• The Korean Journal of Mycology
• /
• v.50 no.4
• /
• pp.347-355
• /
• 2022

A fungal isolate belonging to the phylum Ascomycota was isolated and identified as Talaromyces veerkampii in 2017 during a survey of fungal diversity in field soils in Korea. This fungal isolate was identified and described based on macro- and micromorphological and molecular characterization. The identification was also based on partial 18S-ITS1-5.8S-ITS2-28S rDNA and calmodulin (CaM)-encoding gene sequencing data. Talaromyces veerkampii has not been previously reported in Korea. Thus, we report here a newly discovered species from soil in Korea along with its morphological and molecular characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.861-864
• /
• 2014

Recently, the growth control of crops is developed as one of essential factors for smart agriculture based on ubiquitous sensor network. It is reason of easiability for control of product quantity and management of product quality. In this paper, scenario of smart agriculture is investigated for domestic and foreign countries and currently used sensor data technologies is compared to support a series of technological systemization works for sensor data field of smart agriculture. The results of this paper can be used as basic data for smart agriculture standardizations which is currently under progress at domestic and abroad.

• The Korean Journal of Mycology
• /
• v.50 no.3
• /
• pp.205-215
• /
• 2022

Penicillium pimiteouiense was discovered in South Korea during an investigation of fungal communities in soil collected from the Gyeongsangbuk-do province. In this study, we performed molecular analysis of this fungal isolate using internal transcribed spacer rDNA, β-tubulin, and Calmodulin gene sequences. We also performed morphological analysis using five agar media, potato dextrose, oatmeal, malt extract, czapek yeast extract, and yeast extract sucrose. In this study, the molecular and morphological analyses of P. pimiteouiense with detailed descriptions and figures has been carried out.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.64 no.1
• /
• pp.15-26
• /
• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• The Plant Pathology Journal
• /
• v.37 no.3
• /
• pp.307-314
• /
• 2021

Pepper (Capsicum annuum L.) is an important agricultural crop worldwide. Recently, Colletotrichum scovillei, a member of the C. acutatum species complex, was reported to be the dominant pathogen causing pepper anthracnose disease in South Korea. In the present study, we isolated bacterial strains from rhizosphere soil in a pepper field in Gangwon Province, Korea, and assessed their antifungal ability against C. scovillei strain KC05. Among these strains, a strain named BS1 significantly inhibited mycelial growth, appressorium formation, and disease development of C. scovillei. By combined sequence analysis using 16S rRNA and partial gyrA sequences, strain BS1 was identified as Bacillus velezensis, a member of the B. subtilis species complex. BS1 produced hydrolytic enzymes (cellulase and protease) and iron-chelating siderophores. It also promoted chili pepper (cv. Nockwang) seedling growth compared with untreated plants. The study concluded that B. velezensis BS1 has good potential as a biocontrol agent of anthracnose disease in chili pepper caused by C. scovillei.

• Journal of Drive and Control
• /
• v.20 no.1
• /
• pp.16-26
• /
• 2023

Although the upland field area of Korea is high as 44.8%, the platform optimized for the upland field is insufficient. It is necessary to develop an optimized platform for the upland field because the upland field environment is an irregular environment with many slopes. In addition, due to the characteristic of agricultural operations, the traction power and torque of the platform have to be sufficient. Therefore, in this study, a simulation model that can predict the traction power and driving torque of a crawler-type platform for the upland field was developed and validated using the specifications of the crawler platform. The simulation model was developed using Amesim (19.1, Siemens, Germany). The development of the model was conducted using the specifications of the platform. A measurement system was developed to validate the simulation model. The traction power data of the simulation model was validated with the traction force and vehicle speed. The driving torque data of the simulation model was validated with the torque of the sprocket on the crawler system. As a result of the analysis, the error between measurement and simulation results occurred within 10%, and it was determined that the traction power and driving torque prediction of the crawler platform using this model was possible.

• Journal of the Korea Convergence Society
• /
• v.7 no.6
• /
• pp.49-54
• /
• 2016

The IoT has attracted attention as one of the technologies that are applied to various industries and create new services. The IoT can utilize existing network technologies to create services by providing Internet connection between objects. Objects Personalized services can be created by collecting various data using the IoT. In the field of agriculture, we are promoting sustainable agriculture and enhancing competitiveness through the use of the IoT, and the convergence of IoT in agriculture is pushing for smart agriculture. In Korea, the Ministry of Agriculture, Food and Rural Affairs is preparing measures to spread smart farms to improve agricultural competitiveness using IoT technology. Therefore, we propose the development model of smart agriculture in the future through the case study on the IoT based on agriculture.

• Korean Journal of Agricultural Science
• /
• v.50 no.3
• /
• pp.457-468
• /
• 2023

The purpose of this study is to develop a high-speed combine harvester. The performance was evaluated by composing a dynamic simulation model of a threshing cylinder and analyzing the amount of threshed rice grain during threshing operations. The rotational speed of the threshing cylinder was set at 10 rpm intervals from 500 rpm until 540 rpm, based on the rated rotational speed of 507 rpm. The rice stem model was developed using the EDEM software using measured rice stem properties. Multibody dynamics software was utilized to model the threshing cylinder and tank comprising five sections below the threshing cylinder, and the threshing performance was evaluated by weighing the grain collected in the threshing tank during threshing simulations. The simulation results showed that section 1 and 2 threshed more grains compared to section 3 and 4. It was also found that when the threshing speed was higher, the larger number of grains were threshed. Only simulation was conducted in this study. Therefore, the validation of the simulation model is required. A comparative analysis to validate the simulation model by field experiment will be conducted in the future.

• Journal of Korean Society of Rural Planning
• /
• v.29 no.4
• /
• pp.127-135
• /
• 2023

This study examined the impact of changes in agricultural production methods on society, the economy, and the environment. While traditional open-field farming relied heavily on natural conditions, modern approaches, including greenhouse and smart farming, have emerged to mitigate the effects of climate and seasonal variations. Facility horticulture has been on the rise since the 1990s, and recently, there has been a growing interest in smart farms due to reasons such as climate change adaptation and food security. We compared open-field spinach and greenhouse spinach using agricultural income survey data, and we also compared greenhouse tomato cultivation with smart farming tomato cultivation, utilizing data from the smart farm survey reports. The economic results showed that greenhouse spinach increased yield by 25.8% but experienced a 29% decrease in income due to equipment depreciation. In the case of tomato production in smart farms, both yield and income increased by 36-39% and 34-46%, respectively. In terms of environmental impact, we also compared fertilizer and energy usage. It was found that greenhouse spinach used 29% less fertilizer but 14% more energy compared to open-field spinach. Smart farming for tomatoes saw a negligible decrease in electricity and fuel costs. Regarding the social impact, greenhouse spinach reduced labor hours by 31%, and the introduction of smart farming for tomatoes led to an average 11% reduction in labor hours. This reduction is expected to have a positive effect on sustainable farming. In conclusion, the transition from open-field to greenhouse cultivation and from greenhouse cultivation to smart farming appears to yield positive effects on the economy, environment, and society. Particularly, the reduction in labor hours is beneficial and could potentially contribute to an increase in rural populations.

• Korean Journal of Agricultural Science
• /
• v.47 no.3
• /
• pp.615-624
• /
• 2020

An effective sampling method is necessary to monitor potato tuber moths (Phthorimaea operculella) because they are the biggest concern in potato-cultivating areas. In this study, a sequential sampling method was developed based on the results of field surveys of potato tuber moths in South Korea. Potato tuber moths were collected in fields cultivating potatoes at six sites, and their spatial distribution was investigated using the Taylor power law. The optimal sampling size and cumulative number of potato tuber moths in traps to stop sampling were determined based on the spatial distribution pattern and mean density of the collected potato tuber moths. Finally, the developed sampling method was applied to propose a control action, and its sampling efficiency was compared with that of the traditional sampling method using a binomial distribution. The potato tuber moths tended to aggregate; the optimal number was approximately 5 - 16 traps for sampling, and the number varied with the mean density of potato tuber moths according to the sampling sites. In addition, one, two, and three sites might require the following actions: Continued sampling, control, and no control, respectively. Sampling with the binomial distribution showed the minimum sample size was 12 when considering the economic threshold level. Here, we propose an effective sampling method that can be applied for future monitoring and field surveys of potato tuber moths in South Korea.