Emergence Prediction of Common Cocklebur and Redroot Pigweed in Maize Using Thermal Time Models | ||
| دانش علفهای هرز ایران | ||
| Article 7, Volume 11, Issue 1, January 0, Pages 77-90 PDF (505.84 K) | ||
| Document Type: Research Article | ||
| Abstract | ||
| The knowledge of the relationship between seedling emergence time and the prevailing environmental condition such as temperature is useful to timely application of herbicides. Two years of study was conducted to investigate seedling emergence of Xanthium strumarium and Amaranthus retroflexus in maize in two contrasting environments of Karaj and Tonkabon. Thermal time was used for predicting cumulative weed emergence. The Gompertz model was found more likely to predict weed emergence patterns for different sites and years. X. stramurium started its emergence with receiving 200 GDD. It required 500 GDD to reach its maximum emergence. The emergence of X. stramorium continued through the season up to 900 GDD. For A. retroflexus, emergence started at 400 GDD and with receiving a GDD of 600 reached its maximum level. A. retroflexus showed a relatively whole season emergence and continued its emergence up to 1200 GDD. Therefore, choosing the right time for herbicide spraying is accompanied with complexities. Predicting the start and the duration of seedling emergence in fields could optimize weed control timing. | ||
| Keywords | ||
| Seedling emergence pattern; gompertz; thermal mode; xanthium strumarium; amaranthus retroflexus; maize | ||
| References | ||
|
drich, R.J. and Kremer, R J. 1997. Principles in Weed Management. John Wiley & Sons, New York, NY,Al USA.455p. Alm, D.M., Stoller, E.W., and Wax, L.M. 1993. An index model for predicting seed germination and emergence rates. Weed Technol. 7: 560–569. Anderson, R. L. and Nielsen, D. C. 1996. Emergence pattern of five weeds in the central great plains. Weed Technol. 10: 744–749. Baskin, C. C. and Baskin, J. M. 1998. Seeds: Ecology, Biogeography, and Evolution of Dormancy and Germination. San Diego, CA: Academic. pp. 27–124: 185–200. Baskin, J. M. and Baskin, C. C. 1990. Role of temperature and light in the germination ecology of buried seeds of Potentilla recta. Ann. Appl. Biol. 117:611–616. Benech-Arnold, R. L., Ghersa, C. M., Sanchez, R. A. and Insausti, P.1990. A mathematical model to predict Sorghum halepense (L.) Pers. seedling emergence in relation to soil temperature. Weed Res. 30: 91–99. Bilbro, J. D. and Wanjura, D. F. 1982. Soil crust and cotton emergence relationship. T ASAE. 25: 1485–1488. Black, D. and Dayson, C. B. 1993. An economic threshold model for spraying herbicides in cereals. Weed Res. 33: 279-290. Boyd, N. S. and Van Acker, R. C. 2003. The effects of depth and fluctuating soil moisture on the emergence of eight annual and six perennial plant species. Weed Sci. 51: 725–730. Brain, P., Wilson, B. J., Wright, K. J., Seavers, G. P. and Casele,. J. C. 1999. Modelling the effect of crop and weed on herbicide efficacy in wheat. Weed Res. 39: 21–35. Brown, R. F. and Mayer, D. G. 1988. Representing cumulative germination. 2. The use of the Weibull function and other empirically derived curves. Ann. Bot. 61: 127–138. Chauhan, B. S., Gill, G. and Preston, C. 2006. Seedling recruitment pattern and depth of recruitment of 10 weed species in minimum tillage and no-till seeding systems. Weed Sci. 54: 658–668. Colbach, N., Durr, C., Roger-Estrade, J. and Caneill, J. 2005. How to model the effects of farming practices on weed emergence. Weed Res. 45: 2–17. Donald, W. W. 2000. A degree-day model of Cirsium arvense shoot emergence from adventitious root buds in spring. Weed Sci. 48: 333-341. Dorado, J., Sousa, E., Calha, I. M., Gonzalez-Andujar, J. L. and Frenandez-Quintalilla, C. 2009. Predicting weed emergence in maize crops under two contrasting climatic conditions. Weed Res. 49:251-260. Egley, G. H. and Williams, E. 1991. Emergence periodicity of six summer annual weed species. Weed Sci. 39:595–600. Ekeleme, F., Forcella, F., Archer, D. W., Akobundu, I. O. and Chikoye, D. 2005. Seedling emergence model for tropic ageratum (Ageratum conyzoides). Weed Sci. 53:55–61. Forcella, F. 1998. Real-time assessment of seed dormancy and seedling growth for weed management. Seed Sci. Res. 8: 201–209. Forcella, F., Arnold, R. L. B., Sanchez, R. and Ghersa, C. M. 2000. Modeling seedling emergence. Field Crops Res. 67:123–139. Forcella, F., Wilson, R. G. and Dekker, J. 1997. Weed seed bank emergence across the Corn Belt. Weed Sci. 67:123–129. Grundy, A. C. 2003. Predicting weed emergence: a review of approaches and future challenges. Weed Res. 43: 1–11. Grundy, A. C. and Mead, A. 2000. Modelling weed emergence as a function of meteorological records. Weed Sci. 48: 594–603. Grundy, A. C., Peters, N. C. B. and Ramussen, I. A. 2003. Emergence of Chenopodium album and Stellaria media of different origins under different climatic conditions. Weed Res. 43: 163–176. Haupt, R. L. and Haupt, S. E. 1998. Practical Genetic Algorithms. John Wiley & Sons, New York, NY, USA. Leblanc, M. L., Cloutier, D. C., Stewart, K. and Hamel, C. 2003. The use of thermal time to model common lambsquarters (Chenopodium album) seedling emergence in corn. Weed Sci. 51: 718–724. Leguizamo´n, E. S. 1986. Seed survival and periodicity of seedling emergence in Sorghum halepense L. Weed Res. 26: 397–403. Leguizamon, E. S., Fernandez-Quintanilla, C., Barros, J. and Gonzalez-Andujar, J. L. 2005. Using thermal and hydrothermal time to model seedling emergence of Avena sterilis ssp ludoviciana in Spain. Weed Res. 45: 149–156. Leon, R. G., Knapp, A. D. and Owen, M. D. K. 2004. Effect of temperature on the germination of common waterhemp (Amaranthus tubeculatus), giant foxtail (Setaria faberi), and velvetleaf (Abutilon theophrasti). Weed Sci. 52; 67-73. Martinson, K., Durgan, B., Forcella, F., Wiersma, J., Spokas, K. and Archer, D. 2007. An emergence model for wild oat (Avena fatua). Weed Sci. 55: 584-591. Mohler, C. L. 1993. A model of the effects of tillage on emergence of weed seedlings. Ecol. Appl. 3: 53–73. Myers, M. W., Curran, W. S. and Vangessel, M. J. 2004. Predicting weed emergence for eight annual species in the northeastern United States. Weed Sci. 52: 913–919. Norsworthy, J. k. and Oliveira, M. J. 2007. A model for predicting common cocklebur (Xanthium strumarium) emergence in soybean. Weed Sci. 55: 341–345. Oryokot, J. O. E., Hunt, L. A., Murphy, S. and Swanton, C. J. 1997. Simulation of pigweed (Amaranthus spp.) seedling emergence in different systems. Weed Sci. 45:684–690. Oveisi, M., Rahimian, H., Baghestani and M. A., Alizade, H. 2008. Modelling interactions between multiple weed competition and herbicide dose in corn. Iranian Weed Sci. 4:47-55. (In persian with English abstract). Roach, D. A., and Wullf, R. D. 1987. Maternal effects in plants. Annu. Rev. Ecol. Syst. 18: 209-235. Roberts, H. A. and Feast, P. M. 1970. Seasonal Roman, E. S., Murphy, S.D. and Swanton, C.J. 2000. Simulation of Chenopodium album seedling emergence. Weed Sci. 48:217–224. Schutte, B. J., Regnier, E. E., Harrison, S. K., Schmoll, J. T., Spokas, K. and Forcella, F. 2008. A hydrothermal seedling emergence model for giant ragweed (Ambrosia trifida). Weed Sci. 56: 555-560. Shrestha, A., Roman, E. S., Thomas, A. G. and Swanton, C. J. 1999. Modeling germination and shoot-radicle elongation of Ambrosia artemisiifolia. Weed Sci. 47: 557–562. Stoller, E. W. and Wax, L. M. 1973. Periodicity of germination and emergence of some annual weeds. Weed Sci. 21: 574–580. | ||
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