• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.173-188
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• 2023

This paper analyzed the Earnings management of firms selected as preliminary Unicorn. If a manager is selected as a preliminary unicorn firm, he can receive financial support of up to 20 billion won, creating a factor in managing the manager's earnings. The motive for management's earnings management is related to the capital market. Accounting information is used by investors and financial analysts, and corporate profits affect corporate value. Therefore, if the accounting earning is adjusted upward, the corporate value will be raised and investment conditions will be favorable. In this paper, earnings quality was measured by the modified Jones model of Dechow et al.(1995) by the ROA control model of Kothari et al.(2005) among the discretionary accruals estimated using an alternative accrual prediction model. Competing similar companies in the same market as the selected companies were formed, and the discretionary accruals were mutually compared to verify the research hypotheses, and only the selected companies were analyzed for the audit year and after the audit year. As a result of the analysis, it was found that the companies selected as preliminary unicorns had higher earnings management compared to the corresponding companies in question, which had a negative impact on the quality of accounting profits. It was found that the companies selected as preliminary unicorns continued to receive incentives for management's earnings management even after being selected. These results indicate that the companies selected as prospective unicorns are recognized for their value in the market through external growth rather than internal growth, and thus, incentives for management's earnings management to attract investment from external investors under favorable conditions are continuing. In the future preliminary unicorn selection evaluation, it was possible to present what needs to be reviewed on the quality of accounting earning. The implication of this paper is that the factors of management's earnings management eventually hinder investors and creditors from judging the reliability of accounting information. It was suggested that a policy alternative for the K-Unicorn Project, which enhances reliability were presented by reflecting the evaluation of earnings quality through discretionary accruals.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.4
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• pp.386-408
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• 1988

A study was conducted to develop a model for estimating evapotranspiration and yield of Chinese cabbages from meteorological factors from 1981 to 1986 in Suweon, Korea. Lysimeters with water table maintained at 50cm depth were used to measure the potential evapotranspiration and the maximum evapotranspiration in situ. The actual evapotranspiration and the yield were measured in the field plots irrigated with different soil moisture regimes of -0.2, -0.5, and -1.0 bars, respectively. The soil water content throughout the profile was monitored by a neutron moisture depth gauge and the soil water potentials were measured using gypsum block and tensiometer. The fresh weight of Chinese cabbages at harvest was measured as yield. The data collected in situ were analyzed to obtain parameters related to modeling. The results were summarized as followings: 1. The 5-year mean of potential evapotranspiration (PET) gradually increased from 2.38 mm/day in early April to 3.98 mm/day in mid-June, and thereafter, decreased to 1.06 mm/day in mid-November. The estimated PET by Penman, Radiation or Blanney-Criddle methods were overestimated in comparison with the measured PET, while those by Pan-evaporation method were underestimated. The correlation between the estimated and the measured PET, however, showed high significance except for July and August by Blanney-Criddle method, which implied that the coefficients should be adjusted to the Korean conditions. 2. The meteorological factors which showed hgih correlation with the measured PET were temperature, vapour pressure deficit, sunshine hours, solar radiation and pan-evaporation. Several multiple regression equations using meteorological factors were formulated to estimate PET. The equation with pan-evaporation (Eo) was the simplest but highly accurate. PET = 0.712 + 0.705Eo 3. The crop coefficient of Chinese cabbages (Kc), the ratio of the maximum evapotranspiration (ETm) to PET, ranged from 0.5 to 0.7 at early growth stage and from 0.9 to 1.2 at mid and late growth stages. The regression equation with respect to the growth progress degree (G), ranging from 0.0 at transplanting day to 1.0 at the harvesting day, were: $$Kc=0.598+0.959G-0.501G^2$$ for spring cabbages $$Kc=0.402+1.887G-1.432G^2$$ for autumn cabbages 4. The soil factor (Kf), the ratio of the actual evapotranspiration to the maximum evapotranspiration, showed 1.0 when the available soil water fraction (f) was higher than a threshold value (fp) and decreased linearly with decreasing f below fp. The relationships were: Kf=1.0 for $$f{\geq}fp$$ Kf=a+bf for f$$I{\leq}Esm$$ Es = Esm for I > Esm 6. The model for estimating actual evapotranspiration (ETa) was based on the water balance neglecting capillary rise as: ETa=PET. Kc. Kf+Es 7. The model for estimating relative yield (Y/Ym) was selected among the regression equations with the measured ETa as: Y/Ym=a+bln(ETa) The coefficients and b were 0.07 and 0.73 for spring Chinese cabbages and 0.37 and 0.66 for autumn Chinese cabbages, respectively. 8. The estimated ETa and Y/Ym were compared with the measured values to verify the model established above. The estimated ETa showed disparities within 0.29mm/day for spring Chinese cabbages and 0.19mm/day for autumn Chinese cabbages. The average deviation of the estimated relative yield were 0.14 and 0.09, respectively. 9. The deviations between the estimated values by the model and the actual values obtained from three cropping field experiments after the completion of the model calibration were within reasonable confidence range. Therefore, this model was validated to be used in practical purpose.

• KDI Journal of Economic Policy
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• v.34 no.3
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• pp.95-131
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• 2012

This study examines whether the executive turnover and the executive resignation during the term of office affect the performance of Korean state-owned enterprises. The executive turnover in the paper means the comprehensive change of the executives which includes the change after the term of office, the change after consecutive terms and the change during the term of office. The 'resignation' was named for the executive change during the term of office to distinguish from the executive turnover. The study scope of the paper is restrained to the comprehensive executive change itself irrespective of the term of office and the resignation during the term of office. Therefore the natural change of the executive after the term of office or the change after consecutive terms is not included in the study. Spontaneous resignation and forced resignation are not distinguished in the paper as the distinction between the two is not easy. The paper uses both the margin of return on asset and the margin of return on asset adjusted by industry as proxies of the performance of state-owned enterprises. The business nature of state-owned enterprise is considered in the study, the public nature not in it. The paper uses the five year (2004 to 2008) samples of 24 firms designated as public enterprises by Korean government. The analysis results are as follows. First, 45.1% of CEOs were changed a year during the sample period on the average. The average tenure period of CEOs was 2 years and 3 months and 49.9% among the changed CEOs resigned during the term of office. 41.6% of internal auditors were changed a year on the average. The average tenure period of internal auditors was 2 years and 2 months and 51.0% among the changed internal auditors resigned during the term of office. In case of outside directors, on average, 38.2% were changed a year. The average tenure period was 2 years and 7 months and 25.4% among the changed internal directors resigned during the term of office. These statistics show that numerous CEOs resigned before the finish of the three year term in office. Also, considering the tenure of an internal auditor and an outside director which diminished from 3 years to 2 years by an Act on the Management of Public Institutions (applied to the executives appointed since April 2007), it seems most internal auditors resigned during the term of office but most outside directors resigned after the end of the term. Secondly, There was no evidence that the executives were changed during the term of office because of the bad performance of prior year. On the other hand, contrary to the normal expectation, the performance of prior year of the state-owned enterprise where an outside director resigned during the term of office was significantly higher than that of other state-owned enterprises. It means that the clauses in related laws on the executive dismissal on grounds of bad performance did not work normally. Instead it can be said that the executive change was made by non-economic reasons such as a political motivation. Thirdly, the results from a fixed effect model show there were evidences that performance turned negatively when CEOs or outside directors resigned during the term of office. CEO's resignation during the term of office gave a significantly negative effect on the margin of return on asset. Outside director's resignation during the term of office lowered significantly the margin of return on asset adjusted by industry. These results suggest that the executive's change in Korean state-owned enterprises was not made by objective or economic standards such as management performance assessment and the negative effect on performance of the enterprises was had by the unfaithful obeyance of the legal executive term.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.1-6
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• 2013

This study was aimed to solve the problems of current national genetic evaluation systems in Korea and its development to pass the verification processes as required by International Bull Evaluation Service (Interbull). This will enable Korea to participate in international genetic evaluation program. A total of 1,416,589 test-day milk records with calving dates used in this study were collected by National Agricultural Cooperative Federation from 2001 to 2009. Parity was limited up to fifth calving and milk production records were adjusted to cumulative 305 day lactation. The pedigree consisted of 2,279,741 animals where 2,467 bulls had 535,409 parents. A newly developed multiple trait model was used in calculation of breeding values for milk yield, milk fat, and protein yield. Data were edited with SAS (version 9.2) and R programs, and genetic parameters were estimated using VCE 6.0. Results showed a continuous increase in genetic potentials, in general, and no remarkable differences were found between performances by parity. Except fat yield, potentials in milk yield and protein yield were well calculated. We found an increased number of daughters per each top ranked 1,000 bulls in recent years of calf births compared to the cases of previous evaluations. Of the bulls ranked top 100 by our new models (multiple-trait models) we found that increased numbers of bulls were included. Of twenty eight bulls born in 2006, twenty bulls born in 2007 and eight bulls born in 2008 that were listed by new models, only 23, 12, and 2 bulls born in respective years were represented on top 100 by old single-trait models. Re-ranking of the daughters or sires by multiple-trait models suggest that this new multiple trait approach should be used for dairy cattle genetic evaluation and seed-stock selection in the future to increase the accuracy of multiple trait selection. Breeding values for these traits should also be calculated by new method for international genetic evaluation.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• Journal of dental hygiene science
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• v.14 no.2
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• pp.158-166
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• 2014

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the oral health important cognitive and self-rated oral health status and number of brushing, emphasizing the need for the education of oral health important, providing the basic data in order to accomplish correctly until the enhance of oral health-related quality of the oral health correct behavior. From May to July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of two high school located in Chungcheongnam-do 1, 2 grade. The SPSS PASW Statistics 18.0 and Amos 5.0 program had been used for the statistical data analysis. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral health-related quality of life all showed the significant difference (p<0.001). 3) Oral health-related quality of life was higher as oral health important and self-rated oral health status positive. Furthermore oral health-related quality of life was higher as number of brushing increased; 4) Fit Measures test result of stress, academic level, and family economic level model all showed more than 0.9 in goodness of fit index (GFI), adjusted GFI, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral health-related quality of life.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.8-9
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• 2017

Soybean yield has been low and unstable in Japan and other areas in East Asia, despite long history of cultivation. This is contrasting with consistent increase of yield in North and South America. This presentation tries to describe perspective of breaking stagnation of soybean yield in East Asia, considering the factors of the different yields between regions. Large amount of rainfall with occasional dry-spell in the summer is a nature of monsoon climate and as frequently stated excess water is the factor of low and unstable soybean yield. For example, there exists a great deal of field-to-field variation in yield of 'Tanbaguro' soybean, which is reputed for high market value and thus cultivated intensively and this results in low average yield. According to our field survey, a major portion of yield variation occurs in early growth period. Soybean production on drained paddy fields is also vulnerable to drought stress after flowering. An analysis at the above study site demonstrated a substantial field-to-field variation of canopy transpiration activity in the mid-summer, but the variation of pod-set was not as large as that of early growth. As frequently mentioned by the contest winners of good practice farming, avoidance of excess water problem in the early growth period is of greatest importance. A series of technological development took place in Japan in crop management for stable crop establishment and growth, that includes seed-bed preparation with ridge and/or chisel ploughing, adjustment of seed moisture content, seed treatment with mancozeb+metalaxyl and the water table control system, FOEAS. A unique success is seen in the tidal swamp area in South Sumatra with the Saturated Soil Culture (SSC), which is for managing acidity problem of pyrite soils. In 2016, an average yield of $2.4tha^{-1}$ was recorded for a 450 ha area with SSC (Ghulamahdi 2017, personal communication). This is a sort of raised bed culture and thus the moisture condition is kept markedly stable during growth period. For genetic control, too, many attempts are on-going for better emergence and plant growth after emergence under excess water. There seems to exist two aspects of excess water resistance, one related to phytophthora resistance and the other with better growth under excess water. The improvement for the latter is particularly challenging and genomic approach is expected to be effectively utilized. The crop model simulation would estimate/evaluate the impact of environmental and genetic factors. But comprehensive crop models for soybean are mainly for cultivations on upland fields and crop response to excess water is not fully accounted for. A soybean model for production on drained paddy fields under monsoon climate is demanded to coordinate technological development under changing climate. We recently recognized that the yield potential of recent US cultivars is greater than that of Japanese cultivars and this also may be responsible for different yield trends. Cultivar comparisons proved that higher yields are associated with greater biomass production specifically during early seed filling, in which high and well sustained activity of leaf gas exchange is related. In fact, the leaf stomatal conductance is considered to have been improved during last a couple of decades in the USA through selections for high yield in several crop species. It is suspected that priority to product quality of soybean as food crop, especially large seed size in Japan, did not allow efficient improvement of productivity. We also recently found a substantial variation of yielding performance under an environment of Indonesia among divergent cultivars from tropical and temperate regions through in a part biomass productivity. Gas exchange activity again seems to be involved. Unlike in North America where transpiration adjustment is considered necessary to avoid terminal drought, under the monsoon climate with wet summer plants with higher activity of gas exchange than current level might be advantageous. In order to explore higher or better-adjusted canopy function, the methodological development is demanded for canopy-level evaluation of transpiration activity. The stagnation of soybean yield would be broken through controlling variable water environment and breeding efforts to improve the quality-oriented cultivars for stable and high yield.