• Korean Journal of Organic Agriculture
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• v.9 no.1
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• pp.37-49
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• 2001

This experiment was carried out to investigate the effects of application levels of nightsoil sludge compost(NSC) in 3 and 4 cuttings per annum on the dry matter yields and nutritive value of orchardgrass(Dactylis glomerata L.). Annual nightsoil sludge compost(NSC) were applied at levels of 0, 10, 20, 40 and 80 ton $㏊^{respectively}$ . Relative yields of each cut to annual dry matter yield were 29.9%, 46.% and 23.2% for 1st cut, 2nd cut and 3rd cut in 3 cutting system, 23.7%, 29.3%, 34.0% and 13.0% for 1st cut, 2nd cut, 3rd cut and 4th cut in 4 cutting system, respectively. Significantly higher dry matter yield of orchardgrass obtained were 8.11 ton $㏊^{-1}$ at level of 40 ton ㏊$^{-1}$ $yr^{-1}$ in 3 cutting systems, ranges of 7.50~10.71 ton $㏊^{-1}$ at level of 10~80 ton ㏊$^{-1}$ $yr^{-1}$ in 4 cutting systems than those of non application level of NSC, respectively(p〈0.05). The mean efficiency of dry matter production to application of NSC(kg DM/ton NSC) were 46 and 102 kg in 3 and 4 cutting systems, respectively. Although th contents of crude protein(CP, %) of orchardgrass were significantly higher at the application levels of 10~80 ton $㏊^{-1}$ $yr^{-1}$ -1/ by NSC than those of the application levels at the 0 ton $㏊^{-1}$ $yr^{-1}$ in 3 and 4 cutting systems(p〈0.05), the contents of neutral detergent fiber(NDF, %) and acid detergent fiber(ADF, %) were lower in NSC plots than those at the non-application plots of NSC. The contents of total digestible nutrient(TDN, %) and relative feed value(RFV) of orchardgrass were significantly increased with increase the applicaton levels of NSC(p〈0.05).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.19-26
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• 2021

The lattice structure is attracting attention from industry because of its excellent strength and stiffness, ultra-lightweight, and energy absorption capability. Despite these advantages, widespread commercialization is limited by the difficult manufacturing processes for complex shapes. Additive manufacturing is attracting attention as an optimal technology for manufacturing lattice structures as a technology capable of fabricating complex geometric shapes. In this study, a unit cell was formed using a three-dimensional coordinate method. The relative density relational equation according to the boundary box size and strut radius of the unit cell was derived. Simple cubic (SC), body-centered cubic (BCC), and face-centered cubic (FCC) with a controlled relative density were designed using modeling software. The accuracy of the equations for calculating the relative density proposed in this study secured 98.3%, 98.6%, and 96.2% reliability in SC, BCC, and FCC, respectively. A simulation of the lattice structure revealed an increase in compressive yield load with increasing relative density under the same cell arrangement condition. The compressive yield load decreased in the order of SC, BCC, and FCC under the same arrangement conditions. Finally, structural optimization for the compressive load of a 20 mm × 20 mm × 20 mm structure was possible by configuring the SC unit cells in a 3 × 3 × 3 array.

• Journal of Powder Materials
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• v.15 no.5
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• pp.365-370
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• 2008

In this study, bottom-up powder processing and top-down severe plastic deformation processing approaches were combined in order to achieve both full density and grain refinement with least grain growth. The numerical modeling of the powder process requires the appropriate constitutive model for densification of the powder materials. The present research investigates the effect of representative powder yield function of the Shima-Oyane model and the critical relative density model. It was found that the critical relative density model is better than the Shima-Oyane model for powder densification behavior, especially for initial stage.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.1
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• pp.1-5
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• 2000

Leaf area is critical for crop light interception, and thereby has a substantial influence on crop yield. This experiment was conducted to characterize the development of soybean [Glycine max (L.) Merr.] leaf area. Plastochron index and leaf relative growth rate of Jackson was contrasted with the PI416937, which also has demonstrated tolerance to drought. First, plastochron ratio (PR) and plastochron index (PI) were evaluated in greenhouse to compare the leaf growth rate between two genotypes under well-watered condition. There was reasonable constancy of PR between two genotypes. The PR means of Jackson and PI416937 were 0.41 and 0.44, respectively. A fairly smooth increase of PI during vegetative stage was observed. Second, the relative growth rates were graphed against leaf area, normalized with respect to final leaf area, under well-watered and water-deficit conditions. Leaf growth was sustained longer in well-watered condition than water-deficit condition and there was a sizable proportion of leaves which was ceased earlier their growth in water-deficit condition compared to well-watered condition. The leaf relative growth rate of Jackson until leaves had completed at 45% of their growth during water deficit period was higher than that of PI416937.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.12
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• pp.1696-1701
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• 2006

A random regression model was applied for the first time for the analysis of test day records and to study the genetic persistency of first lactation milk yield of Indian Murrah buffaloes. Wilmink's Function was chosen to describe the shape of lactation curves. Heritabilities of test day milk yield varied from 0.33 to 0.58 in different test days. The highest heritability was found in the initial test day ($5^{th}$ day) milk yield. Genetic correlations among test day milk yields were higher in the initial test day milk yield and decreased when the test day interval was increased. The magnitude of genetic correlations between test day and 305 day milk yield varied from 0.25 to 0.99. The genetic persistencies of first lactation milk yield were estimated based on daily breeding values using two methods. $P_1$ is the genetic persistency estimated as a summation of the deviation of estimated daily breeding value on days to attain peak yield from each day after days to attain peak yield to different lactation days. $P_2$ is the genetic persistency estimated as the additional genetic yield (gained or lost) from days to attain peak yield to estimated breeding value on different lactation days relative to an average buffalo having the same yield on days to attain peak yield. The mean genetic persistency on 90, 120, 180, 240, 278 and 305 days in milk was estimated as -4.23, -21.67, -101.67, -229.57, -330.06 and -388.64, respectively by $P_1$, whereas by $P_2$ on same days in milk were estimated as -3.96 (-0.32 kg), -23.94 (-0.87 kg), -112.81 (-1.96 kg), -245.83 (-2.81 kg), -350.04 (-3.28 kg) and -407.58 (-3.40 kg) respectively. Higher magnitude of rank correlations indicated that the ranking of buffaloes based on their genetic persistency in both methods were similar for evaluation of genetic persistency of buffaloes. Based on the estimated range of genetic persistency three types of genetic persistency were identified. Genetic correlations among genetic persistency in different days in milk and between genetic persistencies on the same day in milk were very high. The genetic correlations between genetic persistency for different days in milk and estimated breeding value for 305 DIM was increased from 90 DIM to 180 DIM, and highest around 240 DIM which indicates a minimum of 240 days as an optimum first lactation length might be required for genetic evaluation of Indian Murrah buffaloes.

• Korean Journal of Medicinal Crop Science
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• v.12 no.3
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• pp.231-236
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• 2004

Crop productivity would be determined by relative capacity of source and sink. The study was carried out to measure the effects of shading and flower bud pinching on growth and yield of Atractylodes japonica Koidz. Shading treatment after transplanting was done at 100%, 65, 45 or 25% level of natural light intensity but the pinching treatment was to remove all the inflorescences formed after June 10, July 10, August 10 or none. Growth and yield at early and late stages were periodically measured. At the early stage, shading mainly influenced fresh weight rather than morphological characters. At the late stage, however, severer shading decreased numbers of stems, leaves, roots, fraction and total fresh weight. 65% shading from July 1 to September 30 after skipped the emerging and early growth stages showed nearly same growth and morphological characters but more rhizome yield per unit area than non-shading. In flower bud pinching treatment, earlier pinching increased number of roots, fraction fresh weights per plant and rhizome yield per unit area.

• Journal of The Korean Society of Grassland and Forage Science
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• v.14 no.2
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• pp.125-131
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• 1994

This experiment was canied out to study -the effects of different seeding date on the yields and nutritional value of Pearl millet. Seeding dates were $S_1$,$S_2$,$S_3$,$S_4$, and $S_5$, and harvest dates were $S_1$, (7 July) and $S_2$, (18Augst), respectively. The results were summarized as follows: 1. Plant length was not influenced by seeding date at each harvest. The seeding date at $S_4$,showed the longest plant length of 90.4 an on average per year, which was longer by 17 cm compared to 73.3 cm harvested at $S_5$. 2. Total dry matter yield was not significantly different among seeding dates. Total dry matter yield in 1993 increased according to delayed seeding date from $S_1$ to $S_4$. Dry matter yield of 17.3 tonha was obtained in $S_4$. 3. The relative yield of leaf tended to increase with delayed seeding date, and varied from 60% to 69%. 4. Dry matter ratio decreased with delayed seeding date from $S_1$,(20 April) to $S_5$ (30 May), and varied from 15.6% to 12.3%. 5. Crude protein content of leaf at 1st and 2nd harvest and stem at 1st harvest were significantly different among various seeding dates. Avenge crude protein content increased with delayed seeding date from 9.0% at $S_1$ (20April) to 12.8% at (30 May) $S_5$ (30 May). 6. NDF and ADF of leaf at the 1st harvested were significantly different among seeding dates. NDF content decreased with delayed seeding date from 61.9% to 57.8%, and ADF content decreased with delayed seeding date from 34.8% to 32.2%.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.3
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• pp.153-157
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• 2019

Salicylic acid (SA) is an essential plant growth regulator that functions as a signaling molecule in plants. The purpose of this study was to clarify how the exogenous application of SA counteracts aluminum stress-induced growth and biomass yield reduction in alfalfa exposed to aluminum (Al) stress. Two-week-old alfalfa seedlings were exposed to a combination of $AlCl_3$ ($0{\mu}M$, $50{\mu}M$ and $100{\mu}M$, respectively) and SA (0.1 mM) for 72 hours. We observed, Al stress-induced plant growth inhibition and forage yield reduction are Al stress-dependent manner. A significant reduction of plant height (42.0-52.9%), leaf relative water content (13.0-21.4%), root length (35.4-48.7%), shoot fresh weight (31.2-25.9%), root fresh weight (15.4-23.3%), shoot dry weight (12.7-22.2%), roots dry weight (47.3-53.5%), were observed in alfalfa. In contrast, SA alleviated the Al-stress and enhanced growth and biomass yield in alfalfa. This study provides useful information concerning the role of SA that counteracts aluminum stress-induced growth and yield reduction in alfalfa.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.75-84
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• 2019

In this study, the random forest approach was used to predict the national mean rice yield of South Korea by using mean climatic factors at a national scale. A random forest model that used monthly climate variable and year as an important predictor in predicting crop yield. Annual yield change would be affected by technical improvement for crop management as well as climate. Year as prediction factor represent technical improvement. Thus, it is likely that the variables of importance identified for the random forest model could result in a large error in prediction of rice yield in practice. It was also found that elimination of the trend of yield data resulted in reasonable accuracy in prediction of yield using the random forest model. For example, yield prediction using the training set (data obtained from 1991 to 2005) had a relatively high degree of agreement statistics. Although the degree of agreement statistics for yield prediction for the test set (2006-2015) was not as good as those for the training set, the value of relative root mean square error (RRMSE) was less than 5%. In the variable importance plot, significant difference was noted in the importance of climate factors between the training and test sets. This difference could be attributed to the shifting of the transplanting date, which might have affected the growing season. This suggested that acceptable yield prediction could be achieved using random forest, when the data set included consistent planting or transplanting dates in the predicted area.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.647-659
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• 2017

Garlic and onion are grown in major cultivation regions that depend on the crop condition and the meteorology of the production area. Therefore, when yields are to be predicted, it is reasonable to use a statistical model in which both the crop and the meteorological elements are considered. In this paper, using a multiple linear regression model, we predicted garlic and onion yields in major cultivation regions. We used the MODIS NDVI that reflects the crop conditions, and six meteorological elements for 7 major cultivation regions from 2006 to 2015. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, the MODIS NDVI in February was chosen the significant independent variable of the garlic and onion yield prediction model. In the case of meteorological elements, the garlic yield prediction model were the mean temperature (March), the rainfall (November, March), the relative humidity (April), and the duration time of sunshine (April, May). Also, the rainfall (November), the duration time of sunshine (January), the relative humidity (April), and the minimum temperature (June) were chosen among the variables as the significant meteorological elements of the onion yield prediction model. MODIS NDVI and meteorological elements in the model explain 84.4%, 75.9% of the garlic and onion with a root mean square error (RMSE) of 42.57 kg/10a, 340.29 kg/10a. These lead to the result that the characteristics of variations in garlic and onion growth according to MODIS NDVI and other meteorological elements were well reflected in the model.