Potassium Physiology of Upland Crops (밭 작물(作物)의 가리(加里) 생리(生理))
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- Korean Journal of Soil Science and Fertilizer
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- v.10 no.3
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- pp.103-134
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- 1977
The physiological and biochemical role of potassium for upland crops according to recent research reports and the nutritional status of potassium in Korea were reviewed. Since physical and chemical characteristics of potassium ion are different from those of sodium, potassium can not completely be replaced by sodium and replacement must be limited to minimum possible functional area. Specific roles of potassium seem to keep fine structure of biological membranes such as thylacoid membrane of chloroplast in the most efficient form and to be allosteric effector and conformation controller of various enzymes principally in carbohydrate and protein metabolism. Potassium is essential to improve the efficiency of phoro- and oxidative- phosphorylation and involve deeply in all energy required metabolisms especially synthesis of organic matter and their translocation. Potassium has many important, physiological functions such as maintenance of osmotic pressure and optimum hydration of cell colloids, consequently uptake and translocation of water resulting in higher water use efficiency and of better subcellular environment for various physiological and biochemical activities. Potassium affects uptake and translocation of mineral nutrients and quality of products. potassium itself in products may become a quality criteria due to potassium essentiality for human beings. Potassium uptake is greatly decreased by low temperature and controlled by unknown feed back mechanism of potassium in plants. Thus the luxury absorption should be reconsidered. Total potassium content of upland soil in Korea is about 3% but the exchangeable one is about 0.3 me/100g soil. All upland crops require much potassium probably due to freezing and cold weather and also due to wet damage and drought caused by uneven rainfall pattern. In barley, potassium should be high at just before freezing and just after thawing and move into grain from heading for higher yield. Use efficiency of potassium was 27% for barley and 58% in old uplands, 46% in newly opened hilly lands for soybean. Soybean plant showed potassium deficiency symptom in various fields especially in newly opened hilly lands. Potassium criteria for normal growth appear 2%
The air pollutants can be classified into the irritant gas and the asphixation gas, and the irritant gas is closely related to the otorhinolaryngological diseases. The common irritant gases are nitrogen oxides, sulfur oxides, hydrogen carbon compounds, and the potent and irritating PAN (peroxy acyl nitrate) which is secondarily liberated from photosynthesis. Those gases adhers to the mucous membrane to result in ulceration and secondary infection due to their potent oxidizing power. 1. Sulfur dioxide gas Sulfur dioxide gas has the typical characteristics of the air pollutants. Because of its high solubility it gets easily absorbed in the respiratory tract, when the symptoms and signs by irritation become manifested initially and later the resistance in the respiratory tract brings central about pulmonary edema and respiratory paralysis of origin. Chronic exposure to the gas leads to rhinitis, pharyngitis, laryngitis, and olfactory or gustatory disturbances. 2. Carbon monoxide Toxicity of carbon monoxide is due to its deprivation of the oxygen carrying capacity of the hemoglobin. The degree of the carbon monoxide intoxication varies according to its concentration and the duration of inhalation. It starts with headache, vertigo, nausea, vomiting and tinnitus, which can progress to respiratory difficulty, muscular laxity, syncope, and coma leading to death. 3. Nitrogen dioxide Nitrogen dioxide causes respiratory disturbances by formation of methemoglobin. In acute poisoning, it can cause pulmonary congestion, pulmonary edema, bronchitis, and pneumonia due to its strong irritation on the eyes and the nose. In chronic poisoning, it causes chronic pulmonary fibrosis and pulmonary edema. 4. Ozone It has offending irritating odor, and causes dryness of na sopharyngolaryngeal mucosa, headache and depressed pulmonary function which may eventually lead to pulmonary congestion or edema. 5. Smog The most outstanding incident of the smog occurred in London from December 5 through 8, 1952, because of which the mortality of the respiratory diseases increased fourfold. The smog was thought to be due to the smoke produced by incomplete combustion and its byproduct the sulfur oxides, and the dust was thought to play the secondary role. In new sense, hazardous is the photochemical smog which is produced by combination of light energy and the hydrocarbons and oxidant in the air. The Yonsei University Institute for Environmental :pollution Research launched a project to determine the relationship between the pollution and the medical, ophthalmological and rhinopharyngological disorders. The students (469) of the "S" Technical School in the most heavily polluted area in Pusan (Uham Dong district) were compared with those (345) of "K" High School in the less polluted area. The investigated group had those with subjective symptoms twice as much as the control group, 22.6% (106) in investigated group and 11.3% (39) in the control group. Among those symptomatic students of the investigated group. There were 29 with respiratory symptoms (29%), 22 with eye symptoms (21%), 50 with stuffy nose and rhinorrhea (47%), and 5 with sore thorat (5%), which revealed that more than half the students (52%) had subjective symptoms of the rhinopharyngological aspects. Physical examination revealed that the investigated group had more number of students with signs than those of the control group by 10%, 180 (38.4%) versus 99 (28.8%). Among the preceding 180 students of the investigated group, there were 8 with eye diseases (44%), 1 with respiratory disease (0.6%), 97 with rhinitis (54%), and 74 with pharyngotonsillitis (41%) which means that 95% of them had rharygoical diseases. The preceding data revealed that the otolaryngological diseases are conspicuously outnumbered in the heavily polluted area, and that there must be very close relationship between the air pollution and the otolaryngological diseases, and the anti-pollution measure is urgently needed.
Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.
To obtain useful fundamental informations for improving cultural practices of barley, an investigation was made on the influences of different fertilizer level and seeding rate as well as seeding date on yield and yield components and their balancing procedure using barley variety Suwon # 18, and at the same time, 8 varieties including Suwon # 18 were also tested to clarify the varietal responses in terms of their yield and yield components under different seeding date at Crop Experiment Station, Suwon, during the period of 1969 and 1970. The results obtained were summarized as follows; 1. Days to emergence of barley variety Suwon # 18 at Suwon, took 8 to 19 days in accordance with given different seeding date (from Sept. 21 to Oct. 31). Earlier emergence was observed by early seeding and most of the seeds were emerged at 15