• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.47-62
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• 2021

Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.41-46
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• 2022

This paper proposes a consumer-tailored solution to prevent the forgery and falsification of data by incorporating blockchain technology in the online and offline distribution of agricultural produce. The solution provides customized services to consumers based on an analysis of the data generated from the sales, distribution, and consumption of quality of the produce. It can also ensure the safety and credibility of the produce, and allow producers to identify consumption intent and the flow of distribution. Producers will be able to determine the flow of produce based on the data collected and thus tailor promotional efforts. This is expected to be the fourth industrial revolution in the agricultural produce distribution sector. Utilizing blockchain and big data technology to create integrated record management systems that combine multiple solutions will shape future technology trends. In addition, if eco-friendly certification is acknowledged as a valuable service and can be incorporated into the distribution process, this solution could become a one-stop distribution solution for agricultural produce.

• Magazine of the Korean Society of Agricultural Engineers
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• v.12 no.4
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• pp.2063-2077
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• 1970

The Purpose of this study is to give the hydrologically basic data for the development of water resources in Korea and a quantity of daily average precipitation and its frequency in a year are investigated to study the presumption which is affected to river flow. Characteristics of precipitation is poor as source of water resources compared with its efficiency. So, because of such characteristics of precipitation, river flow also is in harmony and distribution of river flow comes to the result of irregularity, that is, range of river coefficiet between the quantity of maximum river flow and others river flow is big, and it is insufficient as source of water resources. Yearly river flow being expressed by daily unit indicates the ratio(%) of distribution to total yearly river flow, and the model of hydrograph is drawn up. The gives the basis to make yearly water balance sheet. This study is not completed, yet but in forth-coming days, the water will try continuously to give more correct basis for the development of water resources according to a great deal of data.

• Journal of Korean Society of Rural Planning
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• v.10 no.4 s.25
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• pp.1-7
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• 2004

In Korea, rural community has been becomming unstable by declining of agriculture. In order to solve this problem, there were some trials to activate rural communities by maintaining rural amenities. But, it is difficult to use rural amenities as a development factor to promote rural communities because there are few researches about quantifying rural amenities. In this study, a method fer quantifying rural amenities is suggested using database normalization technique. Previous thirty seven surveying items of rural amenity resources are formally reduced to five common surveying items, seven resources, and eleven surveying tables. Finally, big picture of rural amenity resource map with surveying data for rural development is suggested.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.971-978
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• 2022

Fertigation, which has been introduced in agricultural fields since 1990, has been widely practiced in upland fields as well as in plastic film houses as part of the crop production system. In accordance with demands in the agricultural sector, a huge number of scientific studies on fertigation have been conducted worldwide. Moreover, with a combination of advanced technologies such as big-data, machine learning, etc., fertigation is positioned as an indispensable tool to achieve sustainable crop production and to enhance nutrient and water use efficiency. In this review, we focused on providing valuable information in terms of crop production and nutrient/water use efficiency. A variety of fertigation studies have described that enhancement of crop production did not differ relative to conventional method or slightly increased. In contrast, fertigation significantly improved nutrient/water use efficiency, with a reduction in use ranging from 20 to 50%. Water-soluble organic resources such as livestock manure and agricultural byproducts also have been identified as useful resources like chemical fertilizers. Furthermore, the initial irrigation point was generally recommended in a range of -10 - -40 kPa, although the point differed according to the crop and crop growth stage. From this review, we suggest that fertigation, which is closely integrated with advanced technology, could be a leading technology to attain not only food security but also carbon neutrality via improvement of nutrient/water use efficiency.

• Smart Media Journal
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• v.11 no.4
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• pp.19-29
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• 2022

Recently, with the development of IoT technology, the number of farms using smart farms is increasing. Smart farms monitor the environment and optimise internal environment automatically to improve crop yield and quality. For optimized crop cultivation, researches on predict crop productivity are actively studied, by using collected agricultural digital data. However, most of the existing studies are based on statistical models based on existing statistical data, and thus there is a problem with low prediction accuracy. In this paper, we use various predition models for predicting the production and sales profits, and compare the performance results through models by using the agricultural digital data collected in the facility horticultural smart farm. The models that compared the performance are multiple linear regression, support vector machine, artificial neural network, recurrent neural network, LSTM, and ConvLSTM. As a result of performance comparison, ConvLSTM showed the best performance in R2 value and RMSE value.

• Journal of Bio-Environment Control
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• v.23 no.3
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• pp.192-198
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• 2014

To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

• Journal of Animal Science and Technology
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• v.61 no.6
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• pp.324-332
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• 2019

This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass (Lolium multiflorum Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992-2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order (p < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.

• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.57-65
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• 2020

Agricultural research and development (R&D) investment has contributed not only to agriculture but also to the overall economic growth of the country. The recent arrival of the fourth industrial revolution has raised the need for agricultural R&D as a preparation. Agriculture R&D is directly related to the fourth industrial revolution in the agricultural and livestock sectors that utilize big data, robots, artificial intelligence and cloud. Meanwhile, subsidies or grants are considered the most widely used means of policy. Therefore, in light of the current situation in which Chinese agriculture values R&D investment, this study attempted to analyze the dynamic relationship between variables by establishing a model of agricultural environment subsidy representing the role of government, agricultural technology progress representing existing agricultural R&D investment, agricultural income representing agricultural development and total agricultural output. The analysis results showed that each variable's reaction to the rise in China's agricultural R&D investment has a positive effect on agricultural development, in line with the theory that the investment in science and technology in the agricultural sector has a positive effect. In addition, the response of each variable to China's rising agricultural environment subsidy is shown to have a positive relationship, which can also be said to be in line with the theory that the government's market-friendly intervention is beneficial to economic development.

• 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.