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Applications of Unmanned Aerial Vehicles in Weed Science

Published online by Cambridge University Press:  01 June 2017

J. M. Prince Czarnecki
Affiliation:
Geosystems Research Institute, Mississippi State University, Box 9627, Mississippi State, Mississippi, 39762, USA
S. Samiappan
Affiliation:
Geosystems Research Institute, Mississippi State University, Box 9627, Mississippi State, Mississippi, 39762, USA
L. Wasson
Affiliation:
Geosystems Research Institute, Mississippi State University, Box 9627, Mississippi State, Mississippi, 39762, USA
J. D. McCurdy
Affiliation:
Department of Plant and Soil Sciences, Mississippi State University, Box 9555, Mississippi State, Mississippi, 39762, USA
D. B. Reynolds
Affiliation:
Department of Plant and Soil Sciences, Mississippi State University, Box 9555, Mississippi State, Mississippi, 39762, USA
W. P. Williams
Affiliation:
US Department of Agriculture, Agricultural Research Service, Box 5367, Mississippi State, Mississippi, 39762, USA
R. J. Moorhead
Affiliation:
Geosystems Research Institute, Mississippi State University, Box 9627, Mississippi State, Mississippi, 39762, USA
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Abstract

For most producers, unmanned aerial vehicles (UAV) are a novelty that has been little employed in their agricultural operations. An UAV will not fix every problem on the farm, but there are some practical applications for which UAVs have demonstrated value. Three examples of how UAVs have been used in weed science applications are presented here; the methods are transferable to other agricultural commodities with similar characteristics. The first of these is quantification of the extent and severity of non-target herbicide injury. The second application is calculation of spray thresholds based on weed populations. The third application is development of site-specific herbicide treatment.

Type
UAV applications
Copyright
© The Animal Consortium 2017 

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References

Bagavathiannan, MV and Norsworthy, JK 2012. Late-season seed production in arable weed communities: management implications. Weed Science 60, 325334.CrossRefGoogle Scholar
Bell, GE and Xiong, X 2008. Chapter 36: The History, Role, and Potential of Optical Sensing for Practical Turf Management. In Handbook of Turfgrass Management and Physiology, edited by M Pessarakli, CRC Press, Boca Raton, Florida 641660.Google Scholar
Carrow, RN, Krum, JM, Flitcroft, I and Cline, V 2010. Precision turfgrass management: challenges and field applications for mapping turfgrass soil and stress. Precision Agriculture 11, 115134.CrossRefGoogle Scholar
Chapman, SC, Merz, T, Chan, A, Jackway, P, Hrabar, S, Dreccer, MF, et al. 2014. Pheno-copter: a low-altitude, autonomous remote-sensing robotic helicopter for high-throughput field-based phenotyping. Agronomy 4, 279301.CrossRefGoogle Scholar
Dicke, D, Jacobi, J and Büchse, A 2012. Quantifying herbicide injuries in maize by use of remote sensing. Julius-Kühn-Archiv 434, 199205.Google Scholar
Heap, I 2016. The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org (retrieved 30/11/16).Google Scholar
Longchamps, L, Panneton, B, Simard, M-J and Leroux, GD 2014. An imagery-based weed cover threshold established using expert knowledge. Weed Science 62, 177185.CrossRefGoogle Scholar
Lopez‐Granados, F 2011. Weed detection for site‐specific weed management: mapping and real‐time approaches. Weed Research 51, 111.CrossRefGoogle Scholar
Miller, T, Street, JE, Buehring, N, Kanter, D, Walker, TW, Bond, JA, et al. 2008. Mississippi’s Rice Growers’ Guide. Mississippi State University. Extension Service Publication 2255. http://extension.msstate.edu/sites/default/files/publications/publications/p2255.pdf (retreived 12/12/16).Google Scholar
Pena, JM, Torres-Sanchez, J, de Castro, AI, Kelly, M and Lopez-Granados, F 2013. Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images. PLOS One 8, e77151.CrossRefGoogle ScholarPubMed
Rasmussen, J, Nielsen, J, Garcia‐Ruiz, F, Christensen, S and Streibig, JC 2013. Potential uses of small unmanned aircraft systems (UAS) in weed research. Weed Research 53, 242248.CrossRefGoogle Scholar
Shaner, DL and Beckie, HJ 2014. The future for weed control and technology. Pest management science 70, 13291339.CrossRefGoogle ScholarPubMed
Tanimoto, SL 1981. Template matching in pyramids. Computer Graphics and Image Processing 16, 356369.CrossRefGoogle Scholar

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