• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.187-187
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• 2022

우리나라의 농촌 유역은 크게 1) 상류에 위치한 농업용 저수지, 2) 저수지 방류부, 3) 저수지 하류하천, 4) 하류 농업 지대로 구성된다. 이들 모두 유역의 홍수·침수와 연관되어 있으나 각각의 설계 빈도가 서로 달라 일시에 수용 가능한 수자원의 양이 상이하다. 예컨대 극한 강우가 발생한 경우 PMP를 고려하여 설계된 저수지에서는 유입 홍수량이 통제될 수 있으나 50-200년 빈도로 설계된 하류하천에서는 측면 유입량 때문에 홍수가 발생할 수 있다. 따라서 유역의 홍수 확률을 산출할 때에는 유역 구성지역별 홍수 확률을 산정한 후 종합적으로 고려할 필요가 있다. 특히 농촌유역의 경우 하류하천 및 농경지의 설계 빈도 기준이 도시에 비해 낮아 유역 구성요소 간 처리 가능한 수자원 양의 차이가 크다. 따라서 본 연구에서는 농촌 유역을 대상으로 연구를 진행하였다. 한편, 최근 기후변화로 인해 극한 강우 사상의 빈도가 잦아짐에 따라 유역 내 홍수의 발생이 증가하고 있다. 따라서 기후변화에 따른 미래 농촌 유역의 홍수 발생 여부 파악이 필수적이다. 이에 본 연구에서는 CMIP 6 (Coupled Model Intercomparison Project Phase 6)의 GCM (General Circulation Model) 기상산출물을 농촌 유역에 적용함으로써 미래 농촌 유역의 홍수 발생 여부를 확인하고자 하였다. 또한, CMIP 6의 GCM 산출 기상자료의 시간 단위는 24시간 혹은 3시간으로 시간적 해상도가 낮으므로 유역 홍수 모의를 위하여 GCM 산출물의 시간 분해를 수행하였다. 본 연구에서는 MRC (Multiplicative Random Cascade) 모형을 기후변화 시나리오 기상자료에 적용함으로써 강우 자료의 시간 분해를 수행하고, 시간 분해 결과물을 활용하여 농촌 유역의 미래 홍수 확률을 산정해보고자 하였다. 본 연구의 결과는 향후 농촌 유역의 홍수 확률 산정 기법에 관한 기초 자료로 활용될 수 있을 것으로 사료된다.

• Journal of Soil and Groundwater Environment
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• v.28 no.5
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• pp.51-58
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• 2023

In this study, an empirical experiment was conducted to assess the feasibility of replacing groundwater with rainwater in melon cultivation using a smart rainwater harvesting system. The rainwater harvesting efficiency was calculated under three different melon cultivation scenarios. After cultivation, the quality of the fruits grown with rainwater and groundwater was compared by examining the weight, degree of sweetness, and flesh hardness of the products. The results revealed that the water quality of the smart rainwater harvesting device was suitable for melon cultivation to provide better hardness and chloride levels than groundwater. It was also estimated that about 40% of the total water demand for full growth of the melon could be supplied by rainwater. The fruit weight and sweetness were equivalent or slightly better for the melons cultivated with rainwater than those cultivated with groundwater. In particular, the flesh hardness was significantly improved by rainwater cultivation. These results collectively suggest that rainwater can be used as a substitute for groundwater to preserve groundwater resources without compromizing the produced fruit quality.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.137-152
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• 2023

Data is indispensable for digital transformation of agriculture with the development of innovative information and communication technology (ICT). In order to devise and prioritize strategies for enhancing data competitiveness in the agricultural sector, we employed an Analytic Hierarchy Process (AHP) analysis. Drawing from existing research on data competitiveness indicators, we developed a three-tier decision-making structure reflecting unique characteristics of the agricultural sector such as farmers'awareness of the data industry or awareness of agriculture among data workers. AHP survey was administered to experts from both agricultural and non-agricultural sectors with a high understanding of data. The overall composite importance, derived from the respondents, was rated in the following order: 'Employment Support', 'Data Standardization', 'R&D Support', 'Start-up Ecosystem Support', 'Relaxation of Regulations', 'Legislation', and 'Data Analytics and Utilization Technology'. In the case of experts in the agricultural sector, 'Employment Support' was ranked as the top priorities, and 'Legislation', 'Undergrad and Grad Education', and 'In-house Training' were also regarded as highly important. On the other hand, experts in the non-agricultural sector perceived 'Data Standardization' and 'Relaxation of Regulations' as the top two priorities, and 'Data Center' and 'Open Public Data' were also highly rated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.47-53
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• 2023

With the advent of the 4th Industrial Revolution, diverse and a large amount of data has been accumulated now. The agricultural community has also collected environmental data that affects the growth of crops in smart farms or open fields with sensors. Environmental data has different features depending on where and when they are measured. Studies have been conducted using collected agricultural data to predict growth and yield with statistics and artificial intelligence. The results of these studies vary greatly depending on the data on which they are based. So, studies to enhance data quality have also been continuously conducted for performance improvement. A lot of data is required for high performance, but if there are outlier or missing values in the data, it can greatly affect the results even if the amount is sufficient. So, adjustment of outlier and missing values is essential in the data preprocessing. Therefore, this paper integrates data collected from actual farms and proposes a adjustment system for outlier and missing values based on it.

• Information Systems Review
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• v.22 no.1
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• pp.113-124
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• 2020

In the operation of farms, it is very important to evaluate the quality of harvested crops and to classify defective products. However, farmers have difficulty coping with the cost and time required for quality assessment due to insufficient capital and manpower. This study thus aims to detect defects by analyzing the epidermis of fruit using deep learning algorithm. We developed a model that can analyze the epidermis by applying YOLOv3 algorithm based on Region Convolutional Neural Network to video images of peach. A total of four classes were selected and trained. Through 97,600 epochs, a high performance detection model was obtained. The crop failure detection model proposed in this study can be used to automate the process of data collection, quality evaluation through analyzed data, and defect detection. In particular, we have developed an analytical model for peach, which is the most vulnerable to external wounds among crops, so it is expected to be applicable to other crops in farming.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.

• Journal of Mushroom
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• v.17 no.4
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• pp.197-204
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• 2019

In this study, smart farm technology was used by farmers cultivating 'CHIKUMASSHU T-011' in order to develop an optimal growth model for the precision cultivation of bottle-grown winter mushroom and the results of the same are mentioned herein. Farmers participating in the experiment used 60 ㎡ of bed area with 4 rows and 13 columns of shelf shape, 20 horsepower refrigerator, 100T of sandwich panel for insulation, 6 ultrasonic humidifiers, 12 kW of heating, and 20,000 bottles of Flammulina velutipes mushroom spores. The temperature, humidity, and carbon dioxide concentrations, which directly affect the growth of the mushroom, were collected and analyzed from the environmental sensors installed at the winter mushroom cultivation area. The initial temperature was found to be 14.5℃, which was maintained at 14℃ to 15℃ until the 10th day. In the restriction phase, the initial temperature was 4℃ and was maintained between 2℃ and 3℃ until the 15th day, while during the growth phase, it was maintained between 7.5℃ to 9.5℃. Analysis of the humidity data revealed initial humidity to be 100%, which varied between 88% to 98% during primordia formation period. The humidity remained between 77% to 96% until the 15th day, in the restriction phase and between 75% to 83% during the growth phase. The initial carbon dioxide concentration was 3,500 ppm and varied between 3,500 ppm to 6,000 ppm during primordia formation period and was maintained at 6,000 ppm until the 15th day. During the growth phase, the carbon dioxide concentration was found to be over 6,000 ppm. Fruiting body characteristics of 'CHIKUMASSHU T-011' cultivated in the farmhouse were as follows: Pileus diameter of 7.5 mm and thickness of 4.1 mm, stipe thickness of 3.3 mm, and length of 154.2 mm. The number of valid fruiting bodies was 1,048 unit per 1,400 mL bottle, and the individual weight was 0.71 g per unit. The yield of fruiting bodies was 402.8 g per 1,400 mL bottle.

• Journal of Bio-Environment Control
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• v.27 no.3
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• pp.253-259
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• 2018

This study set out to select a system to realize an optimal environment for strawberry cultivation greenhouses based on data about the growth and development of strawberry and its environment and to provide basic data for the research of its improved productivity. For these purposes, the investigator conducted a field survey with greenhouses for strawberry cultivation in western Gyeongnam. The findings show that farmers in their fifties and sixties accounted for the biggest part in the age groups of strawberry farmers. While those who were under 50 were accounted for approximately 67.5%, those who were 60 or older accounted for 32.5%. As for cultivation experiences, the majority of the farmers had ten years of cultivation experiences or less with some having 30 years of cultivation experiences or more. All the farmers built an arch type single span greenhouse. Those who used nutrient solutions were about 75.0%, being more than those who used soil. All of the farmers that used a nutrient solution adopted an elevated hydroponic system. The single span greenhouses were in the range of 7.5~8.5m, 1.3~1.8m and 2.5~3.5m for width, eaves, and ridge height, respectively, regardless of survey areas. The rafters interval was about 0.7~0.8m. In elevated hydroponic cultivation, the width, height, and interval of the beds were about 0.25m, 1.2m and 1.0m, respectively. As for the strawberry varieties, the domestic ones accounted for approximately 97.5% with Seolhyang being the most favorite one at about 65.0%. As for the internal environment factors of greenhouses, 38 farmers measured only temperature and relatively humidity. As for hydroponics, the farmers used a hydroponics control system. Except for the farmers that introduced a smart farm system for temperature and humidity control, approximately 85.0% controlled temperature and humidity only with a control panel for side windows and ventilation fans. As for heating and heat insulation, all of the farmers were using water curtains with many farmers using an oil or electric boiler, radiating lamp or non-woven fabric, as well, when necessary.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.485-496
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• 2022

Modern agriculture is being transformed into smart agriculture to maximize production efficiency along with changes in the 4th industrial revolution. However, rural areas in Korea are facing challenges of aging, low fertility, and population outflow, making it difficult to transition to smart agriculture. Among ICT technologies, simulation allows users to observe or experience the results of their choices through imitation or reproduction of reality. The combination of the three-dimension (3D) model and the greenhouse simulator enable a 3D experience by virtual greenhouse for fruits and vegetable cultivation. At the same time, it is possible to visualize the greenhouse under various cultivation or climate conditions. The objective of this study is to apply the greenhouse climate management model for simulation development that can visually see the state of the greenhouse environment under various micrometeorological properties. The numerical solution with the mathematical model provided a dynamic change in the greenhouse environment for a particular greenhouse design. Light intensity, crop transpiration, heating load, ventilation rate, the optimal amount of CO₂ enrichment, and daily light integral were calculated with the simulation. The results of this study are being built so that users can be linked through a web page, and software will be designed to reflect the characteristics of cladding materials and greenhouses, cultivation types, and the condition of environmental control facilities for customized environmental control. In addition, environmental information obtained from external meteorological data, as well as recommended standards and set points for each growth stage based on experiments and research, will be provided as optimal environmental factors. This simulation can help growers, students, and researchers to understand the ICT technologies and the changes in the greenhouse microclimate according to the growing conditions.

• Food Science and Preservation
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• v.30 no.2
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• pp.272-286
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• 2023

Garlic sprouts can provide data on functional and food processing materials. This study compared the leaves, bulbs, and roots of garlic sprouts grown on smart farms during two growth periods (20 and 25 days). In addition, data for garlic bulbs grown in open fields were presented as reference materials. All garlic sprouts' total free sugar content decreased as the growth period increased. All plant parts' total organic acid content decreased as the growth period progressed, except for the root section. Potassium, phosphorus, and sulfur content increased during growth in all parts of the garlic sprouts. Alliin content decreased in all parts of the plant over time, whereas thiosulfinate content increased in the roots but decreased in the leaves and bulbs. Total polyphenol content increased in all parts of the plant during the growth period, except for the bulb, whereas the flavonoid content did not change significantly over time. The 2,2-diphenyl-1-picrylhydrazy (DPPH) and 2,2'-azinobis (3-ethylben-zothiazoline 6-sulfonate) (ABTS) free radical scavenging activities, as well as the superoxide dismutase (SOD)-like activity of garlic sprouts were 37.45-65.47%, 59.12-89.81%, and 89.52-98.59%, respectively. These activities tend to decrease during the growth period. Here, we showed that garlic sprouts have higher levels of functional substances and physiological activities than general garlic sprouts. It was also determined that a growth period of 20 days was suitable for garlic sprouts. Data for research on functional and food-processing materials can be obtained by analyzing garlic sprouts produced by smart farms.