Estimation of thermal thresholds for seedling emergence of spring canola in the field

Document Type : Research Paper

Authors

1 Department of Plant Production and Genetics Engineering, Faculty of Agriculture, Ramin Agriculture and Natural Resources University of Khuzestan

2 Seed and Plant Improvement Department, Research and Education Center of Agricultural and Natural Resources of Khuzestan, Agricultural Research Education and Extension Organization (AREEO)

Abstract

Accurate prediction of seedling emergence in the field is crucial for the performance of growth models. In order to determine thresholds of seedling emergence response to temperature, two replicated field experiments were carried out at Ramin Agriculture and Natural Resource University of Khuzestan during 2015-2016 and 2016-2017. In these experiments, seedling emergence of two spring canola cultivars (Hyola 401 and Sarigol) was evaluated in a randomized complete block design with four replications in fifteen planting dates (as environment). Thermal-time model was developed based on the Weibull probability distribution function, and thermal thresholds for seedling emergence response of two spring canola cultivars in field conditions was modeled based on this function. Based on model outputs, the base temperature for seedling emergence (Tb) was estimated to be 5.83 °C in the hybrid Hyola 401 and 4.16 °C in the cultivar Sarigol. The thermal-time required to initiate seedling emergence at sub-optimal temperature range (θT(0)) and the thermal-time needed to complete seedling emergence at supra-optimal temperature regimes without significant differences between two cultivars was estimated to be 55.5 and 5.65 °C d, respectively. Maximum temperature for the 50% probability of the thermoinhibition of seedling emergence (Tm(50)) in hybrid Hyola 401 and cultivar Sarigol was estimated to be 33.02 and 33.30 °C, respectively. The optimum temperature for 50% seedling emergence in the field (To(50)) for hybrid Hyola 401 and cultivar Sarigol was determined to be 30.99 and 31.22 °C, respectively.

Keywords

Main Subjects


  1. Andreucci, M.P., Moot, D.J., Black, A.D. & Sedcole, R. (2016). A comparison of cardinal temperatures estimated by linear and nonlinear models for germination and bulb growth of forage brassicas. European Journal of Agronomy, 81, 52–63.
  2. Chantre, G.R., Batlla, D., Sabbatini, M.R. & Orioli, G. (2009). Germination parameterization and development of an after-ripening thermal-time model for primary dormancy release of Lithospermum arvense seeds. Annals of Botany, 103(8), 1291-1301.
  3. del Monte, J.P., Aguado, P.L. & Tarquis, A.M. (2014). Thermal time model of Solanum sarrachoides germination. Seed Science Research, 24(4), 321–330.
  4. Derakhshan, A., Bakhshandeh, A., Siadat, S.A., Moradi-Telavat, M.R. & Andarzian, S.B. (2018a). Application of thermal-time concept to modeling oilseed rape (Brassica napus L.) seed germination response to temperature. Iranian Journal of Field Crops Research, Under Publishing. (In Farsi)
  5. Derakhshan, A., Bakhshandeh, A., Siadat, S.A., Moradi-Telavat, M.R. & Andarzian, S.B. (2018b). Quantification of thermoinhibition response of seed germination in different oilseed rape cultivars. Environmental Stresses in Crop Sciences, Under Publishing. (In Farsi)
  6. Derakhshan, A., Bakhshandeh, A., Siadat, S.A., Moradi-Telavat, M.R. & Andarzian, S.B. (2018c). Comparison of probability distribution functions in thermal-time models for modeling of spring oilseed rape germination to temperature. Iranian Journal of Field Crop Science, Under Publishing. (In Farsi)
  7. Derakhshan, A. & Gherekhloo, J. (2013) Factors affecting Cyperus difformis seed germination and seedling emergence. Planta Daninha, 31(4), 823–832.
  8. Derakhshan, A., Gherekhloo, J., Ribas, A.V. & Rafael, D.P. (2014). Quantitative description of the germination of Littleseed Canarygrass (Phalaris minor) in response to temperature. Weed Science, 62(2), 250–257.
  9. Derakhshan, A., Moradi-Telavat, M.R. & Siadat, S.A. (2016). Hydrotime analysis of Melilotus officinalis, Sinapis arvensis and Hordeum vulgare seed germination. Iranian Journal of Plant Protection, 30(3), 518-532. (In Farsi)

10. Forcella, F., Benech Arnold, R.L., Sanchez, R. & Ghersa C.M. (2000). Modeling seedling emergence. Field Crops Research, 67(2), 123–139.

11. Garcia-Huidobro, J., Monteith, J.L. & Squire, G.R. (1982). Time, temperature and germination of pearl millet (Pennisetum typhoides S. & H.). I. Constant temperature. Journal of Experimental Botany, 33(2), 288–296.

12. Hardegree, S.P. (2006). Predicting germination response to temperature. III. Model validation under field-variable temperature conditions. Annals of Botany, 98(4), 827–834.

13. Jame, Y.W. & Cutforth, H.W. (2004). Simulating the effects of temperature and seeding depth on germination and emergence of spring wheat. Agricultural and Forest Meteorology, 124(3–4), 207–218.

14. Keating, B.A., Carberry, P.S., Hammer, G.L., Probert, M.E., Robertson, M.J., Holzworth, D., Huth, N.I., Hargreaves, J.N.G., Meinke, H., Hochman, Z., McLean, G., Verbug, K., Snow, V., Dimes, J.P., Silburn, M., Wang, E., Brown, S., Bristow, K.L., Asseng, S., Chapman, S., McCown, R.L., Freebairn, D.M. & Smith, J.C. (2003). An overview of APSIM, a model designed for farming system simulation. Agricultural Systems, 18(3–4), 267–288.

15. Lakzaei, S., Soltani, A., Zeinali, E., Gaderifar, F. & Jafarnodeh, S. (2017). Quantifying response of seedling emergence to temperature in rapeseed (Brassica napus L.) under field conditions. Iranian Journal of Crop Sciences, 19(3), 195–207. (In Farsi)

16. McMaster, G.S., White, J.W., Hunt, L.A., Jamieson, P.D., Dhillon, S.S. & Ortiz-Monasterio, J.I. (2008). Simulating the influence of vernalization, photoperiod and optimum temperature on wheat developmental rates. Annals of Botany, 102(4), 561–569.

17. Meenken, E.D., Brown, H.E., Triggs, C.M., Brooking, I.R. & Forbes, M. (2016). Phenological response of spring wheat to timing of photoperiod perception: The effect of sowing depth on final leaf number in spring wheat. European Journal of Agronomy, 81(1), 72–77.

18. Ritchie, J.T. & Otter, S. (1985). Description and performance of CERES-Wheat: a user oriented wheat yield model. In: W.O. Willis (Ed), ARS Wheat Yield Project. pp. (159–175) Temple, TX: United States Department of Agriculture, Agricultural Research Service.

19. Soltani, A., Hammer, G.L., Torabi, B., Robertson, M.J. & Zeinali, E. (2006a). Modeling chickpea growth and development: phenological development. Field Crops Research, 99(1), 1–13.

20. Soltani, A., Robertson, M.J., Torabi, B., Yousefi-Daz, M. & Sarparast, R. (2006b). Modeling seedling emergence in chickpea as influenced by temperature and sowing depth. Agricultural and Forest Meteorology, 138(1–4), 156–167.

21. Soltani, A. & Sinclair, T.R. (2011). A simple model for chickpea development, growth and yield. Field Crops Research, 124(2), 252–260.

22. Wang, R., Bai, Y. & Tanino, K. (2004). Effect of seed size and sub-zero imbibitions temperature on the thermal time model of winterfat (Eurotia lanata (Pursh) Moq.). Environmental and Experimental Botany, 51(3), 183–197.

23. Wang, H., Cutforth, H., McCaig, T., McLeod, G., Brandt, K., Lemke, R., Goddard, T. & Sprout, C. (2009). Predicting the time to 50% seedling emergence in wheat using a Beta model. NJAS - Wageningen Journal of Life Sciences, 57 (1) 65–71.

24. Wang, R.L., Wendel, J.L. & Dekker, J.H. (1995). Weedy adaptation in Setaria spp. I. Isozyme analysis of genetic diversity and population genetic structure in Setaria viridis. American Journal of Botany, 82(3), 308–317.

25. Watt, M. & Bloomberg, M. (2012). Key features of the seed germination response to high temperatures. New Phytologist, 196(2), 332–336.

26. Watt, M.S., Bloomberg, M. & Finch-Savage, W.E. (2011). Development of a hydrothermal time model that accurately characterises how thermoinhibition regulates seed germination. Plant, Cell & Environment, 34(5), 870–876.

27. Watt, M.S., Whitehead, D., Kriticos, D.J., Gous, S.F. & Richardson, B. (2007). Using a process-based model to analyse compensatory growth in response to defoliation: Simulating herbivory by a biological control agent. Biological Control, 43(1), 119–129.

28. Watt, M.S., Xu, V. & Bloomberg, M. (2010). Development of a hydrothermal time seed germination model which uses the Weibull distribution to describe base water potential. Ecological Modelling, 221(9), 1267–1272.

29. Yin, X., Kropff, M.J., McLaren, G. & Visperas, R.M. (1995). A nonlinear model for crop development as a function of temperature. Agricultural and Forest Meteorology, 77(1–2), 1–16.

Volume 50, Issue 1
May 2019
Pages 59-69
  • Receive Date: 06 March 2018
  • Revise Date: 10 July 2018
  • Accept Date: 21 July 2018
  • Publish Date: 22 May 2019