Hostname: page-component-848d4c4894-m9kch Total loading time: 0 Render date: 2024-06-03T02:22:09.034Z Has data issue: false hasContentIssue false

Evaluation and Economics of a Machine-Vision Guided Cultivation Program in Broccoli and Lettuce

Published online by Cambridge University Press:  20 January 2017

Steven A. Fennimore*
Affiliation:
University of California, Davis, Salinas, CA 93905
Laura Tourte
Affiliation:
University of California, Santa Cruz County, Watsonville, CA 95076
John S. Rachuy
Affiliation:
University of California, Davis, Salinas, CA 93905
Richard F. Smith
Affiliation:
University of California, Monterey County, Salinas, CA 93901
Christina George
Affiliation:
University of California, Davis, CA 95616
*
Corresponding author's E-mail: safennimore@ucdavis.edu.

Abstract

Machine-vision cultivator guidance systems are commercially available to growers, but little work has been done to determine if these guidance systems can improve integrated weed management systems in vegetable crops. Studies were conducted in 2005 and 2006 in broccoli and lettuce to evaluate band-applied DCPA or pronamide, respectively, and four noncultivated bands ranging from 5.1 to 12.7 cm. DCPA or pronamide were applied in bands centered on the seed line at 0, 7.6 or 12.7 cm wide. A commercial machine-vision system was used to guide a commercial cultivator. Generally, weed densities and hand-weeding times were less where the DCPA band in broccoli or the pronamide band in lettuce were 7.6 or 12.7 cm wide compared to no herbicide. Weed densities were lowest in both crops where the noncultivated band width was 5.1 cm compared to 12.7-cm noncultivated bands. For broccoli in both 2005 and 2006, net returns above production costs were generally higher in the 7.6- and 12.7-cm-wide DCPA bands compared with the no-herbicide band. In lettuce in both years, the no-pronamide treatment had higher net returns, when compared with the 7.6- and 12.7-cm pronamide bands. Lettuce yields and higher net returns in the no-pronamide treatment compared to the 7.6- and 12.7-cm pronamide bands may be due to slight yield reduction from pronamide. Results suggest that pronamide was not needed during the dry months of the year when weed management tools such as hand-weeding and cultivation work very well. However, in periods of rainy weather when cultivation and hand-weeding are not possible, then pronamide would likely provide the greatest economic benefit. Given the large impact of cultivation on vegetable weed management programs, the greatest potential benefit of machine-vision guided cultivators is if they facilitate more timely and effective cultivation.

En el mercado para agricultores, varios sistemas automatizados de guía mecánica para el cultivo están disponibles, pero muy poca investigación ha sido llevada a cabo para determinar si estas guías pueden mejorar los sistemas de manejo integrado de maleza en los cultivos de vegetales. En 2005 y 2006 se llevaron a cabo estudios enfocados en brócoli y lechuga para evaluar DCPA aplicado en banda o el uso de pronamide, respectivamente. Como testigo, se incluyeron cuatro bandas no cultivadas de 5.1 a 12.7 cm. El DCPA o el pronamide se aplicaron en bandas en el lomo de los surcos en rangos de 0, 7.6 o 12.7 cm de ancho. Un sistema automatizado (Machine-Vision) fue utilizado para guiar el cultivador comercial. Generalmente, las densidades de maleza y el tiempo utilizado para el deshierbe manual fueron menores en donde la aplicación del DCPA en la línea de brócoli o el pronamide en la lechuga fue mediante bandas de 7.6 o 12.7 cm de ancho comparado con el testigo donde no se aplicó herbicida. Las densidades de maleza fueron menores en ambos cultivos donde el ancho de la banda no cultivada fue de 5.1 cm comparada con 12.7 cm de las bandas no cultivadas. Para el brócoli, tanto en 2005 como en 2006, las utilidades sobre los costos de producción fueron generalmente más altas en las bandas DCPA de 7.6 y 12.7 cm de ancho, comparadas con los testigos sin herbicida. Con respecto a la lechuga, en ambos años, el tratamiento sin pronamide tuvo mayores utilidades, cuando se comparó con las bandas de 7.6 y 12.7 cm con pronamide. Los rendimientos y las mayores utilidades de la lechuga en los tratamientos sin pronamide comparados con la aplicación de pronamide en bandas de 7.6 y 12.7 cm podrían deberse a una leve reducción en el volumen de la cosecha a partir del uso de pronamide. Los resultados sugieren que el uso de pronamide no fue necesario durante los meses secos del año cuando otros recursos para el manejo de maleza como el deshierbe manual y el barbecho funcionan muy bien. Sin embargo, en la temporada de lluvias cuando el barbecho y el deshierbe manual no son posibles, el uso del pronamide podría proporcionar el mayor beneficio económico. Tomando en cuenta el gran impacto que tienen los programas de manejo de maleza en el cultivo de vegetales, el mayor beneficio potencial de los cultivadores automatizados es que facilitan un manejo del cultivo oportuno y efectivo.

Type
Weed Management—Techniques
Copyright
Copyright © 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.)

References

Literature Cited

Bell, C. E. 1995. Broccoli (Brassica oleracea var. botrytis) yield loss from Italian ryegrass (Lolium perenne) interference. Weed Sci 43:117120.Google Scholar
Bruggeman, A. C., Mostaghimi, S., Holtzman, G. I., Shanholtz, V. O., Shukla, S., and Ross, B. B. 1995. Monitoring pesticides and nitrate in Virginia's groundwater—a pilot study. Trans. ASAE (Am. Soc. Agric. Eng.) 38:797807.Google Scholar
Cook, T. D. 1978. Soil Survey of Monterey County, California. Washington, DC: U.S. Department of Agriculture U.S. Forest Service and University of California Agricultural Experiment Station. 235 p.Google Scholar
Fennimore, S. A. and Umeda, K. 2003. Time of glyphosate application in glyphosate-tolerant lettuce. Weed Technol 17:738746.Google Scholar
Gast, R. 2008. Industry view of minor crop weed control. Weed Technol 22:385388.Google Scholar
Haar, M. J. and Fennimore, S. A. 2003. Evaluation of integrated practices for common purslane management in lettuce. Weed Technol 17:229233.Google Scholar
Hahn, R. H. and Rosentreter, E. E. 1994. American Society of Agricultural Engineers Standards Yearbook. 41st ed. St. Joseph, MO: American Society of Agricultural Engineers. 246 p.Google Scholar
Lanini, W. T. and LeStrange, M. 1991. Low-input management of weeds in vegetable fields. Calif. Agric 45 (1):1113.Google Scholar
Lauritzen, E. 2005. Monterey County, Crop Report 2005. Salinas, CA: Monterey County Agricultural Commisioner. 19 p.Google Scholar
Lauritzen, E. 2006. Monterey County, Crop Report 2006. Salinas, CA: Monterey County Agricultural Commisioner. 20 p.Google Scholar
Martin, P. 2007. Farm Labor Shortages: How Real, What Responses? ARE Update. University: of California, Davis. http://www.agecon.ucdavis.edu/extension/update/articles/v10n5_3.pdf. Accessed: February 18, 2009.Google Scholar
[MDCH] Michigan Department of Community Health 2003. Health Consultation. Dacthal® Groundwater Contamination Additional Toxicological Data Coloma Township, Berrien County, Michigan. http://www.michigan.gov/documents/DacthalDiAcidHealthConsult_71729_7.pdf. Accessed: February 18, 2009.Google Scholar
O'Dogherty, M. J., Godwin, R. J., Dedousis, A. P., Brighton, L. J., and Tillett, N. D. 2007. A mathematical model of the kinematics of a rotating disc for inter- and intra-row hoeing. Biosyst. Eng 96:169179.Google Scholar
Roberts, H. A., Hewson, R. T., and Ricketts, M. A. 1977. Weed competition in drilled summer lettuce. Hortic. Res 17:3945.Google Scholar
Ryder, E. J. 1999. Crop Production Science in Horticulture 9: Lettuce, Endive, and Chicory. Wallingford, UK: CABI. 7989.Google Scholar
Shem-Tov, S., Fennimore, S. A., and Lanini, W. T. 2006. Weed management in lettuce (Lactuca sativa) with pre-plant irrigation. Weed Technol 20:10581065.Google Scholar
Slaughter, D. C., Chen, P., and Curley, R. G. 1999. Vision guided precision cultivation. Precision Agric 1:199216.Google Scholar
Smith, R. F., Chaney, W. E., Klonsky, K. M., and DeMoura, R. L. 2004. Sample Costs to Produce Fresh Broccoli. University: of California Special Publication. http://coststudies.ucdavis.edu/files/broccolicc2004.pdf. Accessed: February 18, 2009.Google Scholar
Tickes, B. R. and Kerns, D. R. 1996. Lettuce injury from preplant and preemergence herbicides. University: of Arizona Cooperative Extension. http://www.docstoc.com/docs/3837888/ARIZONA-COOPERATIVE-EXTENSION-The-University-of-Arizona-College-of-Agriculture. Accessed: February 18, 2009.Google Scholar
Tourte, L. and Smith, R. F. 2001. Sample Production Costs for Wrapped Iceberg Lettuce in Monterey and Santa Cruz Counties. University of California, Davis, Cost and Return Studies. http://coststudies.ucdavis.edu/files/lethead2001.pdf. Accessed: February 18, 2009.Google Scholar