Hostname: page-component-74656f9884-2dmjx Total loading time: 0 Render date: 2026-11-08T15:04:25.628Z Has data issue: false hasContentIssue false
  • English
  • Français

Sensor-Controlled Hooded Sprayer for Row Crops

Published online by Cambridge University Press:  12 June 2017

James E. Hanks  and
James L. Beck
James E. Hanks
Affiliation:
USDA-ARS, Application and Production Technology Research Unit, Stoneville, MS 38776
James L. Beck
Affiliation:
Patchen, Inc., A Subsidiary of Deere & Company, Los Gatos, CA 95030
Get access Rights & Permissions [Opens in a new window]

Abstract

Methods were developed and evaluated that utilize state of the art weed-sensing technology in row-crop production systems. Spectral differences in green living plants and bare soil allowed ‘real-time’ weed detection, with intermittent spraying of herbicide only where weeds were present. Sensor units were mounted in 0.7-m-wide hooded sprayers providing sensors with an unobstructed view of the area between soybean rows. Single hood and commercial-size eight-row systems were evaluated, and savings in glyphosate spray solution applied using sensors ranged from 63 to 85%, compared to conventional hooded spray systems with continuous application. Weed control by the sensor-controlled spray system was equal to the conventional system. This technology can significantly reduce herbicide usage and decrease production cost without reducing weed control.

Keywords

Glyphosate, N-(phosphonomethyl)glycinesoybean, Glycine max (L.) Merr. ‘Deltapine 3588.'Application technologyintermittent sprayingoptoelectronicselective applicatorspectral reflectancespot sprayingSorghum halepenseIpomoea hederaceaIpomoea lacunosaSida spinosaCyperus rotundusCYPROIPOHEIPOLASIDSPSORHACRADA, Cooperative Research and Development AgreementEPROM, Erasable Programmable Read Only MemoryFOV, field of viewWAT, weeks after treatment

Information

Type
Research
Information
Weed Technology , Volume 12 , Issue 2 , June 1998 , pp. 308 - 314
Copyright
Copyright © 1998 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Literature Cited

Carpenter, W. D. and Derting, C. W. 1992. What is in the future? In McWhorter, C. G. and Abernathy, J. R., eds., Weeds of Cotton: Characterization and Control. Reference Book Series, No. 2. Memphis, TN: The Cotton Foundation. pp. 579–604.Google Scholar
Chandler, J. M. and Cooke, F. T. 1992. Economics of cotton losses caused by weeds. In McWhorter, C. G. and Abernathy, J. R., eds. Weeds of Cotton: Characterization and Control. Reference Book Series, No. 2. Memphis, TN: The Cotton Foundation. pp. 85–115.Google Scholar
Felton, W. L., Doss, A. F., Nash, P. G., and McCloy, K. R. 1991. To selectively spot spray weeds. Am. Soc. Agric. Eng. Symp. 11:427–432.Google Scholar
Felton, W. L. and McCloy, K. R. 1992. Spot spraying. Agric. Eng. 73:9–12.Google Scholar
Guyer, D. E., Miles, G. E., Schreiber, M. M., Mitchell, O. R., and Vanderbilt, V. C. 1986. Machine vision and image processing for plant identification. Trans. ASAE 29:1500–1506.Google Scholar
Haggar, R. J., Stent, C. J., and Isaac, S. 1983. A prototype hand-held patch sprayer for killing weeds activated by spectral differences in crop/weed canopies. J. Agric. Eng. Res. 28:349–358.CrossRefGoogle Scholar
Hanks, J. E. 1995. Sensor-controlled sprayers for herbicide application. Proc. Natl. Conf. Pestic. Appl. Technol. Guelph, ON: University of Guelph. pp. 176–179.Google Scholar
Mortensen, D. A., Johnson, G. A., and Young, L. J. 1993. Weed distributions in agricultural fields. In Soil Specific Crop Management. Madison, WI: Am. Soc. Agron. Press. pp. 113–124.Google Scholar
Navas, M. L. 1991. Using plant population biology in weed research: a strategy to improve weed management. Weed Res. 31:171–179.Google Scholar
Reusenbach, H. V. 1974. Pneumatic systems for the non-contact scanning of plants. Proc. CIGR 74-III-103. Paris, France: Commission Internationale du Genie Rurale.Google Scholar
Shearer, S. A. and Jones, P. T. 1991. Selective application of post-emergence herbicides using photoelectrics. Trans. ASAE 34:1661–1666.Google Scholar
Thornton, P. K., Fawcett, R. H., Dent, J. B., and Perkins, T. J. 1990. Spatial weed distribution and economic thresholds for weed control. Crop Prot. 9:337–342.Google Scholar
Thonke, K. E. 1988. Research on pesticide use in Denmark to meet political needs. Aspects Appl. Biol. 18:327–329.Google Scholar
Van Groenendael, J. M. 1988. Patchy distribution of weeds and some implications for modeling population dynamics: a short literature review. Weed Res. 28:437–441.CrossRefGoogle Scholar
Von Bargen, K., Meyer, G. E., Mortensen, D. A., Merrit, S. J., and Woebbecke, D. M. 1992. Red-near infrared reflectance sensor system for detecting plants. In DeShazer, J. A. and Meyer, G. E., eds. Optics in Agriculture and Forestry. Proc. SPIE. Bellingham, WA: The International Society for Optical Engineering, Vol. 1836, pp. 231–238.Google Scholar