• 제목/요약/키워드: Onion Model

검색결과 71건 처리시간 0.028초

Analysis of the relationship between garlic and onion acreage response

  • Lee, Eulkyeong;Hong, Seungjee
    • 농업과학연구
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    • 제43권1호
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    • pp.136-143
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    • 2016
  • Garlic and onion are staple agricultural products to Koreans and also are important with regard to agricultural producers' income. These products' acreage responses are highly correlated with each other. Therefore, it is necessary to test whether there is a cointegration relationship between garlic acreage and onion acreage when one tries to estimate the acreage response's function. Based upon the test result of cointegration, it is confirmed that there is no statistically significant cointegration relationship between garlic acreage and onion acreage. In this case, vector autoregressive model is preferred to vector error correction model. This study investigated the dynamic relationship between garlic and onion acreage responses using vector autoregressive (VAR) model. The estimated results of VAR acreage response models show that there is a statistically significant relationship between current and lagged acreage of more than one lag. Therefore, it is recommended that government should consider the long-run period's relationship of each product's acreage when it plans a policy for stabilizing the supply and demand of garlic and onion. For the price variables, garlic price only affects garlic acreage response while onion price affects not only onion acreage response but also garlic acreage response. This implies that the stabilizing policy for onion price could have bigger effects than that for garlic price stabilization.

An Analysis of the Impact of Climate Change on the Korean Onion Market

  • BAEK, Ho-Seung;KIM, In-Seck
    • 산경연구논집
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    • 제11권3호
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    • pp.39-50
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    • 2020
  • Purpose: Agriculture, which is heavily influenced by climate conditions, is one of the industries most affected by climate change. In this respect, various studies on the impact of climate change on the agricultural market have been conducted. Since climate change is a long-term phenomenon for more than a decade, long-term projections of agricultural prices as well as climate variables are needed to properly analyze the impact of climate change on the agricultural market. However, these long-term price projections are often major constraints on studies of climate changes. The purpose of this study is to analyze the impacts of climate changes on the Korean onion market using ex-post analysis approach in order to avoid the difficulties of long-term price projections. Research design, data and methodology: This study develops an annual dynamic partial equilibrium model of Korean onion market. The behavioral equations of the model were estimated by OLS based on the annual data from 1988 to 2018. The modelling system is first simulated to have actual onion market conditions from 2014 to 2018 as a baseline and then compared it to the scenario assuming the climatic conditions under RCP8.5 over the same period. Scenario analyses were simulated by both comparative static and dynamic approach to evaluate the differences between the two approaches. Results: According to the empirical results, if the climate conditions under RCP8.5 were applied from 2014 to 2018, the yield of onion would increase by about 4%, and the price of onion would decrease from 3.7% to 17.4%. In addition, the average price fluctuation rate over the five years under RCP8.5 climate conditions is 56%, which is more volatile than 46% under actual climate conditions. Empirical results also show that the price decreases have been alleviated in dynamic model compared with comparative static model. Conclusions: Empirical results show that climate change is expected to increase onion yields and reduce onion prices. Therefore, the appropriate countermeasures against climate change in Korean onion market should be found in the stabilization of supply and demand for price stabilization rather than technical aspects such as the development of new varieties to increase productivity.

양파 출하시기 도매가격 예측모형 연구 (A Study on Onion Wholesale Price Forecasting Model)

  • 남국현;최영찬
    • 농촌지도와개발
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    • 제22권4호
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    • pp.423-434
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    • 2015
  • This paper predicts the onion's cultivation areas, yields per unit area, and wholesale prices during ship dates by using wholesale price data from the Korea Agro-Fisheries & Food Trade Corporation, the production data from the Statistics Korea, and the weather data from the Korea Meteorological Administration with an ARDL model. By analyzing the data of wholesale price, rural household income and rural total earnings, onion cultivation areas in 2015 are estimated to be 21,035, 17,774 and 20,557(ha). In addition, onion yields per unit area of South Jeolla Province, North Gyeongsang Province, South Gyeongsang Province, Jeju Island, and the whole country in 2015 are estimated to be 5,980, 6,493, 6,543, 6,614, 6,139 (kg/10a) respectively. By using onion production's predictive value found from onion's cultivation areas and yields per unit area in 2015, the onion's wholesale prices in June are estimated to be 780 won, 1,100 won, and 820 won for each model. Predicted monthly price after the onion's ship dates is analyzed to exceed 1,000 won after August.

양파와 마늘가격 예측모형의 예측력 고도화 방안 (Improving Forecasting Performance for Onion and Garlic Prices)

  • 하지희;서상택;김선웅
    • 농촌계획
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    • 제25권4호
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    • pp.109-117
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    • 2019
  • The purpose of this study is to present a time series model of onion and garlic prices. After considering the various time series models, we calculated the appropriate time series models for each item and then selected the model with the minimized error rate by reflecting the monthly dummy variables and import data. Also, we examined whether the predictive power improves when we combine the predictions of the Korea Rural Economic Institute with the predictions of time series models. As a result, onion prices were identified as ARMGARCH and garlic prices as ARXM. Monthly dummy variables were statistically significant for onion in May and garlic in June. Garlic imports were statistically significant as a result of adding imports as exogenous variables. This study is expected to help improve the forecasting model by suggesting a method to minimize the price forecasting error rate in the case of the unstable supply and demand of onion and garlic.

양파껍질과 양파육질의 용매추출물에 따른 항산화 효과 (Antioxidant Effects on various solvent extracts from Onion Peel and Onion Flesh)

  • 조정순;방현아
    • 대한영양사협회학술지
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    • 제4권1호
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    • pp.14-19
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    • 1998
  • This study was designed to investigate the role of onion as a natural antioxidant. Onion was distinguished as yellow onion peel and onion flesh. Onion samples were extracted with 5 different kinds of solvents such as water, 70% ethanol, 99.9%ethanol, 99.9% methanol, and 96% butanol in order to select optimal extraction solvents, In this part of study linoleic acid was used s an model system for the purpose of determining the antioxidant activities. The optimal extraction rate of various solvents containing onion samples was determined by measuring extraction yield, electron donating ability(EDA), thiobarbituric acid(TBA), and thiocyanate, which are common methods for measuring activity. As a result 70% ethanol was shown as the most effective solvent.

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MODIS NDVI와 기상요인을 고려한 마늘·양파 주산단지 단수예측 모형 개발 (Development of Garlic & Onion Yield Prediction Model on Major Cultivation Regions Considering MODIS NDVI and Meteorological Elements)

  • 나상일;박찬원;소규호;박재문;이경도
    • 대한원격탐사학회지
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    • 제33권5_2호
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    • pp.647-659
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    • 2017
  • 마늘과 양파 재배는 작물의 생육 조건과 주산지 기상에 영향을 받는다. 따라서 단수를 예측할 때에는 주산지의 작황과 기상을 고려할 필요가 있다. 본 연구에서는 2006년에서 2015년까지의 작물의 생육 조건을 반영한 MODIS NDVI와 7개 주산지의 기상요인을 다중 회귀 모형에 적용하여 주산지별 마늘 및 양파의 단수예측 모형을 개발하였다. 다중 회귀 모형에서 독립변수 채택은 단계적 선택방법을 이용하였다. 그 결과, 마늘과 양파 단수예측 모형은 2월의 MODIS NDVI가 중요한 독립변수로 채택되었다. 기상요인은 마늘의 경우, 평균온도(3월), 강우량(11월, 3월), 상대습도(4월), 최저온도(6월)가 채택되었으며, 양파는 강우량(11월), 일조시간(1월), 상대습도(4월), 최저온도(6월)가 독립변수로 채택되었다. MODIS NDVI와 기상요인을 이용한 단수예측 모형은 주산지별 마늘, 양파 평균 단수의 84.4%, 75.9% 설명력을 나타내었으며, RMSE는 각각 42.57 kg/10a, 340.29 kg/10a로 나타났다. 따라서 본 모형은 MODIS NDVI와 기상요인에 따른 마늘과 양파의 단수 변화특성을 잘 반영하고 있는 것으로 판단된다.

Modeling for Vacuum Drying Characteristics of Onion Slices

  • Lee, Jun-Ho;Kim, Hui-Jeong
    • Food Science and Biotechnology
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    • 제18권5호
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    • pp.1293-1297
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    • 2009
  • In this study, drying kinetics of onion slices was examined in a laboratory scale vacuum dryer at an air temperature in a range of $50-70^{\circ}C$. Moisture transfer from onion slices was described by applying the Fick's diffusion model, and the effective diffusivity was calculated. Temperature dependency of the effective diffusivity during drying process obeyed the Arrhenius relationship. Effective diffusivity increased with increasing temperature and the activation energy for the onion slices was estimated to be 16.92 kJ/mol. The experimental drying data were used to fit 9 drying models, and drying rate constants and coefficients of models tested were determined by non-linear regression analysis. Estimations by the page and Two-term exponential models were in good agreement with the experimental data obtained.

공간 패널 회귀모형을 이용한 양파 생산량 추정 (Onion yield estimation using spatial panel regression model)

  • 최성천;백장선
    • 응용통계연구
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    • 제29권5호
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    • pp.873-885
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    • 2016
  • 노지에서 재배되는 양파 생산량은 기후환경에 의하여 영향을 받으며, 특정 지역에서 많이 생산되는 지역적인 특성을 가지고 있다. 따라서 생산량 예측시 기상과 지역을 동시에 고려하는 접근이 필요하다. 본 논문에서는 공간 패널 회귀모형을 이용하여 기상변화에 따른 생산량을 추정하였다. 양파 주산지 13곳에 대한 2006년부터 2015년까지의 기상 패널자료를 사용하여, 공간시차를 반영한 공간자기회귀(spatial autoregressive)모형을 사용하였다. 공간가중치 행렬은 임계치 설정방법과 최근거리 설정방법으로 나누어 분석하여, 최근 3곳까지 거리 설정방법을 사용한 모형이 최종 모형으로 선택되었으며, 자기상관성이 유의함을 보였다. 하우스만 검정을 통해 채택된 확률효과모형으로 분석한 결과 누적일조시간(1월), 평균상대습도(4월), 평균최저기온(6월), 누적강수량(11월) 등이 양파 생산량 예측에 유의한 변수로 나타났다.

가시오가피와 양파 혼합 추출물이 Collagen 유발 관절염에 미치는 영향 (Effects of Acanthopanax Senticosus and Onion Mixture Extract on the Collagen-induced Arthritis in Rat Model)

  • 김경윤;심기철;김계엽;최찬헌;정재곤;정재선;정현우
    • 동의생리병리학회지
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    • 제25권6호
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    • pp.1000-1007
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    • 2011
  • This study was conducted to determine the analgesic effect of onion and acanthopanax senticosus mixture extract using the rheumatoid arthritis rat model. Rheumatoid arthritis model was made by the intradermal injection of type II collagen emulsified. Rats were divided into four groups: (1) Sham group(n=5), (2) Control group(administered DW 3 $m{\ell}$/1 day after RA induced, n=7), (3) Experimental group I(administered Onion extractor 600 mg/3 $m{\ell}$/1 day after RA induced, n=7). (4) Experimental group III(administered Onion and Acanthopanax senticosus mixture extractor 600 mg/3 $m{\ell}$/1 day after RA induced, n=7). After that, we examined the arthritic index, paw edema, pain threshold at 1st, 14th, 28th days. And also we examined histopathologic study(safranin-O green), immunohistochamical stain(COX-2) of knee joint at 28th days. Arthritic index, paw edema and pain threshold test were decrease in experimental group I, II than control group. Especially group II was most significantly inhibit effect than the other groups at 28th days. On the histopathologic view, all experimental groups were relieved and reproduced the erosion of arthritic site compared with control group. All experimental groups were COX-2 positive cells in the immunohistological stain of the knee joint were significantly decreased compared with control group. Especially group II was most significantly decreased than the other groups at 28th days. Onion and Acanthopanax senticosus mixture extractor can be used for curing rheumatoid arthritis. Anti-inflammatory effects may be somewhat better in combination of Onion and Acanthopanax senticosus.

Monitoring Onion Growth using UAV NDVI and Meteorological Factors

  • Na, Sang-Il;Park, Chan-Won;So, Kyu-Ho;Park, Jae-Moon;Lee, Kyung-Do
    • 한국토양비료학회지
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    • 제50권4호
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    • pp.306-317
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    • 2017
  • Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.