Volume 6, Issue 2 ((Autumn & Winter) 2020)                   Iranian J. Seed Res. 2020, 6(2): 111-123 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Nikoumaram S, Bayatian N, Ansari O. Quantification of the Priming Effect of Canola (Brassica napus cv. Zafar) Response to Temperature Using Nonlinear Regression Models. Iranian J. Seed Res.. 2020; 6 (2) :111-123
URL: http://yujs.yu.ac.ir/jisr/article-1-418-en.html
Gorgan University of Agricultural Sciences and Natural Resources , omid0091@yahoo.com
Abstract:   (4342 Views)

Extended abstract
Introduction: Temperature is one of the primary environmental regulators of seed germination. Seed priming technique has been known as a challenge to improving germination and seedling emergence under different environmental stresses. Quantification of germination response to temperature and priming is possible, using non-liner regression models. Therefore, the objective of this study was to evaluate the effect of temperature and priming on germination and determination of cardinal temperatures (base, optimum and maximum) of Brassica napus L.
Material and Methods: Treatments included priming levels (non-priming, priming with water, gibberellin 50 and 100 mg/l) and temperature (5, 10, 15, 20, 30, 35 and 40 °C). Germination percentage and time to 50% maximum seed germination of Brassica napus L. were calculated for different temperatures and priming by fitting 3-parameter logistic functions to cumulative germination data. For the purpose of quantifying the response of germination rate to temperature, use was made of 3 nonlinear regression models (segmented, dent-like and beta). The root mean square of errors (RMSE), coefficient of determination (R2), CV and SE for the relationship between the observed and the predicted germination percentage were used to compare the models and select the superior model from among the methods employed.
Results: The results indicated that temperature and priming were effective in both germination percentage and germination rate. In addition, the results showed that germination percentage and rate increase with increasing temperature to the optimum level and using priming. As for the comparison of the 3 models, according to the root mean square of errors (RMSE) of germination time, the coefficient of determination (R2), CV and SE, the best model for the determination of cardinal temperatures of Brassica napus L. for non-primed seeds was the segmented model. For hydro-priming and hormone-priming with 50 mg/l GA, the best models were segmented and dent-like models and for hormone-priming with 100 mg/l GA,  the dent-like model was the best. The results showed that for non-priming, hydropriming with water, gibberellin 50 and 100 mg/l treatments, the segmented model estimated base temperature as 3.54, 2.57, 2.34 and 2.34 °C and dent-model estimated base temperature as 3.34, 2.45, 2.21 and 2.83 °C, respectively. The segmented model estimated optimum temperature as 24.62, 23.23, 23.69 and 24.38 °C. The dent-model estimated lower limit of optimum temperature and upper limit of optimum temperature as 20.01, 19.62, 16.25, 19.87 and 28.81, 27.38, 29.58 and 27.31 °C.
Conclusion: Utilizing non-liner models (segmented, dent-like and beta) for quantification of germination of Brassica napus L. response to different temperatures and priming produced desirable results. Therefore, utilizing the output of these models at different temperatures can be useful in the prediction of germination rate in different treatments.
1-The effect of priming on germination of Brassica napuswas investigated.
2-The temperature range of rapeseed germination of Brassica napus changes with the use of seed priming.
Article number: 8
Full-Text [PDF 515 kb]   (458 Downloads)    
Type of Study: Research | Subject: Seed Ecology
Received: 2019/05/10 | Accepted: 2019/08/25

1. Acosta, J.M., Bentivegna, D.J., Panigo, E.S. and Dellaferrera, I. 2014. Influence of environmental factors on seed germination and emergence of Iresine diffusa. Weed Research, 54(6): 584-592. [DOI:10.1111/wre.12114]
2. Akramghaderi, F., Soltani, A. and Sadeghipour, H.R. 2008. Cardinal temperature of germination in medicinal pumpkin (Cucurbita pepo L. subsp. pepo. Convar. pepo var. styriaca Greb), borage (Borago officinalis L.) and black cumin (Nigella sativa L.). Asian Journal of Plant Science, 2: 101-119. [DOI:10.3923/ajps.2008.574.578]
3. Ansari, O. and Sharif-Zadeh, F. 2012. Does gibberellic acid (GA), salicylic acid (SA) and ascorbic acid (ASc) improve Mountain Rye (Secale montanum) seeds germination and seedlings growth under cold stress?. International Research Journal of Applied and Basic Sciences, 3(8): 1651-1657.
4. Ansari, O., Gherekhloo, J., Kamkar, B. and Ghaderi-Far, F. 2016. Breaking seed dormancy and determining cardinal temperatures for Malva sylvestris using nonlinear regression. Seed Science and Technology, 44(3): 1-14. [DOI:10.15258/sst.2016.44.3.05]
5. Ashraf, M. and Foolad, M.R. 2005. Pre-sowing seed treatment- a shotgun approach to improve germination growth and crop yield under saline and none-saline condition. Advances in Agronomy, 88: 223-271. [DOI:10.1016/S0065-2113(05)88006-X]
6. Bewley, J.D. and Black, M. 1994. Seeds: Physiology of Development and Germination, 2nd ed. Plenum Press, New York. [DOI:10.1007/978-1-4899-1002-8]
7. Bradford, K.J. 2002. Application of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Science, 50: 248-260. [DOI:10.1614/0043-1745(2002)050[0248:AOHTTQ]2.0.CO;2]
8. Buhler, D.D. 2000. Theoretical and practice challenges to an IPM approach to weed management. Weed Science, 48(3): 274-280. [DOI:10.1614/0043-1745(2000)048[0274:TAPCTA]2.0.CO;2]
9. Chen, K. and Arora, R. 2013. Priming memory invokes seed stress-tolerance. Environmental and Experimental Botany, 94: 33-45. [DOI:10.1016/j.envexpbot.2012.03.005]
10. Colbach, N., Du¨rr, C., Roger-Estrade, J. and Caneill, J. 2005. How to model the effects of farming practices on weed emergence. Weed Research, 45(1): 2-17. [DOI:10.1111/j.1365-3180.2004.00428.x]
11. Derakhshan, A., Gherekhloo, J., Vidal, R.B. and De Prado, R. 2013. Quantitative description of the germination of Littleseed canarygrass (Phalaris minor) in response to temperature. Weed Science, 62(2): 250-257. [DOI:10.1614/WS-D-13-00055.1]
12. Dumur, D., Pilbeam, C.J. and Craigon, J. 1990. Use of the Weibull function to calculate cardinal temperatures in Faba bean. Journal of Experimental Botany, 41(11): 1423-1430. [DOI:10.1093/jxb/41.11.1423]
13. Eshraghi Nejad, M., Kamkar, B. and Soltani, A. 2009. Cardinal temperatures and required biological days from sowing to emergence of three millet species (common, foxtail, pearl millet). Journal of Agricultural Science and Technology, 12(3): 36-43.
14. Forcella, F., Benech Arnold, R.L. and Sanchez, R. 2000. Modelling seedling emergence. Field Crops Research, 67(2): 123-139. [DOI:10.1016/S0378-4290(00)00088-5]
15. Ghaderi-Far, F., Soltani, A. and Sadeghipour, H.R. 2009. Evaluation of nonlinear regression models in quantifying germination rate of medicinal pumpkin (Cucurbita pepo L. subsp. pepo. Convar. pepo var. styriaca Greb), borage (Borago officinalis L.) and black cumin (Nigella sativa L.) to temperature. Journal of Plant Production, 16(4): 1-9. [In Persian with English Summary].
16. Hardegree, S. P. 2006. Predicting germination response to temperature. I. Cardinal-temperature models and subpopulation-specific regression. Annals of Botany, 97(6): 1115-1125. [DOI:10.1093/aob/mcl071] [PMID] [PMCID]
17. Heidari, Z., Kamkar, B. and Masoud Sinaki, J. 2014. Determination of cardinal temperatures of milk thistle (Silybum marianum L.) germination. Advances in Plants and Agriculture Research, 1(5): 28. [DOI:10.15406/apar.2014.01.00027]
18. Kamkar, B., Jami Al-Ahmadi, M., Mahdavi-Damghani, A. and Villalobos, F.J. 2011. Quantification of the cardinal temperatures and thermal time requirement of opium poppy (Papaver somniferum L.) seeds germinate using non-linear regression models. Industrial Crops and Products, 35(1): 192-198. [DOI:10.1016/j.indcrop.2011.06.033]
19. Karami, H. 2016. An alternative model to quantifying corn seed germination to temperature and water potential. A thesis submitted in partial fulfillment of the requirements for the degree of M.Sc. in Agronomy. Gorgan University of Agricultural Sciences and Natural Resources. [In Persian with English Summary].
20. Khalaj, H., Allahdadi, I., Irannejad, Gholamabbas, Minbashi, M. and Baghestani, M.A. 2012. Using nonlinear regression approach for prediction of cardinal temperature of canola and four common weed. Journal of Agronomy, 2(1): 21-33.
21. Lakzaei, S., Soltani, A., Zeinali, E., Ghaderifar, F. and Jafanodeh, S. 2018. 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 Persian with English Summary].
22. Parmoon, G., Moosavi, S.A., Akbari, H. and Ebadi, A. 2015. Quantifying cardinal temperatures and thermal time required for germination of Silybum marianum seed. The Crop Journal, 3(2): 145-151. [DOI:10.1016/j.cj.2014.11.003]
23. Patade, V.Y., Maya, K. and Zakwan, A. 2011. Seed priming mediated germination improvement and tolerance to subsequent exposure to cold and salt stress in capsicum. Research Journal of Seed Science, 4(3): 125-136. [DOI:10.3923/rjss.2011.125.136]
24. Piper, E.L., Boote, K.J., Jones, J.W. and Grimm, S.S. 1996. Comparison of two phenology models for predicting flowering and maturity date of soybean. Crop Science, 36: 1606-1614. [DOI:10.2135/cropsci1996.0011183X003600060033x]
25. Shafii, B., Price, W.J., 2001. Estimation of cardinal temperatures in germination data analysis. Journal of Agricultural, Biological, and Environmental Statistics, 6: 356-366. [DOI:10.1198/108571101317096569]
26. Shayanfar, A., Ghaderi-Far, F., Behmaram, R., Soltani, A. and Sadeghipour, H.R. 2017. Assessment of germination and secondary dormancy behaviors of lines and cultivars of canola. Crops Improvement (Journal of Agricultural Crop Production), 19(4): 881-892.
27. Soltani, A., Gholipoor, M. and Zeinali, E. 2006. Seed reserve utilization and seedling growth of wheat as affected by drought and salinity. Environmental and Experimental Botany, 55: 195-200. [DOI:10.1016/j.envexpbot.2004.10.012]
28. Soltani, E., Galeshi, S., Kamkar, B. and Akramghaderi, F. 2008. Modeling seed aging effects on the response of germination to temperature in wheat. Seed Science and Biotechnology, 2(1): 32-36.
29. Wang, J., Ferrell, J., MacDonald, G. and Sellers, B. 2009. Factors affecting seed germination of Cadillo (Urena lobata). Weed Science, 57(1): 31-35. [DOI:10.1614/WS-08-092.1]
30. Wei, S., Zhang, C., Li, X., Cui, H., Huang, H., Sui, B., Meng, Q. and Zhang, H. 2009. Factors affecting Buffalobur (Solanum rostratum) seed germination and seedling emergence. Weed Science, 57(5): 521-525. [DOI:10.1614/WE-09-054.1]
31. Wu, X., Li, J., Xu, H. and Dong, L. 2015. Factors affecting seed germination and seedling emergence of Asia Minor bluegrass (Polypogon fugax). Weed Science, 63: 440-447. [DOI:10.1614/WS-D-14-00093.1]

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2022 CC BY-NC 4.0 | Iranian Journal of Seed Research

Designed & Developed by : Yektaweb

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.