Knowledge of the relationship between crop yield and yield-limiting factors is essential for precision farming. However, developing this knowledge is not easy because these yield-limiting factors are interrelated and affect crop yield in different ways. In this study, data for grain yield and yield-limiting factors, including crop chlorophyll content, soil chemical properties, and topography were collected for a small (0.3 ha) rice paddy field in Korea and a large (36 ha) upland corn field in the USA, and relationships were investigated with path analysis. Using this approach, the effects of limiting factors on crop yield could be separated into direct effects and indirect effects acting through other factors. Path analysis provided more insight into these complex relationships than did simple correlation or multiple linear regression analysis. Results of correlation analysis for the rice paddy field showed that EC, Ca, and $SiO_2$ had significant (P<0.1) correlations with rice yield, while pH, Ca, Mg, Na, $SiO_2,\;and\;P_2O_5$ had significant correlations with the SPAD chlorophyll reading. Path analysis provided additional information about the importance and contribution paths of soil variables to rice yield and growth. Ca had the highest direct effect (0.52) and indirect effect via Mg (-0.37) on rice yield. The indirect effect of Mg through Ca (0.51) was higher than the direct effect (-0.38). Path analysis also enabled more appropriate selection of important factors limiting crop yield by considering cause-and-effect relationships among predictor and response variables. For example, although pH showed a positive correlation (r=0.35) with SPAD readings, the correlation was mainly due to the indirect positive effects acting through Mg and $SiO_2$, while pH not only showed negative direct effects, but also negatively impacted indirect effects of other variables on SPAD readings. For the large upland Missouri corn field, two topographic factors, elevation and slope, had significant (P<0.1) direct effects on yield and highly significant (P<0.01) correlations with other limiting factors. Based on the correlation analysis alone, P and K were determined to be nutrients that would increase corn yield for this field. With the help of path analysis, however, increases in Mg could also be expected to increase corn yield in this case. In general, path analysis results were consistent with published optimum ranges of nutrients for rice and com production. We conclude that path analysis can be a useful tool to investigate interrelationships between crop yield and yield limiting factors on a site-specific basis.
Loop-mediated isothermal amplification (LAMP), a PCR-based diagnostic method, is based on autocycling strand displacement DNA synthesis in the presence of exonuclease-negative Bst DNA polymerase under isothermal conditions. With the help of four specific primers that recognize six different sequences of a target DNA, LAMP has high specificity in pathogenic identification in a short time. Hence, in the present study, LAMP is used as a diagnostic tool in the identification of the most dreadful aquatic pathogenic species, Vibrio alginolyticus, and to develop species-specific LAMP primers and optimization of LAMP reaction conditions such as annealing temperature, elongation time, and other PCR chemical concentrations, including MgSO4, dNTPs, Betaine, and Bst polymerase. The optimized LAMP primers were also checked for specificity with other Vibrio species, which showed that the designed primers were very specific to V. alginolyticus After the first introduction of a species name like this one, the first part (“Vibrio” in this case) should be abbreviated to only the first letter.only. These are usually the most harmful pathogens of the Vibrio species that appear in shrimp and crabs. The results also revealed that the LAMP assay could be 10-fold more sensitive than conventional PCR in detecting V. alginolyticus. This could be the first report on using a rapid and highly sensitive technique, the LAMP assay, in the effective diagnosis of the pathogenic bacteria V. alginolyticus, which could help in the early detection of diseases, particularly in aquaculture.
Polycaprolactone (PCL) and biphasic calcium phosphate (BCP) have been considered as useful materials for orthopedic devices and osseous implants because of their biocompatibility and bone-forming activity. However, PCL-based scaffolds have hydrophobic surfaces reducing initial cell adhesion or proliferation. To overcome the limitation, we fabricated surface-modified PCL/BCP nanofibers using gamma-irradiation for bone tissue engineering. PCL/BCP nanofibers were prepared by electrospinning and then we supplemented hydrophilicity by introducing acrylic acid (AAc) through gamma-irradiation. We confirmed the surface of nanofibers by SEM, and then the initial viability of MG63 was significantly increased on the AAc grafted nanofibers, and alkaline phosphatase activity($1.239{\pm}0.226nmole/{\mu}g/min$) improved on the modified nanofibers than that on the non-modified nanofibers($0.590{\pm}0.286nmole/{\mu}g/min$). Therefore, AAc-grafted nanofibers may be a good tool for bone tissue engineering applications.
This study was conducted to figure out the relationships among soil chemical properties and bacterial biomass related to denitrification and sulfur-reducing and the activity of dehydrogenase, and ultimately to consider the usefulness of dehydrogenase activity as a tool for evaluating the dynamics of forest soil ecosystem. Four sites were selected for the collection of soil samples within two regions(Onsan industrial estate as a polluted region and Mt. Mani at Kanghwa island as a clean area) with two forest types (coniferous and deciduous stands). The soils of Mt. Mani showed higher amount of organic matter, total nitrogen and available phosphorus than those collected from Onsan industrial estate, which indicated that the soils were more beneficial for microbial growth than those of Onsan. The dehydrogenase activity was more sensitive than the denitrifying bacteria or sulfur-reducing bacteria since the activity was significantly different between the regions and season while the two bacterial biomass were not significantly different between the two regions. In addition, the dehydrogenase activity showed relatively high correlation coefficients with organic matter(r=0.53, p=0.004), total nitrogen(r=0.41, p=0.008) and C/Ava. P-ratio(r=-0.52, p=0.001), which was thought to be closely related with microbial activity. Thus, the dehydrogenase activity was thought to be a useful index of soil ecosystem dynamics with considering that the technique need to be applied with the same soil texture for the comparison of the activity as other researchers indicated.
This study assessed ecological health using a multi-metric fish model from 15 sites in the headwater watershed of southern Han River during June${\sim}$August 1999 and then compared the health with conventional community diversity index to figure out differences between health and diversity index. For the analysis, we adopted 10 metric IBI model for regional applications. During this survey, total number of species sampled were 24 (6 families) and varied depending on magnitude of ecological disturbance and stream order. In the mountainous streams, mean proportion of sensitive and insectivore species was composed of 91% and 56%, respectively, indicating a potential healthy conditions. However, tolerant species with 66% and omnivore species with 76% were sampled from the 2nd order stream, which was shown deterioration in the physical habitat quality. In the overall watershed, mean IBI value was 38, judging as "fair" condition by the health criteria. Values of Individual IBI were closely associated with stream order and this pattern was similar to other mountainous streams showing low chemical pollutions and disturbance. Our comparison between IBI and diversity index over the stream order showed a distinct difference; Shannon-Weaver diversity index overestimated the actual community conditions and the variation range in the 2nd order stream was greater in the diversity index. Overall data suggest that the multi-metric approach may to a useful tool for stream ecosystem management and the conventional diversity index may not effective unless the stream order is considered for the stream evaluation.
Objectives : The most frequently cited health related slogan in North Korea is that socialistic medicine is preventive medicine. It implies that North Korea puts preventive medicine at the operational center of its national health care system. This study aimed at examining and comparing preventive medicine practices in North Korea with those of South Korea. Methods : Efforts have been made to obtain a textbook for analysis its contents. Many people have iassisted in the study by joining the interview. Some of these people are as follows : a former professor of PyongYang Medical School, NK physicians living in South Korea, WHO staffs, diplomatic officials, etc. The major items of analysis consisted of industrial medicine and hygiene, nutrition, school health, epidemiology, health statistics and heath policy & management. Results : Public health philosophy is finely noted and well integrated in the operation of the North Korean national health care system, particularly in the area of industrial medicine and hygiene. Preventive medicine with a strong health surveillance system spanning a number of broad social organizations is a major tool to improve the health of the people in North Korea. The emphasis on preventive medicine has a close relationship with the 'Juche Philosophy' and the shortage of pharmaceuticals and medical equipment. To cope with the shortage problem, North Korean health workers are encouraged to grow medicinal herbs. We have found that they put little effort into teaching newly emerging diseases, such as AIDS, VDT syndrome, hazards of EMF, and agricultural chemical poisonings. Of the subjects of the preventive medicine text, 78.9% coincide with those of South Korean industrial health manuals and 34.2% with South Korean epidemiology texts. However, an absolute difference was found to exist between the health policies and management systems. Conclusion : In North Korea, the concept of preventive medicine functions as the basic philosophic strategy of the national health care system. It differs greatly from the South Korean system in both practice and educational content. Its contribution to society is simply incomparable to that of South Korea. More communication and further study is called for in order to improve the preventive medicine practices in the future.
A parametric study on pervaporation-facilitated esterification was performed by using a practical model based on non-perfect separation through membrane which is not perfectly permselective to water. Thus, membrane selectivity as well as membrane capability to remove water should be taken into account in establishing the simulation model to explain how the membrane separation influence the esterification reaction process. It was shown by simulation that in the reaction systems with non-perfect separation, the permeation of reactants which are acid or/and alcohol retards the reaction by inducing the backward reaction so that reaction conversion curve is located between a reaction system coupled with pervaporation process having a perfect permselectivity to water and a reaction system without pervaporation process. The volume change of reaction system occurs as a result of the permeation through the membrane. The reaction volume change which can be characterized by the reaction ratio of $r_{\Psi}\;to\;r_{{\Psi}=1}$ affects reaction kinetics by concentrating reactants and products, respectively, with different extent with time; reactant-concentrating effect is dominant during the initial stage of reaction, resulting in facilitating the reaction, and then product-concentrating effect is exerted more on reaction, causing to slow down the reaction. When pervaporative dehydration is applied to the reaction system plays an important role in the reaction as well. The effect of timing to impose pervaporation on reaction system affected the reaction kinetics in terms of reaction rate and reaction conversion. A relationship was derived to explain membrane unit capacity and reaction parameters that will be used as a design tool to determine membrane unit capacity at a given reaction conditions or reaction parameters at a membrane unit capacity.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1244-1244
/
2001
In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1042-1042
/
2001
In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.
Kim, Sung Tae;Lee, Jeong Bin;Kim, Ui Seong;Shin, Chee Burm
Journal of Energy Engineering
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v.22
no.2
/
pp.175-183
/
2013
For the optimal design of the vehicle electric system, it is important to have a reliable modeling tool to predict the dynamic behavior of the automotive battery. In this work, a one-dimensional modeling was carried-out to predict the dynamic behaviors of a 12-V automotive lead-acid battery. The model accounted for electrochemical kinetics and ionic mass transfer in a battery cell. In order to validate the modeling, modeling results were compared with the experiment data of the dynamic behaviors of the lead-acid batteries of two different capacities that were mounted on the automobiles manufactured by Hyundai Motor Company. The discharge behaviors were measured with various discharge rates of C/3, C/5, C/10, C/20 and combination. And dynamic behaviors of charge and discharge were measured. The voltage curves from the experiment and simulation were in good agreement. Based on the modeling, the distributions of the electrical potentials of the solid and solution phases, and the current density within the electrodes could be predicted as a function of charge and discharge time.
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