• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.25-30
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• 1999

The effectiveness of many greenhouse environment control methodologies depends on the growth information of crops. Acquisition of the growth information of crops requires a non-invasive and continuous monitoring method. Crop growth monitoring system using digital imaging technique was developed to conduct non-destructive and intact plant growth analyses. The monitoring system automatically measures crop growth information sends an appropriate control signal to the nutrient solution supplying system. To develop the monitoring system, a linear model that explains the relationship between the fresh weight and the top projected leaf area of a lettuce plant was developed from an experiment. The monitoring system was evaluated buy successive lettuce growing experiments. Results of the experiments showed that the developed system could estimate the fresh weight of lettuce from a lettuce image by using the linear model and generate an EC control signal according to the lettuce growth stage.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.258-263
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• 2005

The purpose of this research is to present a practical method for efficiently monitoring a reliability growth process using AMSAA(Army Materiel Systems Analysis Activity) reliability growth model. The presented method is viable for identifying failure modes, incorporating design changes and monitoring reliability progress on an on-going basis during the early stages of a product development program. According to the Application Guide for EN 50126(RAM part for Rolling Stock), reliability growth monitoring is essential part of the main tasks of design phase in RAM growth monitoring. Implementation of reliability growth management program will provide very useful information on concept selection, product/process reliability, and cost effectiveness without too much time, money and engineering effort being spent on the development of failure suspect parts.

• Microbiology and Biotechnology Letters
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• v.17 no.3
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• pp.241-246
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• 1989

Continuous on-line monitoring of cell concentration and growth rate in aerobic batch fermentation process was carried out by analyzing the exhaust gas composition of tormentor with a quadrupole mass spectrometer. From the mass spectrometric analyses of major gaseous components, i.e. $N_2$, $O_2$, $CO_2$ and $H_2O$, and the material balance equations for oxygen and carbon dioxide, oxygen uptake rate (OUR) rind carbon dioxide evolution rate (CER) were instantaneously calculated using a computer (16-bit IBM PC-AT) interfaced to a quadrupole mass spectrometer. The calculated OUR and CER data were used for the estimation of cell concentration and growth rate of Candida utilis during batch culture. It was found that the cell concentration could be satisfactorily estimated from the data of OUR arid CER during the culture and this method could be successfully und for the continuous monitoring of cell growth and growth rate.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.373-380
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• 1998

The contribution of this paper is to provide the methods for the production automation of potato microtuber using the vision process in growth monitoring. The first method deals with computation for the growth density in the primary growth process. The second method addresses cognition process to identify the number and the volume of potato microtuber in secondary growth process. The third is to decide whether potato microtubers are infected by a virus or bacteria in growth process. The computation for the growth density in the primary growth process uses the method of Labeling. The second and third methods use template matching based on color patterns. With the developed method using vision process, this experiment is capable of discriminating weekly growth-rate in primary growth process, 85% cognition rate in secondary process and identifying whether there are infections. Therefore, we conclude that our experimental results are capable of growth monitoring for mass production of potato microtubers.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of Microbiology and Biotechnology
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• v.19 no.10
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• pp.1250-1258
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• 2009

Bacillus spp., as a type of plant growth-promoting rhizobacteria (PGPR), were studied with regards promoting plant growth and inducing plant systemic resistance. The results of greenhouse experiments with tobacco plants demonstrated that treatment with the Bacillus spp. significantly enhanced the plant height and fresh weight, while clearly lowering the disease severity rating of the tobacco mosaic virus (TMV) at 28 days post-inoculation (dpi). The TMV accumulation in the young non-inoculated leaves was remarkably lower for all the plants treated with the Bacillus spp. An RT-PCR analysis of the signaling regulatory genes Coil and NPR1, and defense genes PR-1a and PR-1b, in the tobacco treated with the Bacillus spp. revealed an association with enhancing the systemic resistance of tobacco to TMV. A further analysis of two expansin genes that regulate plant cell growth, NtEXP2 and NtEXP6, also verified a concomitant growth promotion in the roots and leaves of the tobacco responding to the Bacillus spp.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.3
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• pp.162-178
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• 2017

Remote sensing can be used to provide information about the monitoring of crop growth condition. Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to assess weather UAV aerial images are suitable for the monitoring of highland Kimchi cabbage. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110, IXUS/ELPH camera during farming season from 2015 to 2016 in the main production area of highland Kimchi cabbage, Anbandegi, Maebongsan, and Gwinemi. The Normalized Difference Vegetation Index (NDVI) by using UAV images was stable and suitable for monitoring of Kimchi cabbage situation. There were strong relationships between UAV NDVI and the growth parameters (the plant height and leaf width) ($R^2{\geq}0.94$). The tendency of UAV NDVI according to Kimchi cabbage growth was similar in the same area for two years (2015~2016). It means that if UAV image may be collected several years, UAV images could be used for estimation of the stage of growth and situation of Kimchi cabbage cultivation.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.795-800
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• 2011

In this paper, to promote the production of agricultural products, it is goal to design and implement the growth environmental management monitoring system. Based on the IT convergence technology, it consists of four components such as sensor nodes to sense environmental factors, sink nodes to communicate with sensors, gateway to link sinknodes to monitoring system, and monitoring software. With monitoring process for temperature and humidity, we can obtain the bast growth environment to be maintained deviation value 10% for temperature and humidity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.1-9
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• 2011

In this paper, Wireless sensor network technology applied to various greenhouse agro-industry items such as horticulture and local specialty etc., we was constructed automatic control system for optimum growth environment by measuring growth status and environmental change. existing monitoring systems of greenhouse gather information about growth environment depends on the temperature. but in this system, Can be efficient collection and control of information to construct wireless sensor network by growth measurement sensor and environment monitoring sensor inside of the greenhouse. The system is consists of sensor manager for information processing, an environment database that stores information collected from sensors, the GUI of show the greenhouse status, it gather soil and environment information to soil and environment(including weather) sensors, growth measurement sensor. In addition to support that soil information service shows the temperature, moisture, EC, ph of soil to user through the interaction of obtained data and Complex Growth Environment information service for quality and productivity can prevention and response by growth disease or disaster of greenhouse agro-industry items how temperature, humidity, illumination acquiring informationin greenhouse(strawberry, ginseng). To verify the executability of the system, constructing the complex growth environment measurement system using wireless sensor network in greenhouse and we confirmed that it is can provide our optimized growth environment information.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.301-309
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• 2012

In this paper, a real-time monitoring system based on WSN is designed and implemented to monitor livestock growth environment information which includes the temperature, humidity and harmful gases such as $CO_{2},\;CO,\;NH_{3},\;H_{2}S$ and so on. The proposed system consists of the wireless sensor nodes, the monitoring management device, the management server and the user interface program based on PC/Smart phone. To verify the performance of the implemented system, gas measurement experiments are performed in laboratory environment by using the designed wireless sensor nodes. And it is able to estimate the concentration of gases. The implemented system is able to monitor the proposed environmental element information through the developed GUI.