• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.4
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• pp.269-273
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• 2006

Multiple linear regression analysis was conducted to interpretate the relationship between sesame grain yield and its components under early sowing cropping condition. The t test showed that stem length, number of capsules per plant, 1000 seeds weight and seed weight per plant gave significant contribution to sesame grain yield, therefore those variables were assumed to mostly influenced components to grain yield of sesame. In the stepwise regression analysis, the predicted equation for sesame grain yield per square meter (Y) was Y = -7.900 + 0.150X1 + 0.461X5 + 15.553X6 + 8.543X7. Meanwhile, F value showed that stem length, number of capsules per plant and seed weight per plant gave significant contribution to sesame grain yield, while 1000 seeds weight did not significantly show. Based on the results, it is reasonable to assume that high yield. potential of sesame under early sowing cropping condition would be obtained by selecting breeding lines with long stem length, number of capsules per plant, and seed weight per plant, which was different result at the late sowing cropping condition in which days to flowering and maturity were assumed to be more affected factors to the sesame grain yield.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.175-179
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• 2003

We propose a new watermarking scheme that can be used to embed multiple bits and also resilient to JPEG compression and geometrical transforms such as scaling, rotation, and cropping based on holographic watermark that allows multiple watermark recovery without original content(cover image).

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.6
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• pp.553-557
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• 2014

The steady increase in livestock industry has greatly required the stable production of food and forage crops. As an alternative, rice-forage cropping system has been attempted in several southern areas. The present study was performed to understand whether an application of cattle-manure compost affects soil chemical properties and crop productivity in rice-forage cropping system, rice ${\rightarrow}$ summer oat ${\rightarrow}$ rye, in Jangheong county, south Jeolla province from 2013 to 2014. Treatments was composed of control (no compost), CM1 (compost application before rice transplanting), and CM2 (two-times compost application, before rice transplanting and after rice harvest), and inorganic fertilizers (N, P, and K) were equally dressed in all plots. Yields of rice were not significantly different between treatments, however, oat production was 1.25-fold higher in CM1 and CM2. Nutrient uptake amounts of rye were higher in CM2 than CM1 and control. Total nitrogen in soil was maintained stable level during crop cultivation. And soil organic matter contents in all treatments were increased by crop residue. Available P_2O_5$ and exchangeable K were increased by cattle manure application. Therefore, it suggested that the amount of nutrient by forage crop residue should be considered in rice-forage multiple cultivation.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.04a
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• pp.84-84
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• 2022

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.181-183
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• 2003

We propose a new watermarking scheme that can be used to embed multiple bits and also resilient to JPEG compression and geometrical transforms such as scaling, rotation, and cropping, based on off-axis holographic watermark that allows multiple watermark recovery without original content(cover image). The holographic watermark is that Fourier transformed digital hologram is embedded into cover image in the spatial domain. The proposed method has not only increased robustness with a stronger embedding but also imperceptibility of the watermark in the evaluation process.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.04a
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• pp.38-38
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• 2019

• Proceedings of the Korean Society of Crop Science Conference
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• 2020.06a
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• pp.22-22
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• 2020

• Proceedings of the Korean Society of Crop Science Conference
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• 2021.10a
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• pp.152-152
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• 2021