• 한국토양비료학회지
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• 제49권5호
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• pp.469-479
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• 2016

Kimchi cabbage is one of the most important vegetables in Korea and a target crop for market stabilization as well. In particular Kimchi cabbages in a highland area are very sensitive to the fluctuations in supply and demand. Yield variability due to growth conditions dictates the market fluctuations of Kimchi cabbage price. This study was carried out to understand the distribution of the highland Kimchi cabbage growth status in Anbandeok. Anbandeok area in Gangneung, Gangwon-do, Korea is one of the main producing districts of highland Kimchi cabbage. The highland Kimchi cabbage status map of each growth factor was obtained from unmanned aerial vehicle (UAV) imagery and field survey data. Six status maps include UAVRGB image map, normalized difference vegetation index (NDVI) distribution/anomaly map, Crop distribution map, Planting/Harvest distribution map, Growth parameter map and Growth disorder map. As a result, the highland Kimchi cabbage status maps from May 31 to Sep. 6 in 2016 were presented to show spatial variability in the field. The benefits of the highland Kimchi cabbage status map can be summarized as follows: crop growth monitoring, reference for field observations and survey, the relative comparison of the growth condition in field scale, evaluation of growth in comparison of average year, change detection of annual crops or planting areas, abandoned fields monitoring, prediction of harvest season etc.

• Journal of Biosystems Engineering
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• 제25권4호
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• pp.293-300
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• 2000

Automated greenhouse production system often require crop growth monitoring involving accurate quantification of plant physiological properties. Conventional methods are usually burdensome, inaccurate, and harmful to crops. A thermal image analysis system can accomplish rapid and accurate measurements of physiological-property changes of stressed crops. In this research a thermal imaging system was used to measure the leaf-temperature changes of several crops according to nutrient stresses. Thermal images were obtained from lettuce, cucumber, and pepper plants. Plants were placed in growth chamber to provide relatively constant growth environment. Results showed that there were significant differences in the temperature of stressed plants and non-stressed plants. In a case of the both N deficiency and excess, the leaf temperatures of cucumber were $2^{\circ}C$ lower than controlled temperature. The leaf temperature of cucumber was $2^{\circ}C$ lower than controlled temperature only when it was under N excess stress. For the potassium deficiency or excess stress, the leaf temperaures of cucumber and hot pepper were $2^{\circ}C$ lower than controls, respectively. The phosphorous deficiency stress dropped the leaf temperatures of cucumber and hot pepper $2^{\circ}C$ and $1.5^{\circ}C$ below than controls. However, the leaf temperature of lettuce did not change. It was possible to detect the changes in leaf temperature by infrared thermography when subjected to nutrition stress. Since the changes in leaf temperatures were different each other for plants and kinds of stresses, however, it is necessary to add a nutrient measurement system to a plant-growth monitoring system using thermography.

• Journal of Biosystems Engineering
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• 제23권3호
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• pp.285-290
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• 1998

Growth information of crops is essential for efficient control of greenhouse environment. However, a few non-invasive and continuous monitoring methods of crop growth has been developed. A computer vision system with a CCD camera and a frame grabber was developed to conduct non-destructive and intact plant growth analyses. The developed system was evaluated by conducting the growth analysis of lettuce. A linear model that explains the relationship between the relative crop coverage by the crop canopy and dry weight of a lettuce was presented. It was shown that this measurement method could estimate the dry weight from the relative crop coverage by the crop canopy. The result also showed that there was a high correlation between the projected top leaf area and the dry weight of the lettuce.

• 한국환경농학회지
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• 제33권4호
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• pp.414-418
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• 2014

BACKGROUND: Benzene, toluene, ethylbenzene and xylene (BTEX), which are volatile aromatic hydrocarbons and main constituents of gasoline, are neuro-carcinogenic organic pollutants in soil and groundwater. Korea Ministry of Environment has established the maximum permissible level of BTEX in arable soil to 1, 20, 50 and 15 mg/kg, respectively. METHODS AND RESULTS: To understand an arable soil contamination by BTEX, we collected 92 samples from the arable lands around oil reservoir, and analyzed the BTEX residue using a GC-MS with head-space sampler. A linear correlation between BTEX concentration and peak areas was detected with coefficient correlations in the range of 0.9807-0.9995. The method LOQ of BTEX was 0.002, 0.014, 0.084, and 0.038 mg/kg, respectively. Recoveries of 0.5 mg/kg BTEX were found to be 73.7-96.9%. The precision was reliable since RSD percentage (0.7-7.5%) was below 30, which was the normal percent value. Also, BTEX in all samples were detected under the LOQ. CONCLUSION: These results showed that the investigated arable soils around airport and oil reservoir in Korea were not contaminated by oils.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.60-60
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• 2017

It is important to measure the gas exchange activity of the crops in canopy scale to understand the process of biomass production and yield formation. Thermal imaging of the canopy surface temperature is a powerful tool to detect the gas exchange activity of the crop canopy. The simultaneous measurement of the canopy temperature and the meteorological data enables us to calculate the canopy diffusive conductance ($g_c$) based on the heat flux model (Monteith et al. 1973, Horie et al. 2006). It is, however, difficult to realize the long-term and continuous monitoring of $g_c$ due to the occurrence of the calculation error caused by the fluctuation of the environmental condition. This is partly because the model assumption is too simple to describe the meteorological and aerodynamic conditions of the crop canopy in the field condition. Here we report the novel method of the direct measurement of the aerodynamic resistance ($r_a$) of the crop canopy, which enables us the stable and continuous measurement of the gas exchange capacity of the crop plants. The modified heat balance model shows the improved performance to quantify $g_c$ under the fluctuating meteorological condition in the field. The relationship between $g_c$ and biomass production of rice and soybean varieties is also discussed in the presentation.

• 한국농공학회논문집
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• 제64권1호
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.479-484
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• 1999

Rice crop has relatively short growing season during the summer in Korea and, therefore, it is often difficult to acquire cloud-free imagery on time. This study was attempt to define the temporal characteristics of radar backscattering observed from satellite L-band SAR data on different growing stages of rice crop. Six scenes of multi-temporal JERS SAR data were obtained from the transplanting season to the harvesting month of October. Six layers of multi-temporal SAR data were registered on a common geographic coordinate system. Using topographic maps, field collected data, and Landsat TM data, several sample rice fields were delineated from the imagery and their relative radar backscatters were calculated by using a set of reference targets. The temporal pattern of radar backscattering was very distinctive by the growing stage of rice crop. It was also separable between two types of rice fields having different cultivation practices. Considering the temporal characteristics of radar backscattering observed from the study, it is obvious that a certain date of the growing season can be more effective to delineate the exact area of the cultivated rice crop field.

• 산업공학
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• 제16권2호
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• pp.248-257
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• 2003

In a heated rolling process of a steel mill where steel plates are pressed to a sheet coil by spreading and expanding, an irregularly-shaped head portion as well as a tail portion of the sheet coil need to be cropped. Any crop which is not clearly cut and separated from the sheet coil may cause critical damages to the facilities of the following processes. As the cropping process is performed very fast, human eyes are not proper for continuous monitoring of the cropping process. To solve this problem, we have developed a machine-vision based crop-drop detection system. The system also measures lengths of major and minor axes for the crops and thereby determines the proper crop size to minimize steel sheet losses.

• 반도체디스플레이기술학회지
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• 제18권4호
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• pp.129-133
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• 2019

In this paper, we developed a system to monitor the storage capacity of suction-type device such as vacuum cleaner or crop harvesters. The monitoring system consists of load cells and a differential pressure sensor which simultaneously monitor the weight and volume of the stock. Since weighing objects stored in storage containers alone cannot fully monitor the level of filling, more accurate monitoring can be achieved by monitoring volume and fusion with weight information. The volume was monitored using a phenomenon in which the flow rate of the inhaled air varies depending on the volume of the object filled in the storage container. In this paper, we developed a system to monitor the storage in three stages: low, medium and high.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.593-599
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• 2000

Accurate quantification of plant physiological properties is often necessary for optimal control of an automated greenhouse production system. Conventional crop growth monitoring systems are usually burdensome, inaccurate, and harmful to crops. A thermal image analysis system was used to accomplish rapid and accurate measurements of physiological-property changes of water-stressed crops. Thermal images were obtained from several species of plants that were placed in a growth chamber. Analyzing the images provided the pattern of temperature changes in a leaf and the amount of differences in the temperature of stressed plants and non-stressed plants.