• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.725-733
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• 2020

The objectives of this study were (1) to develop a temporal mask map using MCD12Q1 data, and (2) to extract the annual variations in paddy, (3) to investigate the correlation analysis between MYD13Q1 NDVI and rice yield, and (4) to review its applicability. For these purposes, the temporal mask map was created using annual MCD12Q1 PFT data from 2002 to 2019, and compared with the fixed mask map. As a result, it found that the temporal mask map well reflected the variations of the paddy area. In addition, the correlation coefficient between NDVI and rice yield was also high significant as compared to the fixed mask map. Therefore, the temporal mask map will be useful for NDVI extraction, crop monitoring, and estimation of rice yield.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.5
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• pp.556-563
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• 2015

Chinese cabbage is one of the most important vegetables in Korea and a target crop for market stabilization as well. Remote sensing has long been used as a tool to extract plant growth, cultivated area and yield information for many crops, but little research has been conducted on Chinese cabbage. This study refers to the derivation of simple Chinese cabbage growth prediction equation by using RapidEye derived vegetation index. Daesan-myeon area in Gochang-gun, Jeollabuk-do, Korea is one of main producing district of Chinese cabbage. RapidEye multi-spectral imagery was taken on the Daesan-myeon five times from early September to late October during the Chinese cabbage growing season. Meanwhile, field reflectance spectra and five plant growth parameters, including plant height (P.H.), plant diameter (P.D.), leaf height (L.H.), leaf length (L.L.) and leaf number (L.N.), were measured for about 20 plants (ten plants per plot) for each ground survey. The normalized difference vegetation index (NDVI) for each of the 20 plants was measured using an active plant growth sensor (Crop $Circle^{TM}$) at the same time. The results of correlation analysis between the vegetation indices and Chinese cabbage growth data showed that NDVI was the most suited for monitoring the L.H. (r=0.958~0.978), L.L. (r=0.950~0.971), P.H. (r=0.887~0.982), P.D. (r=0.855~0.932) and L.N. (r=0.718~0.968). Retrieval equations were developed for estimating Chinese cabbage growth parameters using NDVI. These results obtained using the NDVI is effective provided a basis for establishing retrieval algorithm for the biophysical properties of Chinese cabbage. These results will also be useful in determining the RapidEye multi-spectral imagery necessary to estimate parameters of Chinese cabbage.

• Korean Journal of Organic Agriculture
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• v.21 no.2
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• pp.207-217
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• 2013

This study was conducted to estimate organic Hanwoo carrying capacity when whole crop wheat and triticale as winter forage crops were grown on different applying sources (no fertilizer, organic fertilizer or cattle slurry), and mixed sowing in combination with hairy vetch and forage pea at the level of 50% cattle slurry application during the period of 2009~2011. The experimental plots were consisted of 5 treatments. Each treatment was triplicates and allocated in the randomized complete block design. For whole crop wheat, annual mean dry matter (DM) yield was significantly (P<0.05) higher for fertilizer application treatments than for no fertilizer treatment, and crude protein (CP) yield was significantly (P<0.05) higher for forage pea and hairy vetch-mixed sowing treatments than for no fertilizer and organic ferilizer treatments. Mean CP, total digestible nutrients (TDN) and relative feed value (RFV) contents of legumes-mixed sowing treatments was significantly (P<0.05) higher than those of other treatments. As diets replaced with 70% whole crop wheat were provided for 450kg of Hanwoo heifers, legumes-mixed sowing treatments could raise more heifers than organic fertilizer and no fertilizer treatments. For triticale, annual mean DM, CP and TDN yields were significantly (P<0.05) higher for fertilizer application treatments than for no fertilizer treatment, and CP content of legumes-mixed sowing and cattle slurry application treatments was significantly (P<0.05) higher than that of other treatments. When 450kg of Hanwoo heifers were fed on diets replaced with 70% triticale, it was estimated that legumes-mixed sowing treatments at the level of 50% cattle slurry application could rear average 3.3~3.4 heads/ha/year, which was significantly (P<0.05) higher than no fertilizer treatment (2.5 heads/ha/year). It was indicated that DM yields of whole crop wheat and triticale were much more effective in cattle slurry application than organic fertilizer, and Legumes-mixed sowing at the level of 50% cattle slurry application rather than whole crop wheat or triticale alone increased yields per unit area and nutritional value such as CP content. In conclusion, it is conceived that whole crop wheat or triticale produced in the manner above can be used instead of grains imported as dietary protein sources in the organic Hanwoo feeding regimen.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.96-110
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• 1994

The purpose of this study is to develop soil salt prediction model for the estimation of irrigation water requirements for dry field crops in reclaimed tidelands. The simulation model based on water balance equation, salt balance equation, and salt storage equation was developed for daily prediction of sa]t concentration in root zone. The data obtained from field measurement during the growing period of tomato were used to evaluate the applicability of this model. The results of this study are summarized as follows: 1.The optimum irrigation point which maximizes the crop yield in reclaimed tidelands of silt loam soil while maintaining the salt concentration within the tolerance level, ws found to be pF 1.6, and total irrigation requirement after transplanting was 602mm(6.7 mm/day)for tomato. 2.When the irrigation point was pF 1.6, the deviation between predicted and measured salt concentration was less than 4 % at the significance level of 1 7% 3.Since the deviations between predicted and measured values data decrease as the amount of irrigation water increases, the proposed model appear to be more suitable for use in reclaimed tidelands. 4.The amount of irrigation water estimated by the simulation model was 7.2mm/day in the average for cultivating tomato at the optimum irrigation point of pF 1.6.The simulation model proposed in this study can be generalized by applying it to other crops. This, model, also, could be further improved and extended to estimate desalinization effects in reclaimed tidelands by including meteorological effect, capillary phenomenon, and infiltration.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.2
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• pp.127-136
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• 2019

Sweet sorghum (Sorghum bicolor L. Moench), compared to traditional crops, has been evaluated as a useful crop with high adaptability to the environment and various uses, but cultivation has not expanded owing to a lack of related research and information in Korea. This study was conducted to estimate heading date in 'Chorong' sweet sorghum based on climate data of the last 30 years (1989 - 2018) from six regions (Jeonju, Buan, Jeongup, Imsil, Namwon, and Jangsu) in Jellabuk Province. In addition, we compared the growth and quality factors by sowing date (April 10, April 25, May 10, May 25, June 10, June 25, and July 10) in 2018. Days from sowing to heading (DSH) increased to 107, 96, 83, 70, 59, 64, and 65 days in order of the sowing dates, respectively, and the average was 77.7 days. The effective accumulated temperature for heading date was $1,120.3^{\circ}C$. The mean annual temperature was the highest in Jeonju, followed in descending order by Jeongup, Buan, Namwon, Imsil, and Jangsu. The DSH based on effective accumulated temperature gradually decreased in all sowing date treatments in the six regions during the last 30 years. DSH of the six regions showed a negative relationship with mean temperature (sowing date to heading date) and predicted DSH ($R^2=0.9987**$) calculated by mean temperature was explained with a probability of 89% of observed DSH in 2017 and 2018. At harvest, fresh stem weight and soluble solids content were higher in the April and July sowings, but sugar content was higher in the May 10 ($3.4Mg{\cdot}ha^{-1}$) and May 25 ($3.1Mg{\cdot}ha^{-1}$) sowings. Overall, the April and July sowings were of low quality and yield, and there is a risk of frost damage; thus, we found May sowings to be the most effective. Additionally, sowing dates must be considered in terms of proper harvest stage, harvesting target (juice or grain), cultivation altitude, and microclimate.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.2
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• pp.79-87
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• 2009

Pot experiments using sand culture were conducted in 2004 under greenhouse conditions to evaluate the effect of nitrogen deficiency on red pepper biomass. Nitrogen stress was imposed by implementing 6 levels (40% to 140%) of N in Hoagland's nutrient solution for red pepper. Canopy reflectance measurements were made with hand held spectral sensors including $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$, and $Field\;Scout^{TM}$ Chlorophyll meter, and a spectroradiometer as well as Minolta SPAD-502 chlorophyll meter. Canopy reflectance and dry weight of red pepper were measured at five growth stages, the 30th, 40th, 50th, 80th and 120th day after planting(DAT). Dry weight of red pepper affected by nitrogen stress showed large differences between maximum and minimum values at the 120th DAT ranged from 48.2 to $196.6g\;plant^{-1}$, respectively. Several reflectance indices obtained from $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$ and Spectroradiometer including chlorophyll readings were compared for evaluation of red pepper biomass. The reflectance indices such as rNDVI, aNDVI and gNDVI by the $Crop\;Circle^{TM}$ sensor showed the highest correlation coefficient with dry weight of red pepper at the 40th, 50th, and 80th DAT, respectively. Also these reflectance indices at the same growth station was closely correlated with dry weight, yield, and nitrogen uptake of red pepper at the 120th DAT, especially showing the best correlation coefficient at the 80th DAT. From these result, the aNDVI at the 80th DAT can significantly explain for dry weight of red pepper at the 120th DAT as well as for application level of nitrogen fertilizer. Consequently ground remote sensing as a non-destructive real-time assessment of plant nitrogen status was thought to be a useful tool for in season nitrogen management for red pepper providing both spatial and temporal information.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.6
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• pp.516-521
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• 2004

The straw of thirty one rice varieties were evaluated for their feed value and related agronomic traits. The rice straw were hand-harvested, dried to constant weight at $75^{\circ}C$ and ground through a 20 mesh seive in a Wiley mill, analyzed with crude protein (CP), acid detergent fiber (ADF) and neutral detergent fiber (NDF). Relative feed value (RFV) was calculated from NDF and ADF. The sum of standardized score was estimated by dry weight of rice straw, content of CP, ADF and NDF. The straw yield of Daeanbyeo was 725.9 kg/10a, showed heighest value among the varieties and remainder was in the order of Keumnambyeo, Donginbyeo #1 and Chucheongbyeo. Crude protein (CP) content in a Dasanbyeo was higher than those in other varieties. The content of ADF in a Junghwabyeo and NDF in a Sobaegbyeo were $34.3\%$ and $63.8\%$, respectively, showed lowest value among the varieties. The rice straw of Dunnaebyeo, Obongbyeo, Seoanbyeo, Keumobyeo, Hwaseongbyeo, Noganbyeo and Gyehwabyeo belonged to the high feed value varieties by estimation of cluster analysis, sum of standardized score and RFV. The content of CP was found to be positively related with dry weight of leaf and grain, but negatively related with heading days after seeding, culm length, specific leaf weight (SLW) and dry weight of stem. ADF and NDF were found to be positively related with heading days after seeding, culm length, SLW and dry weight of leaf, but negatively related with dry weight of stem. The sum of standardized score and RFV were the only positive relationship with dry weight of stem and negative relationship with other traits.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.299-311
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• 2006

In this paper it is outlined the methodology of estimating the parameters of water balance analysis method for calculating recharge, using ground water level rises in monitoring well when values of specific yield of aquifer are not available. This methodology is applied for two monitoring wells of the case study area in northern area of the Jeiu Island. A water balance of soil layer of plant rooting zone is computed on a daily basis in the following manner. Diect runoff is estimated by using SCS method. Potential evapotranspiration calculated with Penman-Monteith equation is multiplied by crop coefficients($K_c$) and water stress coefficient to compute actual evapotranspiration(AET). Daily runoff and AET is subtracted from the rainfall plus the soil water storage of the previous day. Soil water remaining above soil water retention capacity(SWRC) is assumed to be recharge. Parameters such as the SCS curve number, SWRC and Kc are estimated from a linear relationship between water level rise and recharge for rainfall events. The upper threshold value of specific yield($n_m$) at the monitoring well location is derived from the relationship between rainfall and the resulting water level rise. The specific yield($n_c$) and the coefficient of determination ($R^2$) are calculated from a linear relationship between observed water level rise and calculated recharge for the different simulations. A set of parameter values with maximum value of $R^2$ is selected among parameter values with calculated specific yield($n_c$) less than the upper threshold value of specific yield($n_m$). Results applied for two monitoring wells show that the 81% of variance of the observed water level rises are explained by calculated recharge with the estimated parameters. It is shown that the data of groundwater level is useful in estimating the parameter of water balance analysis method for calculating recharge.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.