• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.358-383
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• 2015

The concept of 'carbon footprint' has been developed as a means of quantifying the specific emissions of the greenhouse gases (GHGs) that cause global warming. Although there are still neither clear definitions of the term nor rules for units or the scope of its estimation, it is broadly accepted that the carbon footprint is the total amount of GHGs, expressed as $CO_2$ equivalents, emitted into the atmosphere directly or indirectly at all processes of the production by an individual or organization. According to the ISO/TS 14067, the carbon footprint of a product is calculated by multiplying the units of activity of processes that emit GHGs by emission factor of the processes, and by summing them up. Based on this, 'carbon labelling' system has been implemented in various ways over the world to provide consumers the opportunities of comparison and choice, and to encourage voluntary activities of producers to reduce GHG emissions. In the agricultural sector, as a judgment basis to help purchaser with ethical consumption, 'low-carbon agricultural and livestock products certification' system is expected to have more utilization value. In this process, the 'cradle to gate' approach (which excludes stages for usage and disposal) is mainly used to set the boundaries of the life cycle assessment for agricultural products. The estimation of carbon footprint for the entire agricultural and forestry sector should take both removals and emissions into account in the "National Greenhouse Gas Inventory Report". The carbon accumulation in the biomass of perennial trees in cropland should be considered also to reduce the total GHG emissions. In order to accomplish this, tower-based flux measurements can be used, which provide a direct quantification of $CO_2$ exchange during the entire life cycle. Carbon footprint information can be combined with other indicators to develop more holistic assessment indicators for sustainable agricultural and forestry ecosystems.

• Journal of Distribution Science
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• v.10 no.7
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• pp.33-41
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• 2012

The purpose of this study is to analyse the state of the energy industry and to determine the efficiency of its functioning on the basis of energy conservation principle and application of innovative technologies aimed at improving the ecological modernisation of agricultural sectors of Kazakhstan. The research methodology is based on an integrated approach of financial and economic evaluation of the effectiveness of the investment project, based on calculation of elasticity, total costs and profitability, as well as on comparative, graphical and system analysis. The current stage is characterised by widely spread restructuring processes of electric power industry in many countries through introduction of new technical installations of energy facilities and increased government regulation in order to enhance the competitive advantage of electricity market. Electric power industry features a considerable value of creating areas. For example, by providing scientific and technical progress, it crucially affects not only the development but also the territorial organisation of productive forces, first of all the industry. In modern life, more than 90% of electricity and heat is obtained by Kazakhstan's economy by consuming non-renewable energy resources: different types of coal, oil shale, oil, natural gas and peat. Therefore, it is significant to ensure energy security, as the country faces a rapid fall back to mono-gas structure of fuel and energy balance. However, energy resources in Kazakhstan are spread very unevenly. Its main supplies are concentrated in northern and central parts of the republic, and the majority of consumers of electrical power live in the southern and western areas of the country. However, energy plays an important role in the economy of industrial production and to a large extent determines the level of competitive advantage, which is a promising condition for implementation of energy-saving and environmentally friendly technologies. In these circumstances, issues of modernisation and reforms of this sector in Kazakhstan gain more and more importance, which can be seen in the example of economically sustainable solutions of a large local monopoly company, significant savings in capital investment and efficiency of implementation of an investment project. A major disadvantage of development of electricity distribution companies is the prevalence of very high moral and physical amortisation of equipment, reaching almost 70-80%, which significantly increases the operating costs. For example, while an investment of 12 billion tenge was planned in 2009 in this branch, in 2012 it is planned to invest more than 17 billion. Obviously, despite the absolute increase, the rate of investment is still quite low, as the total demand in this area is at least more than 250 billion tenge. In addition, industrial infrastructure, including the objects of Kazakhstan electric power industry, have a tangible adverse impact on the environment. Thus, since there is a large number of various power projects that are sources of electromagnetic radiation, the environment is deteriorated. Hence, there is a need to optimise the efficiency of the organisation and management of production activities of energy companies, to create and implement new technologies, to ensure safe production and provide solutions to various environmental aspects. These are key strategic factors to ensure success of the modern energy sector of Kazakhstan. The contribution of authors in developing the scope of this subject is explained by the fact that there was not enough research in the energy sector, especially in the view of ecological modernisation. This work differs from similar works in Kazakhstan in the way that the proposed method of investment project calculation takes into account the time factor, which compares the current and future value of profit from the implementation of innovative equipment that helps to bring it to actual practise. The feasibility of writing this article lies in the need of forming a public policy in the industrial sector, including optimising the structure of energy disbursing rate, which complies with the terms of future modernised development of the domestic energy sector.

• Korean Journal of Ecology and Environment
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• v.43 no.2
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• pp.279-287
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• 2010

This study was to evaluate ecological conditions of Hyeongsan River watershed from April to September 2009. The ecological health assessments was based on Qualitative Habitat Evaluation Index (QHEI), water chemistry during 2000~2009, and the fish multi-metric model, Index of Biological Integrity (IBI). For the study, the models of IBI and QHEI were modified as 8 and 11 metric attributes, respectively. Values of IBI averaged 25.4 (n=6), which is judged as a "fair" condition (C) after the criteria of Barbour et al. (1999). The distinct spatial variation was found in the IBI. Physical habitat health, based on the values of QHEI, varied from 76 in the downriver (H6) to 150.5 in the headwater (H1) and was evidently more disturbed in the downriver reach. Values of BOD and COD averaged 2.4 $mgL^{-1}$ (range: 0.3~13.8 $mgL^{-1}$) and 4.3 $mgL^{-1}$ (scope: 0.6~12.8 $mgL^{-1}$), respectively during the study period. Total nitrogen (TN) and total phosphorus (TP) averaged 3.0 $mgL^{-1}$ and 103.5 ${\mu}gL^{-1}$, respectively, indicating a severe eutrophication, and the nutrients increased more in the downriver than the headwater. Overall, physical, chemical and IBI parameters showed a typical downriver degradation along main axis of the river from the headwater-to-the downriver. This was mainly attributed to livestock waste and residential influences along with industrial discharge from the urban region.

• Journal of Korean Home Economics Education Association
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• v.32 no.4
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• pp.81-101
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• 2020

The purpose of this study is to develop and implement a process-based evaluation program with the theme of school space design in the housing area of the middle school home economics. In order to achieve For thispurpose, a process-based evaluation program based on the theme of school space design was developed following the ADDIE instructional design model, and the program was executed to a total of 93 students. A questionnaire survey and in-depth interview were conducted for the evaluation of the program. The results of this study are as follows. First, based on the results of a 2015-Revised Curriculum analysis, a school space design program evaluation plan was established, and two evaluation tasks were developed. Accordingly, scoring criteria were prepared and 8 evaluation materials for students and 2 evaluation materials for teachers were developed. A total of 9 sessions were developed for teaching and learning activities and evaluation-linked operation procedures to perform evaluation tasks. As a result of an expert validity test for the program, all items were verified to be appropriate in content validity and content composition with an average of 3.6 to 4 points (4 points). Second, after conducting the school space design program, a survey on students were conducted, and as a result, all three areas of school space design class, process-based evaluation, interest scored high in average scores of 4.12 to 4.27 out of 5. According to the survey and interview results, the program provided new learning opportunities for school space design, the students were able to reach the suggested achievement goals, and the self-assessment, peer evaluation and teacher feedback positively affected the students during the learning process so that they could reflect on their learning and actively participate in the subsequent learning activity. This study has a limitation in generalizability in that the program was conducted on a limited number of students, and future studies are expected to expand the scope in terms of research participants, evaluation criteria, and school space design classes. This study laid the foundation for theory and practice by developing and implementing a process-based evaluation program for home economics education, and it has contribution in that it suggested the possibility that teachers and students can take the initiatives in school space design, focusing on the housing content elements of home economics.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.3
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• pp.285-299
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• 2022

The aim of this study is to investigate the awareness and perception of pediatric dentists regarding dental health insurance (DHI) system in Korea. Online surveys were sent to the members of the Korean Academy of Pediatric Dentistry (KAPD), and the responses were collected. The survey, consisting of 41 questions, was subdivided into 'general background of the respondents', 'the awareness on national health insurance (NHI) and DHI', 'the awareness on DHI pertaining to pediatric dentistry', 'issues that need improvement on DHI pertaining to pediatric dentistry', 'DHI claims', and 'the roles of KAPD in DHI'. In total, 302 responded, with a response rate of 28.9%. Excluding 2 questionnaires with insufficient answers, a total of 300 survey results were analyzed. According to the analysis, pediatric dentists thought that the coverage of DHI was not as sufficient compared to that of NHI, but were expecting its scope to broaden in the future. The satisfaction rate was higher in pit and fissure sealant and composite resin filling than in caries-detecting quantitative light-induced fluorescence. Pediatric dentists considered permanent tooth composite resin filling (65.7%) needed an increase in insurance copayment, while topical fluoride application (74.7%) to require insurance coverage. DHI claims were generally handled by dental hygienists and/or nursing assistants. Approximately half of the respondents answered that they have had experiences on appealing for insurance denials. Lastly, pediatric dentists generally had a positive attitude towards providing information for the DHI. This study is expected to be used as a sound dataset for the DHI policy development concerning pediatric dentistry.

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.59-69
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• 2023

FIDIC White Book is a Model Services Agreement between the Client and the Consultant. This study aimed to derive the Key Risk Sub-Clauses out of 63 Sub-Clauses of General Conditions of the FIDIC White Book by using the Delphi technique. A panel of 40 experts with more than 10 years of experience and expertise in overseas construction services agreements and FIDIC White Book was formed, and the reliability was improved in the direction of increasing the consensus of experts through a total of three Delphi survey processes. In the first Delphi survey, a closed-type survey was conducted on the impact of risk among 63 Sub-Clauses of General Conditions on a Likert 5-point scale, and 26 main risk Sub-Clauses were derived. The Content Validity of the results of the first Delphi survey was verified with the CVR value. In the 2nd and 3rd Delphi surveys, a closed-type survey was conducted on a Likert 10-point scale for 26 main risk Sub-Clauses and the risk possibility and impact of each main risk Sub-Clause were evaluated. The reliability of the 3rd Delphi survey result was verified with the COV value. Total 14 Key Risk Sub-Clauses were derived by applying the average risk possibility and impact of each of the 26 main risk Sub-Clauses to the PI Risk Matrix. The results of deriving Key Risk Sub-Clauses showed that agreement on specific scope of service, delay management, and change management were the most important. As a result of this study, from a practical point of view, consultants of consulting companies provide guidelines that should be reviewed to minimize contractual risks when signing service contracts with clients. From an academic point of view, the direction of research on deriving key risks related to service contracts for consultants participating in overseas construction is presented.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Restorative Dentistry and Endodontics
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• v.25 no.3
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• pp.390-398
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• 2000

The purpose of this study was to evaluate the apical fitness of non-standardized gutta-percha cones in root canals prepared with rotary Ni-Ti root canal instruments of various tapers and apical tip sizes. Simulated sixty curved root canals of plastic blocks were prepared with crown-down technique using rotary root canal instruments of Maillefer ProFile$^{(R)}$ .04 and .06 taper (Maillefer Instrument SA, Switzerland). Specimens were divided into six groups and prepared as follows: Group 1, prepared up to size 25 of .04 taper ; Group 2, prepared up to size 30 of .04 taper ; Group 3, prepared up to size 35 of .04 taper ; Group 4, prepared up to size 25 of .06 taper ; Group 5, prepared up to size 30 of .06 taper ; Group 6 ; prepared up to size 35 of .06 taper. After cutting off the coronal portion of plastic, blocks perpendicular to the long axis of the canal with the use of a diamond saw, apical 5mm of canal space was analyzed. Prepared apical canal spaces were duplicated using rubber base impression material to evaluate two dimensional total area of apical canal space. Various sized gutta-percha cones were applied in the 5mm-apical canal space, which were size 25, size 30 and size 35 standardized gutta-percha cone, Diadent Dia-Pro ISO-.04$^{TM}$ and .06$^{TM}$(Diadent, Korea), and medium-fine (MF), fine (F), fine-medium (FM) and medium (M) sized non-standardized gutta-percha cones (Diadent, Korea). Coronal excess gutta-percha were cut off with a sharp blade. Photographs of impressed apical canal spaces and gutta-percha cones were taken with a CCD camera under a stereomicroscope and stored in a computer. Areas of the total canal space and gutta-percha cones were calculated using a digitalized image analysing program, CompuScope (Sungjin Multimedia Co., Korea). Ratio of apical fitness was obtained by calculating the area of gutta-percha cone to the total area of the canal space. The data were analysed statistically using One-way Analysis of Variance and Duncan's Multiple Range Test. The results were as follows: 1. In canals prepared up to size 25 ProFile$^{(R)}$ of .04 taper, non-standardized MF and F cones occupied significantly more canal space than Dia-Pro ISO-.04$^{TM}$ or size 25 standardized ones (p<0.05). 2. In canals prepared up to size 30 ProFile$^{(R)}$ of .04 taper, non-standardized F cones occupied significantly more canal space than Dia-Pro ISO-.04$^{TM}$ or size 30 standardized ones (p<0.05), and non-standardized MF cones occupied more canal space than size 30 standardized ones (p<0.05). 3. In canals prepared up to size 35 ProFile$^{(R)}$ of .04 taper, there was no significant difference in canal space occupation among non-standardized MF and F, size 35 standardized, and Dia-Pro ISO-.04$^{TM}$ cones (p>0.05). 4. In canals prepared up to size 25 ProFile$^{(R)}$ of .06 taper, non-standardized MF and F cones occupied significantly more canal space than Dia-Pro ISO-.06$^{TM}$, or size 25 standardized ones (p<0.05), and Dia-Pro ISO-.06$^{TM}$, cones occupied significantly more space than size 25 standardized ones (p<0.05). 5. In canals prepared up to size 30 ProFile$^{(R)}$ of .06 taper, non-standardized FM cones occupied significantly more canal space than Dia-Pro ISO-.06$^{TM}$ or size 30 standardized ones (p<0.05), and non-standardized F cones occupied significantly more canal space than size 30 standardized ones (p<0.05). 6. In canals prepared up to size 35 ProFile$^{(R)}$ of .06 taper, non-standardized M and FM, Dia-Pro ISO-.06$^{TM}$ occupied significantly more canal space than size 35 standardized ones (p<0.05). In summary, in both canals prepared with .04 or .06 taper ProFile$^{(R)}$, non-standardized cones showed better fitness than Dia-Pro ISO$^{TM}$ or standardized ones, which was more characteristic in smaller canals.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Horticultural Science & Technology
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• v.29 no.5
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• pp.389-406
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• 2011

As part of a feasibility study for introducing carbon labeling of fruit products in Korea, we explore the use of carbon footprints for Korean kiwifruit from Gyeongnam region as a case study. In Korea, the Korean Environmental Industry and Technology Institute (KEITI) is responsible for the carbon footprint labeling certification, and has two types of certification programs: one program focuses on climate change response (carbon footprint labeling analysis) and the other on low-carbon products (reduction of carbon footprints analysis). Currently agricultural products have not yet been included in the program. Carbon labeling could soon be a prerequisite for the international trading of agricultural products. In general the carbon footprints of various agricultural products from New Zealand followed the methodology described in the ISO standards and conformed to the PAS 2050. The carbon footprint assessment focuses on a supply chain, and considers the foreground and the background systems. The basic scheme consists of four phases, which are the 'goal', 'scope', 'inventory analysis', and 'interpretation' phases. In the case of the carbon footprint of New Zealand kiwifruit the study tried to understand each phase's contribution to total GHG emissions. According to the results, shipping, orchard, and coolstore operation are the main life cycle stages that contribute to the carbon footprint of the kiwifruit supply chain stretching from the orchard in New Zealand to the consumer in the UK. The carbon emission of long-distance transportation such as shipping can be a hot-spot of GHG emissions, but can be balanced out by minimizing the carbon footprint of other life cycle phases. For this reason it is important that orchard and coolstore operations reduce the GHG-intensive inputs such as fuel or electricity to minimize GHG emissions and consequently facilitate the industry to compete in international markets. The carbon footprint labeling guided by international standards should be introduced for fruit products in Korea as soon as possible. The already established LCA methodology of NZ kiwifruit can be applied for fruit products as a case study.