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פותח על ידי קלירמאש פתרונות בע"מ -
Sensing technologies for precision specialty crop production
Year:
2010
Authors :
אלחנתי, ויקטור
;
.
Volume :
74
Co-Authors:
Lee, W.S., University of Florida, Agricultural and Biological Engineering Department, P.O. Box 110570, Frazier Rogers Hall, Museum Road, Gainesville, FL 32611-0570, United States
Alchanatis, V., Department of Sensing, Information and Mechanization Engineering, Institute of Agricultural Engineering, ARO - The Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Yang, C., U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Kika de la Garza Subtropical Agricultural Research Center, Integrated Farming and Natural Resources Research Unit, 2413 E. Highway 83, Weslaco, TX 78596, United States
Hirafuji, M., National Agriculture and Food Research Organization, National Agricultural Research Center and University of Tsukuba, 3-1-1 Kannondai Tsukuba, Ibaraki 305-8666, Japan
Moshou, D., Aristotle University of Thessaloniki (A.U.Th.), Agricultural Engineering Laboratory, Faculty of Agriculture, P.O. 275, Egnatias street 124, 54124, Thessaloniki, Greece
Li, C., Biological and Agricultural Engineering, University of Georgia, 2329 Rainwater Road, Tifton, GA 31793, United States
Facilitators :
From page:
2
To page:
33
(
Total pages:
32
)
Abstract:
With the advances in electronic and information technologies, various sensing systems have been developed for specialty crop production around the world. Accurate information concerning the spatial variability within fields is very important for precision farming of specialty crops. However, this variability is affected by a variety of factors, including crop yield, soil properties and nutrients, crop nutrients, crop canopy volume and biomass, water content, and pest conditions (disease, weeds, and insects). These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote sensing, satellite imagery, thermal imaging, RFID, and machine olfaction system, among others. Sensing techniques for crop biomass detection, weed detection, soil properties and nutrients are most advanced and can provide the data required for site specific management. On the other hand, sensing techniques for diseases detection and characterization, as well as crop water status, are based on more complex interaction between plant and sensor, making them more difficult to implement in the field scale and more complex to interpret. This paper presents a review of these sensing technologies and discusses how they are used for precision agriculture and crop management, especially for specialty crops. Some of the challenges and considerations on the use of these sensors and technologies for specialty crop production are also discussed. © 2010 Elsevier B.V.
Note:
Related Files :
computer vision
Crop Production
disease incidence
Nutrients
precision agriculture
remote sensing
Review
thermal imaging
עוד תגיות
תוכן קשור
More details
DOI :
10.1016/j.compag.2010.08.005
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
סקירה
;
.
Language:
אנגלית
Editors' remarks:
ID:
19030
Last updated date:
02/03/2022 17:27
Creation date:
16/04/2018 23:26
Scientific Publication
Sensing technologies for precision specialty crop production
74
Lee, W.S., University of Florida, Agricultural and Biological Engineering Department, P.O. Box 110570, Frazier Rogers Hall, Museum Road, Gainesville, FL 32611-0570, United States
Alchanatis, V., Department of Sensing, Information and Mechanization Engineering, Institute of Agricultural Engineering, ARO - The Volcani Center, P.O. Box 6, Bet Dagan 50250, Israel
Yang, C., U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Kika de la Garza Subtropical Agricultural Research Center, Integrated Farming and Natural Resources Research Unit, 2413 E. Highway 83, Weslaco, TX 78596, United States
Hirafuji, M., National Agriculture and Food Research Organization, National Agricultural Research Center and University of Tsukuba, 3-1-1 Kannondai Tsukuba, Ibaraki 305-8666, Japan
Moshou, D., Aristotle University of Thessaloniki (A.U.Th.), Agricultural Engineering Laboratory, Faculty of Agriculture, P.O. 275, Egnatias street 124, 54124, Thessaloniki, Greece
Li, C., Biological and Agricultural Engineering, University of Georgia, 2329 Rainwater Road, Tifton, GA 31793, United States
Sensing technologies for precision specialty crop production
With the advances in electronic and information technologies, various sensing systems have been developed for specialty crop production around the world. Accurate information concerning the spatial variability within fields is very important for precision farming of specialty crops. However, this variability is affected by a variety of factors, including crop yield, soil properties and nutrients, crop nutrients, crop canopy volume and biomass, water content, and pest conditions (disease, weeds, and insects). These factors can be measured using diverse types of sensors and instruments such as field-based electronic sensors, spectroradiometers, machine vision, airborne multispectral and hyperspectral remote sensing, satellite imagery, thermal imaging, RFID, and machine olfaction system, among others. Sensing techniques for crop biomass detection, weed detection, soil properties and nutrients are most advanced and can provide the data required for site specific management. On the other hand, sensing techniques for diseases detection and characterization, as well as crop water status, are based on more complex interaction between plant and sensor, making them more difficult to implement in the field scale and more complex to interpret. This paper presents a review of these sensing technologies and discusses how they are used for precision agriculture and crop management, especially for specialty crops. Some of the challenges and considerations on the use of these sensors and technologies for specialty crop production are also discussed. © 2010 Elsevier B.V.
Scientific Publication
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