• Title/Summary/Keyword: Site-specific spraying

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Development of Real-time Precision Spraying System Using Machine Vision and DGPS (기계시각과 DGPS를 이용한 실시간 정밀방제 시스템 개발)

  • 조성인;정재연;김유용;남기찬;이중용
    • Journal of Biosystems Engineering
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    • v.27 no.2
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    • pp.143-150
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    • 2002
  • Several researches for site-specific weed control have tried to increase accuracy of weed detection with machine vision technique. However, there is a problem which needs substantial time to perform site-specific spraying. Therefore, new technology for real-time precision spraying system is needed. This research was executed to develope the new technology to estimate weed density and size in real time, and to conduct a real-time site-specific spraying. It would effectively reduce herbicide amounts applied for a crop field. The real-time precision spraying system consisted of a Differential Global Positioning System (DGPS) with an error of 2 cm, a machine vision system, a geomagnetic sensor for correction of view point of CCD camera and an automatic sprayer with separately controlled nozzle. The weed density was calculated with comparison between position information and a pre-designed electronic map. The position information was obtained in real time using the DGPS and the machine vision. The electronic map contained a position database of crops automatically constructed when seeding. The developed system was tested on an experimental field of Seoul National University. Success rate of the spraying was about 61%.

The Analysis of Herbicide Penetration with Spray Deposit Characteristics on Plant Leaves (잎 표면의 분무입자 부착특성에 따른 제초제 침투성 분석)

  • 장영창
    • Journal of Biosystems Engineering
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    • v.25 no.4
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    • pp.287-292
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    • 2000
  • The herbicide penetration on weed leaves was spatially analyzed by using chlorophyll fluorescent emission and machine vision technique. Velvetleaf and metribuzin were used as experimental materials in the study. The herbicide spray images were obtained by a combinaton of a fluorescent dye and a UV lighting system. The herbicide penetration was analyzed by means of detecting chlorophyll fluorescent emission under blue-green lighting. According to the experiment results, the number and the size of spray droplets decreased with coverage increasing. The herbicide penetrated mainly along leaf veins and the time for complete penetration over the whole leaf was approximately 100 minutes after herbicide spraying. When the coverage of herbicide droplets on the surface of leaves increased, the speed of herbicide penetration also increased. This study suggested a way of characerizing herbicide spatial penetration and distribution in leaves.

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Case Study: Cost-effective Weed Patch Detection by Multi-Spectral Camera Mounted on Unmanned Aerial Vehicle in the Buckwheat Field

  • Kim, Dong-Wook;Kim, Yoonha;Kim, Kyung-Hwan;Kim, Hak-Jin;Chung, Yong Suk
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.64 no.2
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    • pp.159-164
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    • 2019
  • Weed control is a crucial practice not only in organic farming, but also in modern agriculture because it can lead to loss in crop yield. In general, weed is distributed in patches heterogeneously in the field. These patches vary in size, shape, and density. Thus, it would be efficient if chemicals are sprayed on these patches rather than spraying uniformly in the field, which can pollute the environment and be cost prohibitive. In this sense, weed detection could be beneficial for sustainable agriculture. Studies have been conducted to detect weed patches in the field using remote sensing technologies, which can be classified into a method using image segmentation based on morphology and a method with vegetative indices based on the wavelength of light. In this study, the latter methodology has been used to detect the weed patches. As a result, it was found that the vegetative indices were easier to operate as it did not need any sophisticated algorithm for differentiating weeds from crop and soil as compared to the former method. Consequently, we demonstrated that the current method of using vegetative index is accurate enough to detect weed patches, and will be useful for farmers to control weeds with minimal use of chemicals and in a more precise manner.