Seedling emergence of tall fescue and wheatgrass under different climate conditions in Iran

  • B. Behtari Department of Crop Ecology, Faculty of Agronomy, Tabriz Branch, Islamic Azad University, Postal code: 1655, Tabriz
  • M. de Luis Departament of Geography. University of Zaragoza
Keywords: Agropyron desertorum, Festuca arundinacea, Gompertz model, Weibull model, germination

Abstract

Seedling emergence is one of the most important processes determining yield and the probability of crop failure. The ability to predict seedling emergence could enhance crop management by facilitating the implementation of more effective weed control strategies by optimizing the timing of weed control. The objective of the study was to select a seedling emergence thermal time model by comparing five different equations for tall fescue and wheatgrass in two sites with different climate conditions (semiarid- temperate and humid-warm) in Iran. In addition, seedling emergence between two target species were studied. Among the five models compared, the Gompertz and Weibull models gave more succesful results. In humid-warm conditions, the total emergence of wheatgrass was higher than observed in tall fescue. In contrast, emergence was faster in tall fescue than wheatgrass in both study sites.Given that early-emerging plants have been described as contributing more to crop yield than later-emerging ones, tall fescue is proposed as a more suitable specie for semiarid- temperate conditions in Iran.

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Author Biographies

B. Behtari, Department of Crop Ecology, Faculty of Agronomy, Tabriz Branch, Islamic Azad University, Postal code: 1655, Tabriz
M. de Luis, Departament of Geography. University of Zaragoza
Department Geography. Associated profeesor

References

Akaike H, 1974. A new look at the statistical model identifcation. IEEE Trans Automat Contr 19: 716–723. http://dx.doi.org/10.1109/TAC.1974.1100705

Behtari B, 2009. Effect of hydropriming and osmopriming on germination, seedling emergence, quality and quantity of forage production of Festuca arundinaceae Schreb and Agropyron desertorum (Fisch. ex Link) J.A. Schultes. MS thesis. Fac Nat Resour, Tarbiat Modares Univ. Tehran, Iran. 78 pp.

Burnham KP, Anderson, DR, 2002. Model selection and multimodel inference: a practical information-theoretic approach, 2nd ed. Springer-Verlag. NY. 488 pp.

De Luis M, Verdú M, Raventós J, 2008. Early to rise makes a plant healthy, wealthy and wise. Ecol 89: 3061-3071. http://dx.doi.org/10.1890/07-1828.1

Forcella F, 1998. Real-time assessment of seed dormancy and seedling growth for weed management. Seed Sci Res 8: 201–209. http://dx.doi.org/10.1017/S0960258500004116

Forcella F, Bench Arnold RL, Sanchez R, Ghersa CM, 2000. Modeling seedling emergence. Field Crop Res 67: 123-139. http://dx.doi.org/10.1016/S0378-4290(00)00088-5

France J, Thornley JHM, 1984. Mathematical models in agriculture. Oxford Univ Press. Butterworths, London. 335 pp.

Gan Y, Stobe EH, Moes J, 1992. Relative date of wheat seedling emergence and its impact on grain yield. Crop Sci 32: 1275–1281. http://dx.doi.org/10.2135/cropsci1992.0011183X003200050042x

Gazanchian A, Khosh Kholgh Sima NA, Malboobi MA, Majidi Heravan E, 2006. Relationships between emergence and soil water content for perennial cool-season grasses native to Iran. Crop Sci 46: 544-553. http://dx.doi.org/10.2135/cropsci2005.04-0357

Gompertz B, 1825. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos Trans Royal Soc 182: 513–585. http://dx.doi.org/10.1098/rstl.1825.0026

Grundy AC, Phelps K, Reader RJ, Burston S, 2000. Modelling the germination of Stellaria media using the concept of hydrothermal time. N Phyto 148: 433–444. http://dx.doi.org/10.1046/j.1469-8137.2000.00778.x

Haj Seyed Hadi MR, González-Andujar JL, 2009. Comparison of fitting weed seedling emergence models with nonlinear regression and genetic algorithm. Comput Electron Agr 65: 19–25. http://dx.doi.org/10.1016/j.compag.2008.07.005

Harper JL, 1977. Population biology of plants. Academic Press. London, 892 pp.

Iran Meteorological Organization, 2009. Ministry of Road and Urban Development. Available in http://www.irimo.ir. [April 27, 2009].

Karssen CM, 1982. Seasonal patterns of dormancy in weed seeds. In: The physiology and biochemistry of seed development, dormancy and germination (Khan AA, ed.). Elsevier Biomedical Press, Amsterdam, pp: 243–270.

Kingland S, 1982. The refractory model: The logistic curve and history of population ecology. Quart Rev Biol 57: 29-51. http://dx.doi.org/10.1086/412574

Kowalenko BL, Romo JT, 1998. Regrowth and rest requirements of northern wheatgrass following defoliation. J Range Manage 51: 73-78. http://dx.doi.org/10.2307/4003567

Leblanc ML, Cloutier DC, Stewart KA, Hamel C, 2004. Calibration and validation of a common lambsquarter (Chenopodium album) seedling emergence model. Weed Sci 52: 61–66. http://dx.doi.org/10.1614/P2002-109

Mohanty M, Painuli DK, 2004. Modeling rice seedling emergence and growth under tillage and residue management in a rice–wheat system on a Vertisol in Central India. Soil Till Res 76: 167–174. http://dx.doi.org/10.1016/j.still.2003.10.001

Motulsky HJ, Christopoulos A, 2003. Fitting models to biological data using linear and nonlinear regression: a practical guide to curve fitting. GraphPad Software Inc., San Diego, CA, USA. 352 pp.

Mozaffarian V, 1996. A dictionary of Iranian plant names. Farhang Moaser, Tehran, Iran, 547 pp.

Myers MW, Curran WS, Vangessel MJ, Galvin 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. http://dx.doi.org/10.1614/WS-04-025R

Palazzo AJ, Brar GS. 1997. The effects of temperature on germination of eleven Festuca cultivars. US Army Crops of Enginering, Hanover, NH, USA, Special Report, pp: 97-19.

Phil SA, Benech-Arnold RL, Batlla D, Bradford KJ, 2007. modeling of seed dormancy, In: Seed development, dormancy and germination (Bradford KJ, Nonogaki H, eds.), Blackwell Publ Ltd, Oxford, UK, pp. 72-112.

Richards FJ, 1959. A flexible growth functions for empirical use. J Exper Bot 10: 290–300. http://dx.doi.org/10.1093/jxb/10.2.290

Roush WB, Branton SL, 2005. A comparison of fitting growth models with a genetic algorithm and nonlinear regression. Poult Sci 84: 494–502. PMid:15782921

Snedecor GW, Cochran GW, 1973. Statistical methods. The Iowa Stat e Univ Press, Ames, IA, USA. 503 pp.

Soltani A, Zeinali E, Galeshi S, Latifi N, 2001. Genetic variation for and interrelationships among seed vigor traits in wheat from the Caspian Sea coast of Iran. Seed Sci Technol 29: 653–662.

Verhulst PF, 1838. A note on population growth. Correspondence Mathematiques et Physiques 10: 113–121.

Vleeshouwers LM, Kropff MJ, 2000. Modeling field emergence patterns in arable weeds. N Phytol 148: 445–457. http://dx.doi.org/10.1046/j.1469-8137.2000.00773.x

Published
2012-01-30
How to Cite
Behtari, B., & de Luis, M. (2012). Seedling emergence of tall fescue and wheatgrass under different climate conditions in Iran. Spanish Journal of Agricultural Research, 10(1), 183-190. https://doi.org/10.5424/sjar/2012101-486-10
Section
Plant production (Field and horticultural crops)