Crop–Weed Competition

Abstract

Competition from weeds is the most important of all biological factors that reduce agricultural crop yield. This occurs primarily because weeds use resources that would otherwise be available to the crop. The magnitude of yield loss is affected by numerous agronomic and environmental factors, most importantly, weed density and time of emergence relative to the crop. Practices that (1) reduce the density of weeds, (2) maximise occupation of space or uptake of resources by the crop or (3) establish an early‐season size advantage of the crop over the weeds will minimise the competitive effects of weeds on crops. Longer term management of crop–weed competition can be achieved through crop rotations, specifically crop sequences that reduce the weed seed bank, and therefore seedling density, and prevent proliferation of perennial weeds.

Key Concepts

  • Plant growth requires sunlight, water and nutrients, which in turn are converted into biomass that captures additional resources.
  • In crop or weed monocultures, increasing density increases total production to a maximum that is determined by the resource status of the site, generally with a corresponding decrease in per plant mass.
  • In crop–weed mixtures, increasing weed density results in large initial reductions in crop yield, again reaching an asymptote of maximum yield loss that varies among crop species, environments and weed cohorts.
  • Farmers manage crop–weed competition by (1) reducing weed density (i.e. ‘weeding’), (2) establishing an early‐season competitive advantage to the crop and (3) maximising resource capture by the crop using competitive species, competitive cultivars, high sowing densities, optimal spatial arrangement, intercropping complimentary species or transplanting.

Keywords: agroecology; crop yield loss; inter‐specific; interference; weed management

Figure 1. Annual weeds interfere with pumpkin harvest and reduce fruit yield. The abundant seed rain ensures an abundant weed population in future years. Photo: E. Gallandt.
Figure 2. The effects of plant density on biomass in single‐species populations (monoculture). At very low densities, there is no competition and total biomass increases linearly with density (a). As density increases, competition becomes important and the increase in biomass is less than proportional to density (curved part of graph a). At high densities, further increases in density do not lead to any increase in biomass (Law of Constant Final Yield). The effects of density on mean individual plant biomass are best illustrated with a log–log plot (b). The proportional increase in total biomass with density at low densities on graph (a) corresponds to the flat part of graph (b). The flat part of graph (a) corresponds to the linear decrease (slope = −1) on graph (b).
Figure 3. The right‐rectangular hyperbolic model relating crop yield loss to weed density (Cousens, ). Crop yield loss = i*N/1+((i*N)/A) where N is the weed density; i and A fit parameters with i representing the slope as N approaches zero and A the slope as N approaches infinity.
Figure 4. Results from an experiment designed to determine the ‘critical period’ for weed control. Data from two complementary experiments are plotted on the same axes. Results from one experiment show cabbage yield when the crop is maintained weed‐free for 0, 1, 2, 4, 6 and 14 weeks. Results from the second experiment show cabbage yield when the crop is unweeded for 0, 2, 4, 6 and 14 weeks. Weeds present for only a short period of time have no effect on yield, and the end of the critical period marks the point at which the crop has a sufficient size advantage to be unaffected by subsequently emerging weeds. (Data from Miller and Hopen, 1991 © Allen Press Inc.)
Figure 5. Effect of sequence of seed sowing, and resulting sequence of seedling emergence, over 10 consecutive days on space, estimated as proportional to biomass, occupied by individual plants. Panels show the randomly selected positions in which seeds were sown, and the area occupied on days 4, 8, 12, 16 and 20. Seedlings from seeds sown on days 7 through 10 occupy very little space which have been pre‐empted by earlier‐emerging individuals. (Adapted with permission from Harper (1977). © Academic Press Inc.)
close

References

Ali A, Streibig JC and Andreasen C (2013) Yield loss prediction models based on early estimation of weed pressure. Crop Protection 53: 125–131. DOI: 10.1016/j.cropro.2013.06.010.

Ballaré CL (2009) Illuminated behaviour: phytochrome as a key regulator of light foraging and plant anti‐herbivore defense. Plant, Cell and Environment 32: 713–725.

Begon M, Harper JL and Townsend CR (2006) Ecology: Individuals, Populations and Communities. Oxford, UK: Blackwell Scientific Publications 1068 pp.

Blackshaw RE, Brandt RN, Janzen HH, et al. (2003) Differential response of weed species to added nitrogen. Weed Science 51: 532–539.

Bleasdale JKA and Nelder JA (1960) Plant population and crop yield. Nature 188: 342.

Callaway MB (1992) A compendium of crop varietal tolerance to weeds. American Journal of Alternative Agriculture 7: 168–179.

Colbach N, Collard A, Guyot SHM, et al. (2014) Assessing innovative sowing patterns for integrated weed management with a 3D crop:weed competition model. European Journal of Agronomy 53: 74–89.

Connolly J (1986) On difficulties with replacement‐series methodologies in mixture experiments. Journal of Applied Ecology 23: 125–137.

Cousens R (1985a) A simple model relating yield loss to weed density. Advances in Applied Biology 107: 239–252.

Cousens R (1985b) An empirical model relating crop yield to weed and crop density and a statistical comparison with other models. Journal of Agricultural Science 105: 513–521.

DiTomaso JM (1995) Approaches for improving crop competitiveness through the manipulation of fertilization strategies. Weed Science 43: 491–497.

Fischer DW, Harvey RG, Bauman TT, et al. (2004) Common lambs quarters (Chenopodium album) interference with corn across the north central United States. Weed Science 52: 1034–1038.

Fischer RA and Miles RE (1973) The role of spatial pattern in the competition between crop plants and weeds: a theoretical analysis. Mathematical Biosciences 18: 335–350.

Fuerst EP and Putnam AR (1983) Separating the competitive and allelopathic components of interference. Journal of Chemical Ecology 9: 937–944.

Glauninger J and Holzner W (1982) Interference between weeds and crops: a review of literature. In: Holzner W and Numata M, (eds). Biology and Ecology of Weeds, pp. 149–159. The Hague: W. Junk.

Grime JP (1979) Plant Strategies and Vegetation Processes. New York: John Wiley & Sons, Inc.

Harper JL (1977) Population Biology of Plants. San Diego, CA: Academic Press, 892 pp.

Hauggaard‐nielsen H, Ambus P and Jensen ES (2001) Interspecific competition, N use and interference with weeds in pea‐barley intercropping. Field Crops Research 70: 101.

Holliday RJ (1960) Plant population and crop yield. Field Crop Abstracts 13: 159–167.

Holopainen JKND and Blande JD (2012) Molecular plant volatile communication. In: López‐Larrea C, (ed). Sensing in Nature, pp. 17–31. Austin, TX: Landes Bioscience and Springer Media.

Jordan N (1996) Weed prevention: priority research for alternative weed management. Journal of Production Agriculture 9: 485–490.

Keddy PA (2001) Competition, 2nd edn. Dordrecht: Kluwer, 5 p.

Knezevic SZ, Evans SP, Blankenship EE, et al. (2002) Critical period for weed control: the concept and data analysis. Weed Science 50: 773–786.

Kropff MJ and Spitters CJT (1991) A simple model of crop loss by weed competition from early observations on relative leaf area of the weeds. Weed Research 31: 97–105.

Liebman M and Dyck E (1993) Crop rotation and intercropping strategies for weed management. Ecological Applications 3: 92–122.

Lindquist JL (2001) Performance of INTERCOM for predicting corn‐velvetleaf interference across north‐central United States. Weed Science 49: 195–201.

Lindquist JL, Mortensen DA, Clay SA, et al. (1996) Stability of coefficients in the corn yield loss – velvetleaf density relationship across the North Central US. Weed Science 44: 309–313.

Lindquist JL, Mortensen DA, Westra P, et al. (1999) Stability of corn (Zea mays)—foxtail (Setaria spp.) interference relationships. Weed Science 47: 195–200.

Malézieux E, Crozat Y and Dupraz C (2009) Mixing plant species in cropping systems: concepts, tools and models: a review. Agronomy for Sustainable Development 29: 43–62.

Marin C and Weiner J (2014) Effects of density and sowing pattern on weed suppression and yield in three varieties of maize under high weed pressure. Weed Research 54: 467–474.

Miller AB and Hopen HJ (1991) Critical weed‐control period in seeded cabbage (Brassica oleracea var. capitata). Weed Technology 5: 852–857.

Mohler CL (2001) Enhancing the competitive ability of crops. In: Liebman M, Mohler CL and Staver CP, (eds). Ecological Management of Agricultural Weeds, pp. 269–321. Cambridge, UK: Cambridge University Press.

Nordell A and Nordell E (2009) Weed the soil, not the crop. Acres USA 40 (6): 6.

Norris RF (1999) Ecological implications of using thresholds for weed management. Journal of Crop Production 2 (1): 31–58.

Norris RF (2007) Weed fecundity: current status and future needs. Crop Protection 26 (3): 182–188.

Oerke EC (2006) Crop losses to pests. Journal of Agricultural Science 144: 31–43.

Page ER, Tollenaar M, Lee EA, et al. (2010) Shade avoidance: an integral component of crop‐weed competition. Weed Research 50: 281–288.

Page ER, Liu W, Cerrudo D, et al. (2011) Shade avoidance influences stress tolerance in maize. Weed Science 59 (3): 326–334.

Putnam AR (1988) Allelopathy: problems and opportunities in weed management. In: Altieri MA and Liebman M, (eds). Weed Management in Agroecosystems: Ecological Approaches, pp. 77–88. Boca Raton, FL: CRC Press, Inc.

Radosevich SR, Holt JS and Ghersa CM (1997) Weed Ecology, Implications for Management. New York, NY: John Wiley & Sons, Inc, 589 pp.

Schwinning S and Weiner J (1998) Mechanisms determining the degree of size‐asymmetry in competition among plants. Oecologia 113: 447–455.

Slaughter DC, Giles DK and Downey D (2008) Autonomous robotic weed control systems: a review. Computers and Electronics in Agriculture 61 (1): 63–78.

Tilman D (1982) Resource Competition and Community Structure. Princeton, NJ: Princeton University Press.

van Heemst HDJ (1985) The influence of weed competition on crop yield. Agricultural Systems 18: 81–93.

Vandermeer J (1984) Plant competition and the yield‐density relationship. Journal of Theoretical Biology 109: 393–399.

Watkinson AR (1980) Density‐dependence in single‐species populations of plants. Journal of Theoretical Biology 83: 345–357.

Weiner J (1990) Asymmetric competition in plant populations. Trends in Ecology and Evolution 5: 360–364.

Weiner J, Andersen SB, Wille WKM, et al. (2010) Evolutionary agroecology: the potential for cooperative, high density, weed‐suppressing cereals. Evolutionary Applications 3: 473–475.

Weiner J, Griepentrog H‐W and Kristensen L (2001a) Suppression of weeds by spring wheat (Triticum aestivum) increases with crop density and spatial uniformity. Journal of Applied Ecology 38: 784–790.

Weiner J, Stoll P, Muller‐Landau H, et al. (2001b) The effects of density, spatial pattern, and competitive symmetry on size variation in simulated plant populations. American Naturalist 158: 438–450.

Willey RW and Heath SB (1969) The quantitative relationships between plant population and crop yield. Advances in Agronomy 21: 281–321.

Wortman SE, Davis AS, Schutte BJ, et al. (2011) Integrating management of soil nitrogen and weeds. Weed Science 59 (2): 162–170.

Further Reading

DeWit CT (1960) On Competition. Wageningen, The Netherlands: Institute for Biological and Chemical Research on Field Crops and Herbage, 82 pp.

Firbank LG and Watkinson AR (1990) On the effects of competition: from monocultures to mixtures. In: Grace JB and Tilman D, (eds). Perspectives on Plant Competition, pp. 165–187. San Diego, CA: Academic Press.

Kropff MJ and van Laar HH (1993) Modeling Crop‐Weed Interactions. Wallingford: CAB International, 304 pp.

Liebman M, Mohler CL and Staver CP (2001) Ecological Management of Agricultural Weeds. Cambridge, UK: Cambridge University Press, 532 pp.

Radosevich SR, Holt JS and Ghersa CM (1997) Weed Ecology, Implications for Management, 2nd edn. New York: John Wiley & Sons, Inc, 589 pp.

Tilman D (1990) Mechanisms of plant competition for nutrients: the elements of a predictive theory of competition. In: Grace JB and Tilman D, (eds). Perspectives on Plant Competition, pp. 117–141. San Diego, CA: Academic Press.

Zimdahl RL (1980) IPPC #31‐A‐80, (ed). Weed‐Crop Competition, a Review. Corvallis, OR: International Plant Protection Center, 196 pp.

Zimdahl RL (2004) Weed‐Crop Competition: A Review, 2nd edn. Ames, IA: Blackwell Publishing 32 pp.

Contact Editor close
Submit a note to the editor about this article by filling in the form below.

* Required Field

How to Cite close
Gallandt, Eric R, and Weiner, Jacob(May 2015) Crop–Weed Competition. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0020477.pub2]