• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.2
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• pp.73-80
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• 1993

A simplified physiologically-based dynamic model, SIMRIW was selected for predicting the growth and yield of rice. The applicability of the model to the rice cultivars and weather conditions in the Republic of Korea was evaluated. Parameters of the model were calibrated using actual rice yields in Suweon region and an optimization scheme, Constrained Rosenbrock Algorithm. The simulated results from the calibrated model were in good agreement with the field data. The model with parameters calibrated for Suweon was applied to other five regions for the evaluation of transferability, but the simulated results fell short of satisfaction. However, the model is found to be applied to real-time prediction of the growth and yield of rice crop, which is believed to be useful for timely rice crop management, agricultural policy making, and optimal irrigation water management.

• Journal of Plant Biotechnology
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• v.49 no.4
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• pp.356-361
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• 2022

Bacillus sp. is a useful strain for agriculture because it promotes plant growth and controls plant pathogens through a variety of mechanisms. In this study, we obtained a microbial preparation with a high number of viable cells by culturing newly isolated soil bacteria on an optimized medium. Subsequently, we applied this preparation to lettuce to enhance its growth and yield. First, B. amyloliquefaciens ISP-5 was isolated from soil. Next, optimization of culture medium was carried out using 5 L scale fermenters. When culturing B. amyloliquefaciens ISP-5 on this optimized medium, the number of viable cells was approximately 1000 times higher than that obtained from culturing on the commercial medium. Afterwards, the plant growth promotion properties of the ISP-5 strain were evaluated using lettuce as a test plant. Foliar spray treatment of lettuce was carried out by inoculating half the standard concentration suspension (0.5 × 10⁷ cfu/ml). As a result, leaf width increased by 8.6% and leaf length increased by 12.9% compared to the control group. Live weight also increased by 24.2% and dry weight by 23.9%. Considering the results from field test, B. amyloliquefaciens ISP-5 showed potential as a plant growth-promoting bacteria.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.398-406
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• 2011

In this paper, we introduce a new architecture of PSO-based Polynomial Neural Networks (PNN) and discuss its comprehensive design methodology. The conventional PNN is based on a extended Group Method of Data Handling (GMDH) method, and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons located in each layer through a growth process of the network. Moreover it does not guarantee that the conventional PNN generated through learning results in the optimal network architecture. The PSO-based PNN results in a structurally optimized structure and comes with a higher level of flexibility that the one encountered in the conventional PNN. The PSO-based design procedure being applied at each layer of PNN leads to the selection of preferred PNs with specific local characteristics (such as the number of input variables, input variables, and the order of the polynomial) available within the PNN. In the sequel, two general optimization mechanisms of the PSO-based PNN are explored: the structural optimization is realized via PSO whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the PSO-based PNN, the model is experimented with using Gas furnace process data, and pH neutralization process data. For the characteristic analysis of the given entire data with non-linearity and the construction of efficient model, the given entire system data is partitioned into two type such as Division I(Training dataset and Testing dataset) and Division II(Training dataset, Validation dataset, and Testing dataset). A comparative analysis shows that the proposed PSO-based PNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1873-1893
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• 2023

The development of lightweight, low energy and small-sized sensors incorporated with the wireless networks has brought about a phenomenal growth of Wireless Sensor Networks (WSNs) in its different fields of applications. Moreover, the routing of data is crucial in a wide number of critical applications that includes ecosystem monitoring, military and disaster management. However, the time-delay, energy imbalance and minimized network lifetime are considered as the key problems faced during the process of data transmission. Furthermore, only when the functionality of cluster head selection is available in WSNs, it is possible to improve energy and network lifetime. Besides that, the task of cluster head selection is regarded as an NP-hard optimization problem that can be effectively modelled using hybrid metaheuristic approaches. Due to this reason, an Improved Coyote Optimization Algorithm-based Clustering Technique (ICOACT) is proposed for extending the lifetime for making efficient choices for cluster heads while maintaining a consistent balance between exploitation and exploration. The issue of premature convergence and its tendency of being trapped into the local optima in the Improved Coyote Optimization Algorithm (ICOA) through the selection of center solution is used for replacing the best solution in the search space during the clustering functionality. The simulation results of the proposed ICOACT confirmed its efficiency by increasing the number of alive nodes, the total number of clusters formed with the least amount of end-to-end delay and mean packet loss rate.

• Mycobiology
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• v.40 no.2
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• pp.111-116
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• 2012

Ten strains of the entomopathogenic fungi Metarhizium anisopliae and Beauveria bassiana were evaluated to find the most effective strain for optimization studies. The first criterion tested for strain selection was the mortality (> 50%) of Spodoptera litura larvae after inoculation of the fungus for 4 days. Results on several bioassays revealed that B. bassiana BNBCRC showed the most virulence on mortality S. litura larvae (80% mortality). B. bassiana BNBCRC also showed the highest germination rate (72.22%). However, its conidia yield ($7.2{\times}10^8$ conidia/mL) was lower than those of B. bassiana B 14841 ($8.3{\times}10^8$ conidia/mL) and M. anisopliae M6 ($8.2{\times}10^8$ conidia/mL). The highest accumulative radial growth was obtained from the strain B14841 (37.10 mm/day) while the strain BNBCRC showed moderate radial growth (24.40 mm/day). M. anisopliae M6 possessed the highest protease activity (145.00 mU/mL) while M. anisopliae M8 possessed the highest chitinase activity (20.00 mU/mL) during 96~144 hr cultivation. Amongst these criteria, selection based on virulence and germination rate lead to the selection of B. bassiana BNBCRC. B. bassiana B14841 would be selected if based on growth rate while M. anisopliae M6 and M8 possessed the highest enzyme activities.

• 한국생물공학회:학술대회논문집
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• 2003.10a
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• pp.723-729
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• 2003

Xenorhabdus nematophilus Kor-Al was cultured at flask and 5L jar fermentor at $28^{\circ}C$, 5% YS media condition. Antibiotic activity for X. nematophilus Kor-Al was experimented by paper disk method. As the result, antibiotic activity was growth associated form during culture time of X. nematophilus Kor-Al at flask. The maximum production and antibiotic activity were obtained at stationary period of cell growth. The optimum conditions of cell growth and antibiotic production at 5L jar fermentor were 400rpm agitation and 50% DO conditions.

• Food Science of Animal Resources
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• v.38 no.2
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• pp.240-250
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• 2018

This study was undertaken to find the optimum soy-peptone, glucose, yeast extract, and magnesium sulfate amounts for the maximum growth of Lactobacillus plantarum JNU 2116 and to assess the effects of these medium factors through the use of response surface methodology. A central composite design was used as the experimental design for the allocation of treatment combinations. In the analysis of the experiment, due to a significant lack of fit of the second-order polynomial regression model that was used at first, cubic terms were added to the model, and then two-way interaction terms were deleted from the model since they were found to be all statistically insignificant. A relative comparison among the four factors showed that the growth of L. plantarum JNU 2116 was affected strongly by yeast extract, moderately by glucose and peptone, and slightly by magnesium sulfate. The estimated optimum amounts of the medium factors for the growth of L. plantarum JNU 2116 are as follows: soy-peptone 0.213%, glucose 1.232%, yeast extract 1.97%, and magnesium sulfate 0.08%. These results may contribute to the production of L. plantarum L67 as a starter culture that may have potential application in yogurt and fermented meat products.

• Microbiology and Biotechnology Letters
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• v.47 no.4
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• pp.614-620
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• 2019

Microalgae have been explored as potential host species for biofuel production. Environmental factors affect algal growth and cellular composition. The effects of several key environmental factors, such as temperature, light, and pH of the medium on the growth and biochemical composition of Scenedesmus obliquus were investigated in this study. The highest growth rate of microalgae was observed at an optimal temperature of 25℃, 150 μmol/(m²·s) light intensity, and pH 10.0. The biochemical composition analysis revealed that the carbohydrate content decreased at lower (20℃) or higher temperature (35℃), whereas the protein and lipid contents increase at these temperatures. The fluctuation of light intensity significantly affected the contents of protein, carbohydrate, and lipid. The protein levels varied greatly when the pH of the medium was below 7.0. The carbohydrate and lipid contents significantly increased at pH above 7.0.

• The Korean Journal of Food And Nutrition
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• v.15 no.3
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• pp.215-219
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• 2002

Growth characteristics of sourdough lactic acid bacteria was investigated to obtain basic informations for sourdough starter. The optimum temperature and pH on bacterial growth and lactic acid production of Lactobacillus brevis UC-22 in sourdough broth were 35'E and around pH 5.5, respectively. And the optimum concentrations of the carbohydrate sources added to the broths was 2% maltose. The acidity significantly increased during growth by Lactobacillus brevis UC-22 fur 18 hours while pH significantly decreased during growth.

• KSBB Journal
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• v.18 no.6
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• pp.443-447
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• 2003

The microorganism was isolated from the night soil treatment plant for the removal of sulfur compounds. The growth conditions of the sulfur-oxidizing bacteria were investigated and the isolate characterized as Thiobacillus noveilus SRM. The optimal pH of Thiobacillus novellus SRM on cell growth was pH 7.0 and the optimal temperature was 30$^{\circ}C$ and the optimal air flow rate was 1 vvm, respectively. As a results of cell growth from the Monod plot, the specific growth rate was 0.032 hr$\^$-l/, $V_{max}$ was 1.43 hr$\^$-l/ and $K_{m}$ was 0.32, respectively. The thiosulfate oxidation by Thiobacillus novellus SRM was made of sulfate ion. The sulfate ion reduced pH and decreased cell growth.