• Mycobiology
• /
• v.36 no.4
• /
• pp.270-273
• /
• 2008

Trichoderma spp. cause large crop losses of the cultivated shiitake mushroom, Lentinula edodes. We bred several shiitake strains that are resistant to Trichoderma spp. using di-mon mating to establish a useful method for controlling the greenmold disease. We examined the competitive ability of L. edodes against Trichoderma spp. using a dual culture system to select resistant strains. By screening Trichoderma-resistant strains, we found that among 11 parental strains, 4 strains, including KFRI 36, were confirmed resistant strains. They showed especially strong resistance to T. harzianum, which formed deadlock after mycelial contact and then invaded into the territory of T. harzianum. KFRI 171 also showed resistance to T. atroviride strains. Among 13 strains, which were made by hybridization of shiitake strains, 5 were confirmed to be resistant to Trichoderma, including KFRI 58-1. Their resistance was not correlated to the resistant activity of their parents’ strains. Two strains lose resistance and two strains acquire resistance compared to their parents’ strains. In SEM observation, the mycelium of L. edodes at the interaction zone of Lentinula-Trichoderma was rugged and swollen by T. harzianum.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.767-770
• /
• 2008

This study was to investigate the establish situation of coastal disaster prevention forest for future-oriented management and establishment method of stands. As a result, the area of coastal disaster prevention forest was about 1,479ha in Korea. Therefore, it is necessary to prepare the thining regime for area of coastal disaster prevention forest and make a management method for fallen poor disaster prevention function of coastal forests. In addition, more positive counterplan would be necessary to conclude the protection against this disasters because the damage from coastal erosion or pine wilt disease were increased partly in some area.

• Journal of Forest and Environmental Science
• /
• v.37 no.2
• /
• pp.154-162
• /
• 2021

Blueberry, which produces phenolic compounds, is one of the most popular fruits in Korea. During a survey on blueberry diseases, 16 Colletotrichum isolates were obtained from blueberry leaves in Chuncheon and Gosung, Kangwon province, Korea. Using morphological and molecular analyses, the isolates were identified as Colletotrichum aenigma, C. fioriniae, C. fructicola, C. gloeosporioides, and C. nymphaeae. C. gloeosporioides was the most frequently isolated (11 isolates), and only one or two isolates of the other species were found. After inoculation with all isolates, those leaves and fruits with wounds easily developed anthracnose; whereas, fruits without wounds became infected but leaves without wounds were infected by only two of C. gloeosporioides. Typically, around seven fungicidal agents are used to control anthracnose on blueberries in Korea. Fluzinam and prochloraz manganese complex strongly (over than 80%) inhibited the growth of all Colletotrichum species, while dithianon and mancozeb only weakly (about 80% or less) inhibited their growth.

• International journal of advanced smart convergence
• /
• v.13 no.2
• /
• pp.61-68
• /
• 2024

In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.

• Journal of Korean Society of Forest Science
• /
• v.105 no.1
• /
• pp.12-18
• /
• 2016

This study was carried out to investigate the change on soil $CO_2$ efflux rates, soil temperature, soil water content and soil pH by thinning intensity treatments (heavy thinning, light thinning, control) of a black pine (Pinus thunbergii Parl.) stand disturbed by pine wilt disease in Wola National Experimental Forests in Jinju, Gyeongnam province. Monthly variations of soil $CO_2$ efflux rates were not significantly different between the thinning and the control treatments (P>0.05). The annual mean soil $CO_2$ efflux rates were $0.58g\;CO_2m^{-2}h^{-1}$ for the light thinning, $0.49g\;CO_2m^{-2}h^{-1}$ for the heavy thinning and $0.45g\;CO_2m^{-2}h^{-1}$ for the control treatments, respectively. There was a significant exponential relation between soil $CO_2$ efflux rates and soil temperature, but no correlation between soil water content or soil pH and soil $CO_2$ efflux rates. The values of $Q_{10}$ were 3.40 for the light thinning, 3.20 for the heavy thinning and 3.06 for the control treatments, respectively. The results indicate that soil $CO_2$ efflux rates in a black pine stand disturbed by pine wilt disease could be affected by thinning treatments.

• The Korean Journal of Pesticide Science
• /
• v.12 no.4
• /
• pp.363-367
• /
• 2008

Abamectin 1.8% EC and emamectin benzoate 2.15% were evaluated the simultaneous control effect of both insect pests on black pine (Pinus thunbergii) against Thecodiplosis japonensis and Matsucoccus thunbergianae. Abamectin 1.8% EC was highly effective against T. japonensis and M thunbergianae, however, emamectin benzoate was highly effective against only M. thunbergianae when abamectin and emamectin benzoate were applied through trunk injection against T. japonensis and M thunbergianae at the rate of 1 ml per cm in diameter of breast height. The rate of gall formation of T. japonensis was 0% at the applied year, but 85% at the following year. However, the rate of gall formation was over 90% at the treatment of emamectin benzoate showing no difference compared with control. Abamectin 1.8% EC and emamectin benzoate 2.15% showed high control efficacy representing 89.1% and 91.4% against M. thunbergiana, respectively.

• The Korean Journal of Mycology
• /
• v.44 no.4
• /
• pp.300-306
• /
• 2016

Recently, the incidence of oak wilt disease has been increasing in Korea, resulting in an increasing number of dead trees. In this study, we performed sawdust bag cultivation of shiitake (Lentinula edodes) using oak wilt-diseased logs and measured the antioxidant activities of the resulting mushrooms. For sawdust media, 4 types of logs (healthy, infected, dead, and fumigated ones) were used. As inocula, three strains of L. edodes (NIFoS 764, Sanjo 701ho, and Sanmaru 2ho) were used. The productivity of L. edodes from dead logs was similar to that from healthy logs. Except for the Sanmaru 2ho strain, fumigated logs and infected logs yielded a lower productivity of L. edodes compared to healthy logs. In terms of antioxidant activity, L. edodes grown on sawdust from fumigated logs showed higher values than those from other logs.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.290-297
• /
• 2024

We investigate the efficacy of ensemble learning methods, specifically the soft voting technique, for enhancing heart disease prediction accuracy. Our study uniquely combines Logistic Regression, SVM with RBF Kernel, and Random Forest models in a soft voting ensemble to improve predictive performance. We demonstrate that this approach outperforms individual models in diagnosing heart disease. Our research contributes to the field by applying a well-curated dataset with normalization and optimization techniques, conducting a comprehensive comparative analysis of different machine learning models, and showcasing the superior performance of the soft voting ensemble in medical diagnosis. This multifaceted approach allows us to provide a thorough evaluation of the soft voting ensemble's effectiveness in the context of heart disease prediction. We evaluate our models based on accuracy, precision, recall, F1 score, and Area Under the ROC Curve (AUC). Our results indicate that the soft voting ensemble technique achieves higher accuracy and robustness in heart disease prediction compared to individual classifiers. This study advances the application of machine learning in medical diagnostics, offering a novel approach to improve heart disease prediction. Our findings have significant implications for early detection and management of heart disease, potentially contributing to better patient outcomes and more efficient healthcare resource allocation.

• Journal of Plant Biotechnology
• /
• v.45 no.2
• /
• pp.125-130
• /
• 2018

In this experiment, we investigated the effects of various carbon sources and concentrations on the microtuber induction and acclimatization of the yam (Dioscorea cayenensis). First, the effects of the in vitro carbon sources and concentrations on the microtuber induction were examined. The highest efficiency of the microtuber induction was obtained in the 7% sucrose treatment, whereas the glucose treatment shows no effect on the microtuber formation. Secondly, the effects of the survival rate and the microtuber formation rate after the acclimatization were examined. The diameter (6.1 mm) and fresh weight (0.5g) of the tuberous root are the highest in the pretreatment of the 7% sucrose. Although the survival rate of the pretreatment of the low concentration sucrose (3% sucrose) is 100 %, the growth and development were inhibited. These results suggest the 7% sucrose treatment is appropriate for the yam microtuber formation and acclimatization. In addition, this protocol could be used for the propagation of virus- or disease-free clones and the multiplication of elite yam cultivars.

• Journal of the Korean Wood Science and Technology
• /
• v.42 no.2
• /
• pp.163-171
• /
• 2014

Environmental issues about indoor air quality have been increased and focused on volatile organic compounds (VOCs) caused cancer, asthma, and skin disease. Reducing VOCs has been attempted in many different methods such as using environmentally friendly materials and air cleaner or purifier. Charcoal is well known material for absorbing VOCs. Therefore, carbonized board from medium density fiberboard has been developed. We assumed that the source of carbonized boards can be any type of wood-based panels. In this study, carbonized boards were manufactured from oriented strand board (OSB) at 400, 600, 800, and $1000^{\circ}C$. Each carbonized OSB (c-OSB) was evaluated and determined physiomechanical characteristics such as exterior defects, dimensional shrinkage, modulus of elasticity, and bending strength. No external defects were observed on c-OSBs at all carbonizing conditions. As carbonizing temperature increased, less porosity between carbonized wood fibers was observed by SEM analysis. The higher rate of dimensional shrinkage was observed on c-OSB at $1000^{\circ}C$ (66%) than c-OSB at 400, 600, and $800^{\circ}C$ (47%, 58%, and 63%, respectively). The densities of c-OSBs were lower than original OSB, but there was no significant different among the c-OSBs. The bending strength of c-OSB increased 1.58 MPa (c-OSB at $400^{\circ}C$) to 8.03 MPa (c-OSB at $1000^{\circ}C$) as carbonization temperature increased. Carbonization temperature above $800^{\circ}C$ yielded higher bonding strength than that of gypsum board (4.6 MPa). In conclusion, c-OSB may be used in sealing and wall for decorating purpose without additional artwork compare to c-MDF which has smooth surface.