• Journal of Advanced Technology Convergence
• /
• v.1 no.1
• /
• pp.1-6
• /
• 2022

Since 2015, the government has been making efforts to distribute Korean smart farms. However, the supply is limited to large-scale facility vegetable farms due to the limitations of technology and current cultivation research data. In addition, the efficiency and reliability compared to the introduction cost are low due to the simple application of IT technology that does not consider the crop growth and cultivation environment. Therefore, in this paper, data analysis services was performed based on public and external data. To this end, a data-based target smart farm system was designed that is suitable for the situation of farms growing in facilities. To this end, a farm risk information notification service was developed. In addition, light environment maps were provided for proper fertilization. Finally, a disease prediction model for each cultivation crop was designed using temperature and humidity information of facility farms. Through this, it was possible to implement a smart farm data service by linking and utilizing existing smart farm sensor data. In addition, economic efficiency and data reliability can be secured for data utilization.

• Journal of Internet of Things and Convergence
• /
• v.8 no.2
• /
• pp.71-78
• /
• 2022

Recently, the number of people wishing to return to farming is increasing, However, the lack of farming experience and management information of returnees is one of the main reasons for increasing the probability of agricultural failure. This study proposes an interface to support early facility cultivation management decision-making for returnees who want facility cultivation. The proposed interface is designed with UML(Unified Modeling Language) and provides key decision-making information such as land/crop suitability, land/facility costs, and management costs according to input data such as cultivation areas, selected crops, and cultivation types selected by the user. Through the proposed interface, facility cultivators can effectively and quickly acquire initial decision-making information for facility cultivation in the desired target area.

• Journal of Biosystems Engineering
• /
• v.43 no.4
• /
• pp.342-351
• /
• 2018

Purpose: Recently, an increasing number of farms have been cultivating shiitake mushrooms using a sawdust substrate and a cooler/heater. In this study, an attempt was made to develop an environmental control system using a heat pump for cultivating high-quality shiitake mushrooms. Methods: An environmental control system, consisting of an air-to-water type heat pump, a thermal storage tank, and a radiator in a variable opening chamber, was designed and fabricated. The system was also installed in the cultivation facility of a farm cultivating shiitake mushrooms so as to compare the proposed control system with a conventional environmental control system using a cooler-condensing unit and an electric hot water boiler. Results: The uniformity of the environment was analyzed through environment measurements taken at several positions inside the cultivation facility. It was determined that the developed environmental control system is able to control the variations in temperature and relative humidity to within 1% and 3%, respectively. In addition, a maximum temperature difference of $30^{\circ}C$ (maximum of $35^{\circ}C$, minimum of $5^{\circ}C$) and a maximum relative humidity difference of 30% (maximum of 90%, minimum of 60%) can be attained within 30 min inside the cultivation facility through the cooling of the heat pump and heating of the radiator in a variable opening chamber. Thus, the developed control system can be used to cultivate high-quality shiitake mushrooms more effectively than a conventional cooler and heater. Conclusions: In comparison with a conventional environmental control system, the developed system decreased the yield of ordinary mushrooms by 65%, and increased that of high-quality mushrooms by 217%. This corresponds to a 16% increase in gross farm income. Consequently, the developed system is expected to improve the income of shiitake mushroom cultivating farms.

• 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.

• Journal of People, Plants, and Environment
• /
• v.23 no.6
• /
• pp.655-665
• /
• 2020

Background and objective: This study was conducted to compare the cultivation environment, growth of cut flowers, and management performance of conventional farms and smart farms growing the standard cut chrysanthemum, 'Jinba'. Methods: Conventional and smart farms were selected, and facility information, cultivation environment, cut flower growth, and management performance were investigated. Results: The conventional and smart farms were located in Muan, Jeollanam-do, and conventional farming involved cultivating with soil culture in a plastic greenhouse, while the smart farm was cultivating with hydroponics in a plastic greenhouse. The conventional farm did not have sensors for environmental measurement such as light intensity and temperature and pH and EC sensors for fertigation, and all systems, including roof window, side window, thermal screen, and shading curtain, were operated manually. On the other hand, the smart farm was equipped with sensors for measuring the environment and nutrient solution, and was automatically controlled. The day and night mean temperatures, relative humidity, and solar radiation in the facilities of the conventional and the smart farm were managed similarly. But in the floral differentiation stage, the floral differentiation was delayed, as the night temperature of conventional farm was managed as low as 17.7℃ which was lower than smart farm. Accordingly, the harvest of cut flowers by the conventional farm was delayed to 35 days later than that of the smart farm. Also, soil moisture and EC of the conventional farm were unnecessarily kept higher than those of the smart farm in the early growth stage, and then were maintained relatively low during the period after floral differentiation, when a lot of water and nutrients were required. Therefore, growth of cut flower, cut flower length, number of leaves, flower diameter, and weight were poorer in the conventional farm than in the smart farm. In terms of management performance, yield and sales price were 10% and 38% higher for the smart farm than for the conventional farm, respectively. Also, the net income was 2,298 thousand won more for the smart farm than for the conventional farm. Conclusion: It was suggested that the improved growth of cut flowers and high management performance of the smart farm were due to precise environment management for growth by the automatic control and sensor.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.3
• /
• pp.185-199
• /
• 2019

Korea's facility horticulture has developed remarkably in a short period of time. However, in order to secure international competitiveness in response to unfavorable surrounding conditions such as high operating costs and market opening, it is necessary to diagnose the problems of facility horticulture and prepare countermeasures through analysis. The purpose of this study was to analyze the case of leading farmers by introducing information and communication technology (ICT) in hydroponic cultivation agriculture and horticulture, and to examine how agricultural technology utilizing smart farm and big data of facility horticulture contribute to farm productivity. Crop growth information gathering and analysis solutions were developed to analyze the productivity change factors calculated from hydroponics tomato farms and strawberry farms. The results of this study are as follows. The application range of the leaf temperature was verified to be variously utilized such as house ventilation in the facility, opening and closing of the insulation curtain, and determination of the initial watering point and the ending time point. Second, it is necessary to utilize water content information of crop growth. It was confirmed that the crop growth rate information can confirm whether the present state of crops is nutrition or reproduction, and can control the water content artificially according to photosynthesis ability. Third, utilize EC and pH information of crops. Depending on the crop, EC values should be different according to climatic conditions. It was confirmed that the current state of the crops can be confirmed by comparing EC and pH, which are measured from the supplied EC, pH and draining. Based on the results of this study, it can be confirmed that the productivity of smart farm can be affected by how to use the information of measurement growth.

• Journal of Fisheries and Marine Sciences Education
• /
• v.26 no.2
• /
• pp.444-454
• /
• 2014

The range of optimization problem in aquaculture is very wide, resulting from the range of species, mode of operation. Quite a few studies focus marine net-cages, but studies on land based culture farm are few or no. This paper considers a allocation problem to meet production planning in land based aquaculture system. A water pool allocation model in land based aquaculture system was developed. The solution finds the value of decision variable to minimize yearly production costs that sums up the water pool usage cost and sorting cost. The model inputs were (1) the fish growth rate (2) critical standing corp (3) number of water pool (4) number of fish. The model outputs were (5) number of water pool in growing phase (6) cost of cultivation (6) optimal facility allocation(number of water pool for each growing phase). To solve the problem, an efficient heuristic algorithm based on a greedy manner is developed. Branch and bound and heuristic is evaluated through numerical examples.

• Journal of Biosystems Engineering
• /
• v.38 no.4
• /
• pp.270-278
• /
• 2013

Purpose: Using agricultural machinery was not easy in the conventional shading structure, specified as a standard facility by standard cultivation methods for ginseng. Thus, this study designed the new types of facility allowing machine access by modifying the conventional type. Methods: Two types of facility (i.e. wide roof type and long & short roof type) were designed and installed in an experimental site to evaluate its growing environments and applicability of riding-type cultivator. Results: From the results of incoming light measurement, all three types (i.e. two new types and a conventional type) of shading structures blocked the incoming light after 9:00 am. The temperature distribution inside the new types was similar with the one in the conventional type, so the growth of ginseng was in good condition in all three types of facility. The riding-type cultivator was operated well with the low speed first gear of 0.13 m/s in the new types. However, a long & short typed roof needs to be raised 18 cm height in order to use the cultivator. Conclusions: With the results of this study, the new types of roof can be used in the ginseng farm in that they satisfied the growing environments for ginseng and the needs for agricultural mechanization.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.65 no.6
• /
• pp.15-22
• /
• 2023

In this study, We conduct a comparative study of deep learning-based classification of agricultural field attributes using Tagged Image File (TIF) and Enhanced Compression Wavelet (ECW) images. The goal is to interpret and classify the attributes of agricultural fields by analyzing the differences between these two image formats. "FarmMap," initiated by the Ministry of Agriculture, Food and Rural Affairs in 2014, serves as the first digital map of agricultural land in South Korea. It comprises attributes such as paddy, field, orchard, agricultural facility and ginseng cultivation areas. For the purpose of comparing deep learning-based agricultural attribute classification, we consider the location and class information of objects, as well as the attribute information of FarmMap. We utilize the ResNet-50 instance segmentation model, which is suitable for this task, to conduct simulated experiments. The comparison of agricultural attribute classification between the two images is measured in terms of accuracy. The experimental results indicate that the accuracy of TIF images is 90.44%, while that of ECW images is 91.72%. The ECW image model demonstrates approximately 1.28% higher accuracy. However, statistical validation, specifically Wilcoxon rank-sum tests, did not reveal a significant difference in accuracy between the two images.

• The Korean Journal of Mycology
• /
• v.32 no.2
• /
• pp.89-94
• /
• 2004

This study was carried out to investigate the suitability of various agricultural by-products as basal substrates for the mycelial growth and fruiting body formation of Hericium erinaceum. For this aim, oak sawdust, cotton waste, sugarcane bagasse, Job's tears, rice hull, Chinese cabbage, and coconut waste were used as sole or mixed substrate(s). Corn waste and rice bran were used as nutrient supplements. The growth and density of mycelium, yield of fruiting body, and biological efficiency were compared among tested substrates colonized by Hericium erinaceum. The best measurement of mycelial growth and density, yield of fruiting body, and biological efficiency in a laboratory test was found in a spawn substrate composed with oak sawdust 80% and rice bran 20%. The suitability of this spawn substrate composition for Hericium fruiting body production was testified through practical tests in plastic bottles (850 ml) in a mushroom farm which had bottle cultivation facility. However, test in a mushroom farm which had plastic bag cultivation facility, best production of Hericium fruiting body (520 g per one bag) was observed in a spawn substrate composed of cotton waste 40%, saw dust 40%, corn waste 10%, and rice bran 10%.