• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.3
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• pp.318-325
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• 1986

The studies were performed to obtain the basic informations on the influence of weather condition for grain yield and yield components in barley. The data of Olbori tested in 9 sites for 12 years were used in the studies. Milled grain yield was decreased in paddy field after rice harvested comparing to the upland condition, and yield potential was differed by test sites with the most stable yield in Gyeongnam. The coefficients of variation analyzed for milled grain yield by years were 12.2-42.6% with the differences between high-yield and low-yield year. Heading date was earlier in high-yield year and southern part compared to the low-yield year and middle part of the Korean peninsular showing the negative correlation between grain yield and heading date. High-yield year showed longer in culm length, shorter in spike length, almost same in number of grains per spike, and lower in 1,000grain weight compared to the low-yield year. Correlation analyzed between number of spikes and grain yield showed positive relationship. Temperatures affected to the grain yield analyzed by high in vegitative growth stage, low in alternative growth stage, and almost same in reproductive growth stage in high-yield year comparing to the low-yield year, however no remarkable differences of temperatures affected were detected in over wintering stage between high-yield and low-yield year. Precipitation amount in high-yield year was lesser in sowing time, more in seedling time, and lesser in over wintering time than those of the low-yield year. Correlation between rainfall amount in the early of April and grain yield showed significant negative correlation with the remarkable affects to the grain yield. Sunshine hours in high-yield year were longer in sowing time, shorter in over wintering time, and after the over wintering time to harvesting time was longer than those of the low-yie-ld year.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.311-311
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• 2017

The relationships between rice grain filling and air temperature of maturing period in paddy field were analyzed to evaluate the effects of climatic change on rice productivity in Korea. Data of air temperature of 31, 41 and 51 days after heading(DAH) for 11 years from 2002 to 2016 were collected and analyzed to determine the effects on rice yield and yield component related traits of Chucheogbyeo, popular cultivar in Gyeonggi province in Korea. As the results, ripening ratio was closely correlated with the mean of daily maximum temperature (DMAT $r=0.71^*$), the mean of daily temperature difference (DTD, $r=0.67^*$) of 41 DAH and DTD ($0.65^*$) of 51 DAH. Weight of 1,000 paddy rice grains was closely correlated with accumulated sunshine hours (ASH) of 31 ($r=0.84^{**}$), 41 ($r=0.75^{**}$), 51 ($r=0.72^*$) DAH. Brown rice grain weight recovery ratio was closely correlated with DTD ($r=0.76^{**}$) and ASH ($r=0.84^{**}$) of 31 DAH, DMAT ($r=0.75^{**}$, $r=0.79^{**}$), DTD ($r=0.79^{**}$, $r=0.77^{**}$) and ASH ($r=0.81^{**}$, $r=0.79^{**}$) of 41 and 51 DAH. Paddy rice yield was closely correlated with MDT ($r=-0.63^*$) of 31 DAH, mean of daily minimum temperature (DMIT, $r=-0.83^{**}$, $r=-0.70^*$), DTD ($r=0.71^*$, $r=0.62^*$) of 31 and 41 DAH. Brown rice yield was correlated closely with DMIT ($r=-0.86^{**}$, $r=-0.73^*$) and DTD ($r=0.80^{**}$, $r=0.72^*$) of 31, 41 DAH, and DTD ($r=0.69^*$) of 51 DAH. Milled rice yield was correlated closely with DMIT ($r=-86^{**}$, $r=-0.73^*$), DTD ($r=0.79^{**}$, $r=0.71^*$) of 31, 41 DAH, and DTD ($r=0.68^*$) of 51 DAH.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5417-5422
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• 2013

This research was performed in order to improve the goodness of fit of paddy rice production forecasting using MODIS images and to find out appropriate explanatory variables in the forecasting model. The aim of this paper is to review the use of satellite images for the survey of paddy rice production in Korea. Many developed countries, including the United States, Australia, and Japan, have been using satellite images to produce agricultural statistics such as crop production, cultivated acreage, etc. The survey accuracy of crop production by using satellite images, however, is not satisfied in practical use. In this paper, we reviewed several methods to increase the survey accuracy of rice production statistics, gained from satellite images. Rice was selected for this study because its cultivated area and production amount could be more easily identified than other crops by using satellite images. The MODIS images were used because they involved more appropriate images to estimate and analyze rice production. This study estimated yield functions by using the NDVIs, gained from paddy rice yields and annual average isothermal lines, and the meteorological variables such as sunshine hours, rainfall, and temperature during ripening stage. As a result of yield function estimation, the goodness of fit(R-squared) for the models was shown from 0.768 to 0.891. In this study, it is noteworthy academically and practically that vegetation index(NDVIs) identified by annual average isothermal lines and meteorological variables are very useful for estimating yield functions.

• Research in Plant Disease
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• v.16 no.2
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• pp.183-190
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• 2010

During the period from 1999 to 2008, we surveyed the major diseases incidence of rice in Korea. Leaf blast showed 0.85% of the diseased leaf area in 2000 and then consistently decreased to 0.02% by 2008. However, panicle blast irregularly appeared by the years depending on weather conditions for disease development from heading to milk stage of rice. Diseased lesion height of sheath blight had the lowest (10.1%) incidence in 2001 and the highest (21.4%) incidence in 2007. A negative corelation ($r=-0.88^*$) was measured between diseased lesion height of sheat blight and sunshine hours from mid- to late August. In Chunbuk, Gyeongbuk, and Gyeongnam provinces, brown spot occurrence declined since 2001, however, in Chungnam, Jeonbuk, and Jeonnam provinces, it increased since 2005. False smut drastically decreased after showing the highest incidence of 7.59% in panicles in 2000. The correlation coefficient between diseased panicles of false smut and rainfall during the late August was calculated as $0.94^{**}$. Bacterial leaf blight severely increased in the chronically infested fields in Jeonnam, Jeonbuk, Gyeongnam, and Chungnam province since 2003.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.56 no.2
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• pp.99-106
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• 2011

Here we reported an analyzing result for the relationship between climatic variables and rice(c.v. Odaebyeo and Ilpumbyeo) yield characteristics (including some growth characteristics) based on a long-term observed data at GARES and at KMA for rice and weather, respectively. Most of crop parameters investigated, such as heading date, culm height, panicle number $m^{-2}$, grain number $panicle^{-1}$ ripening rate, 1,000 grain weight and yield were strongly affected by wind velocity and relative humidity, as well as by daily mean air temperature, precipitation, sunshine hours and daily variations in air temperature depending on variety and crop developmental stages. Air velocity and relative humidity had not been studied as climatic variables affecting on the characteristics of rice growth and yield, however, they turned out to affect all the characteristics of rice investigated, especially ripening rate and yield, as much as any other climatic variables in this study. Air velocity appeared to affect highly the culm height and yield of Odaebyeo and ilpumbyeo. Relative humidity appeared to affect highly grain number and ripening rate of Odaebyeo and yield of Ilpumbyeo. Consequently Rice yield revealed to increase in the climatic conditions of high air velocity and low relative humidity.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.642-652
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• 2006

In order to understand the characteristics of surface ozone concentration and high $O_3$ concentration days, regional data from seven air quality monitoring stations which were operated by local governments were analyzed Regional characteristics of $O_3$ concentration were analyzed with the data of $O_3$ concentration and the characteristics of $O_3$ generation and weather conditions by the selection of the days in which the concentration was higher than 80 ppb. In the case of daily variation, the lowest $O_3$ concentration was shown in all regions from 7am to 8am and the highest around at 4 pm. The monthly variation of mean $O_3$ concentration and ${\Delta}O_3$ values revealed a reducing pattern in July and August following the peak in June, and again a gradual increasing trend in September and October. The result shows that the amount of ozone is dependent on photochemical reaction. The days of $O_3$ generated more than 80 ppb in the region of Gwangyang-bay were 544 days(1,760 hrs). The frequency of occurrence in the region revealed a strong pattern with the order of Samil-dong, Jinsang, and Gwangmu-dong stations in the Gwangyang region. However, Tein-dong, which is the nearest station to air pollution material generation source, showed the lowest frequency in the study area. Consequently, the meteorological parameters which can easily generate the high concentration of $O_3$ in the region of Gwangyang-bay are characterized as follows; atmospheric temperature which is higher than $19^{\circ}C$, relative humidity with the range of $60{\sim}85%$, the less average wind velocity than 5 m/s, cloud cover which is less than 5/10, and the more duration of sunshine than 8 hours.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.4
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• pp.323-328
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• 1988

The hop alpha-acid content prediction model developed with meteorological elements in Hoeongseong was Y=28.369-0.003X$_1$＋1.558X$_2$-1.953X$_3$-0.335X$_4$-0.003X$\sub$5/-0.119X$\sub$6/, with MSEp of 0.004, Rp$^2$ of 0.9987, Rap$_2$ of 0.9949 and Cp of 7.00. The total sunshine hours (X$_1$), the maximum temperature (X$_3$) and the total precipitation (X$\sub$5/) at flowering stage. the maximum temperature at flower bud differentiation stage (X$_4$) and the maximum temperature at cone ripening stage (X$\sub$6/) influenced on hop alpha .acid content as decrement weather elements. The maximum temperature at cone development stage(X$_2$) effected on ${\alpha}$-acid content as increment weather element.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.2
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• pp.79-86
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• 2017

This study was conducted to analyze seasonal and annual variations in rice quality and factors affecting the quality, for quality evaluation of the brand rice varieties produced in Jeonnam region. Coefficient of variation (CV) values for the seasonal variation in the rice quality were 3.1% in Toyo value, 2.1% in whiteness, 1.6% in protein content, 1.0% in moisture content, and 0.4% in head rice ratio. Quality characteristics of the brand rice varieties generally showed a decreasing tendency after April, as the months progressed. CV values for the annual variation in the rice quality were relatively high at 5.6% in protein content and 5.2% in Toyo value whereas those for whiteness and head rice ratio were relatively low, at 2.7% and 1.8%, respectively. Palatability and protein content showed high correlations with minimum air temperature, sunshine hours, rainfall, and daily temperature range. Head rice ratio had a negative correlation with daily temperature range whereas chalky rice ratio had a positive correlation with rainfall. Based on these results, we formulated a multiple regression equation to estimate palatability of cooked rice using protein content, whiteness, head rice ratio, and moisture content as follows: y = - 6.71a + 2.27b + 1.29c + 0.51d - 15.34 ($R^2$=0.51*) (y: palatability of cooked rice, a: protein content, b: moisture content, c: whiteness, d: head rice ratio).