• Journal of Biosystems Engineering
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• v.34 no.3
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• pp.161-166
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• 2009

This study was conducted to investigate the growth characteristics of cherry tomatoes in greenhouse using far infrared heating system. The far infrared greenhouse heating systems were installed in two ways on the greenhouse side wall and at the greenhouse ceiling. The heating characteristics of far infrared heating system were analyzed by investigating the heating load, internal temperature, energy consumption, growth characteristics and quality evaluation. The results were compared with heated air heating system using kerosene. The results showed that tomatoes grown in the greenhouse with the far infrared heating system had relatively better plant height, leaf length, leaf width, stem diameter than ones from the greenhouse with hot air heating system and both heating methods had no significant difference on Cherry tomato sugar contents. At the same time, the far infrared heating system reduced heating cost from 34.5 to 41.4% on comparing with hot air heating system.

• Agribusiness and Information Management
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• v.7 no.2
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• pp.12-18
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• 2015

Since 2000s, proper utilization of IoT (Internet of Things) technology is a key factor for a firm to become more competitive, and this stream is not exceptional for the food and agriculture industry. Along with this stream, Korea government organization, for example MAFRA (Ministry of Agriculture, Food and Rural Affairs), elected to adopt IoT technology, such as USN and RFID technologies, in the food and agriculture industry. Based on the IoT technology, MAFARA launched six "IoT based farm" project in 2007. IoT based farm project includes IoT based greenhouse system project, and it shows drastic efficiency in terms of cost reduction. When it comes to the productivity, however, the effect of IoT based greenhouse system is still ambiguous. In this regard, this study conducted systems analysis and design for IoT based tomato greenhouse in order to help farmers' decision making related to the productivity by establishing standardized database structure and designing output form to analyze productivity indices. Proposed systems analysis and design can be utilized as a data analysis tools by farmers. Productivity data from the proposed systems is can be used by researchers to identify the relationship among environment, plant growth and productivity. Policy makers also can refer to the data and output forms to predict the quantity of fruit during certain period and to revise production guideline more precisely.

• The Plant Pathology Journal
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• v.40 no.3
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• pp.310-321
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• 2024

Tomato yellow leaf curl virus (TYLCV) and tomato spotted wilt virus (TSWV) are well-known examples of the begomovirus and orthotospovirus genera, respectively. These viruses cause significant economic damage to tomato crops worldwide. Weeds play an important role in the ongoing presence and spread of several plant viruses, such as TYLCV and TSWV, and are recognized as reservoirs for these infections. This work applies a comprehensive approach, encompassing field surveys and molecular techniques, to acquire an in-depth understanding of the interactions between viruses and their weed hosts. A total of 60 tomato samples exhibiting typical symptoms of TYLCV and TSWV were collected from a tomato greenhouse farm in Nonsan, South Korea. In addition, 130 samples of 16 different weed species in the immediate surroundings of the greenhouse were collected for viral detection. PCR and reverse transcription-PCR methodologies and specific primers for TYLCV and TSWV were used, which showed that 15 tomato samples were coinfected by both viruses. Interestingly, both viruses were also detected in perennial weeds, such as Rumex crispus, which highlights their function as viral reservoirs. Our study provides significant insights into the co-occurrence of TYLCV and TSWV in weed reservoirs, and their subsequent transmission under tomato greenhouse conditions. This project builds long-term strategies for integrated pest management to prevent and manage simultaneous virus outbreaks, known as twindemics, in agricultural systems.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.357-364
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• 2023

In this study, we propose a ripe tomato bunch localization method based on convolutional neural networks, to be applied in robotic harvesting systems. Tomato images were obtained from a smart greenhouse at the Rural Development Administration (RDA). The sample images for training were extracted based on tomato maturity and resized to 128 × 128 pixels for use in the classification model. The model was constructed based on four-layer convolutional neural networks, and the classes were determined based on stage of maturity, using a Softmax classifier. The localization of the ripe tomato bunch region was indicated on a class activation map. The class activation map could show the approximate location of the tomato bunch but tends to present a local part or a large part of the ripe tomato bunch region, which could lead to poor performance. Therefore, we suggest a recursive method to improve the performance of the model. The classification results indicated that the accuracy, precision, recall, and F1-score were 0.98, 0.87, 0.98, and 0.92, respectively. The localization performance was 0.52, estimated by the Intersection over Union (IoU), and through input recursion, the IoU was improved by 13%. Based on the results, the proposed localization of the ripe tomato bunch area can be incorporated in robotic harvesting systems to establish the optimal harvesting paths.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.373-379
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• 2019

Smart-farm has been spreading across Korea to improve the labor efficiency and productivity of greenhouse crops. Although notable improvements have been made in the monitoring technologies and environmental-controlling systems in greenhouses, only a few simple decision-support systems are available for predicting the optimum environmental conditions for crop growth. In this study, a tomato growth model (GreenTom), which was developed by Seoul National University in 1997, was calibrated and validated to examine if the model can be used as a decision-supporting system. The original GreenTom model was not able to simulate artificial defoliation, which resulted in overestimation of the leaf area index in the late growth. Thus, an algorithm for simulating the artificial defoliation was developed and added to the original model. The node development, leaf growth, stem growth, fruit growth, and leaf area index were generally well simulated by the modified model indicating that the model could be used effectively in the decision-making of smart greenhouse.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.1
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• pp.37-42
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• 2012

Improvement of plant growth by Methylotrophic bacteria can be influenced through alterations in growth modulating enzymes or hormones, especially by decreasing ethylene levels enzymatically by 1-aminocyclopropane-1-carboxylate (ACC) deaminase or by production of indole-3-acetic acid (IAA). In this study, the effect of seven strains of Methylobacterium on seedling ethylene emission of tomato and red pepper plants was evaluated under greenhouse condition. Ethylene emission was lowest in Methylobacterium oryzae CBMB20 inoculated tomato plants and CBMB110 inoculated red pepper plants at 47 days after sowing (DAS). However, at 58 DAS all inoculated plants showed almost similar pattern of ethylene emission. Methylobacterium inoculated tomato and red pepper plants showed significantly less ethylene emission compared to control. Our results demonstrated that Methylobacterium spp. inoculation promotes plant growth due to the reduction of ethylene emission and therefore can be potentially used in sustainable agriculture production systems.

• Journal of Bio-Environment Control
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• v.15 no.3
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• pp.211-216
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• 2006

This study was carried out to investigate the effect of greenhouse cooling by a geothermal heat pump system on greenhouse temperature and growth of vegetable transplants in summer season. Greenhouse air temperature in day time was $3-4^{\circ}C$ lower in fog plus shading system than in shading, while in night time that was $5-7^{\circ}C$ lower in geothermal heat pump (GHP) plus shading system compared to shading or fogplus shading. system. Plant height of cucumber, tomato and hot pepper transplants was shortened in GHP plus shading compared to shading or fog plus shading system. And Leaf area and dry weight were slightly decreased in GHP plus shading compared to the other systems. Therefore, healthy transplant index on cucumber, tomato and hot pepper was higher in GHP plusshading than in shading or fogplusshading system.

• Horticulture, Environment, and Biotechnology : HEB
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• v.59 no.6
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• pp.827-833
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• 2018

Plasma lighting systems have been engineered to simulate sunlight. The objective of this study was to determine the effects of plasma lighting on tomato plant growth, photosynthetic characteristics, flowering rate, and physiological disorders. Tomato plants were grown in growth chambers at air temperatures of $25/23^{\circ}C$ (light/dark period), in a $16h\;day^{-1}$ light period provided by four different light sources: 1 kW and 700 W sulfur plasma lights (1 SPL and 0.7 SPL), 1 kW indium bromide plasma light, and 700 W high pressure sodium lamp (0.7 HPS) as a control. The totaldry weight and leaf area at 0.7 SPL were approximately 1.2 and 1.3 times greater, respectively, than that of 0.7 HPS at the 62 days after sowing (DAS). The maximum light assimilation rate was observed at 1 SPL at the 73 DAS. In addition, the light compensation and saturation points of the plants treated with plasma lighting were 98.5% higher compared with HPS. Those differences appeared to be related to more efficient light interception, provided by the SPL spectrum. The percentage of flowering at 0.7 SPL was 30.5%, which was higher than that at 0.7 HPS; however, there were some instances of severe blossom end rot. Results indicate that plasma lighting promotes tomato growth, flowering, and photosynthesis. Therefore, a plasma lighting system may be a valuable supplemental light source in a greenhouse or plant factory.

• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.289-295
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• 2006

A computational fluid dynamics (CFD) numerical model has been developed to effectively study the ventilation efficiency of multi-span greenhouses with internal crops. As the first step of the study, the internal plants of the CFD model had to be designed as a porous media because of the complexity of its physical shapes. In this paper, the results of the wind tunnel tests were introduced to find the aerodynamic resistance of the plant canopy. The Seogun tomato was used for this study which made significant effects on thermal and mass exchanges with the adjacent air as well as internal airflow resistance. With the main factors of wind speed, static pressure, and density of plant canopy, the aerodynamic resistance factor was statically found. It was finally found to be 0.26 which will be used later as an input data of the CFD model. Moreover, the experimental procedure of how to find the aerodynamic resistance of various plants using, wind tunnel was established through this study.

• Journal of Bio-Environment Control
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• v.23 no.1
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• pp.11-18
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• 2014

To investigate the influence of surrounding environment on the plant temperature and examine the effect of plant temperature control by fogging and airflow, plant temperature of tomato, inside and outside air temperature and relative humidity, solar radiation and wind speed were measured and analyzed under various experimental conditions in plastic greenhouse with two-fluid fogging systems and air circulation fans. According to the analysis of plant temperature and the change of inside and outside air temperature in each condition, inside air temperature and plant temperature were significantly higher than outside air temperature in the control and shading condition. However, in the fogging condition, inside air temperature was lower or slightly higher than outside air temperature. It showed that plant temperature could be kept with the temperature similar to or lower than inside air temperature in fogging and airflow condition. To derive the relationship between surrounding environmental factor and plant temperature, we did multiple regression analysis. The optimum regression equation for the temperature difference between plant and air included solar radiation, wind speed and vapor pressure deficit and RMS error was $0.8^{\circ}C$. To investigate whether the fogging and airflow contribute to reduce high temperature stress of plant, photosynthetic rate of tomato leaf was measured under the experimental conditions. Photosynthetic rate was the highest when using both fogging and airflow, and then fogging, airflow and lastly the control. So, we could assume that fogging and airflow can make better effect of plant temperature control to reduce high temperature stress of plant which can increase photosynthetic rate. It showed that the temperature difference between plant and air was highly affected by surrounding environment. Also, we could estimate plant temperature by measuring the surrounding environment, and use it for environment control to reduce the high temperature stress of plant. In addition, by using fogging and airflow, we can decrease temperature difference between plant and air, increase photosynthetic rate, and make proper environment for plants. We could conclude that both fogging and airflow are effective to reduce the high temperature stress of plant.