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Reliability of a Visual Recognition System for Detection of Johnsongrass (Sorghum halepense) in Corn

Published online by Cambridge University Press:  20 January 2017

Dionisio Andújar ,
Ángela Ribeiro ,
Cesar Fernández-Quintanilla  and
José Dorado
Dionisio Andújar
Affiliation:
Instituto de Ciencias Agrarias, CSIC, Serrano 115B, 28006 Madrid, Spain
Ángela Ribeiro
Affiliation:
Centro de Automática y Robótica, CSIC-UPM, 28500 Arganda del Rey, Madrid, Spain
Cesar Fernández-Quintanilla
Affiliation:
Instituto de Ciencias Agrarias, CSIC, Serrano 115B, 28006 Madrid, Spain
José Dorado*
Affiliation:
Instituto de Ciencias Agrarias, CSIC, Serrano 115B, 28006 Madrid, Spain
*
Corresponding author's E-mail: [email protected]
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Abstract

The feasibility of visual detection of weeds for map-based patch spraying systems needs to be assessed for use in large-scale cropping systems. The main objective of this research was to evaluate the reliability and profitability of using maps of Johnsongrass patches constructed at harvest to predict spatial distribution of weeds during the next cropping season. Johnsongrass patches visually were assessed from the cabin of a combine harvester in three corn fields and were compared with maps obtained in the subsequent year prior to postemergence herbicide application. There was a good correlation (71% on average) between the position of Johnsongrass patches on the two maps (fall vs. spring). The highest correlation (82%) was obtained with relatively large infestations, whereas the lowest (58%) was obtained when the infested area was smaller. Although the relative positions of the patches remained almost unchanged from 1 yr to the next, the infested area increased in all fields during the 4-yr experimental period. According to our estimates, using a strategy based on spraying full rates of herbicides to patches recorded in the map generated in the previous fall resulted in higher net returns than spraying the whole field, either at full or half rate. This site-specific strategy resulted in an average 65% reduction in the volume of herbicide applied to control this weed.

La viabilidad de la detección visual de malezas para su tratamiento localizado en base a mapas debe ser evaluada de cara a su aplicación en sistemas de cultivo a gran escala. El objetivo principal de esta investigación fue evaluar la fiabilidad y rentabilidad del uso de mapas de rodales de Sorghum halepense elaborados durante la recolección en otoño para predecir la distribución espacial de la maleza en la siguiente campaña de cultivo. Los rodales de S. halepense fueron localizados de forma visual desde la cabina de una cosechadora en tres campos de maíz, y su posición se comparó con la de los mapas obtenidos la primavera siguiente, antes del tratamiento de post-emergencia. Los resultados mostraron una buena correlación (71% en promedio) de la ubicación de los rodales de la maleza entre los dos mapas (otoño vs. primavera). La mayor correlación (82%) se observó con infestaciones relativamente grandes, mientras que la menor (58%) se obtuvo cuando el área infestada era más pequeña. Aunque las posiciones relativas de los rodales se mantuvieron constantes de un año al otro, el área infestada se incrementó en todos los campos durante los cuatro años del período experimental. Según nuestras estimaciones, la estrategia basada en aplicar una dosis completa de herbicida a los rodales localizados el otoño del año anterior produjo un beneficio neto mayor que la aplicación de herbicida sobre todo el campo, ya sea a dosis completa o a mitad de dosis. Esta estrategia de tratamiento localizado resultó en una reducción media del 65% respecto al volumen de herbicida aplicado en toda la superficie para el control de esta maleza.

Keywords

Johnsongrass, Sorghum halepense (L.) Pers. SORHAcorn, Zea mays L.Weed mapsvisual estimationpatchy weed distributionpatch spraying
Type
Weed Management—Techniques
Information
Weed Technology , Volume 25 , Issue 4 , December 2011 , pp. 645 - 651
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Andújar, D., Ruiz, D., Ribeiro, A., Fernández-Quintanilla, C., and Dorado, J. 2011. Spatial distribution patterns of Johnsongrass (Sorghum halepense) in corn fields in Spain. Weed Sci. 59:82–89.Google Scholar
Barroso, J., Fernández-Quintanilla, C., Maxwell, B. D., and Rew, L. J. 2004. Simulating the effects of weed spatial pattern and resolution of mapping and spraying on economics of site-specific management. Weed Res. 44:460–468.Google Scholar
Barroso, J., Ruiz, D., Fernández-Quintanilla, C., Leguizamon, E. S., Hernaiz, P., Ribeiro, A., Diaz, B., Maxwell, B. D., and Rew, L. J. 2005. Comparison of sampling methodologies for site-specific management of Avena sterilis . Weed Res. 45:165–174.Google Scholar
Belles, D. S., Thill, D. C., and Shafii, B. 2000. PP-604 rate and Avena fatua density effects on seed production and viability in Hordeum vulgare . Weed Sci. 48:378–384.Google Scholar
Bendixen, L. E. 1986. Corn (Zea mays) yield in relationship to Johnsongrass (Sorghum halepense) population. Weed Sci. 34:449–451.Google Scholar
Brown, R. B. and Noble, S. D. 2005. Site-specific weed management: sensing requirements—what do we need to see? Weed Sci. 53:252–258.Google Scholar
Burgos-Artizzu, X. P., Ribeiro, A., Tellaeche, A., Pajares, G., and Fernández-Quintanilla, C. 2009. Improving weed pressure assessment using digital images from an experience-based reasoning approach. Comput. Electron. Agric. 65:176–185.Google Scholar
Christensen, S., Sagaard, H. T., Kudsk, P., Norrenmark, M., Lund, I., Nadini, E. S., and Jorgensen, R. 2009. Site-specific weed control technologies. Weed Res. 49:233–241.Google Scholar
Colbach, N., Forcella, F., and Johnson, G. A. 2000. Spatial and temporal stability of weed populations over five years. Weed Sci. 48:366–377.Google Scholar
Colliver, C. T., Maxwell, B. D., Tyler, D. A., Roberts, D. W., and Long, D. S. 1996. Georeferencing wild oat infestations in small grains: accuracy and efficiency of three weed survey techniques. Pages 453–463 in Robert, P. C., Rust, R. H., and Larson, W. E., eds. Proceedings of the 3rd International Conference on Precision Agriculture, Minneapolis, MN. Madison, WI American Society of Agronomy.Google Scholar
Forcella, F. 1993. Value of managing within-field variability. Pages 125–132 in Robert, P. C., Rust, R. H., and Larson, W. E., eds. Proceedings of Soil Specific Crop Management Management: A Workshop on Research and Development Issues, Minneapolis, MA. Madison, WI American Society of Agronomy.Google Scholar
Gerhards, R. and Christensen, S. 2003. Real-time weed detection, decision making and patch spraying in maize, sugarbeet, winter wheat and winter barley. Weed Res. 43:385–392.Google Scholar
Gerhards, R. and Oebel, H. 2006. Practical experiences with a system for site-specific weed control in arable crops using real-time image analysis and GPS-controlled patch spraying. Weed Res. 46:185–193.Google Scholar
Gerhards, R. and Sökefeld, M. 2003. Precision farming in weed control—system components and economic benefits. Pages 229–234 in Staffoard, J. V. and Werner, A., eds. Proceedings of 4th European Conference on Precision Agriculture, Berlin, Germany. Wageningen, the Netherlands Wageningen Academic.Google Scholar
Gerhards, R., Wyse-Pester, D. Y., Mortensen, D., and Johnson, G. A. 1997. Characterizing spatial stability of weed populations using interpolated maps. Weed Sci. 45:108–119.Google Scholar
Ghersa, C. M., Martinez-Ghersa, M. A., Satorre, E. H., Van Esso, M. L., and Chichotky, G. 1993. Seed dispersal, distribution and recruitment of seedlings of Sorghum halepense (L.) Pers. Weed Res. 33:79–88.Google Scholar
Hamouz, P., Soukup, J., Holec, J., and Jursik, M. Field-scale variability of weediness on arable land. Plant Soil Environ. 2004. 50:134–140.Google Scholar
Holm, L. G., Plucknett, D. L., Pancho, J. V., and Herberger, J. P. 1977. The World's Worst Weeds. Distribution and Biology. Honolulu, HI University Press of Hawaii. 609 p.Google Scholar
Luschei, E. C., Van Wychen, L. R., Maxwell, B. D., Bussan, A. J., Buschena, D., and Goodman, D. 2001. Implementing and conducting on-farm weed research with the use of GPS. Weed Sci. 49:536–542.Google Scholar
McWorther, C. 1981. Johnson grass as a weed. USDA Farmers' Bull. 1537:3–19.Google Scholar
Mitskas, M. B., Tsolis, C. E., Eleftherohorinos, I. G., and Damalas, C. A. 2003. Interference between corn and Johnsongrass (Sorghum halepense) from seed or rhizomes. Weed Sci. 51:540–545.Google Scholar
Oriade, C. A., King, R. P., Forcella, F., and Gunsolus, J. L. 1996. A bioeconomic analysis of site-specific management for weed control. Rev. Agric. Econ. 18:523–535.Google Scholar
Rew, L. J., Miller, P. C. H., and Paice, M. E. R. 1997. The importance of patch mapping resolution for sprayer control. Aspect Appl. Biol. 48:49–55.Google Scholar
Ruiz, D., Escribano, C., and Fernández-Quintanilla, C. 2006a. Assessing the opportunity for site-specific management of Avena sterilis in winter barley fields in Spain. Weed Res. 46:379–387.Google Scholar
Ruiz, D., Escribano, C., and Fernández-Quintanilla, C. 2006b. Identifying associations among sterile oat (Avena sterilis) infestation level, landscape characteristics, and crop yields. Weed Sci. 54:1113–1121.Google Scholar
Scopel, A. I., Ballare, C. L., and Ghersa, C. M. 1988. The role of seed reproduction in the population ecology of Sorghum halepense (L.) Pers. in maize crops. J. Appl. Ecol. 25:951–962.Google Scholar
Timmermann, C., Gerhards, R., and Kühbauch, W. 2003. The economic impact of site-specific weed control. Precis. Agric. 4:249–260.Google Scholar
Van Wychen, L. R., Luschei, E. C., Bussan, A. J., and Maxwell, B. D. 2002. Accuracy and cost effectiveness of GPS-assisted wild oat mapping in spring cereal crops. Weed Sci. 50:120–129.Google Scholar
Warwick, S. and Black, L. 1983. The biology of Canadian weeds—Sorghum halepense . Can. J. Plant Sci. 63:997–1014.Google Scholar
Zhang, J. H. and Hamill, A. S. 1998. Temporal and spatial distributions of velvetleaf seedlings after 1 year's seeding. Weed Sci. 46:414–418.Google Scholar
Zhang, J., Weaver, S. E., and Hamill, A. S. 2000. Risks and reliability of using herbicides at below-labeled rates. Weed Technol. 14:106–115.Google Scholar