Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-29T06:02:33.589Z Has data issue: false hasContentIssue false
  • English
  • Français

Interference of large crabgrass (Digitaria sanguinalis), redroot pigweed (Amaranthus retroflexus), and hairy galinsoga (Galinsoga ciliata) with bell pepper

Published online by Cambridge University Press:  20 January 2017

Rongwei Fu  and
Richard A. Ashley
Richard A. Ashley
Affiliation:
Department of Plant Science, U-4067, University of Connecticut, Storrs, CT 06269
Get access Rights & Permissions [Opens in a new window]

Abstract

Large crabgrass, redroot pigweed, and hairy galinsoga are three important weed species in bell pepper and other crops in the northeastern United States. Field experiments were conducted in 1998 and 1999 to determine the influence of density and relative emergence time of the three weed species on bell pepper fruit yield. Densities of 0, 1, 2, 4, 8, 16, and 32 plants m−1 row were established for each weed species from naturally occurring weed populations. The effects of relative emergence time were studied by investigating the different yield responses to weeds emerging at two different times: 3 d or 2 wk after transplanting of pepper. Both weed density and relative emergence time affected pepper yield loss. The relative competitive ability of weed species varied between years. Large crabgrass was the most competitive species in 1998 and the measure of yield loss at low weed densities, I, was estimated to be 34% on the basis of the nonlinear hyperbolic equation. Redroot pigweed was most competitive in 1999 with an estimate of 88% for I. Hairy galinsoga was the least competitive weed in both years. Maximum yield loss under 32 plants m−1 row ranged from 19% with late-emerging hairy galinsoga in 1998 to 99% with early-emerging redroot pigweed in 1999. A new equation was proposed to characterize the relation between yield loss and weed pressure by expanding the nonlinear hyperbolic equation to include a parameter to account for the change of maximum yield loss with emergence time. The expanded equation generally provided a more accurate prediction of yield loss. In addition, several models are introduced to describe both the effects of density and relative emergence time of multiple weed species on crop yield. Generally these models provided an adequate fit of the data and a good description of the competitive ability of the mixed population.

Keywords

Hairy galinsoga, Galinsoga ciliata (Raf.) Blake, GASCIlarge crabgrass, Digitaria sanguinalis (L.) Scop. DIGSAredroot pigweed, Amaranthus retroflexus L. AMAREbell pepper, Capsicum annuum L.Interferencetime of emergenceweed densityyield lossweed interference modelmultiple species interference
Type
Weed Management
Information
Weed Science , Volume 54 , Issue 2 , April 2006 , pp. 364 - 372
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.)

Footnotes

Current address: Department of Public Health and Preventive Medicine, Oregon Health and Science University, 3181 Southwest Sam Jackson Park Road, CB 669, Portland, OR 97239; fur@ohsu.edu

References

Literature Cited

Akaike, H. 1974. A new look at the statistical model identification. IEEE Trans Auto Control AC-19:716–723.CrossRefGoogle Scholar
Amador-Ramírez, M. D. 2002. Critical period of weed control in transplanted chilli pepper. Weed Res 42:203–209.CrossRefGoogle Scholar
Ashley, R. A. 1997. Critical period for weed control in peppers on black plastic. Pages 62–63 in 1997 Proceedings of New England Vegetable and Berry Conference. Durham, NH: University of New Hampshire.Google Scholar
Bates, D. M. and Watts, D. G. 1988. Nonlinear Regression Analysis and Its Application. New York: Wiley. Pp. 67–133.Google Scholar
Bosnic, Ač and Swanton, C. J. 1997. Influence of barnyardgrass (Echinochloa crus-galli) time of emergence and density on corn (Zea mays). Weed Sci 45:276–282.Google Scholar
Burnham, K. P. and Anderson, D. R. 1998. Model Selection and Inference: A Practical Information-Theoretic Approach. New York: Springer-Verlag. P. 353.CrossRefGoogle Scholar
Census of Agriculture. 1997. Census of Horticultural Specialties. Vol. 3, Special Studies Part 2. Washington, DC: U.S. Department of Agriculture, AC97, sp2, March 2000.Google Scholar
Chikoye, D., Wiese, S. F., and Swanton, C. J. 1995. Influence of common ragweed (Ambrosia artemisiifolia) of time of emergence and density on white bean. Weed Sci 43:375–380.CrossRefGoogle Scholar
Chism, W. J., Birch, J. B., and Bingham, S. W. 1992. Nonlinear regressions for analyzing growth stage and quinclorac interactions. Weed Technol 6:898–903.Google Scholar
Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol 107:239–252.CrossRefGoogle Scholar
Cousens, R., Brain, P., O'Donovan, J. T., and O'Sullivan, P. A. 1987. The use of biologically realistic equations to describe the effects of weed density and relative time of emergence on crop yield. Weed Sci 35:720–725.Google Scholar
Cowan, P., Weaver, S. E., and Swanton, C. J. 1998. Interference between pigweed (Amaranthus spp.), barnyardgrass (Echinochloa crus-galli) and soybean (Glycine max). Weed Sci 46:533–539.Google Scholar
Draper, N. R. and Smith, H. 1998. Applied Regression Analysis. 3rd ed. New York: Wiley. Pp. 505–553.Google Scholar
Fischer, D. W., Harvey, R. G., Bauman, T. T., Phillips, S., Hart, S. E., Johnson, G. A., Kells, J. J., Westra, P., and Lindquist, J. 2004. Common lambsquarters (Chenopodium album) interference with corn across the northcentral United States. Weed Sci 52:1034–1038.CrossRefGoogle Scholar
Frank, J. R., Schwartz, P. H. Jr., and Bourke, J. B. 1988. Insect and weed interaction on bell peppers (Capsicum annuum). Weed Technol 2:423–428.Google Scholar
Frank, J. R., Schwartz, P. H. Jr., and Potts, W. E. 1992. Modeling the effects of weed interference periods and insects on bell peppers (Capsicum annuum). Weed Sci 40:308–312.Google Scholar
Gonzalez Ponce, R., Zancada, M. C., Verdugo, M., and Salsa, L. 1996. Plant height as a factor in competition between black nightshade and two horticultural crops (tomato and pepper). J. Hort. Sci 71:453–460.CrossRefGoogle Scholar
Jasieniuk, M., Maxwell, B. D., and Anderson, R. L. et al. 1999. Site-to-site and year-to-year variation in Triticum aestivum–Aegilops cylindrica interference relationships. Weed Sci 47:529–537.CrossRefGoogle Scholar
Knezevic, S. Z., Horak, M. J., and Vanderlip, R. L. 1997. Relative time of redroot pigweed (Amaranthus retroflexus L.) emergence is critical in pigweed-sorghum [Sorghum bicolor (L.) Moench] competition. Weed Sci 45:502–508.CrossRefGoogle Scholar
Knezevic, S. Z., Wiese, S. F., and Swanton, C. J. 1994. Interference of redroot pigweed (Amaranthus retroflexus) in corn (Zea mays). Weed Sci 42:568–573.CrossRefGoogle Scholar
Kropff, M. J. 1988. Modeling the effects of weeds on crop production. Weed Res 28:465–471.CrossRefGoogle Scholar
Lindquist, J. L., Mortensen, D. A., Clay, S. A., Schmenk, R., Kells, J. J., Howatt, K., and Westra, P. 1996. Stability of corn (Zea mays)-velvetleaf (Abutilon theophrasti) interference relationships. Weed Sci 44:309–313.Google Scholar
Lindquist, J. L., Mortensen, D. A., and Westra, P. et al. 1999. Stability of corn (Zea mays)–foxtail (Setaria spp.) interference relationships. Weed Sci 47:195–200.Google Scholar
Morales-Payan, J. P., Santos, B. M., Stall, W. M., and Bewick, T. A. 1997. Effects of purple nutsedge (Cyperus rotundus) on tomato (Lycopersicon esculentum) and bell pepper (Capsicum annuum) vegetative dry matter and fruit yield. Weed Technol 11:672–676.CrossRefGoogle Scholar
Morales-Payan, J. P., Santos, B. M., Stall, W. M., and Bewick, T. A. 1998. Interference of purple nutsedge (Cyperus rotundus) population densities on bell pepper (Capsicum annuum) yield as influenced by nitrogen. Weed Technol 12:230–234.CrossRefGoogle Scholar
Motis, T. N., Locascio, S. J., Gilreath, J. P., and Stall, W. M. 2003. Season-long interference of yellow nutsedge (Cyperus esculentus) with polyethylene-mulched bell pepper (Capsicum annuum). Weed Technol 17:543–549.Google Scholar
Norsworthy, J. K. and Meehan, J. T. IV. 2005. Wild radish-amended soil effects on yellow nutsedge (Cyperus esculentus) interference with tomato and bell pepper. Weed Sci 53:77–83.CrossRefGoogle Scholar
[SAS] Statistical Analysis Systems. 2003. Version 9.1. Cary, NC: Statistical Analysis Institute.Google Scholar
Schroeder, J., Thomas, S. H., and Murray, L. W. 2004. Root-knot nematodes affect annual and perennial weed interactions with chile pepper. Weed Sci 52:28–46.Google Scholar
Steckel, L. E. and Sprague, C. L. 2004. Common waterhemp (Amaranthus rudis) interference in corn. Weed Sci 52:359–364.CrossRefGoogle Scholar
Swanton, C. J. and Murphy, S. D. 1996. Weed science beyond the weeds: the role of integrated weed management (IWM) in agroecosystem health. Weed Sci 44:437–445.CrossRefGoogle Scholar
Swinton, S. W., Buhler, D. D., Forcella, F., Gunsolus, J. L., and King, R. P. 1994. Estimation of crop yield loss due to interference by multiple weed species. Weed Sci 42:103–109.CrossRefGoogle Scholar
Wiese, A. M. and Binning, L. K. 1987. Calculating the threshold temperature of development for weeds. Weed Sci 35:177–179.Google Scholar
Zancada, M. C., Gonzalez Ponce, R., and Verdugo, M. 1998. Competition between Solanum nigrum and peppers in the presence of Meloidogyne incognita . Weed Res 38:47–53.CrossRefGoogle Scholar
Zou, G. Y. 1998. Weed Population Sequential Sampling Plan and Weed Seedling Emergence Pattern Prediction. Ph.D. Dissertation. University of Connecticut, Storrs, CT. Pp. 85–91.Google Scholar