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Predicting Emergence of 23 Summer Annual Weed Species

Published online by Cambridge University Press:  20 January 2017

Rodrigo Werle ,
Lowell D. Sandell ,
Douglas D. Buhler ,
Robert G. Hartzler  and
John L. Lindquist
Rodrigo Werle
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583
Lowell D. Sandell*
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583
Douglas D. Buhler
Affiliation:
Michigan State University, East Lansing, MI 48824
Robert G. Hartzler
Affiliation:
Iowa State University, Ames, IA 50011
John L. Lindquist
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583
*
Corresponding author's E-mail: lsandell2@unl.edu
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Abstract

First- and second-year seedbank emergence of 23 summer annual weed species common to U.S. corn production systems was studied. Field experiments were conducted between 1996 and 1999 at the Iowa State University Johnson Farm in Story County, Iowa. In the fall of 1996 and again in 1997, 1,000 seeds for most species were planted in plastic crates. Seedling emergence was counted weekly for a 2-yr period following seed burial (starting in early spring). Soil temperature at 2 cm depth was estimated using soil temperature and moisture model software (STM2). The Weibull function was fit to cumulative emergence (%) on cumulative thermal time (TT), hydrothermal time (HTT), and day of year (DOY). To identify optimum base temperature (Tbase) and base matric potential (ψbase) for calculating TT or HTT, Tbase and ψbase values ranging from 2 to 17 C and −33 to −1,500 kPa, respectively, were evaluated for each species. The search for the optimal model for each species was based on the Akaike's Information Criterion (AIC), whereas an extra penalty cost was added to HTT models. In general, fewer seedlings emerged during the first year of the first experimental run (approximately 18% across all species) than during the second experimental run (approximately 30%). However, second-year seedbank emergence was similar for both experimental runs (approximately 6%). Environmental effects may be the cause of differences in total seedling emergence among years. Based on the AIC criterion, for 17 species, the best fit of the model occurred using Tbase ranging from 2 to 15 C with four species also responding to ψbase = −750 kPa. For six species, a simple model using DOY resulted in the best fit. Adding penalty costs to AIC calculation allowed us to compare TT and HTT when both models behaved similarly. Using a constant Tbase, species were plotted and classified as early-, middle-, and late-emerging species, resulting in a practical tool for forecasting time of emergence. The results of this research provide robust information on the prediction of the time of summer annual weed emergence, which can be used to schedule weed and crop management.

Keywords

AIC criterioninformation-theoretic model comparison approachthermal timeweather dataWeibull model
Type
Weed Biology and Ecology
Information
Weed Science , Volume 62 , Issue 2 , June 2014 , pp. 267 - 279
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Abul-Fatih, HA, Bazzaz, FA (1979) The biology of Ambrosia trifida L. II. Germination, emergence, growth and survival. New Phytol. 83:817–827 Google Scholar
Al-Ahmadi, MJ, Kafi, M (2007) Cardinal temperatures for germination of Kochia scoparia (L.). J Arid Environ. 68:308–314 Google Scholar
Alm, DM, Stoller, EW, Wax, LM (1993) An index model for predicting seed germination and emergence rates. Weed Technol. 7:560–569 Google Scholar
Anderson, DR (2008) Model based inference in the life sciences: primer on evidence. New York Springer. 184 pGoogle Scholar
Anderson, RL (1994) Characterizing weed community seedling emergence for a semiarid site in Colorado. Weed Technol. 8:245–249 Google Scholar
Baskin, CC, Baskin, JM (1988) Germination ecophysiology of herbaceous plant species in a temperature region. Am J Bot. 75:286–305 Google Scholar
Bello, IA, Hatterman-Valenti, H, Owen, MDK (2000) Factors affecting germination and seed production of Eriochloa villosa . Weed Sci. 48:749–754 Google Scholar
Buhler, DD, Hartzler, RG (2001) Emergence and persistence of seed of velvetleaf, common waterhemp, woolly cupgrass, and giant foxtail. Weed Sci. 49:230–235 Google Scholar
Buhler, DD, Hartzler, RG, Forcella, F, Gunsolus, JL (1997) Sustainable agriculture: Relative emergence sequence for weeds of corn and soybeans. Iowa State University Extension Bulletin SA-11, 4 pGoogle Scholar
Burnside, OC, Wilson, RG, Weisberg, S, Hubbard, KG (1996) Seed longevity of 41 weed species buried 17 years in eastern and western Nebraska. Weed Sci. 44:74–86 Google Scholar
Chachalis, D, Korres, N, Khah, EM (2008) Factors affecting seed germination and emergence of Venice mallow (Hibiscus trionum). Weed Sci. 56:509–515 Google Scholar
Clay, SA, Davis, A, Dille, A, Lindquist, J, Ramirez, A, Sprague, C, Reicks, G, Forcella, F (2014) Common sunflower seedling emergence across the U.S. Midwest. Weed Sci. 62:63–70 Google Scholar
Conn, JS, Beattie, KL, Blanchard, A (2006) Seed viability and dormancy of 17 weed species after 19.7 years of burial in Alaska. Weed Sci. 54:464–470 Google Scholar
Crawley, MJ (2007) The R Book. West Sussex, UK J. Wiley. 942 pGoogle Scholar
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. 61:415–421 Google Scholar
Davis, AS, Schutte, BJ, Iannuzzi, J, Renner, KA (2008) Chemical and physical defense of weed seeds in relaion to soil seedbank persistence. Weed Sci. 56:676–684 Google Scholar
Forcella, F, Benech-Arnold, RL, Sanchez, RE, Ghersa, CM (2000) Modeling seedling emergence. Field Crop Res. 67:123–139 Google Scholar
Forcella, F, Wilson, RG, Dekker, J, Kremer, R, Cardina, J, Anderson, RL, Alm, D, Renner, KA, Harvey, RG, Clay, S, Buhler, DD (1997) Weed seed bank emergence across the Corn Belt. Weed Sci. 67:123–129 Google Scholar
Grundy, AC (2003) Predicting weed emergence: a review of approaches and future challenges. Weed Res. 43:1–11 Google Scholar
Gummerson, RJ (1986) The effect of constant temperatures and osmotic potential on the germination of sugar beet. J Exp Bot. 41:1431–1439 Google Scholar
Hartzler, RG, Buhler, DD, Stoltenberg, DE (1999) Emergence characteristics of four annual weed species. Weed Sci. 47:578–584 Google Scholar
Izquierdo, J, Gonzalez-Andujar, JL, Bastida, F, Lezaun, JA, del Arco, MJS (2009) A thermal time model to predict corn poppy (Papaver rhoeas) emergence in cereal fields. Weed Sci. 57:660–664 Google Scholar
Leguizamon, ES, Fernandez-Quintanilla, C, Barroso, J, Gonzalez-Andujar, JL (2005) Using thermal and hydrothermal time to model seedling emergence of Avena sterilis ssp. ludoviciana in Spain. Weed Res. 45:149–156 Google Scholar
Leon, RG, Knapp, AD, Owen, MDK (2004) Effect of temperature on the germination of common waterhemp (Amaranthis tuberculatus), giant foxtail (Setaria faberi), and velvetleaf (Abutilon theophrasti). Weed Sci. 52:67–73 Google Scholar
Lindquist, JL, Mortensen, DA, Clay, SA, Schmenk, R, Kells, JJ, Howatt, K, Westra, P (1996) Stability of corn (Zea mays)-velvetleaf (Abutilon theophrasti) interference relationships. Weed Sci. 44:309–313 Google Scholar
Mann, RK, Rieck, CE, Witt, WW (1981) Germination and emergence of burcucumber (Sicyos angulatus). Weed Sci. 29:83–86 Google Scholar
Martinson, K, Durgan, B, Forcella, F, Wiersma, J, Spokas, K, Archer, D (2007) An emergence model for wild oat (Avena fatua). Weed Sci. 55:584–591 Google Scholar
Masin, R, Loddo, D, Benvenuti, S, Zuin, MC, Macchia, M, Zanin, G (2010) Temperature and water potential as parameters for modeling weed emergence in central-northern Italy. Weed Sci. 58:216–222 Google Scholar
Mayer, DG, Butler, DG (1993) Statistical validation. Ecol Model. 68:21–32 Google Scholar
Myers, MM, Curran, WS, Vangessel, MJ, Calvin, DD, Mortensen, DA, Majek, BA, Karsten, HD, Roth, GW (2004) Predicting weed emergence for eight annual species in the northeastern United States. Weed Sci. 52:913–919 Google Scholar
Norsworthy, JK, Oliveira, MJ (2007) A model for predicting common cocklebur (Xanthium strumarium) emergence in soybean. Weed Sci. 55:341–345 Google Scholar
Nussbaum, ES, Wiese, AF, Crutchfield, DE, Chenault, EW, Lavake, D (1985) The effects of temperature and rainfall on emergence and growth of eight weeds. Weed Sci. 33:165–170 Google Scholar
Ogg, AG Jr., Dawson, JH (1984) Time of emergence of eight weed species. Weed Sci. 32:327–335 Google Scholar
Pawlak, JA, Murray, DS, Smith, BS (1990) Influence of capsule age on germination of nondormant jimsonweed (Datura stramonium) seed. Weed Technol. 4:31–34 Google Scholar
Radosevish, S, Holt, J, Ghersa, C (1997) Weed Ecology. 2nd edn. New York J. Wiley. 589 pGoogle Scholar
Roman, ES, Murphy, SD, Swanton, CJ (2000) Simulation of Chenopodium album seedling emergence. Weed Sci. 48:217–224 Google Scholar
Roman, ES, Thomas, AG, Murphy, SD, Swanton, CJ (1999) Modeling germination and seedling elongation of common lambsquarters (Chenopodium album). Weed Sci. 47:149–155 Google Scholar
Schutte, BJ, Regnier, EE, Harrison, SK (2012) Seed dormancy and adaptive seedling emergence timing in giant ragweed (Ambrosia trifida). Weed Sci. 60:19–26 Google Scholar
Schwinghamer, TD, Van Acker, RC (2008) Emergence timing and persistence of kochia (Kochia scoparia). Weed Sci. 56:37–41 Google Scholar
Shrestha, A, Roman, ES, Thomas, AG, Swanton, CJ (1999) Modeling germination and shoot-radicle elongation of Ambrosia artemisiifolia . Weed Sci. 47:557–562 Google Scholar
Spokas, K, Forcella, F (2009) Software tools for weed seed germination modeling. Weed Sci. 57:216–227 Google Scholar
Stoller, EW, Wax, LM (1973) Periodicity of germination and emergence of some annual weeds. Weed Sci. 21:74–580 Google Scholar
Vangessel, MJ, Renner, KA (1990) Effect of soil type, hilling time, and weed interference on potato (Solanum tuberosum) development and yield. Weed Technol. 4:299–305 Google Scholar
Weaver, SE, Tan, CS, Brain, P (1988) Effect of temperature and soil moisture on time of emergence of tomatoes and four weed species. Can J Plant Sci. 68:877–886 Google Scholar
Werle, R, Bernards, ML, Arkebauer, TJ, Lindquist, JL (2014) Environmental triggers of winter annual weed emergence in the midwestern United States. Weed Sci. 62:83–96 Google Scholar