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Spatial Pattern of Weeds Based on Multispecies Infestation Maps Created by Imagery

  • Louis Longchamps (a1), Bernard Panneton (a2), Robin Reich (a3), Marie-Josée Simard (a2) and Gilles D. Leroux (a4)...

Abstract

Weeds are often spatially aggregated in maize fields, and the level of aggregation varies across and within fields. Several annual weed species are present in maize fields before postemergence herbicide application, and herbicides applied will control several species at a time. The goal of this study was to assess the spatial distribution of multispecies weed infestation in maize fields. Ground-based imagery was used to map weed infestations in rain-fed maize fields. Image segmentation was used to extract weed cover information from geocoded images, and an expert-based threshold of 0.102% weed cover was used to generate maps of weed presence/absence. From 19 site-years, 13 (68%) demonstrated a random spatial distribution, whereas six site-years demonstrated an aggregated spatial pattern of either monocotyledons, dicotyledons, or both groups. The results of this study indicated that monocotyledonous and dicotyledonous weed groups were not spatially segregated, but discriminating these weed groups slightly increased the chances of detecting an aggregated pattern. It was concluded that weeds were not always spatially aggregated in maize fields. These findings emphasize the need for techniques allowing the assessment of weed aggregation prior to conducting site-specific weed management.

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Corresponding author

Corresponding author's E-mail: louis.longchamps@colostate.edu

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Associate Editor for this paper: Anita Dille, Kansas State University.

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References

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Backes, M, Jacobi, J (2006) Classification of weed patches in Quickbird images: verification by ground truth data. Eur Assoc Remote Sens Lab eProc 5: 173179
Baddeley, A, Turner, R (2005) Spatstat: an R package for analyzing spatial point patterns. J Statistical Software 12: 142
Barroso, J, Fernandez-Quintanilla, C, Maxwell, BD, Rew, LJ (2004) Simulating the effects of weed spatial pattern and resolution of mapping and spraying on economics of site specific management. Weed Res 44: 460468
Barroso, J, Navarrete, L, Sánchez del Arco, MJ, Fernandez-Quintanilla, C, Lutman, PJW, Perry, NH, Hull, RI (2006) Dispersal of Avena fatua and Avena sterilis patches by natural dissemination, soil tillage and combine harvesters. Weed Res 46: 118128
Bassett, IJ, Crompton, CW (1978). The biology of Canadian weeds: 32 Chenopodium album L. Can J Plant Sci 58: 10611072
Benvenuti, S (2007). Weed seed movement and dispersal strategies in the agricultural environment. Weed Biol Manag 7: 141157
Bolker, BM, Pacala, SW, Neuhauser, C (2003) Spatial dynamics in model plant communities: what do we really know? Amer Nat 162: 135148
Cardina, J, Johnson, GA, Sparrow, DH (1997) The nature and consequence of weed spatial distribution. Weed Sci 45: 364373
Cardina, J, Sparrow, DH, McCoy, EL (1996) Spatial relationships between seedbank and seedling populations of common lambsquarters (Chenopodium album) and annual grasses. Weed Sci 44: 298308
Cavers, PB, Harper, JL (1967) The comparative biology of closely related species living in the same area: IX. Rumex: The nature of adaptation to a sea-shore habitat. J Ecol 55: 7382
Colbach, N, Roger-Estrade, J, Chauvel, B, Caneill, J (2000) Modelling vertical and lateral seed bank movements during mouldboard ploughing. Eur J Agron 13: 111124
Cousens, RD, Woolcock, JL (1997) Spatial dynamics of weeds: an overview. Pages 613618 in Proceedings of the Brighton Crop Protection Conference Weeds (British Crop Protection Council). Farnham, UK: British Crop Protection Council
Cuzick, J, Edwards, R (1990) Spatial clustering for inhomogeneous populations. J R Stat Soc. Series B (Methodol) 52: 73104
Dieleman, JA, Mortensen, DA (1999) Characterizing the spatial pattern of Abutilon theophrasti seedling patches. Weed Res 39: 455467
Dieleman, JA, Mortensen, DA, Buhler, DD, Cambardella, CA, Moorman, TB (2000) Identifying associations among site properties and weed species abundance. I. Multivariate analysis. Weed Sci 48: 567575
Efloras. 2015. Chenopodium album . Page 296 in Flora of North America. Vol. 4. http://www.efloras.org/florataxon.aspx?flora_id=1&taxon_id=200006809. Accessed December 7, 2015
[EWRS–SSWM] European Weed Research Society–Site Specific Weed Management (2005) Site-Specific Weed Management Working Group. http://web.agrsci.dk/jbt/sch/ewrs/. Accessed June 24, 2015
Fortin, M-J, Dale, MRT (2005) Spatial Analysis: A Guide for Ecologists. Cambridge, UK: Cambridge University Press. 365 p
Gerhards, R, Christensen, S (2003) Real-time weed detection, decision making and patch spraying in maize, sugarbeet, winter wheat and winter barley. Weed Res 43: 385392
Gerhards, R, 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: 185193
Gonzalez-Andujar, JL, Saavedra, M (2003) Spatial distribution of annual grass weed populations in winter cereals. Crop Prot 22: 629633
Goudy, HJ, Bennett, KA, Brown, RB, Tardif, FJ (2001) Evaluation of site-specific weed management using a direct-injection sprayer. Weed Sci 49: 359366
Greig-Smith, P (1983) Quantitative Plant Ecology. 3rd edn. Berkeley, CA: University of California Press. 359 p
Hamouz, P, Soukup, J, Holec, J, Jursík, M (2004) Field-scale variability of weediness on arable land. Plant Soil Environ 50: 134140
Heijting, S, Van der Werf, W, Stein, A, Kropff, MJ (2007) Are weed patches stable in location? Application of an explicitly two-dimensional methodology. Weed Res 47: 381395
Jhala, AJ, Knezevic, SZ, Ganie, ZA, Singh, M (2014) Integrated weed management in maize. Pages 177196 in Chauhan, BS, Mahajan, G, eds. Recent Advances in Weed Management. New York: Springer-Verlag
Johnson, GA, Mortensen, DA, Gotway, CA (1996) Spatial and temporal analysis of weed seedling populations using geostatistics. Weed Sci 44: 704710
Jurado-Expósito, M, López-Granados, F, García-Torres, L, García-Ferrer, A, Sánchez de la orden, M, Atenciano, S (2003) Multi-species weed spatial variability and site-specific management maps in cultivated sunflower. Weed Sci 51: 319328
Longchamps, L, Panneton, B, Simard, M-J, Leroux, GD (2012) Could weed sensing in corn interrows result in efficient weed control? Weed Technol 26: 649656
Longchamps, L, Panneton, B, Simard, M-J, Leroux, GD (2013) A technique for high-accuracy ground-based continuous weed mapping at field scale. Trans Am Soc Agric Biol Eng 56: 15231533
Longchamps, L, Panneton, B, Simard, M-J, Leroux, GD (2014) An imagery-based weed cover threshold established using expert knowledge. Weed Sci 62: 177185
Marshall, EJP, Brain, P (1999) The horizontal movement of seeds in arable soil by different soil cultivation methods. J Appl Ecol 36: 443454
Marshall, G, Kirkwood, RC, Martin, DJ (1987) Studies on the mode of action of asulam, aminotriazole, and glyphosate in field horsetail Equisetum arvense L. (field horsetail). II. The metabolism of [14C] asulam,[14C] aminotriazole, and [14C] glyphosate. Pestic Sci 18: 6577
McGrew, JC, Lembo, AJ, Monroe, CB (2000). An Introduction to Statistical Problem Solving in Geography. 2nd edn. Boston, MA: McGraw Hill. 254 p
Meagher, TR, Burdick, DS (1980) The use of nearest neighbor frequency analyses in studies of association. Ecology 61: 12531255
Mountford, MD (1961) On EC Pielou's index of non-randomness. J Ecol 49: 271275
Nordmeyer, H (2006) Patchy weed distribution and site-specific weed control in winter cereals. Precis Agric 7: 219231
Norsworthy, JK, Griffith, G, Griffin, T, Bagavathiannan, M, Gbur, EE (2014) In-field movement of glyphosate-resistant Palmer amaranth (Amaranthus palmeri) and its impact on cotton lint yield: evidence supporting a zero-threshold strategy. Weed Sci 62: 237249
Pacala, SW (1997) Dynamics of plant communities. Pages 532555 in Crawley, MJ, ed. Plant Ecology. 2nd edn. Oxford, UK: Blackwell Scientific
Petit, S, Fried, G (2012) Patterns of weed co-occurrence at the field and landscape level. J Veg Sci 23: 11371147
Pielou, EC (1959) The use of point-to-plant distances in the study of the pattern of plant populations. J Ecol 47: 607613
Pielou, EC (1961) Segregation and symmetry in two-species populations as studied by nearest-neighbor relationships. J Ecol 49: 255269
R Development Core Team (2012) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project.org/. Accessed April 1, 2016
Schenk, HJ, Callaway, RM, Mahall, BE (1999) Spatial Root Segregation: Are Plants Territorial? Adv Ecol Res 28: 145180
Schuster, I, Nordmeyer, H, Rath, T (2007). Comparison of vision-based and manual weed mapping in sugar beet. Biosys Eng 98: 1725
Slaughter, DC, Giles, DK, Downey, D (2008) Autonomous robotic weed control systems: a review. Comput Electron Agric 61: 6378
Tardif-Paradis, C, Simard, M-J, Leroux, GD, Panneton, B, Nurse, R, Vanasse, A (2015) Effect of planter and tractor wheels on row and inter-row weed populations. Crop Prot 71: 6671
Timmermann, C, Gerhards, R, Küthbauch, W (2003) The economic impact of site-specific weed control. Precis Agric 4: 249260
[USDA–NRCS] U.S. Department of Agriculture–Natural Resources Conservation Service 2010. The PLANTS Database. http://plants.usda.gov. Accessed December 7, 2015
Walter, AM, Christensen, S, Simmelsgaard, SE (2002) Spatial correlation between weed species densities and soil properties. Weed Res 42: 2638
Wiles, LJ, Oliver, GW, York, AC, Gold, HJ, Wilkerson, GG (1992). Spatial distribution of broadleaf weeds in North Carolina soybean (Glycine max) fields. Weed Sci 40: 554557
Zanin, G, Berti, A, Riello, L (1998) Incorporation of weed spatial variability into the weed control decision-making process. Weed Res 38: 107118
Zimdahl, RL (2004) Weed–Crop Competition: A Review. 2nd ed. Ames, IA: Blackwell Publishing. 220 p

Keywords

Spatial Pattern of Weeds Based on Multispecies Infestation Maps Created by Imagery

  • Louis Longchamps (a1), Bernard Panneton (a2), Robin Reich (a3), Marie-Josée Simard (a2) and Gilles D. Leroux (a4)...

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