• Korean Journal of Medicinal Crop Science
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• v.9 no.2
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• pp.91-98
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• 2001

Scutellaria baicalensis G. was cultivated in plots of different soil textures which were sand loam(SL), loam(L) and clay loam(CL). Also three fertilizer conditions were used; non application (NA)treatment, rice straw manure(RSM) treatment and N-P-K, chemical fertilization(CF) treatment. The chemical-physical properties, such as organic matter, available phosphate, $K_2O$, CaO, clay contents and porosity ratio in CL plot with RSM application were the most proper in CL plot and RSM application for the culture of S. baicalensis plants. RSM had very high contents of total nitrogen, 2.25% and C/N ratios, 21.4. Thus the growth of shoot and root in loam plot with RSM treatment were greater compared to that of CL plot with NA treatment. Whereas, The highest baicalin, baicalein and wogonin contents in roots were found in CL plot with RSM treatment. There was significantly positive correlation between aerial and underground parts of plant, yield and contents of T-N, $K_2O$ but negatively correlated with the contents of baicalin, baicalein and wogonin in S. baicalensis roots.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Journal of The Korean Society of Grassland and Forage Science
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• v.4 no.1
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• pp.41-60
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• 1983

Experiments were conducted to study the effect of stage of maturity at harvest on the quality of silage. Herbage samples taken from the barley plant, rye plant, wheat plant, oat plant, Orchardgrass, Italian ryegrass, a mixed grass sward of Orchardgrass and Italian ryegrass and corn plant at different stages of maturity and ensiled in order to evaluate the effect of maturity on the chemical composition and feeding value as well as digestibility using sheep. Forage material were ensiled in small concrete silo. 1. The dry matter yield per 10a increased with advancing the maturity. Yield of brarley plant was 404, 635 and 900 kg at heading, milk and milk dough stage, respectively. Rye plant yield was 279, 589, 708, 10,000, 1,265, 1,376 and 1,492 kg at booting, before heading, early heading, late heading, early flowering, late flowering and after flowering stage, respectively. Italian ryegrass yield was 355, 613, 844 and 1,109 kg at vegetative, booting, heading and flowering, respectively. Orchardgrass/Italian ryegrass production was 477, 696, 891 and 1,027 kg at before was 458, 1,252, 1,534, 1,986 and 2,053 kg at tassel, early milk, yellow ripe and ripe stage, respectively. 2. Dry matter content increased with advancing maturity, but crude protein declined markedly. The NFE content decreased with advancing maturity of all the herbages except corn plant where NFE content increased, but corn plant increased. The content of crude fiber increased with advancing maturity except corn plant. The content of crude ash decreased with advancing maturity. In the rye plant, the content of neutral detergent fiber (NDF), acid detergent fiber (ADF) and cellulose increased with advancing maturity. 3. In vitro dry matter digestibilities of the rye plant was 53.6, 54.1, 50.7, 47.1, 44.9, 40.1 and 38.9% booting, before hcading, early heading, late heading, early flowering, late flowering and after flowering stage, respectively. The regression equation was $Y=56.22-0.74X+0.009X^2$ (X=cutting date from the first cut, Y=dry matter digestibilities). 4. In vitro digestible dry matter yield (kg/10a) of rye plant increased with advancing maturity, but declined from the flowering stage. The regression equation was $Y=168.88+26.09X-0.41X^2$ (X=cutting date from the first cut). 5. In vitro digestibility of dry matter in the corn plant was 69.2, 71.5, 69.8 and 69.9% at tassel, early milk, milk and yellow ripe stage, respectively. 6. The digestibility of crude protein and crude fiber of all plants decreased with advancing matuity, but NFE of the barley and corn generally increased. 7. The TDN contents on the dry matter basis decreased, but those of barley and corn silage were not different. TDN content of barley was 57.8, 57.1 and 57.9% at heading, milk and milk dough stage, respectively. That of rye silage was 50.0, 27.2 and 43.7% at early flowering, after flowering and milk stage, respectively. Italian ryegrass silage was 67.9, 63.7, and 54.9% at before heading, early heading and after heading, respectively. In case of Orchardgrass silage the TDN was 54.8, 52.9 and 46.1% at after heading, after flowering and milk, respectively. Corn shows TDN value of 59.5, 62.8 and 61.6% at milk, yellow ripe and ripe, respectively. 8. The pH value increased slightly by advancing maturity. 9. the content of organic acid decreased by advancing maturity and also increasing the DM content.