• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.103-109
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• 2018

Purpose: This study has been conducted to develop a potato yield monitoring system, consisting of a segmentation algorithm to detect potatoes scattered on a soil surface and a counting system to count the number of potatoes and convert the data from two-dimensional images to masses. Methods: First, a segmentation algorithm was developed using top-hat filtering and processing a series of images, and its performance was evaluated in a stationary condition. Second, a counting system was developed to count the number of potatoes in a moving condition and calculate the mass of each using a mass estimation equation, where the volume of a potato was obtained from its two-dimensional image, and the potato density and a correction factor were obtained experimentally. Experiments were conducted to segment potatoes on a soil surface for different potato sizes. The counting system was tested 10 times for 20 randomly selected potatoes in a simulated field condition. Furthermore, the estimated total mass of the potatoes was compared with their actual mass. Results: For a $640{\times}480$ image size, it took 0.04 s for the segmentation algorithm to process one frame. The root mean squared deviation (RMSD) and average percentage error for the measured mass of potatoes using this counting system were 12.65 g and 7.13%, respectively, when the camera was stationary. The system performance while moving was the best in L1 (0.313 m/s), where the RMSD and percentage error were 6.92 g and 7.79%, respectively. For 20 newly prepared potatoes and 10 replication measurements, the counting system exhibited a percentage error in the mass estimation ranging from 10.17-13.24%. Conclusions: At a travel speed of 0.313 m/s, the average percentage error and standard deviation of the mass measurement using the counting system were 12.03% and 1.04%, respectively.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1324-1337
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• 2019

This study set out to investigate an energy harvesting device to ensure stable energy supply to batteries and data collection devices and a monitoring system for acer pictum sap to check collected data. Acer pictum sap farmers have written down weather information and yield of acer pictum sap manually for data storage. Since the job is done manually, there are many missing values in their data. In addition, it is not easy to manage batteries due to the characteristics of the areas where acer pictum sap is collected. The present study thus decided to build an energy harvesting device based on new renewable energy to ensure stable energy supply by taking into consideration power load, daily power consumption, and number of days with no sunshine for various devices. For a monitoring system, the investigator proposed a JSP-based web page to monitor temperature, humidity, volume of collected water, and battery state in real time. The proposed energy harvesting device was applied to reduce missing values in data. It promoted stable energy supply to the batteries and data collection devices, reducing the percentage of missing values in data from 30.55% to 0%.

• Analytical Science and Technology
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• v.11 no.1
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• pp.36-41
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• 1998

A gas chromatography-mass spectrometry method for the determination of 5-fluorourasil in human plasma is described. The method involves a single extraction procedure with 10 ml of isopropanol-ether(20:80) solution and pentafluoro-benzylation. Samples were injected using an automatic injector, followed by separation on a nonpolar capillary column and detection with a mass selective detector(MSD). No endogeneous compounds were found to interfere. The detection limit, based upon an assayed plasma volume of 0.5, was 3 ng/ml. The extraction yield was found to be above 80%. Plasma 5-FU concentrations were determined by this method in about 500 plasma samples from cancer patients undergoing treatment with 5-FU. This method is suitable for monitoring of 5-FU in plasma of cancer patients.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.28-38
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• 2001

Traffic information can be broadly categorized into point information and spatial information. Point information can be obtained by chocking only the presence of vehicles at prespecified points(small area), whereas spatial information can be obtained by monitoring large area of traffic scene. To obtain spatial information by image processing, we need to track vehicles in the whole area of traffic scene. Image detector system based on global tracking consists of video input, vehicle detection, vehicle tracking, and traffic information measurement. For video input, conventional approaches used auto iris which is very poor in adaptation for sudden brightness change. Conventional methods for background generation do not yield good results in intersections with heave traffic and most of the early studies measure only point information. In this paper, we propose user-controlled iris method to remedy the deficiency of auto iris and design flame difference-based background generation method which performs far better in complicated intersections. We also propose measurement method for spatial traffic information such as interval volume/lime/velocity, queue length, and turning/forward traffic flow. We obtain measurement accuracy of 95%∼100% when applying above mentioned new methods.