• 대한원격탐사학회지
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• 제32권4호
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• pp.383-401
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• 2016

In this paper, we described the statistical modeling of crop yields using satellite images, climatic datasets, soil property maps, and fertilizer data for the Midwestern United States during 2001-2012. Satellite images were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic datasets were provided by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group. Soil property maps were derived from the Harmonized World Soil Database (HWSD). Our multivariate regression models produced quite good prediction accuracies, with differences of approximately 8-15% from the governmental statistics of corn and soybean yields. The unfavorable conditions of climate and vegetation in 2012 could have resulted in a decrease in yields according to the regression models, but the actual yields were greater than predicted. It can be interpreted that factors other than climate, vegetation, soil, and fertilizer may be involved in the negative biases. Also, we found that soybean yield was more affected by minimum temperature conditions while corn yield was more associated with photosynthetic activities. These two crops can have different potential impacts regarding climate change, and it is important to quantify the degree of the crop sensitivities to climatic variations to help adaptation by humans. Considering the yield decreases during the drought event, we can assume that climatic effect may be stronger than human adaptive capacity. Thus, further studies are demanded particularly by enhancing the data regarding human activities such as tillage, fertilization, irrigation, and comprehensive agricultural technologies.

• 한국작물학회지
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• 제36권2호
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• pp.112-126
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• 1991

The atmospheric carbon dioxide concentration is ever-increasing and expected to reach about 600 ppmv some time during next century. Such an increase of $CO_2$ may cause a warming of the earth's surface of 1.5 to 4.5$^{\circ}C$, resulting in great changes in natural and agricultural ecosystems. The climatic scenario under doubled $CO_2$ projected by general circulation model of Goddard Institute for Space Studies(GISS) was adopted to evaluate the potential impact of climate change on agroclimatic resources, net primary productivity and rice productivity in Korea. The annual mean temperature was expected to rise by 3.5 to 4.$0^{\circ}C$ and the annual precipitation to vary by -5 to 20% as compared to current normal climate (1951 to 1980), resulting in the increase of possible duration of crop growth(days above 15$^{\circ}C$ in daily mean temperature) by 30 to 50 days and of effective accumulated temperature(EAT=∑Ti, Ti$\geq$1$0^{\circ}C$) by 1200 to 150$0^{\circ}C$. day which roughly corresponds to the shift of its isopleth northward by 300 to 400 km and by 600 to 700 m in altitude. The hydrological condition evaluated by radiative dryness index (RDI =Rn/ $\ell$P) is presumed to change slightly. The net primary productivity under the 2$\times$$CO_2$ climate was estimated to decrease by 3 to 4% when calculated without considering the photosynthesis stimulation due to $CO_2$ enrichment. Empirical crop-weather model was constructed for national rice yield prediction. The rice yields predicted by this model under 2 $\times$ $CO_2$ climatic scenario at the technological level of 1987 were lower by 34-43% than those under current normal climate. The parameters of MACROS, a dynamic simulation model from IRRI, were modified to simulate the growth and development of Korean rice cultivars under current and doubled $CO_2$ climatic condition. When simulated starting seedling emergence of May 10, the rice yield of Hwaseongbyeo(medium maturity) under 2 $\times$ $CO_2$ climate in Suwon showed 37% reduction compared to that under current normal climate. The yield reduction was ascribable mainly to the shortening of vegetative and ripening period due to accelerated development by higher temperature. Any simulated yields when shifted emergence date from April 10 to July 10 with Hwaseongbyeo (medium maturity) and Palgeum (late maturity) under 2 $\times$ $CO_2$ climate did not exceed the yield of Hwaseongbyeo simulated at seedling emergence on May 10 under current climate. The imaginary variety, having the same characteristics as those of Hwaseongbyeo except growth duration of 100 days from seedling emergence to heading, showed 4% increase in yield when simulated at seedling emergence on May 25 producing the highest yield. The simulation revealed that grain yields of rice increase to a greater extent under 2$\times$ $CO_2$-doubled condition than under current atmospheric $CO_2$ concentration as the plant type becomes more erect.

• 한국농공학회지
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• 제39권6호
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• pp.31-40
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• 1997

Potential impacts for unfavourable weather conditions and the assessment of the magnitudes of their adverse effects on crop yields were studied. EPIC model was investigated for its capability on crop yield predictions for rice and soybean. Weather generationmodel was used to generate long-term climatic data. The model was verified with ohserved climate data of Suwon city. Fifty years weather data including abnormal conditions were generated and used for crop yield simulation by EPIC model. Crop yield probability function was derived from simulated crop yield data, which followed normal distribution. Probable crop yield reductions due to abnormal weather conditions were also analyzed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.107-114
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• 1999

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.970-972
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• 2003

Due to rapid increase in the demand of Natural Rubber (NR) few years ago, NR price sore very higher. The rubber plantation in Thailand expanded very fast to non traditional areas with the result Thai become the biggest NR exporting country in the world. However, the average yield is still lower compared to experimental yield of RRIT (Rubber Research Institute of Thailand) or just 60 % (RRIT, 1998). This is due to many of new rubber planting areas, which are not suitable. The Thai Ministry of Agriculture and Cooperatives thus has set 'The complete cycle development strategies for natural rubber' in the medium-term measures by reducing the rubber planting areas by 300,000 rai (1 rai = 0.16ha) through replanting with oil palm. The aim of this study is to find out land having lowest potential for rubber production (R3) but highest for oil palm production (P1). Find areas which are unsuitable for rubber and can be replaced by oil palm in order to get a better agricultural production. The study was applied upon Krabi province, Thailand. Crops requirement, degree of limitation to crops growth, climatic data, crops yield, soil map, topographic map etc., were used to evaluate land potential for both rubber and oil palm production according to FAO framework (Sys, 1992). An Agro-ecological suitability map for rubber and oil palm were produced. This was done by mean of GIS. The database was generated and guide map for the decision makers in view of suitable crop substitution was prepared.

• 한국농림기상학회지
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• 제25권4호
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• pp.284-301
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• 2023

본 연구에서는 1km 고해상도 앙상블 신기후변화 시나리오(공통사회 경제경로 시나리오) 자료를 기반으로 하여 남한을 포함한 한반도 전체의 벼 기후생산성(CYP) 변화를 평가하였다. 이때, 기후변화 시나리오자료에서 제공하는 제한적인 변수를 활용하기 위해 일조시간을 대신하여 일사량을 이용하였다. 연구 결과에 따르면, 현재 기후에 비해 온난화된 미래 기후조건에서 CYPmax 값은 감소하고 최적출수일은 점차 늦춰지는 경향이 나타났다. 이는 고도가 높은 한반도 북동부의 산악 지역을 제외하고 모든 지역에서 나타나는 현상이며, 특히 온난화가 빠르게 진행되는 SSP585시나리오 일수록 더욱 뚜렷하게 나타났다. 이러한 결과는 낮은 배출 시나리오의 이점을 보여주는 동시에 온실 가스 배출을 제한하기 위해 더 많은 노력을 기울일 필요가 있음을 강조한다. 한편, CYPmax의 시계열에서 넓은 폭의 앙상블 스프레드가 나타났는데, 이는 단일모형 혹은 작은 수의 모형을 선택하였을 때 미래 변화 분석에 내재된 불확실성을 보여주며 앙상블 예측의 중요성을 보여준다. 본 연구를 통해 분석된 장기간의 기온 및 일사 조건의 변화에 따른 기후학적 벼 생산성 변화 및 불확실성에 대한 분석은 기후변화 대응을 위한 기초정보로써 가치가 있다.

• 한국농림기상학회지
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• 제16권4호
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• pp.316-326
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• 2014

출수한계기의 설정을 통해 이앙한계기 및 파종한계기 추정이 가능하며, 이는 이모작 가능 지대를 파악할 수 있게 하여 기후변화에 따른 작부체계 설정에 도움을 줄 수 있다. 본 연구에서는 과거평년인 1971년부터 2000년까지의 기상자료와 현재평년인 1981년부터 2010년까지의 기상자료를 이용하여 51개의 관측지점에서의 출수한계기를 설정하였으며 최대 잠재적 수량 개념인 기후등숙량을 이용하여 생산성을 검정하였다. 출수 후 40일 동안 평균기온의 누적온도를 이용하여 계산되는 출수한계기를 설정하기 위해 $760^{\circ}C$, $800^{\circ}C$, $840^{\circ}C$ 및 $880^{\circ}C$를 기준온도로 사용하였다. 또한, 기후등숙량은 출수 후 40일 간의 평균온도 및 일조시간을 이용하였다. 출수한계기에서 출수를 하였을 경우 일반적인 벼 재배시기에 비해 수량이 얼마나 감소하는지를 분석하기 위해 출수한계기에서의 기후등숙량을 기후등숙량의 최대값으로 나눠 그 비율값인 $CYP/CYP_{max}$을 구하였다. 출수한계기 분석 결과 과거평년에 비해 현재평년에서 출수한계기가 앞당겨지거나 변화가 없는 관측지점도 있었으나 대부분의 지점에서 출수한 계기가 늦추어졌으며 기준온도별로 그 변화가 상이하였다. $CYP/CYP_{max}$값은 모든 조건에서 81.8%이상의 값을 보였으며 대부분의 조건에서 90%이상의 값을 보였다. 따라서, 출수한계기까지 출수를 늦추더라도 기후적인 측면에서는 수량에 대한 손실이 크지 않을 것으로 사료된다. 출수한계기가 늦추어진 경우, 이는 이앙한계기 역시 늦추어질 것을 나타내며, 결국, 기후변화 조건에서 이모작 가능 지역이 증가할 가능성이 높을 것으로 사료되었다. 본 연구는 출수 후 40일간의 평균온도와 일조만을 대상으로 분석하여, 급작스러운 기온저하나 개화기 고온장해 등과 같은 기상장해 등은 고려하지 않았다. 따라서, 등숙기 기간동안의 특이적인 기상조건을 고려하고 보다 생물리학적인 수량예측을 위해 작물 모델을 사용한 연구가 추후에 수행되어야 할 것으로 사료된다. 또한, 이러한 방법을 사용하여 우리나라뿐만 아니라 동아시아 지역에서 미래기후조건에서의 재배한계기에 대한 분석를 통해 지역적인 기후변화적응 대책에 대한 연구가 필요할 것이다.

• Asian-Australasian Journal of Animal Sciences
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• 제32권2호
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• pp.224-232
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• 2019

Objective: Apart from various climatic differences, corn harvest stage and varieties are two major factors that can influence the yield and quality of corn silage in the tropics. A study was conducted to determine the optimum harvest stage of four corn varieties for silage production in Malaysia. Methods: Corn was harvested at four growth stages; silking, milk, dough, and dent stages from four varieties; Sweet Corn hybrid 926, Suwan, breeding test line (BTL) 1 and BTL 2. Using a split plot design, the treatments were then analysed based on the plant growth performance, yield, nutritive and feeding values followed by a financial feasibility study for potential commercialization. Results: Significant differences and interactions were detected across the parameters suggesting varying responses among the varieties towards the harvest stages. Sweet Corn was best harvested early in the dough stage due to high dry matter (DM) yield, digestible nutrient, and energy content with low fibre portion. Suwan was recommended to be harvested at the dent stage when it gave the highest DM yield with optimum digestible nutrient and energy content with low acid detergent fibre. BTL 1 and BTL 2 varieties can either be harvested at dough or dent stages as the crude protein, crude fibre, DM yield, DM content, digestible nutrient and energy were not significantly different at either stage. Further financial analysis showed that only Sweet Corn production was not financially feasible while Suwan had the best financial appraisal values among the grain varieties. Conclusion: In conclusion, only the grain varieties tested had the potential for silage making according to their optimum harvest stage but Suwan is highly recommended for commercialization as it was the most profitable.

• 한국농림기상학회지
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• 제6권1호
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• pp.61-69
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• 2004

A long-term growth simulation was performed at 99 land units in Yeoncheon county to test the potential adaptability of each land unit for growing soybean cultivars. The land units for soybean cultivation(CZU), each represented by a geographically referenced land patch, were selected based on land use, soil characteristics, and minimum arable land area. Monthly climatic normals for daily maximum and minimum temperature, precipitation, number of rain days and solar radiation were extracted for each CZU from digital climate models(DCM). The DCM grid cells falling within a same CZU were aggregated to make spatially explicit climatic normals relevant to the CZU. A daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CROPGRO-soybean model suitable for 2 domestic soybean cultivars were derived from long-term field observations. Three foreign cultivars with well established parameters were also added to this study, representing maturity groups 3, 4, and 5. Each treatment was simulated with the randomly generated 30 years' daily weather data(from planting to physiological maturity) for 99 land units in Yeoncheon to simulate the growth and yield responses to the inter-annual climate variation. The same model was run with input data from the Crop Experiment Station in Suwon to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for evaluation. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific cultivar. A computer program(MAPSOY) was written to help utilize the results in a decision-making procedure for agrotechnology transfer. transfer.

• 한국미생물·생명공학회지
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• 제49권2호
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• pp.249-254
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• 2021

The study of the impact of weather on viral respiratory infections enables the assignment of causality to disease outbreaks caused by climatic factors. A better understanding of the seasonal distribution of viruses may facilitate the development of potential treatment approaches and effective preventive strategies for respiratory viral infections. We analyzed the incidence of human mastadenovirus infection using real-time reverse transcription polymerase chain reaction in 9,010 test samples obtained from Cheonan, South Korea, and simultaneously collected the weather data from January 1, 2012, to December 31, 2018. We used the data collected on the infection frequency to detect seasonal patterns of human mastadenovirus prevalence, which were directly compared with local weather data obtained over the same period. Descriptive statistical analysis, frequency analysis, t-test, and binomial logistic regression analysis were performed to examine the relationship between weather, particulate matter, and human mastadenovirus infections. Patients under 10 years of age showed the highest mastadenovirus infection rates (89.78%) at an average monthly temperature of 18.2℃. Moreover, we observed a negative correlation between human mastadenovirus infection and temperature, wind chill, and air pressure. The obtained results indicate that climatic factors affect the rate of human mastadenovirus infection. Therefore, it may be possible to predict the instance when preventive strategies would yield the most effective results.