using 80% ACN. For purification, ACN saturated n-hexane was used to remove fat composition. The standard calibration curves showed good linearity as correlation coefficients; $r^2$ was > 0.99. Average recoveries expressed were within the range of 67.9-105% for samples fortified at three different levels ($0.5{\times}MRL$, $1{\times}MRL$ and $2{\times}MRL$). The correlation coefficient expressed as precision was within the range of 0.55-7.93%. The limit of quantification (LOQ) was 0.0002-0.002 mg/kg. The proposed analytical method showed high accuracy and acceptable sensitivity based on Codex guideline requirements (CAC/GL71-2009). This method can be used to analyze the residue of carazolol, azaperone, and azaperol in livestock and fishery products.

• Tuberculosis and Respiratory Diseases
• /
• v.56 no.4
• /
• pp.393-404
• /
• 2004

Background : Nucleic acid hybridization has become an essential technique in the development of our understanding of gene structure and function. The quantitative analysis of hybridization has been used in the measurement of genome complexity and gene copy number. The filter hybridization assay is rapid, sensitive and can be used to measure RNAs complementary to any cloned DNA sequence. Methods : The authors assessed the accuracy, linearity, correlation coefficient and specificity of the hybridization depending on the added dose(0, 1, 5, and $10{\mu}g$) of non-specific rat spleen RNA to hybridization of surfactant protein A mRNA. Filter hybridization assays were used to obtain the equation of standard curve and thereby to quantitate the mRNA quantitation. Results : 1. Standard curve equation of filter hybridization assay between counts per minute (X) and spleen RNA input (Y) was Y=0.13X-19.35. Correlation coefficient was 0.98. 2. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) was Y=0.00066X-0.046. Correlation coefficient was 0.99. 3. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $1{\mu}g$ spleen RNA was Y=0.00056X-0.051. Correlation coefficient was 0.99. 4. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $5{\mu}g$ spleen RNA was Y=0.00065X-0.088. Correlation coefficient was 0.99. 5. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $10{\mu}g$ spleen RNA was Y=0.00051X-0.10. Correlation coefficient was 0.99. Conclusions : Comparison of cpm/filter in a linear range allowed accurate and reproducible estimation of surfactant protein A mRNA copy number irrespective of the addition dosage of non-specific rat spleen RNA over the range $0-10{\mu}g$.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.41 no.4
• /
• pp.287-294
• /
• 2021

The objective of this study was conducted to calculate the damage of whole crop maize in accordance with abnormal climate using the forage yield prediction model through machine learning. The forage yield prediction model was developed through 8 machine learning by processing after collecting whole crop maize and climate data, and the experimental area was selected as Gyeonggi-do. The forage yield prediction model was developed using the DeepCrossing (R²=0.5442, RMSE=0.1769) technique of the highest accuracy among machine learning techniques. The damage was calculated as the difference between the predicted dry matter yield of normal and abnormal climate. In normal climate, the predicted dry matter yield varies depending on the region, it was found in the range of 15,003~17,517 kg/ha. In abnormal temperature, precipitation, and wind speed, the predicted dry matter yield differed according to region and abnormal climate level, and ranged from 14,947 to 17,571, 14,986 to 17,525, and 14,920 to 17,557 kg/ha, respectively. In abnormal temperature, precipitation, and wind speed, the damage was in the range of -68 to 89 kg/ha, -17 to 17 kg/ha, and -112 to 121 kg/ha, respectively, which could not be judged as damage. In order to accurately calculate the damage of whole crop maize need to increase the number of abnormal climate data used in the forage yield prediction model.

• Journal of Bio-Environment Control
• /
• v.31 no.4
• /
• pp.401-408
• /
• 2022

As research on a controlled environment system based on crop growth environment sensing for sustainable production of horticultural crops and its industrial use has been important, research on how to properly utilize soil moisture sensors for outdoor cultivation is being actively conducted. This experiment was conducted to suggest the proper method of utilizing the TEROS 12, an FDR (frequency domain reflectometry) sensor, which is frequently used in industry and research fields, for each orchard soil in three regions in Korea. We collected soils from each orchard where fruit trees were grown, investigated the soil characteristics and soil water retention curve, and compared TEROS 12 sensor calibration equations to correlate the sensor output to the corresponding soil volumetric water content through linear and cubic regressions for each soil sample. The estimated value from the calibration equation provided by the manufacturer was also compared. The soil collected from all three orchards showed different soil characteristics and volumetric water content values by each soil water retention level across the soil samples. In addition, the cubic calibration equation for TEROS 12 sensor showed the highest coefficient of determination higher than 0.95, and the lowest RMSE for all soil samples. When estimating volumetric water contents from TEROS 12 sensor output using the calibration equation provided by the manufacturer, their calculated volumetric water contents were lower than the actual volumetric water contents, with the difference up to 0.09-0.17 m³·m^-3 depending on the soil samples, indicating an appropriate calibration for each soil should be preceded before FDR sensor utilization. Also, there was a difference in the range of soil volumetric water content corresponding to the soil water retention levels across the soil samples, suggesting that the soil water retention information should be required to properly interpret the volumetric water content value of the soil. Moreover, soil with a high content of sand had a relatively narrow range of volumetric water contents for irrigation, thus reducing the accuracy of an FDR sensor measurement. In conclusion, analyzing soil water retention characteristics of the target soil and the soil-specific calibration would be necessary to properly quantify the soil water status and determine their adequate irrigation point using an FDR sensor.

• Journal of IKEEE
• /
• v.27 no.1
• /
• pp.122-126
• /
• 2023

In this paper, a control system for a complex microbial incubator was proposed. The proposed control system consists of a control unit, a communication unit, a power supply unit, and a control system of the complex microbial incubator. The controller of the complex microbial incubator is designed and manufactured to convert analog signals and digital signals, and control signals of sensors such as displays using LCD panels, water level sensors, temperature sensors, and pH concentration sensors. The water level sensor used is designed and manufactured to enable accurate water level measurement by using the IR laser method with excellent linearity in order to solve the problem that existing water level sensors are difficult to measure due to foreign substances such as bubbles. The temperature sensor is designed and used so that it has high accuracy and no cumulative resistance error by measuring using the thermal resistance principle. The communication unit consists of two LAN ports and one RS-232 port, and is designed and manufactured to transmit signals such as LCD panel, PCT panel, and load cell controller used in the complex microbial incubator to the control unit. The power supply unit is designed and manufactured to supply power by configuring it with three voltage supply terminals such as 24V, 12V and 5V so that the control unit and communication unit can operate smoothly. The control system of the complex microbial incubator uses PLC to control sensor values such as pH concentration sensor, temperature sensor, and water level sensor, and the operation of circulation pump, circulation valve, rotary pump, and inverter load cell used for cultivation. In order to evaluate the performance of the control system of the proposed complex microbial incubator, the result of the experiment conducted by the accredited certification body showed that the range of water level measurement sensitivity was -0.41mm~1.59mm, and the range of change in water temperature was ±0.41℃, which is currently commercially available. It was confirmed that the product operates with better performance than the performance of the products. Therefore, the effectiveness of the control system of the complex microbial incubator proposed in this paper was demonstrated.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.18 no.1
• /
• pp.1-8
• /
• 2015

To evaluate accuracy and precision of determination of total alkalinity ($Alk_T$) and carbon dioxide ($TCO_2$) derived from present study, experiment was applied with $CO_2$ CRM (Batch 132, Scripps Institution of Oceanography; $Alk_T=2229.24{\pm}0.39{\mu}mol/kg$, $TCO_2=2032.65{\pm}0.45{\mu}mol/kg$). As the result, average concentration of $Alk_T$ and $TCO_2$ was $2354.09{\mu}mol/kg$ (~5.6% difference with $CO_2$ CRM) and $2089.60{\mu}mol/kg$ (~2.3% difference with $CO_2$ CRM), respectively. For previous method (Gran Titration) by addition $NaHCO_3$ to deionized water($Alk_T$ $2023.33{\mu}mol/kg$), average concentration was $2193.39{\mu}mol/kg$ (sd=57.15, n=7). Whereas, average concentration was $2017.02{\mu}mol/kg$ (sd=10.98, n=7) for the present study. Recovery yield experiments of total alkalinity in deionized water and seawater were implemented by addition of $NaHCO_3$. The recovery yield of deionized water in the range 0 to $4952.39{\mu}mol/kg$ was 100.8% ($R^2$=0.999), and seawater in the range 0 to $2041.32{\mu}mol/kg$ was 102.3% ($R^2$=0.999). Comparison of $pCO_2$ sensor (PSI $CO_2-Pro^{TM}$) with present method showed very meaningful correlation coefficient ($R^2$=0.977) in the range of 427 to $705{\mu}atm$ and 9.16 to $15.24{\mu}mol/kg$ throught elapsed time for two weeks. Field experiment of diurnal variation of total carbon dioxide was accomplished at Sachon harbor in the coastal waters of East Sea of Korea. Concentration of $Alk_T$ and $TCO_2$ was increased during night, and decreased during daylight hours. The results showed mirror type between $TCO_2$ and dissolved oxygen, which was attributable to photosynthesis and respiration of phytoplankton. Also, open ocean field study was performed to obtain vertical profile of $Alk_T$ and $TCO_2$ in C-C zone (Clarion-Clipperton Fracture Zone), Northeastern Pacific. Average concentrations of $Alk_T$ in the surface mixed layer (0~60 m) and deeper layer below 200 m were $2422.38{\mu}mol/kg$ (sd=78.73, n=20) and $2465.87{\mu}mol/kg$ (sd=57.68, n=103), respectively. And average concentrations of $TCO_2$ were $2134.47{\mu}mol/kg$ (sd=65.4, n=20) and $2431.87{\mu}mol/kg$ (sd=65.02, n=103) in the same depth ranges such as $Alk_T$. Vertical distributions of $Alk_T$ and $TCO_2$ concentrations tended to increase with depth, and analyzed concentrations showed slightly higher than those of previous studies in this area.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.19 no.1
• /
• pp.4296-4311
• /
• 1977

This study was conducted to derive an Instantaneous Unit Hydrograph for the accurate and reliable unitgraph which can be used to the estimation and control of flood for the development of agricultural water resources and rational design of hydraulic structures. Eight small watersheds were selected as studying basins from Han, Geum, Nakdong, Yeongsan and Inchon River systems which may be considered as a main river systems in Korea. The area of small watersheds are within the range of 85 to 470$\textrm{km}^2$. It is to derive an accurate Instantaneous Unit Hydrograph under the condition of having a short duration of heavy rain and uniform rainfall intensity with the basic and reliable data of rainfall records, pluviographs, records of river stages and of the main river systems mentioned above. Investigation was carried out for the relations between measurable unitgraph and watershed characteristics such as watershed area, A, river length L, and centroid distance of the watershed area, Lca. Especially, this study laid emphasis on the derivation and application of Instantaneous Unit Hydrograph (IUH) by applying Nash's conceptual model and by using an electronic computer. I U H by Nash's conceptual model and I U H by flood routing which can be applied to the ungaged small watersheds were derived and compared with each other to the observed unitgraph. 1 U H for each small watersheds can be solved by using an electronic computer. The results summarized for these studies are as follows; 1. Distribution of uniform rainfall intensity appears in the analysis for the temporal rainfall pattern of selected heavy rainfall event. 2. Mean value of recession constants, Kl, is 0.931 in all watersheds observed. 3. Time to peak discharge, Tp, occurs at the position of 0.02 Tb, base length of hlrdrograph with an indication of lower value than that in larger watersheds. 4. Peak discharge, Qp, in relation to the watershed area, A, and effective rainfall, R, is found to be {{{{ { Q}_{ p} = { 0.895} over { { A}^{0.145 } } }}}} AR having high significance of correlation coefficient, 0.927, between peak discharge, Qp, and effective rainfall, R. Design chart for the peak discharge (refer to Fig. 15) with watershed area and effective rainfall was established by the author. 5. The mean slopes of main streams within the range of 1.46 meters per kilometer to 13.6 meter per kilometer. These indicate higher slopes in the small watersheds than those in larger watersheds. Lengths of main streams are within the range of 9.4 kilometer to 41.75 kilometer, which can be regarded as a short distance. It is remarkable thing that the time of flood concentration was more rapid in the small watersheds than that in the other larger watersheds. 6. Length of main stream, L, in relation to the watershed area, A, is found to be L=2.044A0.48 having a high significance of correlation coefficient, 0.968. 7. Watershed lag, Lg, in hrs in relation to the watershed area, A, and length of main stream, L, was derived as Lg=3.228 A0.904 L-1.293 with a high significance. On the other hand, It was found that watershed lag, Lg, could also be expressed as {{{{Lg=0.247 { ( { LLca} over { SQRT { S} } )}^{ 0.604} }}}} in connection with the product of main stream length and the centroid length of the basin of the watershed area, LLca which could be expressed as a measure of the shape and the size of the watershed with the slopes except watershed area, A. But the latter showed a lower correlation than that of the former in the significance test. Therefore, it can be concluded that watershed lag, Lg, is more closely related with the such watersheds characteristics as watershed area and length of main stream in the small watersheds. Empirical formula for the peak discharge per unit area, qp, ㎥/sec/$\textrm{km}^2$, was derived as qp=10-0.389-0.0424Lg with a high significance, r=0.91. This indicates that the peak discharge per unit area of the unitgraph is in inverse proportion to the watershed lag time. 8. The base length of the unitgraph, Tb, in connection with the watershed lag, Lg, was extra.essed as {{{{ { T}_{ b} =1.14+0.564( { Lg} over {24 } )}}}} which has defined with a high significance. 9. For the derivation of IUH by applying linear conceptual model, the storage constant, K, with the length of main stream, L, and slopes, S, was adopted as {{{{K=0.1197( {L } over { SQRT {S } } )}}}} with a highly significant correlation coefficient, 0.90. Gamma function argument, N, derived with such watershed characteristics as watershed area, A, river length, L, centroid distance of the basin of the watershed area, Lca, and slopes, S, was found to be N=49.2 A1.481L-2.202 Lca-1.297 S-0.112 with a high significance having the F value, 4.83, through analysis of variance. 10. According to the linear conceptual model, Formular established in relation to the time distribution, Peak discharge and time to peak discharge for instantaneous Unit Hydrograph when unit effective rainfall of unitgraph and dimension of watershed area are applied as 10mm, and $\textrm{km}^2$ respectively are as follows; Time distribution of IUH {{{{u(0, t)= { 2.78A} over {K GAMMA (N) } { e}^{-t/k } { (t.K)}^{N-1 } }}}} (㎥/sec) Peak discharge of IUH {{{{ {u(0, t) }_{max } = { 2.78A} over {K GAMMA (N) } { e}^{-(N-1) } { (N-1)}^{N-1 } }}}} (㎥/sec) Time to peak discharge of IUH tp=(N-1)K (hrs) 11. Through mathematical analysis in the recession curve of Hydrograph, It was confirmed that empirical formula of Gamma function argument, N, had connection with recession constant, Kl, peak discharge, QP, and time to peak discharge, tp, as {{{{{ K'} over { { t}_{ p} } = { 1} over {N-1 } - { ln { t} over { { t}_{p } } } over {ln { Q} over { { Q}_{p } } } }}}} where {{{{K'= { 1} over { { lnK}_{1 } } }}}} 12. Linking the two, empirical formulars for storage constant, K, and Gamma function argument, N, into closer relations with each other, derivation of unit hydrograph for the ungaged small watersheds can be established by having formulars for the time distribution and peak discharge of IUH as follows. Time distribution of IUH u(0, t)=23.2 A L-1S1/2 F(N, K, t) (㎥/sec) where {{{{F(N, K, t)= { { e}^{-t/k } { (t/K)}^{N-1 } } over { GAMMA (N) } }}}} Peak discharge of IUH) u(0, t)max=23.2 A L-1S1/2 F(N) (㎥/sec) where {{{{F(N)= { { e}^{-(N-1) } { (N-1)}^{N-1 } } over { GAMMA (N) } }}}} 13. The base length of the Time-Area Diagram for the IUH was given by {{{{C=0.778 { ( { LLca} over { SQRT { S} } )}^{0.423 } }}}} with correlation coefficient, 0.85, which has an indication of the relations to the length of main stream, L, centroid distance of the basin of the watershed area, Lca, and slopes, S. 14. Relative errors in the peak discharge of the IUH by using linear conceptual model and IUH by routing showed to be 2.5 and 16.9 percent respectively to the peak of observed unitgraph. Therefore, it confirmed that the accuracy of IUH using linear conceptual model was approaching more closely to the observed unitgraph than that of the flood routing in the small watersheds.