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Spatial Distribution Patterns of Johnsongrass (Sorghum halepense) in Corn Fields in Spain

Published online by Cambridge University Press:  20 January 2017

Dionisio Andújar ,
David Ruiz ,
Ángela Ribeiro ,
César Fernández-Quintanilla  and
José Dorado
Dionisio Andújar
Affiliation:
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Serrano 115 B, 28006 Madrid, Spain
David Ruiz
Affiliation:
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Serrano 115 B, 28006 Madrid, Spain
Ángela Ribeiro
Affiliation:
Centro de Automática y Robótica, Consejo Superior de Investigaciones Científicas-Universidad Politécnica de Madrid, 28500 Arganda del Rey, Madrid, Spain
César Fernández-Quintanilla
Affiliation:
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Serrano 115 B, 28006 Madrid, Spain
José Dorado*
Affiliation:
Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Serrano 115 B, 28006 Madrid, Spain
*
Corresponding author's E-mail: jose.dorado@ccma.csic.es
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Abstract

This study describes the distribution patterns of Johnsongrass populations present in 38 commercial corn fields located in three major corn growing regions of Spain. A total of 232 ha were visually assessed from the cabin of a combine during harvesting using a three-category ranking (high density, low density, no presence) and recording the georeferenced data in a tablet personal computer. On average, 10.3 and 3.9% of the surveyed area were infested with high and low density of Johnsongrass, respectively. Most of the infested area was concentrated in a few large patches with irregular shape. Small patches (less than 1,000 m2) represented only 27% of the infested area. Management factors could explain much of the spatial distribution of this weed in the studied fields. Tillage direction was the main factor explaining patch shape: the length width−1 ratio of the patches was greater than two in the tillage direction. In sprinkler irrigated fields, higher levels of infestation were generally observed close to the sprinkler lines. Areas close to the edges of the field had a higher risk of infestation than the areas in the middle of the fields: a negative relationship between distance from the edge and weed abundance was established. Because a few patches, located in some predictable parts of the field, such as field edges, represent most of the seriously infested area, site-specific treatments of these areas could reduce herbicide inputs, until more reliable, spatially precise and practical detection, mapping, and spraying systems are developed.

Keywords

Johnsongrass, Sorghum halepense (L.) Pers. SORHAcorn, Zea mays LWeed spatial distributionsite-specific weed managementweed patchesmanagement factors
Type
Weed Biology and Ecology
Information
Weed Science , Volume 59 , Issue 1 , March 2011 , pp. 82 - 89
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Backes, M., Schumacher, D., and Plümer, L. 2005. The sampling problem in weed control: are currently applied sampling strategies adequate for site-specific weed control? Pages 155–161 in Stafford, J. V., ed. Precision Agriculture '05. Wageningen, The Netherlands Wageningen Academic Publishers.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
Berge, T. W., Fykse, H., and Aastveit, A. H. 2007. Patch spraying of weeds in spring cereals: simulated influences of threshold level and spraying resolution on spraying errors and potential herbicide reduction. Acta Agric. Scand. Sect. B-Soil Plant Sci. 57:212–221.Google Scholar
Blackshaw, R. E., O'Donovan, J. T., Harker, K. N., Clayton, G. W., and Stougaard, R. N. 2006. Reduced herbicide doses in field crops: a review. Weed Biol. Manag. 6:10–17.Google Scholar
Brain, P. and Cousens, R. 1990. The effect of weed distribution on predictions of yield loss. J. Appl. Ecol. 27:735–742.Google Scholar
Cardina, J., Johnson, G. A., and Sparrow, D. H. 1997. The nature and consequence of weed spatial distribution. Weed Sci. 45:364–373.Google Scholar
Cardina, J., Sparrow, D. H., and McCoy, E. L. 1995. Analysis of spatial-distribution of common lambsquarters (Chenopodium album) in no-till soybean (Glycine max). Weed Sci. 43:258–268.Google Scholar
Christensen, S., Søgaard, H. T., Kudsk, P., Nørremark, M., Lund, I., Nadimi, E. S., and Jørgensen, R. 2009. Site-specific weed control technologies. Weed Res. 49:233–241.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. Madison, WI ASA/CSSA/SSSA.Google Scholar
Damalas, C. A. and Eleftherohorinos, I. G. 2001. Dicamba and atrazine antagonism on sulfonylurea herbicides used for Johnsongrass (Sorghum halepense) control in corn (Zea mays). Weed Technol. 15:62–67.Google Scholar
Dewar, A. M. 2009. Weed control in glyphosate-tolerant maize in Europe. Pest Manag. Sci. 65:1047–1058.Google Scholar
European Council. 2009. Directive 2009/128/EC of the European Parliament and the Council establishing a framework for Community action to achieve the sustainable use of pesticides. Official Journal of the E. U. 309:71–86.Google Scholar
Forcella, F. 1993. Value of managing within-field variability. Pages 125–132 in Pierce, F. J. and Sadler, E. J., eds. Proceedings of Soil Specific Crop Management: A Workshop on Research and Development Issues. Madison, WI ASA/CSSA/SSSA.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
Ghersa, C. M., Martinez-Ghersa, M. A., Satorre, E. H., Vanesso, 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
Ghersa, C. M. and Satorre, E. H. 1981. La dinámica de la población de rizomas de sorgo de alepo en relación con los sistemas de control más frecuentes. Revista Facultad de Agronomía. 3:133–138. [In Spanish].Google Scholar
Holm, L. R. G., Plucknett, D. L., Pancho, J. V., and Herberger, J. P. 1977. The World's Worst Weeds: Distribution and Biology. Honolulu, HI The University Press of Hawaii. 609 p.Google Scholar
Humston, R., Mortensen, D. A., and Bjornstad, O. N. 2005. Anthropogenic forcing on the spatial dynamics of an agricultural weed: the case of the common sunflower. J. Appl. Ecol. 42:863–872.Google Scholar
Johnson, G. A., Mortensen, D. A., and Gotway, C. A. 1996. Spatial and temporal analysis of weed seedling populations using geostatistics. Weed Sci. 44:704–710.Google Scholar
Kelner, D. The effect of zero tillage on weed populations. 1995. http://www.mandakzerotill.org/books/proceedings/Proceedings%201995/weed_pop.html. Accessed: August 5, 2010.Google Scholar
Lamn, R. D., Slaughter, D. C., and Giles, D. K. 2002. Precision weed control system for cotton. Trans. ASAE. 45:231–238.Google Scholar
Lee, W. S., Slaughter, D. C., and Giles, D. K. 1999. Robotic weed control systems for tomatoes. Precis. Agric. 1:95–113.Google Scholar
Luschei, E. C., Van Wychen, L. R. M., 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
McWhorter, C. G. 1973. Johnsongrass. Its history and control. Weeds Today. 3:12–13.Google Scholar
Mitskas, M. B., Eleftherohorinos, I. G., and Damalas, C. A. 2003. Interference between corn and Johnsongrass (Sorghum halepense) from seed or rhizome. Weed Sci. 51:540–545.Google Scholar
Nosratti, I., Alizadeh, H. M., and Rasoolzadeh, S. 2007. Control of Johnsongrass (Sorghum halepense) with nicosulfuron in maize at different planting patterns. J. Agron. 6:444–448.Google Scholar
Perry, N. H., Lutman, P. J. W., Miller, P. C. H., and Wheeler, H. C. 2001. A map-based system for patch spraying weeds: weed mapping. Pages 841–846 in Proceedings of the British Crop Protection Council Conference—Weeds. Volume 2. Farnham, Surrey, UK The British Crop Protection Council.Google Scholar
Rew, L. J., Cussans, G. W., Mugglestone, M. A., and Miller, P. C. H. 1996. A technique for mapping the spatial distribution of Elymus repens, with estimates of the potential reduction in herbicide usage from patch spraying. Weed Res. 36:283–292.Google Scholar
Rew, L. J., Miller, P. C. H., and Paice, M. E. R. 1997. The importance of patch mapping resolution for sprayer control. Aspects Appl. Biol.: Optimising Pesticide Applications. 48:49–56.Google Scholar
Ruiz, D., Escribano, C., and Fernández-Quintanilla, C. 2006a. Identifying associations among sterile oat (Avena sterilis) infestation level, landscape characteristics and crop yields. Weed Sci. 54:1113–1121.Google Scholar
Ruiz, D., Escribano, C., and Fernández-Quintanilla, C. 2006b. Assessing the opportunity for site-specific management of Avena sterilis in winter barley fields in Spain. Weed Res. 46:379–387.Google Scholar
[SPSS] Statistical Product and Service Solutions. 2008. SPSS 17.0 User's Guide. Chicago SPSS.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
Williams, M. M., Gerhards, R., Reichart, S., Mortensen, D. A., and Martin, A. R. 1999. Weed seedling population responses to a method of site-specific weed management. Pages 123–132 in Robert, P. C., Rust, R. H., and Larson, W. E., eds. Proceedings of the 4th International Conference on Precision Agriculture. Madison, WI ASA/CSSA/SSSA.Google Scholar
Young, D. L., Kwon, T. J., Smith, E. G., and Young, F. L. 2003. Site-specific herbicide decision model to maximize profit in winter cereals. Prec. Agric. 4:227–238.Google Scholar