Korean Journal of Agricultural and Forest Meteorology
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v.8
no.4
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pp.229-241
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2006
Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.
The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66%, followed by G$\times$E interaction variability, 21%, and variability by environment, 13%. G$\times$E interaction was partitioned into two significant (P<0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.
Journal of the Korea Academia-Industrial cooperation Society
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v.21
no.1
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pp.725-731
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2020
This study analyzed the impact of increasing orange imports on the domestic fruit markets, focusing on the period January to May when oranges were imported and sold intensively after implementation of the Korea-US FTA. In this study, only citrus fruits that compete with U.S. oranges were limited to domestic fruits; of these, Hallabong, which is consistent with consumption of U.S. oranges, was selected as an analysis target. A dynamic recursive simulation model was established to evaluate the ex-post effects of the Korea-U.S. FTA, and to conduct mid and long-term forecasts for the Hallabong market. In addition, major policy simulations were performed on the Hallabong market to assess the effect of each scenario. The ex-post impact evaluation reveals that between December and February, Hallabong had no effect on the seasonal tariff of oranges. However, from 2012 to 2017, the actual import decreased by 21.9 billion won annually due to the TRQ, with the accumulated 6-year decrease being 131.5 billion won. Major policy simulation analysis shows that the change in the unit cost of import due to the U.S orange crop and the increase of Hallabong export will help in expanding the market, and thus effectively increase income.
Amylose and protein contents are important traits determining the edible quality of rice, especially in East Asian countries. Near-Infrared Reflectance Spectroscopy (NIRS) has become a powerful tool for rapid and nondestructive quantification of natural compounds in agricultural products. To test the practically of using NIRS for estimation of brown rice amylose and protein contents, the spectral reflectances ($400{\sim}2500\;nm$) of total 9,483 accessions of rice germplasm in Rural development Administration (RDA) Genebank ere obtained and compared to chemically determined amylose and protein content. The protein content of tested 119 accessions ranged from 6.5 to 8.0% and 25 accessions exhibited protein contents between 8.5 to 9.5%. In case of amylose content, all tested accessions ranged from 18.1 to 21.7% and the grade from 18.1 to 19.9% includes most number of accessions as 152 and 4 accessions exhibited amylose content between 20.5 to 21.7%. The optimal performance calibration model could be obtained from original spectra of brown rice using MPLS (Modified Partial Least Squares) with the correlation coefficients ($r_2$) for amylose and protein content were 0.865 and 0.786, respectively. The standard errors of calibration (SEC) exhibited good statistic values: 2.078 and 0.442 for amylose and protein contents, respectively. All these results suggest that NIR spectroscopy may serve as reputable and rapid method for quantification of brown rice protein and amylose contents in large numbers of rice germplasm.
Park, Seol Hwa;Baek, Youl Chang;Lee, Seul;Kim, Byeong Hyeon;Ryu, Chae Hwa
Journal of The Korean Society of Grassland and Forage Science
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v.40
no.4
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pp.236-243
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2020
This study was to evaluate the feed value of whole crop rice silage (WCRS) and to investigate a suitable ratio of the WCRS and concentrate by an analysis of rumen fermentation. A total of 6 treatments were used according to WCRS: concentrate ratio on in vitro rumen fermentation: T1 (100:0), T2 (60:40), T3 (40:60), T4 (20:80), T5 (10:90), and T6 (0:100). The ruminal pH, total gas emission, ammonia nitrogen, and volatile fatty acid (VFA) were determined as fermentation parameters. Total nutrients digestibility trial was conducted by 4 treatments according to WCRS: concentrate ratio at 40:60 (W40), 20:80 (W20), and 10:90 (W10), respectively. Feed value was analyzed according to AOAC (2019) and nutrient digestibility was calculated based on NRC (2001). The levels of crude protein (CP), crude fat, and neutral detergent fiber of the WCRS were 12.29%, 1.67%, and 59.79%, respectively. It was found to be 51.49% as a result of predicting the total digestible nutrient of WCRS using the NRC (2001) model. In vitro rumen fermentation, T4, T5, and T6 treatments showed a greater gas emission and total VFA concentration compared with other treatments (p<0.05). Acetate and acetate to propionate ratio of T4, T5, and T6 were significantly higher than other treatments (p<0.05). There was a significant difference in the level of propionate and butyrate according to the WCRS: concentrate ratio (p<0.05). The digestibility of dry matter and CP was significantly lower in W40 than in other treatments (p<0.05); however, there was no difference in W20 and W10. In conclusion, the 20:80 (WCRS: concentrate) is beneficial for stabilizing the rumen that does not inhibit rumen fermentation and nutrient digestion. This ratio might have a positive effect on the economics of farms as a valuable feed.
Min-Seo Kang;Jae-Sang Shim;Hye-Jin Lee;Hee-Ju Lee;Yoon-Ah Jang;Woo-Moon Lee;Sang-Gyu Lee;Seung-Hwan Wi
Journal of Bio-Environment Control
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v.32
no.4
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pp.366-376
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2023
This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the 'Cheongmyeong Gaual' variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37' N 128°32' E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.
Korean Journal of Agricultural and Forest Meteorology
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v.17
no.2
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pp.108-125
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2015
The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.
To mitigate the impacts of climate change on agricultural ecosystems, development of agricultural management for enhanced soil carbon sequestration is required. In this study, the effects of fertilizer types (chemical fertilizer and manure compost), cropping systems, and crop residue management on SOC(Soil Organic Carbon) sequestration were investigated. Summer corn and winter barley were cultivated on experimental plots under natural rainfall conditions for two years with chemical fertilizer and manure compost. Soil samples were collected conducted and analyzed for SOC for soil. To estimate long-term variation patterns of SOC, DNDC was run with the experimental data and the weather input parameters from 1981 to 2010. DNDC simulation demonstrated SOC reduction by chemical fertilizer treatment unless plant residues are returned; whereas compost treatments increased SOC under the same conditions and SOC increment was proportional to compost application rate. In addition, SOC further increased under corn-barley cropping system over single corn cropping due to more compost application. Regardless of nutrient input type, residue return increased SOC; however, the magnitude of SOC increase by residue return was lower than by compost application.
Domestic facility agriculture grows rapidly, such as modernization and large-scale. And the production scale increases significantly compared to the area, accounting for about 60% of the total agricultural production. Greenhouses require energy input to create an appropriate environment for stable mass production throughout the year, but the energy load per unit area is large because of low insulation properties. Through the rooftop greenhouse, one of the types of urban agriculture, energy that is not discarded or utilized in the building can be used in the rooftop greenhouse. And the cooling and heating load of the building can be reduced through optimal greenhouse operation. Dynamic energy analysis for various environmental conditions should be preceded for efficient operation of rooftop greenhouses, and about 40% of the solar energy introduced in the greenhouse is energy exchange for crops, so it should be considered essential. A major analysis is needed for each sensible heat and latent heat load by leaf surface temperature and evapotranspiration, dominant in energy flow. Therefore, an experiment was conducted in a rooftop greenhouse located at the Korea Institute of Machinery and Materials to analyze the energy exchange according to the growth stage of crops. A micro-meteorological and nutrient solution environment and growth survey were conducted around the crops. Finally, a regression model of leaf temperature and evapotranspiration according to the growth stage of leafy vegetables was developed, and using this, the dynamic energy model of the rooftop greenhouse considering heat transfer between crops and the surrounding air can be analyzed.
In order to estimate the demand for water resources planning and operation, methodology for determining the size of water supply facilities has been mainly applied to agricultural water, unlike living and industrial water, which reflects actual usage trends. This inevitably leads to an overestimation of agricultural water and can lead to an imbalance in the supply and demand of each use in terms of the total water resources plan. In this study, the difference of approaches of concept of net consumption was examined in comparison with the existing methodology and the characteristics of agricultural water demand were analyzed by applying it to whole Jeju Island. SWAT model was applied to estimate the amount of evapotranspiration, which is a key factor in estimating demand, and watershed modeling was performed to reflect geographical features, weather, runoff and water use characteristics of Jeju Island. For the past period (1992~2013), demand of Jeju Island as a whole was analyzed as 427 mm per year, and it showed a relatively high demand around the eastern and western coastal regions. Annual demand and seasonal variation characteristics of 10 river basins with watershed area of $30km^2$ or more were also analyzed. In addition, by applying the cultivated area of each crop in 2020 in the future, it is estimated that the demand corresponding to the 10-year frequency drought is 54% of the amount demanded in the previous research. This is due to the difference in approach depending on the purpose of the demand calculation. From the viewpoint of water resource management and operation, additional demand is expected as much as the net consumption. However, from the actual supply perspective, it can be judged that a facility plan that meets the existing demand amount is necessary. In order to utilize the methodologies and results presented in this study in practice, it is necessary to make a reasonable discussion in terms of policy and institutional as well as engineering verification.
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