Estimation of Cardinal Temperatures of Carthamus oxycantha Germination Using Different Regression Models

پژوهش های حفاظت گیاهان ایران

Article 10, Volume 32, Issue 4 - Serial Number 42, December 2019, Pages 569-578   

Document Type: Research Article

DOI: 10.22067/jpp.v32i4.66879

Authors

fatemeh fakhrrad^* ; ali ghanbari; mehdi rastgoo

ferdowsi

Abstract

Introduction: The genus Carthamus includes 25 species and subspecies in Iran, the two species C. oxycantha and C. lanatus have the most diversity, distribution and adaptation to the climatic conditions of Iran. C. oxycantha is a broadleaf weed and belongs to sunflower (Asteraceae) family. As seed germination is the beginning of the life cycle of plants, seedling emergence is critical for the establishment of plant populations. Germination and early seedling growth of many plants are the most sensitive stages to environmental stresses. Environmental factors, such as temperature, soil solution osmotic potential, solution pH, light quality, management practices and seed location in the soil seed bank, affect weed seed germination and emergence. Temperature is the most important environmental factors that control plant development, growth and yield. All biological processes respond to temperature, and all responses can be summarized in terms of three cardinal temperatures, namely the base or minimum (Tmin), the optimum (Topt), and the maximum (Tm) temperatures. Modeling of seed germination is considered an effective approach to determining cardinal temperatures for most plant species. Determination of cardinal temperatures could be a useful guidance to introduce new species in a new area or in selection of the sowing time. A clear understanding of cardinal temperatures could also be the first step for domestication of new species. There are various mathematical models describing seed germination responses to temperature, among which three have been used more often: intersected lines (ISL), quadratic polynomial (QPN) and five parameters beta (FPB).
 Material and Methods: In order to investigate percentage and germination rate of C. oxycantha seeds, a laboratory experiment was conducted in complete randomized design (CRD) with four replications and under 7 constant temperatures 5, 10, 15, 20, 25, 30 and 35 ºC. Seeds were sterilized with 0.5% sodium hypochlorite solution for 1 min. Followed by washing with distilled water. Then, they were transferred to 9 cm diameter sterilized petri dish containing single layer of filter paper (Wathman #1). The germinated seeds were counted daily and continued until a cumulative germination reached a fixed amount (up to 14 days) or when 100% germination was achieved. Seeds were considered as germinated if the radicle was visible. To estimate the effects of temperature on germination rate of C. oxycantha seeds, three regression models included: Five-parameters Beta (FPB), Intersected-lines (ISL) and Quadratic Polynomial (QPN), were used. The germination data were tested for normality before analysis of variance. Data were analyzed using SAS 9.1 and Microsoft Excel 2007, and figures were designed by Sigmaplot 12.5.
 Results and Discussion: The results of the experiment showed that the temperature had a significant effect on the percentage and rate of germination. The lowest germination percentage was at 30°C (23%), while the lowest germination rate (0.62) occurred at 5°C. The highest germination percentage and germination rate occurred in 15-20 ºC. Generally, by increasing temperature from 5 °C to 20 °C, the percentage and germination rate increased and decreased after 20 °C, so that at 35 ºC, no seeds of wild safflower germinated. Based on the regression models the cardinal temperatures (Tbase, Topt and Tmax) were (4.4-5), (19.6-19.91) and (28.4-33.66) °C, respectively. ISL was the best model to estimate cardinal temperature of C. oxycantha based on the root-mean-square error, determination coefficient and residual values. According this model, the base, optimum and maximum temperatures were estimated as 4.41°C, 19.6°C and 33.3 °C. Khalaj et al (2015) modeled the germination rate of three medicinal plants, including wild oat (Avena fatua L.), wild mustard (Sinapis arvensis L.) and Descurania Sophia (L.). They showed that the segmented model was the best. But parmoon et al (2015) showed that the beta model was found to be the best model for predicting the germination rate and cardinal temperature of milk thistle (Silybum marianum L.). Soltani et al (2006) showed that the response of chickpea (Cicer arietinum L.) emergence to temperature is best described by a dent-like function.
 Conclusion: The result of this experiment showed the best model to estimate cardinal temperature of C. oxycantha was ISL. According this model Tb, To and Tm were estimated as1.4.41°C, 19.6°C and 33.3°C, respectively.  It should be noted that although according to the results of this experiment, the optimum germination temperature in the wild safflower was about 20 °C and high temperatures were effective in reducing germination percentage and consequently inducing dormancy in the safflower seedlings, with climate change, plants such as wild safflower adapted to the new conditions, and the cardinal temperatures of this plant may also be changed in accordance with the new conditions.

Keywords

Germination rate; Optimum temperature; Intersected-line model

References

1. Asgarpour R., Mijani S., and Ghorbani R. 2013. Effect of temperature on germination rate of two passion grasses (Salsola kali L.) based on regression models, Journal of Plant Protection (Agriculture Sciences and Technology), 7(4): 476-483. (In Persian with English abstract)

2. Alvarado V., and Bradford K.J. 2002. A hydrothermal time model explains the cardinal temperatures for seed germination. Journal of Plant, Cell and Environment, 25: 1061-1069.

3. Bassiri A., Rouhani I., and Ghorashy S.R. 1975. Effect of temperature and scarification on germination and emergence of wild safflower, Carthamus oxyacantha. Agricultural Science, 84: 239-243.

4. Behdani M.A., Koocheki A., Nassiri M., and Rezvani P. 2008. Models of predict flowering time in the main Saffron production regions of Khorasan province. Applied Sciences, 8: 907-909.

5. Bewley J.D., ‎Bradford K.j., Hilhorst H.W.M., and Nonogaki H. 2012. Seeds: Physiology of Development, Germination and Dormancy, Third Edition. Press, Springer New York, Heidelberg Dordrecht London.

6. Bradford K.J. 2002. Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Science, 50: 248–260.

7. Cave R.L, Birch C.J., Hammer G.L., Erwin J.E., and Johnston M.E. 2011. Cardinal temperature and thermal time for seed germination of Brunonia australis (Goodeniaceae) and Calandrinia sp. (Portulacaceae). HortScience, 46:753–758.

8. Dashti M., Kafi M., Tavakkoli H., and Mirza M. 2015. Cardinal temperatures for germination of Salvia leriifolia Benth. herba polonica, 60: 5-18.

9. Dittrich M., Petrak F., Rechinger K.H., and Wagenitz G. 1979. Compositae Cynareae. In: Rechinger, K.H. (ed.), Flora Iranica, Pp: 139-468. Journal of Echology, 18:1216–1220.

10. Ebrahimi E., and Eslami S.V. 2012. Effect of environmental factors on seed germination and emergence of invasive Ceratocarpus arenarius. Weed Research, 52: 50–59.

11. Forcella F., Benech-Arnold R.L., Sanchez R., and Ghersa C.M. 2000. Modelling seedling emergence. Field Crops Research, 67: 123-139.

12. Ghaderi–Far F., Soltani A., and Sadeghi-pour H.R. 2009. Evaluation of nonlinear regression models in quantifying germination rate of medicinal pumpkin (Cucurbita pepo L.) Journal of Plant Protection (Agriculture Sciences and Technology), 16(4): 1 - 19. (In Persian with English abstract)

13. Ghaderi-Far F., Gherekhloo J., and Alimagham M. 2010. Influence of environmental factors on seed germination and seedling emergence of yellow sweet clover (Melilotus officinalis). Planta Daninha, 28: 463–469.

14. Ghersa C.M., Benech-Arnold R.L., Sattore E.H., and Martınez-Ghersa M.A. 2000. Advances in weed management strategies. Field Crop Research, 67: 95–104.

15. Hakansson I., Myrbeck A., and Erarso A. 2002. A review of research on seedbed preparation for small grains in Sweden. Soil Tillage Research, 64: 23–40.

16. Hashemi A., Baruti S.H., and Tavakolafshari R. 2017. Determine the cardinal temperatures of Marguerite seed (Chrysanthemum maximum Ramond). Iranian Journal of Seed Science and Technology, 5: 77-84. (In Persian)

17. Hosseini M., Mojab M., and Zamani G.H. 2017. Cardinal temperatures for seed germination of wild barley, barley grass and hoary cress. Archives of Agronomy and Soil Science, 63: 352-361.

18. Khalaj H., Allahdadi I., Iranejad H., Akbari G.A., MinBashi M., Baghestani M.A., Labbafi M., and Mehrafarin A. 2015. Using nonlinear regression model for estimation of cardinal temperatures in three medicinal plants. Journal of Kasetsart -Natural Science, 49: 165 – 173.

19. Maguire J.D. 1962. Speed of germination aid in selection and evaluation for seedling emergence and vigor. Crop Science, 2: 176-177.

20. Masin R., Zuin M.C., Archer D.W., Forcella F., and Zanin G. 2005. A predictive model to aid control of annual summer weeds in turf. Weed Science, 53:193–201.

21. Meyer S.E., and Pendleton R.L. 2000. Genetic regulation of seed dormancy in Purshia tridentata (Rosaceae). Annuals of Botany, 85: 521-529.

22. Parmoona G.H., Hamed Akbarib S.A., and Ebadia A. 2015. Quantifying cardinal temperatures and thermal time required for germination of Silybum marianum. Journal of Seed and Crop, 3: 145-151.

23. Pourreza J., and Bahrani S.A. 2012. Estimating Cardinal Temperatures of Milk Thistle (Silybum marianum) Seed Germination. Agriculture and Environment Science, 12: 1030-1034.

24. Rashed Mohsen M., Najafi H., and Akbarzadeh M. 2001. Biology and Weed Control. Ferdowsi University Press, Mashhad. (In Persian)

25. Rowse H.R., and Finch-Savage W.E. 2003. Hydrothermal threshold models can describe the germination response of carrot (Daucus carota) and onion (Allium cepa) seed populations across both sub-and supra-optimal temperatures. New Phytologist, 158: 101–108.

26. Shafii B., and PriceSource W.J. 2001. Estimation of cardinal temperatures in germination data analysis. Journals of Agriculture Biology and Environments Statistics, 6: 356–366.

27. Saeidnejad A. H., Kafi M., and Pessarakli M. 2012 Evaluation of cardinal temperatures and germination responses of four ecotypes of Bunium persicum under different thermal conditions. Agriculture and Crop Science, 4: 1266-1271.

28. Soltani A., Robertson M.J., Torabi B., Yousefi-Daz M., and Sarparast R. 2006. Modeling seedling emergence in chickpea as affected by temperature and sowing depth. Agricultural and Forest Meteorology, 138: 156-167.

29. Soltani A., and Sinclair T.R. 2012. Modeling physiology of crop development, growth and yield. Oxford shire: CABI Press; p.322.

30. Steckel L.E., Sprague C.L., Stoller E.W., and Wax L.M. 2004. Temperature effects on germination of nine Amaranthus species. Weed Science, 52: 217–221.

31. SitiAishah H., Saberi A.R., Halim R.A., and Zaharah A.R 2010. Salinity effects on germination of 585 forage sorghumes. Journal of Agronomy, 9: 169-174

32. Taherabadi S.H., Goldani M., Taherabadi S.H., and Fazeli Kakhki S.F. 2015. Determination of cardinal temperatures of germination of weed seeds of Hyoscyamus niger, Aconitum napellus and Cannabis sativa. Journal of plant protection, 29: 16-22. (In Persian)

33. Tanveer A., Muhammad Zeshan Farid M., Tahir M., Mansoor Javaid M., and Khaliq A. 2012. Environmental factors affecting the germination and seedling emergence of Carthamus oxyacantha M. Bieb. (Wild Safflower). Pakistan Journal of Weed Science and Research, 18: 221-235.

34. Wang R., Bai Y., and Tanino K. 2004. Effect of seed size and sub-zero imbibitions-temperature on the thermal time model of winterfat (Eurotia lanata (Pursh) Moq.). Journal of Environmental and Experimental Botany, 51: 183-187.

35. Wang R. 2006. Seedling emergence of winterfat (Krascheninnikovia lanata (Pursh) A.D.J. Meeuse & Smit) in the field and its prediction using the hydrothermal time model. Journal of Arid Environments, 64: 37-53.

36. Wang L., Jin S., Wu L., Zhou X., Liu X., and Bai L. 2016. Influence of Environmental Factors on Seed Germination and Emergence of Asia Minor Bluegrass (Polypogon fugax). Weed Technology, 30: 533-538.

37. Zarif-ketabi H., Kazaei H.R., and A Nezami A. 2016. Estimation of the cardinal temperatures for germination of four Satureja species growing in Iran. Herba Polonica, 62: 7-21.

38. Zhou J., Deckard E.L., and Ahrens W.H. 2005. Factors affecting germination of hairy nightshade (Solanum sarrachoides) seeds. Weed Science, 53: 41-45