• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.858-860
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• 2019

본 논문에서 우리는 범함수 회귀모형을 이용한 양파의 성장단계별 무게를 예측할 수 있는 새로운 통계적 추정방법을 제안한다. 여기서 우리는 풍속, 평균온도, 강우량, 일조량 그리고 습도 등 나타내는 환경요인들을 설명변수들로 사용하고, 양파의 성장단계별 무게를 반응변수로 사용하여 범함수 회귀모형을 적용하였다. 먼저 그래프분석과 상관분석을 통하여 우리는 일일 평균온도는 양파의 무게 증진에 가장 큰 양의상관이 있고, 풍속이나 습도 그리고 일조량들은 양파의 성장에 약간의 영향력이 있으며 강우량은 양파의 성장에 전혀 도움이 안됨을 알 수 있었다. 두 번째로 범함수 회귀 분석을 통하여 얻어진 각 환경요인들에 대한 회귀계수들의 그림을 통하여 우리는 양파의 성장 기간 동안에 이들의 무게를 향상시키기 위해서는 어떻게 환경요인들을 관리해야 되는 가를 알 수 있는 재배방법을 유도하였다.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.873-885
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• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.233-238
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• 2020

Process-based model (PBM), based on the interactions between endogenous physiological processes and many environmental factors, can be a powerful tool for estimating crop growth and productivity. Carbon acquisition and biomass accumulation are the main components in PBM, so it has become important to understand and integrate gas exchange process in crop model. This study aimed to assess the applicability of FvCB model (a leaf model of C3 photosynthesis proposed by Farquhar, von C aemmerer, and Berry (1980)) in onion (Allium cepa L.). For parameterization, two early-maturing onion cultivars, 'Singsingball' and 'Thunderball', grown in a temperature gradient plastic film house, were used in measuring leaf net CO2 assimilation rate (A), and then, parameter estimation was carried out for four parameters including Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), TPU (rate of triose phosphate utilization), and Rd (Dark respiration rate). The gas-exchange model calibrated in this research is expected to be able to explain the photosynthetic responses of onion under various environmental conditions (R2=0.95***).

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.647-659
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• 2017

Garlic and onion are grown in major cultivation regions that depend on the crop condition and the meteorology of the production area. Therefore, when yields are to be predicted, it is reasonable to use a statistical model in which both the crop and the meteorological elements are considered. In this paper, using a multiple linear regression model, we predicted garlic and onion yields in major cultivation regions. We used the MODIS NDVI that reflects the crop conditions, and six meteorological elements for 7 major cultivation regions from 2006 to 2015. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, the MODIS NDVI in February was chosen the significant independent variable of the garlic and onion yield prediction model. In the case of meteorological elements, the garlic yield prediction model were the mean temperature (March), the rainfall (November, March), the relative humidity (April), and the duration time of sunshine (April, May). Also, the rainfall (November), the duration time of sunshine (January), the relative humidity (April), and the minimum temperature (June) were chosen among the variables as the significant meteorological elements of the onion yield prediction model. MODIS NDVI and meteorological elements in the model explain 84.4%, 75.9% of the garlic and onion with a root mean square error (RMSE) of 42.57 kg/10a, 340.29 kg/10a. These lead to the result that the characteristics of variations in garlic and onion growth according to MODIS NDVI and other meteorological elements were well reflected in the model.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.763-776
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• 2020

Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1103-1115
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• 2012

In this study, we studied the effect of onion on hyperlipidemia in terms of factors, such as body weight, liver weight, kidney weight, heart weight, blood glucose, total cholesterol, triglycerides, HDL-cholesterol, and LDL-cholesterol. The hyperlipidemia supplement was significantly effective on the liver weight, kidney weight, blood glucose, total cholesterol, triglycerides, and LDL-cholesterol with the fixed effect model. However, the liver weight, blood glucose, total cholesterol, and triglycerides were significantly decreased with the random effect model on the heterogeneous factors selected by Galbraith plot. The existence of publication bias was checked by using a funnel plot.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.440-447
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• 2020

The purpose of this study is to identify the causation and variation among the various types of onion prices in the major production sites to predict these prices. The Granger causal relationship was tested on the basis of VECM by setting the onion price of the early, middle, and late species as individual variables. The analysis shows that the amount of onions produced in the prior term affects the price of onions for the later period, while garlic in the substitution relationship with onions also affects the prices of onions for the early and middle-variety. On the other hand, the price of the late-variety is affected by the price of the early-variety, and the price of the middle-variety is also affected by the price of the early-variety. If the price of onions on Jeju changes due to other factors, the prices of onions in Jeollanam-do and Gyeongsangnam-do provinces will be affected. Accordingly, when the production of late-variety increases or decreases in production under any factor and to promote stability of the prices of middle and late-variety through preemptive supply and demand measures when the prices of ultra-breed onions rise or fall due to any factor (Ed- I cannot understand this last sentence and cannot guess at the correct meaning. Please try to rewrite very simply).

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2917-2932
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• 2018

Many researches are accomplished as a result of the efforts of developing the production predicting model to solve the supply imbalance of onions which are vegetables very closely related to Korean food. But considering the possibility of storing onions, it is very difficult to solve the supply imbalance of onions only with predicting the production. So, this paper's purpose is trying to build a sentiment dictionary to predict the price of onions by using the internet articles which include the informations about the production of onions and various factors of the price, and these articles are very easy to access on our daily lives. Articles about onions are from 2012 to 2016, using TF-IDF for comparing with four kinds of TF-IDFs through the documents classification of wholesale prices of onions. As a result of classifying the positive/negative words for price by k-means clustering, DBSCAN (density based spatial cluster application with noise) clustering, GMM (Gaussian mixture model) clustering which are partitional clustering, GMM clustering is composed with three meaningful dictionaries. To compare the reasonability of these built dictionary, applying classified articles about the rise and drop of the price on logistic regression, and it shows 85.7% accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.1-14
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• 2021

Onions are a representative produce that requires supply-demand control measures due to large fluctuations in production and price by growing season. Accurate forecasts of crop production can improve the effectiveness of such measures. However, it is challenging to obtain accurate estimates of crop productivity for onions because they are mainly grown on the open fields. The objective of this study was to perform the empirical analysis of the relationship between factors for crop growth and meteorological conditions, which can support the development of models to predict crop growth and production. The growth survey data were collected from open fields. The survey data included the weight of above ground organs as well as that of the bulbs. The estimates of meteorological data were also compiled for the given fields. Correlation analysis between these factors was performed. The random forest was also used to compare the importance of the meteorological factors by the growth stage. Our results indicated that insolation in early March had a positive effect on the growth of the above-ground. There was a negative correlation between precipitation and the growth of the above-ground at the end of March although it has been suggested that drought can deter the growth of onion. The negative effects of precipitation and daylight hours on the growth of the above-ground and under-ground were significant during the harvest period. These meteorological factors identified by growth stage can be used to develop models for onion growth and production forecast.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.57-63
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• 2016

The purpose of this study is to draw implications about a practice of university faculty member's teaching reflection by considering the concept, process, and content of reflection as a theoretical basis of teaching reflection. The concept of reflection is based upon 'reflection-in-action' suggested by $Sch{\ddot{o}}n$, and the process and content of reflection is explained through Korthagen's Core Reflection model. The following three implications conclude: First, a faculty member should write a reflection journal by observing and reflecting consistently one's own behavior in a context of teaching. Second, the center for teaching and learning should provide an orientation and consultation about the content and process of teaching reflection. Finally, sharing lessons with the colleague faculty member is required to make an effective reflection for each faculty member.