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פותח על ידי קלירמאש פתרונות בע"מ -
A robotic monitoring system for diseases of pepper in greenhouse
Year:
2015
Authors :
איגנת, תימאה
;
.
אלעד, יגאל
;
.
בכר, אביטל
;
.
דומברובסקי, אביב
;
.
Volume :
Co-Authors:
Schor, N., Department of Industrial Engineering and Management, Ben-Gurion University of Negev, Beer- Sheva, Israel, Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Beit Dagan, Israel
Berman, S., Department of Industrial Engineering and Management, Ben-Gurion University of Negev, Beer- Sheva, Israel
Dombrovsky, A., Agricultural Research Organization, Volcani Center, Institute of Plant Sciences, Beit Dagan, Israel
Elad, Y., Department of Plant Pathology and Weed Research, Volcani Center, Beit Dagan, Israel
Ignat, T., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Beit Dagan, Israel
Bechar, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Beit Dagan, Israel
Facilitators :
From page:
627
To page:
634
(
Total pages:
8
)
Abstract:
Powdery mildew and tomato spotted wilt virus (TSWV) are the two main threats to pepper plants (Capsicum annuum) grown in greenhouses causing severe damage and yield loss. The paper reports the development of a robotic disease monitoring system for early detection of both threats. The research faced several challenges as, currently, algorithms for powdery mildew detection have only been implemented on other crops and there are no known algorithms for TSWV detection. Moreover, monitoring several diseases of pepper plants using a single monitoring system has not been reported. The system development was based on a holistic approach, integrating the design of both motion and perception systems. Preliminary results for TSWV detection are promising. Analysis of powdery mildew database is currently being conducted. The physical hardware system has been constructed and once the image processing algorithms are finalized, the system will be ready for extensive testing.
Note:
Related Files :
Agriculture
fungi
greenhouses
monitoring
powdery mildew
spectroscopy
Tomato spotted wilt virus
Viruses
עוד תגיות
תוכן קשור
More details
DOI :
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר מתוך כינוס
;
.
Language:
אנגלית
Editors' remarks:
ID:
21079
Last updated date:
02/03/2022 17:27
Creation date:
16/04/2018 23:41
Scientific Publication
A robotic monitoring system for diseases of pepper in greenhouse
Schor, N., Department of Industrial Engineering and Management, Ben-Gurion University of Negev, Beer- Sheva, Israel, Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Beit Dagan, Israel
Berman, S., Department of Industrial Engineering and Management, Ben-Gurion University of Negev, Beer- Sheva, Israel
Dombrovsky, A., Agricultural Research Organization, Volcani Center, Institute of Plant Sciences, Beit Dagan, Israel
Elad, Y., Department of Plant Pathology and Weed Research, Volcani Center, Beit Dagan, Israel
Ignat, T., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Beit Dagan, Israel
Bechar, A., Agricultural Research Organization, Volcani Center, Institute of Agricultural Engineering, Beit Dagan, Israel
A robotic monitoring system for diseases of pepper in greenhouse
Powdery mildew and tomato spotted wilt virus (TSWV) are the two main threats to pepper plants (Capsicum annuum) grown in greenhouses causing severe damage and yield loss. The paper reports the development of a robotic disease monitoring system for early detection of both threats. The research faced several challenges as, currently, algorithms for powdery mildew detection have only been implemented on other crops and there are no known algorithms for TSWV detection. Moreover, monitoring several diseases of pepper plants using a single monitoring system has not been reported. The system development was based on a holistic approach, integrating the design of both motion and perception systems. Preliminary results for TSWV detection are promising. Analysis of powdery mildew database is currently being conducted. The physical hardware system has been constructed and once the image processing algorithms are finalized, the system will be ready for extensive testing.
Scientific Publication
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