This research is about visualizing data for efficient use in agriculture, by measuring the understanding of graphs according to their features. A questionnaire consisting of one graph, either a bar graph or line graph, and a question about data, was made. According to the results, the time spent answering the question did not differ between the line graph and the bar graph. However, the rate of correct answers differed: that of the bar graph was 50% and the line graph was 0%. This implies that participants answered using the bar graph more accurately regarding whether the data involved understanding the absolute value. From this result, it is clear that using proper features of graphs according to the characteristics of data improves the understanding of information. In addition, a strategy to utilize information and communication technology in agriculture effectively was discussed.

In several industries, including the agriculture industry, information and communication technology (ICT) expenditure has been gradually increasing. This study explores the ICT investment of Korean agricultural corporations, and examines the effect of ICT investment on their profitability using an IT portfolio framework. As the organizational capabilities and environment in which ICT is used is critical in examining its impact, the IT-savvy level is used as a moderator. An increase in ICT investment size results in a significantly positive effect on profitability in organizations with higher IT-savvy levels, whereas there is no effect in organizations with lower IT-savvy levels. This study shows the necessity of understanding the structure of ICT investments in the agriculture industry, and suggests the importance of organizational capabilities and environment in making best use of ICT.

Since 2000s, proper utilization of IoT (Internet of Things) technology is a key factor for a firm to become more competitive, and this stream is not exceptional for the food and agriculture industry. Along with this stream, Korea government organization, for example MAFRA (Ministry of Agriculture, Food and Rural Affairs), elected to adopt IoT technology, such as USN and RFID technologies, in the food and agriculture industry. Based on the IoT technology, MAFARA launched six “IoT based farm” project in 2007. IoT based farm project includes IoT based greenhouse system project, and it shows drastic efficiency in terms of cost reduction. When it comes to the productivity, however, the effect of IoT based greenhouse system is still ambiguous. In this regard, this study conducted systems analysis and design for IoT based tomato greenhouse in order to help farmers’ decision making related to the productivity by establishing standardized database structure and designing output form to analyze productivity indices. Proposed systems analysis and design can be utilized as a data analysis tools by farmers. Productivity data from the proposed systems is can be used by researchers to identify the relationship among environment, plant growth and productivity. Policy makers also can refer to the data and output forms to predict the quantity of fruit during certain period and to revise production guideline more precisely.