Kim, Kil-Ja;Kim, Da-Mi;An, Ho-Sub;Choi, Jin-Kyung;Kim, Seon-Gon
Journal of Mushroom
/
v.17
no.4
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pp.211-217
/
2019
Currently, cultivation of mushrooms using the Information and Communication Technology (ICT)-based smart farming technique is increasing rapidly. The main environmental factors for growth of mushrooms are temperature, humidity, carbon dioxide (CO2), and light. Among all the mentioned factors, currently, only temperature has been maintained under automatic control. However, humidity and ventilation are controlled using a timer, based on technical experience.Therefore, in this study, a Pleurotus eryngii first-generation smart farm model was set up that can automatically control temperature, humidity, and ventilation. After installing the environmental control system and the monitoring device, the environmental condition of the mushroom cultivation room and the growth of the fruiting bodies were studied. The data thus obtained was compared to that obtained using the conventional cultivation method.In farm A, the temperature during the primordia formation stage was about 17℃, and was maintained at approximately 16℃ during the fruiting stage. The humidity was initially maintained at 95%, and the farm was not humidified after the primordia formation stage. There was no sensor for CO2 management, and the system was ventilated as required by observing the shape of the pileus and the stipe. It was observed that, the concentration of CO2 was between 700 and 2,500 ppm during the growth period. The average weight of the mushrooms produced in farm A was 125 g, and the quality was between that of the premium and the first grade.In farm B. The CO2 sensor was in use for measurement purposes only; the system was ventilated as required by observing the shape of the pileus and the stipe. During the growth period, the CO2 concentration was observed to be between 640 and 4,500 ppm. The average weight of the mushrooms produced in farm B was 102 g.These results indicate that the quality of the king oyster mushroom is determined by the environmental conditions, especially by the concentration of CO2. Thus, the data obtained in this study can be used as an optimal smart farm model, where, by improving the environmental control method of farm A, better quality mushrooms were obtained.
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.3
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pp.133-144
/
2022
This study was conducted to investigate the cultivation period, adaptive genetic resources, growth and development patterns, and water consumption for rice cultivation in the desert environment of United Arab Emirates (UAE). R esearch on rice cultivation in the desert environment is expected to contribute to resolving food shortages caused by climate change and water scarcity. It was found that the optimal cultivation period of rice was from late November to late April of the following year during which the low temperature occurred at the vegetative growth stage of rice in the UAE. Asemi and FL478 were selected to be candidate cultivars for temperature and day-length conditions in the desert areas as a result of pre-testing genetic resources under reclaimed soil and artificial meteorological conditions. In the desert environment in the UAE, FL478 died before harvest due to the etiolation and poor growth in the early stage of growth. In contrast, Asemi overcame the etiolation in the early stage of growth, which allowed for harvest. The vegetative growth phases of Asemi were from early December to early March of the following year whereas its reproductive growth and ripening phases were from early March to late March and from late March to late April, respectively. The yield of milled rice for Asemi was 763kg/10a in the UAE, which was about 41.8% higher than that in Korea. Such an outcome was likely due to the abundant solar radiation during the reproductive growth and grain filling periods. On the other hand, water consumption during the cultivation period in the UAE was 2,619 ton/10a, which was about three times higher than that in Korea. These results suggest that irrigation technology and development of cultivation methods would be needed to minimize water consumption, which would make it economically viable to grow rice in the UAE. In addition, select on of genetic resources for the UAE desert environments such as minimum etiolation in the early stages of growth would be merited further studies, which would promote stable rice cultivation in the arid conditions.
Journal of the Korea Society of Computer and Information
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v.25
no.11
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pp.1-8
/
2020
In this paper, we proposed a smart greenhouse system that can easily grow plants indoors without professional knowledge by using the criteria of factors affected by common plants (temperature, humidity, soil humidity), and implemented a system that can check the greenhouse state in real time and control the device remotely through mobile applications. Based on Raspberry pie and Arduino, the system measures the state of greenhouse in real time through sensors and automatically controls the device. After growing and experimenting with plants in a greenhouse for a certain period of time, it was confirmed that the environment suitable for each plant was maintained. Therefore, the smart greenhouse system in this paper is expected to improve plant cultivation efficiency and user convenience and also increase beginners' access to plants.
A study proposes possibility of new IoT measuring system blended with a smart device. The research serves the best cultivation information for domestic fruit's enhancement of competitive power and also develops a glucose measuring system by which people manage fructose with the mobile device. The mobile glucose tester is designed with a form of accessory which has high portability and utility because the product connects an existing analogy refractometer to the smart phone. You can check the glucose rates data by commodity, region, and season then save measurement results with server in real time for an exclusive application. It's possible to serve the glucose map, graph, and data list through the web service. This is very useful to do collect, analyze, and process the glucose data.
Ha, Ji Young;Lee, Seung Hyun;Na, Myung Hwan;Kim, Deok Hyeon;Lee, Hye Lim;Lee, Yong Gyeon
Journal of Korean Society for Quality Management
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v.49
no.2
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pp.213-231
/
2021
Purpose: This study intends to provide decision-making information to improve efficiency by analyzing the management efficiency of smart greenhouse business entities and identifying factors that affect the efficiency based on input and output. Methods: The subjects of analysis were business entities for cultivating strawberries in smart greenhouses in Jeolla region (northern and southern Jeolla provinces), and the analysis focused on the management performance of the 2019-2020 crop period (year). Data Envelopment Analysis(DEA) was applied as an analysis method for efficiency analysis, Quantile Regression(QR) analysis was applied as a factor affecting the efficiency. Results: The reason for the efficiency gap between business entities was that there were many business entities that did not minimize the input cost at the current level of output, and the area where the variance among business entities was large was the fixed cost per 10a. In the results of the affecting factor analysis, it was found that the seed-seedlings cost, fertilizer cost, other material cost, and employment and labor cost had a negative (-) effect on the efficiency, and that the repair and maintenance cost had a positive (+) effect. Conclusion: Therefore, to achieve the efficiency of scale, it is necessary to reduce the input scale to an appropriate level. In the case of business entities with low efficiency by quartile, the seed-seedlings, fertilizer, and other material costs reduce expenditures, and repair maintenance costs can improve efficiency by increasing expenditures.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2021.10a
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pp.376-378
/
2021
According to the 2020 Global Climate Report released by the World Meteorological Organization, the average temperature of the Earth in 2019 was measured 1.1℃ higher on average than the temperature measured between 1850 and 1900 before industrialization. The change in average temperature affects the distribution of plants, and according to the vulnerability analysis paper, it can be seen that there is a change in the distribution area of plants when the average temperature rises. In this paper, to cope with these environmental changes, we propose a method of fabricating intermittent flow hydroponic smart farms using Arduino and sensors and controlling them through PCs and applications. The manufactured hydroponic smart farm identifies the farm's temperature and humidity, positive pH concentration, illumination, and water quality to check the amount of pumping, supplement LED control, sensor condition, overall management and cultivation of the farm, and grows in an appropriate environment.
This study aimed to investigate the growth parameters and antioxidant activity of Cnidium officinale under controlled temperature and carbon dioxide levels during the cultivation period. The plants were cultivated for four months, each group being set at the average temperature of the cultivation area +1.8℃/445ppm(SSP1), +3.6℃/872ppm(SSP3), and +4.4℃/1,142ppm(SSP5), respectively. During the cultivation period, the growth, Top/Root ratio, and leaf weight ratio(LWR) of C. officinale slightly decreased in SSP3 and SSP5 compared to SSP1, while the root weight ratio(RWR) increased. The antioxidant activity and related phenolic compound content in the aerial parts of C. officinale increased proportionally with temperature and CO2 concentration. However, an adverse effect was observed in the high-concentration SSP5 group. Conversely, in the roots, the SSP5 group exhibited the highest antioxidant activity. This study suggests that it can be utilized as fundamental data necessary for understanding the correlation between environmental conditions and the growth as well as physiological activities of medicinal plants.
This study was conducted to the improvement of solar light-based artificial light supply system and effect of lettuce cultivation. The artificial light supply system was consisted of units such as light source, power, system measurement and controller. The light source supply was composed of a solar transmitter and an LED lamp. The power supply consisted of an leakage breaker, SMPS, LED controller and relay. The solar transmitter was made of a quartz optical fiber with optimal light transmission. Artificial light used white lamp among LEDs. System measurement and control consisted of touch screen, Zigbee communication module and light quantity sensor. The results of test confirmed that the LED light is automatically activated when the intensity measured by the light intensity sensor is 200 μmolm-2s-1 or less. Moreover, the leaf length, root length, chlorophyll content and root fresh weight of optical fiber treatment was hight than LED lamp treatment. Therefore, it can be inferred that the energy-saving solar light collector device can be effective in the indoor lettuce production. However, the use of LED lamp is also recommended to assure the availability of sufficient sunlight in cloudy and rainy days.
Agriculture plays an industrial and economic role, as well as an environmental and ecological conservation role, group harmony and the inheritance of traditional culture. However, no matter how advanced the industry is, the basic food necessary for human life can only be produced through the photosynthesis of plants with natural resources such as the sun, water, and air. The Food and Agriculture Organization of the United Nations (FAO) predicts that the world's population will increase by another 2 billion people by 2050, and it faces a myriad of complex and diverse factors to consider, including climate change, food security concerns, and global ecosystems and political factors. In particular, in order to solve problems such as increasing productivity and production of agricultural products, improving quality, and saving energy, it is difficult to solve them with traditional farming methods. Recently, with the wind of the 4th industrial revolution, ICT convergence technology and artificial intelligence have been rapidly developing in many fields, but it is also true that the application of new technologies is somewhat delayed due to the unique characteristics of agriculture. However, in recent years, as ICT and artificial intelligence utilization technologies have been developed and applied by many researchers, a revolution is also taking place in agriculture. This paper summarizes the current state of research so far in four categories of agriculture, namely crop cultivation environment management, soil management, pest management, and irrigation management, and smart farm research data that has recently been actively developed around the world.
In this study, the morphology and antioxidant content of shiitake mushrooms (Lentinula edodes) cultivated in smart farms and general farms have been compared. With regard to morphology, mushrooms produced in the smart farm system exhibited a slightly thicker and wider pileus and thicker and longer stipe than those in the general farm system. The stipe in the mushrooms from moderate-sized farms was harder, because the low relative humidity of cultivation rooms could induce mushroom tissue to harden. With regard to the antioxidant content, the free radical scavenging activity was evaluated by the DPPH assay. Among the various treatments, hot water extracts of freeze-dried shiitake produced from smart farms exhibited the highest DPPH value of 37.8%. In contrast, the lowest activity of 12.2% was observed in a 70% fermented alcohol extract of shiitake that was dried by hot air. The polyphenol content was higher in hot water extracts than in 70% fermented alcohol extracts. Additionally, the polyphenol content was higher in the freeze-dried samples than in hot-air dried ones. The smart-farm system was preferred over the general cropping system for cultivating shiitake mushrooms, because the antioxidant activity and polyphenol content of mushrooms from the smart-farm system was better; the functionality of this system was more improved than that of the general cropping system, and it enables mushrooms to be cultivated more efficiently. The antioxidant content is represented as the $mean{\pm}SD$ of three replicates. Different letters indicate significant differences among samples, i.e., p<0.05.
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