• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.3
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• pp.195-201
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• 2001

Sowing date experiments were carried out by employing a rice variety "Kwanganbyeo" in both field and phytotron with natural daylength. In phytotron, temperatures were controlled at daily mean of 21$^{\circ}C$ and 24$^{\circ}C$. The responses of final leaf number and beading date were analyzed in relation to daylength during photo-sensitive period (PSP). Based on the component models predicting the final leaf number and leaf appearance rate, a rice phenology model was established and verified. Days from sowing to flowering (DSF) were shortened and final number of leaves (FNL) increased as sowing dates were delayed from 25 April to 5 June in field and phytotron. The increased leaf appearance rate (LAR) and the reduced FNL, respectively, due to the higher temperature and the shorter daylength in delayed sowings in the field brought about greater shortening of DSF than in the phytotron where only FNL was reduced by shorter daylength in delayed sewings. FNL showed very close relationship with the average daylength during PSP of six-leaf stage to panicle initiation, being well fitted to the following rational function ($R^2$=0.98):(equation omitted) where D is daylength and a, b, and c are the constants that were estimated as 14.694, -0.992, and -0.068 in Kwanganbyeo, respectively. The rice phonology model, which was composed of two component models for LAR and FNL, predicted DSF very accurately. The differences between the observed and predicted DSF was less than two days in the sewing date field experiments in 1999 and 2000 of which data were not used for the model construction.struction.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.71-79
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• 2017

Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of $R^2$ and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ${\pm}1^{\circ}C{\sim}{\pm}3^{\circ}C$ and average annual rainfall to ${\pm}5%{\sim}{\pm}30%$, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.751-760
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• 2015

Management of renewable organic resources is important in attaining the sustainability of agricultural production. However, nutrient management with organic resources is more complex than fertilization with chemical fertilizer because the composition of the organic input or the environmental condition will influence organic matter decomposition and nutrient release. One of the most effective methods for estimating nutrient release from organic amendment is the use of N mineralization models. The present study aimed at parameterizing N mineralization models for a number of organic amendments being used as a nutrient source for crop production. Laboratory incubation experiment was conducted in aerobic condition. N mineralization was investigated for nineteen organic amendments in sandy soil and clay soil at $20^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$. N mineralization was facilitated at higher temperature condition. Negative correlation was observed between mineralized N and C:N ratio of organic amendments. N mineralization process was slower in clay soil than in sandy soil and this was mainly due to the delayed nitrification. The single and the double exponential models were used to estimate N mineralization of the organic amendments. N mineralization potential $N_p$ and mineralization rate k were estimated in different temperature and soil conditions. Estimated $N_p$ ranged from 28.8 to 228.1 and k from 0.0066 to 0.6932. The double exponential model showed better prediction of N mineralization compared with the single exponential model, particularly for organic amendments with high C:N ratio. It is expected that the model parameters estimated based on the incubation experiment could be used to design nutrient management planning in environment-friendly agriculture.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.719-729
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• 2017

Recently, the field of agriculture has been gaining a new leap with the integration of ICT technology in agriculture. In particular, smart farms, which incorporate the Internet of Things (IoT) technology in agriculture, are in the spotlight. Smart farm technology collects and analyzes information such as temperature and humidity of the environment where crops are cultivated in real time using sensors to automatically control the devices necessary for harvesting crops in the control device, Environment. Although smart farm technology is paying attention as if it can solve everything, most of the research focuses only on increasing crop yields. This paper focuses on the development of a system architecture that can harvest high quality crops at the optimum stage rather than increase crop yields. In this paper, we have developed an architecture using apple trees as a sample and used the color information and weight information to predict the harvest time of apple trees. The simple board that collects color information and weight information and transmits it to the server side uses Arduino and adopts model-driven development (MDD) as development methodology. We have developed an architecture to provide services to PC users in the form of Web and to provide Smart Phone users with services in the form of hybrid apps. We also developed an architecture that uses beacon technology to provide orchestration information to users in real time.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.1
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• pp.29-34
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• 2012

The objective of this study was to rapidly evaluate fatty acids in a collection of millet (Panicum miliaceum subsp. miliaceum) of different origins so that this information could be disseminated to breeders to advance germplasm use and breeding. To develop the calibration equations for rapid and nondestructive evaluation of fatty acid content, near-infrared reflectance spectroscopy (NIRs) spectra (1104-2494 nm) of samples ground into flour ($n$=100) were obtained using a dispersive spectrometer. A modified partial least-squares model was developed to predict each component. For foxtail millet germplasm, our models returned coefficients of determination ($R^2$) of 0.89, 0.89, 0.89, and 0.92 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively. The prediction of the external validation set (n=10) showed significant correlation between references values and NIRs values ($r^2$=0.64, 0.90, 0.79, and 0.89 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). Standard deviation/standard errors of cross-validation (SD/SECV) values were close to 3 (2.62, 2.40, 1.85, and 2.23 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). These results indicate that these NIRs equations are functional for the mass screening and rapid quantification of the oleic and total fatty acids characterizing millet germplasm. Among the samples, IT153514 showed an especially high content of fatty acids ($48.14mg\;g^{-1}$), whereas IT123909 had a very low content ($34.44mg\;g^{-1}$).

• Journal of Plant Biotechnology
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• v.48 no.3
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• pp.148-155
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• 2021

Gibberellins (GAs) are essential phytohormones for plant growth that influence developmental processes and crop yields. Recent functional genomic analyses of model plants have yielded good characterizations of the canonical GA signaling pathways and related genes. Although Panax ginseng has long been considered to have economic and medicinal importance, functional genomic studies of the GA signaling pathways in this crucial perennial herb plant have been rarely conducted. Here, we identified and performed functional analysis of the GA signaling-related genes, including PgGID1s, PgSLY1s, and PgRGAs. We confirmed that the physiological role of GA signaling components in P. ginseng was evolutionarily conserved. In addition, the important functional domains and amino acid residues for protein interactions among active GA, GID1, SCF^SLY1, and RGA were also functionally conserved. Prediction and comparison of crystallographic structural similarities between PgGID1s and AtGID1a supported their function as GA receptors. Moreover, the subcellular localization and GA-dependent promotion of DELLA degradation in P. ginseng was similar to the canonical GA signaling pathways in other plants. Finally, we found that overexpression of PgRGA2 and PgSLY1-1 was sufficient to complement the GA-related phenotypes of atgid1a/c double- and rga quintuple-mutants, respectively. This critical information for these GA signaling genes has the potential to facilitate future genetic engineering and breeding of P. ginseng for increased crop yield and production of useful substances.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Korean Journal of Soil Science and Fertilizer
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• v.29 no.4
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• pp.342-346
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• 1996

Field experiments were conducted to investigate the mode of changes in exchangeable K contents in the soil under the continued(for three years) application of different levels of K fertilizer(KCl) with and without application of conventional compost(CC) and chicken-dung derived compost (CDC) for red pepper cultivation at two field parcels with different exchageable K contents on Gopyong silty loamy soil. The application of KCl at standard rate for red-pepper resulted in the increase in exchangeable K in the soil after each harvest of the crop. while no application of K and the application of KCl at one half of the standard rate tended to lower the exchangeable K in top soil with the cultivation of the crop. The application of compost in addition to KCl ammplified the difference in exchangeable K in the soil before and after the harvest of each crop. An equation could resonably well predict the exchageable K content in top soil after the years of crop cultivation, under different treatments. were developed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.203-214
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• 2017

There are two references of genetic information in Korean soybean cultivar. This study suggested that the new seven genetic information to supplement the uncertainty on prediction of potential yield of two references in soybean, and assessed the availability of two references and seven genetic information for future research. We carried out evaluate the prediction on flowering time and potential yield of the two references of genetic parameters and the new seven genetic parameters (New1~New7); the new seven genetic parameters were calibrated in Jinju, Suwon, Chuncheon during 2003-2006. As a result, in the individual and regional combination genetic parameters, the statistical indicators of the genetic parameters of the each site or the genetic parameters of the participating stations showed improved results, but did not significant. In Daegu, Miryang, and Jeonju, the predictability on flowering time of genetic parameters of New7 was not improved than that of two references. However, the genetic parameters of New7 showed improvement of predictability on potential yield. No predictability on flowering time of genetic parameters of two references as having the coefficient of determination ($R^2$) on flowering time respectively, at 0.00 and 0.01, but the predictability of genetic parameter of New7 was improved as $R^2$ on flowering time of New7 was 0.31 in Miryang. On the other hand, $R^2$ on potential yield of genetic parameters of two references were respectively 0.66 and 0.41, but no predictability on potential yield of genetic parameter of New7 as $R^2$ of New7 showed 0.00 in Jeonju. However, it is expected that the regional combination genetic parameters with the good evaluation can be utilized to predict the flowering timing and potential yields of other regions. Although it is necessary to analyze further whether or not the input data is uncertain.

• Journal of Crop Science and Biotechnology
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• v.11 no.2
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• pp.141-150
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• 2008

The response of grain yield(GY) and milled-rice protein content(PC) to crop growth status and nitrogen(N) rates at panicle initiation stage(PIS) is critical information for prescribing topdress N rate at PIS(Npi) for target GY and PC. Three split-split-plot experiments including various N treatments and rice cultivars were conducted in Experimental Farm, Seoul National University, Korea in 2003-2005. Shoot N density(SND, g N in shoot $m^{-2}$) and canopy reflectance were measured before N application at PIS, and GY, PC, and SND were measured at harvest. Data from the first two years(2003-2004) were used for calibrating the predictive models for GY, PC, and SND accumulated from PIS to harvest using SND at PIS and Npi by multiple stepwise regression. After that the calibrated models were used for calculating N requirement at PIS for each of nine plots based on the target PC of 6.8% and the values of SND at PIS that was estimated by canopy reflectance method in the 2005 experiment. The result showed that SND at PIS in combination with Npi were successful to predict GY, PC, and SND from PIS to harvest in the calibration dataset with the coefficients of determination ($R^2$) of 0.87, 0.73, and 0.82 and the relative errors in prediction(REP, %) of 5.5, 4.3, and 21.1%, respectively. In general, the calibrated model equations showed a little lower performance in calculating GY, PC, and SND in the validation dataset(data from 2005) but REP ranging from 3.3% for PC and 13.9% for SND accumulated from PIS to harvest was acceptable. Nitrogen rate prescription treatment(PRT) for the target PC of 6.8% reduced the coefficient of variation in PC from 4.6% in the fixed rate treatment(FRT, 3.6g N $m^{-2}$) to 2.4% in PRT and the average PC of PRT was 6.78%, being very close to the target PC of 6.8%. In addition, PRT increased GY by 42.1 $gm^{-2}$ while Npi increased by 0.63 $gm^{-2}$ compared to the FRT, resulting in high agronomic N-use efficiency of 68.8 kg grain from additional kg N. The high agronomic N-use efficiency might have resulted from the higher response of grain yield to the applied N in the prescribed N rate treatment because N rate was prescribed based on the crop growth and N status of each plot.