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Giant Ragweed (Ambrosia trifida) Emergence Model Performance Evaluated in Diverse Cropping Systems

  • Jared J. Goplen (a1), Craig C. Sheaffer (a1), Roger L. Becker (a1), Roger D. Moon (a2), Jeffrey A. Coulter (a1), Fritz R. Breitenbach (a3), Lisa M. Behnken (a3) and Jeffrey L. Gunsolus (a1)...


Accurate weed emergence models are valuable tools for scheduling planting, cultivation, and herbicide applications. Multiple models predicting giant ragweed emergence have been developed, but none have been validated in diverse crop rotation and tillage systems, which have the potential to influence weed emergence patterns. This study evaluated the performance of published giant ragweed emergence models across various crop rotations and spring tillage dates in southern Minnesota. Across experiments, the most robust model was a mixed-effects Weibull (flexible sigmoidal function) model predicting emergence in relation to hydrothermal time accumulation with a base temperature of 4.4 C, a base soil matric potential of −2.5 MPa, and two random effects determined by overwinter growing degree days (GDD) (10 C) and precipitation accumulated during seedling recruitment. The deviations in emergence between individual plots and the fixed-effects model were distinguished by the positive association between the lower horizontal asymptote (Drop) and maximum daily soil temperature during seedling recruitment. This finding indicates that crops and management practices that increase soil temperature will have a shorter lag phase at the start of giant ragweed emergence compared with practices promoting cool soil temperatures. Thus, crops with early-season crop canopies such as perennial crops and crops planted in early spring and in narrow rows will likely have a slower progression of giant ragweed emergence. This research provides a valuable assessment of published giant ragweed emergence models and illustrates that accurate emergence models can be used to time field operations and improve giant ragweed control across diverse cropping systems.

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Associate Editor for this paper: John L. Lindquist, University of Nebraska



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Anderson, DR (2008) Model Based Inference in the Life Sciences: Primer on Evidence. New York: Springer Science + Business Media. 184 p
Anderson, RL (1994) Weed community seedling emergence for a semiarid site in Colorado. Weed Technol 8:245249
Archer, DW, Forcella, F, Korth, A, Kuhn, A, Eklund, J, Spokas, K (2006) WeedCast. Accessed: December 6, 2016
Ballard, TO, Foley, ME, Bauman, TT (1996) Germination, viability, and protein changes during cold stratification of giant ragweed (Ambrosia trifida L.) seed. J Plant Physiol 149:229232
Benech Arnold, RL, Ghersa, CM, Sanchez, RA, Insausti, P (1990a) Temperature effects on dormancy release and germination rate in Sorghum halepense (L.) Pers. seeds: a quantitative analysis. Weed Res 30:8189
Benech Arnold, RL, Ghersa, CM, Sanchez, RA, Insausti, P (1990b) A mathematical model to predict Sorghum halepense (L.) Pers. seedling emergence in relation to soil temperature. Weed Res 30:9199
Buhler, DD, Hartzler, RG, Forcella, F, Gunsolus, JL (1997) Sustainable Agriculture: Relative Emergence Sequence for Weeds of Corn and Soybeans. Ames, IA: Iowa State University Extension Bulletin SA-11
Burnham, KP, Anderson, DR (2002) Model Selection and Inference: A Practical Information-Theoretic Approach. 2nd edn. New York: Springer Verlag, 488 p
Carey, JB, Kells, JJ (1995) Timing of total postemergence herbicide applications to maximize weed control and corn yield. Weed Technol 9:356361
Davis, AS, Clay, S, Cardina, J, Dille, A, Forcella, F, Lindquist, J, Sprague, C (2013) Seed burial physical environment explains departures from regional hydrothermal model of giant ragweed (Ambrosia trifida) seedling emergence in U.S. Midwest. Weed Sci 61:415421
Forcella, F, Benech-Arnold, RL, Sanchez, R, Ghersa, CM (2000) Modeling seedling emergence. Field Crops Res 67:123139
Forcella, F, Eradat-Oskoui, K, Wagner, SW (1993) Application of weed seedbank ecology to low-input crop management. Ecol Appl 3:7483
Goplen, JJ (2017) Emergence modeling and economics of managing herbicide-resistant giant ragweed (Ambrosia trifida) with crop rotation. Ph.D. dissertation. Minneapolis, MN: University of Minnesota. 73 p
Goplen, JJ, Sheaffer, CC, Becker, RL, Coulter, JA, Breitenbach, FR, Behnken, LM, Johnson, GA, Gunsolus, JL (2017) Seed bank depletion and emergence patterns of giant ragweed (Ambrosia trifida) in Minnesota cropping systems. Weed Sci 65:5260
Griffith, DR, Mannering, JV, Galloway, HM, Parsons, SD, Richey, CB (1973) Effect of eight tillage-planting systems on soil temperature, percent stand, plant growth, and yield of corn on five Indiana soils. Agron J 65:321326
Gunsolus, JL (1990) Mechanical and cultural weed control in corn and soybeans. Am J Alternative Agr 5:114119
Heap, I (2016) The International Survey of Herbicide-Resistant Weeds. Accessed: December 6, 2016
Hoeting, JA, Madigan, D, Raftery, AE, Volinsky, CT (1999) Bayesian model averaging: a tutorial (with discussion). Stat Sci 14:382417
Hurvich, CM, Tsai, CL (1989) Regression and time series model selection in small samples. Biometrika 76:297307
King, CA, Oliver, LR (1994) A model for predicting large crabgrass (Digitaria sanguinalis) emergence as influenced by temperature and water potential. Weed Sci 42:561567
Kladivko, EJ, Griffith, DR, Mannering, JV (1986) Conservation tillage effects on soil properties and yield of corn and soya beans in Indiana. Soil Till Res 8:277287
Kobayashi, K, Salam, MU (2000) Comparing simulated and measured values using mean squared deviation and its components. Agron J 92:345352
Legates, DR, McCabe, GJ Jr (1999) Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resources Res 35:233241
Liebman, M, Dyck, E (1993) Crop rotation and intercropping strategies for weed management. Ecol Appl 3:92122
Luschei, EC, Jackson, RD (2005) Research methodologies and statistical approaches for multitactic systems. Weed Sci 53:393403
Meek, DW, Howell, TA, Phene, CJ (2009) Concordance correlation for model performance assessment: an example with reference evapotranspiration observations. Agron J 101:10121018
Menalled, F, Schonbeck, M (2013) Manage the weed seed bank—minimize “deposits” and maximize “withdrawals.” eXtension. Accessed: December 6, 2016
Mitchell, PL (1997) Misuse of regression for empirical validation of models. Agric Syst 54:313326
Perreault, S, Chokmani, K, Nolin, MC, Bourgeois, G (2013) Validation of a soil temperature and moisture model in southern Quebec, Canada. Soil Sci Soc Am J 77:606617
Schutte, BJ, Regnier, EE, Harrison, SK (2012) Seed dormancy and adaptive seedling emergence timing in giant ragweed (Ambrosia trifida). Weed Sci 60:1926
Schutte, BJ, Regnier, EE, Harrison, SK, Schmoll, JT, Spokas, K, Forcella, F (2008) A hydrothermal seedling emergence model for giant ragweed (Ambrosia trifida). Weed Sci 56:555560
Sellers, BA, Ferrell, JA, MacDonald, GE, Kline, WN (2009) Dogfennel (Eupatorium capillifolium) size at application affects herbicide efficacy. Weed Technol 23:247250
Spokas, K, Forcella, F (2009) Software tools for weed seed germination modeling. Weed Sci 57:216227
Sugiura, N (1978) Further analysis of the data by Akaike’s information criterion and the finite corrections. Commun Stat-Theor M 7:1326
Tedeschi, LO (2006) Assessment of the adequacy of mathematical models. Agric Syst 89:225247
Webster, TM, Loux, M, Regnier, EE, Harrison, SK (1994) Giant ragweed (Ambrosia trifida) canopy architecture and interference studies in soybean (Glycine max). Weed Technol 8:559564
Werle, R, Sandell, LD, Buhler, DD, Hartzler, RG, Lindquist, JL (2014) Predicting emergence of 23 summer annual weed species. Weed Sci 62:267279
Wortman, SE, Davis, AS, Schutte, BJ, Lindquist, JL, Cardina, J, Felix, J, Sprague, CL, Dille, JA, Ramirez, AHM, Reicks, G, Clay, SA (2012) Local conditions, not regional gradients, drive demographic variation of giant ragweed (Ambrosia trifida) and common sunflower (Helianthus annuus) across northern U.S. maize belt. Weed Sci 60:440450
Zhang, S, Lovdaul, L, Grip, H, Tong, Y, Yang, X, Wang, Q (2009) Effects of mulching and catch cropping on soil temperature, soil moisture, and wheat yield on the loess plateau of China. Soil Till Res 102:7886



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