Volume 10, Issue 2 ((Autumn & Winter) 2024)
Iranian J. Seed Res. 2024, 10(2): 67-80 |
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Shahbazi M, Asghari J, Kamkar B, Taghvaie Salimi E. (2024). Quantifying and analysis of germination responses of invasive weed Western ragweed (Ambrosia psilostachya) to temperature and under different water potential conditions. Iranian J. Seed Res.. 10(2), : 5 doi:10.61186/yujs.10.2.67
URL: http://yujs.yu.ac.ir/jisr/article-1-583-en.html
URL: http://yujs.yu.ac.ir/jisr/article-1-583-en.html
University of Guilan , asghari@guilan.ac.ir
Abstract: (1153 Views)
Extended abstract
Introduction: The germination process is one of the most critical stages of a plant's growth and determines the success of the emergence of a weed in an agroecosystem because it is the first stage in which the weed competes for a niche. Various environmental factors, including temperature and moisture, affect the germination of weed seeds. Modeling techniques are capable of predicting germination, seedling emergence, and establishment of weed species. The ability to predict weed germination in response to environmental conditions is very effective for the development of control programs. The experiment was conducted to determine the cardinal temperature and evaluate the best model for quantifying the response of the germination rate of Western ragweed weed seeds under different water stress conditions.
Materials and Methods: A factorial experiment was conducted in the form of a completely randomized design in three replications. The investigated factors include temperature with eight levels (5, 10, 15, 20, 25, 30, 35, and 40 C˚) and water potential with six levels (0, -0.3, -0.6, -0.9, -1.2, and -1.5 MPa) on the germination of Western ragweed. In order to quantify the response of Western ragweed germination rate to temperature, three non-linear Dent-like, Beta, and Segmented regression models were used.
Results: The results showed that the effect of temperature, water potential, and their interactions on maximum germination, germination rate, and time required to reach 10, 50, and 90 percent germination were significant. Also, the results showed that by increasing the temperature from 10 to 25 C˚, the percentage and rate of germination increased whereas by increasing water potential, the percentage and rate of germination decreased. In comparing the models, based on RMSE, R2, CV, and coefficients a and b parameters, the Beta model was the most suitable for estimating the temperatures of cardinal Western ragweed. The base, optimum, and ceiling temperatures using the Beta model were 3.88, 25, and 40 C˚, respectively.
Conclusions: The use of the Beta model to quantify the germination response of Western ragweed seeds to different levels of water potential at different temperatures had acceptable results. Therefore, by using the output of these models at different temperatures, it is possible to predict the germination rate at different potentials.
Highlights:
1- Germination cardinal temperatures and the effect of water potential on western ragweed weed were investigated.
2- Estimation of different models to quantify the response of germination rate to temperature and different water potentials.
Introduction: The germination process is one of the most critical stages of a plant's growth and determines the success of the emergence of a weed in an agroecosystem because it is the first stage in which the weed competes for a niche. Various environmental factors, including temperature and moisture, affect the germination of weed seeds. Modeling techniques are capable of predicting germination, seedling emergence, and establishment of weed species. The ability to predict weed germination in response to environmental conditions is very effective for the development of control programs. The experiment was conducted to determine the cardinal temperature and evaluate the best model for quantifying the response of the germination rate of Western ragweed weed seeds under different water stress conditions.
Materials and Methods: A factorial experiment was conducted in the form of a completely randomized design in three replications. The investigated factors include temperature with eight levels (5, 10, 15, 20, 25, 30, 35, and 40 C˚) and water potential with six levels (0, -0.3, -0.6, -0.9, -1.2, and -1.5 MPa) on the germination of Western ragweed. In order to quantify the response of Western ragweed germination rate to temperature, three non-linear Dent-like, Beta, and Segmented regression models were used.
Results: The results showed that the effect of temperature, water potential, and their interactions on maximum germination, germination rate, and time required to reach 10, 50, and 90 percent germination were significant. Also, the results showed that by increasing the temperature from 10 to 25 C˚, the percentage and rate of germination increased whereas by increasing water potential, the percentage and rate of germination decreased. In comparing the models, based on RMSE, R2, CV, and coefficients a and b parameters, the Beta model was the most suitable for estimating the temperatures of cardinal Western ragweed. The base, optimum, and ceiling temperatures using the Beta model were 3.88, 25, and 40 C˚, respectively.
Conclusions: The use of the Beta model to quantify the germination response of Western ragweed seeds to different levels of water potential at different temperatures had acceptable results. Therefore, by using the output of these models at different temperatures, it is possible to predict the germination rate at different potentials.
Highlights:
1- Germination cardinal temperatures and the effect of water potential on western ragweed weed were investigated.
2- Estimation of different models to quantify the response of germination rate to temperature and different water potentials.
Article number: 5
Type of Study: Research |
Subject:
Seed Ecology
Received: 2023/07/1 | Revised: 2024/06/9 | Accepted: 2023/11/15 | ePublished: 2024/06/9
Received: 2023/07/1 | Revised: 2024/06/9 | Accepted: 2023/11/15 | ePublished: 2024/06/9
References
1. Ahmadi, M., Kamkar, B., Soltani, A. and Zeinali, E. 2010. Evaluation of non-Linear regression models to predict stem elongation rate of wheat (Tajan cultivar) in response to temperature and Photoperiod. Electronic Journal of Crop Production, 2(4): 39-54. [In Persian with English Summary]
2. Ansari, O., Gherekhloo, J., Ghadri-Far, F. and Kamkar, B. 2018. The effect of osmotic stress on the germination cardinal temperatures of cheese seeds (Malva sylvestris). Environmental Stresses in Crop Sciences, 10(2): 341-352. [In Persian with English Summary]
3. Buttenschon, R.M., Waldisp, U. and Bohern, C. 2009. Guidelines for management of common ragweed (Ambrosia artemisiifolia). Available at: http://www.Euphresco.org.
4. Cardoso, V.J.M. 2011. Metodologia para analysis da dependence thermal da germination pelo model de graus.dia. Oecologia Australis, 15(2): 236-248. [DOI:10.4257/oeco.2011.1502.04]
5. Cheraghian, A. 2016. Pernnial ragweed (Ambrosia psilostachya D.C). Bureau of plant pest surveillance and pest risk analysis, 13Pp.
6. Derakhshan, A., Gherekhloo, J. and Parvar, A. 2014. Estimation of cardinal temperatures and thermal time requirement for Cyperus difformis seed germination. Weed Science Journal, 9: 27-38. [In Persian with English Summary]
7. Darri, M.A., Kamkar, B., Aghdasi, M. and Kamikamar, E. 2014. Determining the best model for evaluating the cardinal temperatures of plant seed germination (Silybum marianum.). Journal of Iranian Seed Science and Technology, 10(2): 189-200. [In Persian with English Summary]
8. Dehimfard, R., Nazari, Sh. and Qorani, Y. 2018. Estimation of cardinal temperature of Lepyrodiclis holosteoides using regression models. Iranian Journal of Seed Science and Technology, 6(2): 107-117. [In Persian with English Summary]
9. Duke, J., Handbook, A., Press, C. and Raton, B. 1985. Germination response of subterranean, berseem, and rose clovers to alternating temperatures. Agronomy Journal, 83: 1000-1004. [DOI:10.2134/agronj1991.00021962008300060015x]
10. Hegarty, T.W. 1978. The physiology of seed hydration and dehydration, and the relation between water stress and the control of germination: A Review. Plant, Cell and Environment, 1: 101-119 [DOI:10.1111/j.1365-3040.1978.tb00752.x]
11. Heidari, Z., Kamkar, B. and Masoud Sinaki, J. 2014. Influence of temperature on seed germination response of fennel. Advances in Plants and Agriculture Research, 1(5): 1-7. [DOI:10.15406/apar.2014.01.00032]
12. ISTA. 2015. International Rules for Seed Testing, Chapter 5, i-5-56 (60). [DOI:10.15258/istarules.2015.05]
13. Kamkar, B., Koochaki, A., Nassiri Mahallati, M. and Rezvani-Moghaddam, P. 2006. Cardinal temperatures for germination in three millet species (Panicum miliaceum, Pennisetum glaucum, and Setaria italic). Asian Journal of Plant Sciences, 5(2): 316-319. [DOI:10.3923/ajps.2006.316.319]
14. Kamkar, B. 2011. GS_2011. A Pocket Software to calculate germination and emergence indices. GUASNR.
15. Kamkar, B., Jami Al-Ahmadi, M. and Mahdavi-Damghani, A. 2012. Quantification of the cardinal temperatures and termal time requirement of Opium poppy (Papaver somniferum L.) seeds germinate using non-linear regression models. Industrial Crops and Products, 35: 192-198. [DOI:10.1016/j.indcrop.2011.06.033]
16. Khalili, N., Soltani, A., Zeinali, E and Ghaderi Far., F. 2013. Evaluation of nonlinear regression models to quantify barley germination rate response to temperature and water potential. Agricultural Plant Production Journal, 7(4): 23-40. [In Persian with English Summary]
17. Khodabakhshi, A., kamkar, B. and Khalili, N. 2015. Using nonlinear regression models to quantify germination response of annual savory to temperature and water potential. Agricultural Crop Management, 17(1): 229-240. [In Persian with English Summary]
18. Mamedi, M., Tavakol Afshar, R. and Oveisi, M. 2017. Cardinal temperatures for seed germination of three Quinoa (Chenopodium quinoa Willd.) cultivars. Iranian Journal of Field Crop Science, 48(Special Issue): 89-100. [In Persian with English Summary]
19. Masin, R., Loddo, D., Benvenuti, S., Zuin, M., Macchia, M. and Zanin, G. 2010. Temperature and water potential as parameters for modeling weed emergence in central- Northern Italy, Weed Science, 58: 216-222. [DOI:10.1614/WS-D-09-00066.1]
20. Michel, B.E. and Kaufmann, M.R. 1973. The osmotic potential of polyethylene glycol 6000. Plant Physiology, 51: 914-916. [DOI:10.1104/pp.51.5.914] [PMID] []
21. Montagnani, C., Gentili, R., Smith, M., Guarino, M.F. and Citterio, S. 2017. The worldwide spread, success, and impact of Ragweed (Ambrosia spp.). Critical Reviews in Plant Sciences, 36(3): 1-40. [DOI:10.1080/07352689.2017.1360112]
22. Nezhad-Hasan, B., Siahmarguee, A., Zeinali, E. and Ghadri-far, F. 2017. Non-linear regression evaluation of Arugula (Eruca sativa Mill.) germination rate to temperature and water stress. Iranian Journal of Seed Science and Research, 4(2): 1-16. [In Persian with English Summary]
23. Nozari-nejad, M., Zeinali, E., Soltani, A., Soltani, E. and Kamkar, B. 2013. Quantify wheat germination rate response to temperature and water potential. Crop Production Journal, 6(4): 117-135. [In Persian with English Summary]
24. Parmoon, G.H., Mousavi, 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: 145-151. [DOI:10.1016/j.cj.2014.11.003]
25. Pinke, G., Karacsony, P., Czucz, B. and Botta-Dukat, Z. 2011. Environmental and land-use variables determining the abundance of (Ambrosia artemisiifolia) in arable fields in Hungary. Preslia, 83: 219-235.
26. 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]
27. Poshtdar, A., Tabatabaei, A. and Ansari, O. 2020. Quantification of sorghum seed germination in response to temperature. Journal of Seed Research, 10(1): 43-52. [In Persian with English Summary]
28. Rostami, A. 2014. Investigating the global distribution potential of the invasive Ambrozoa species and its biological control agent (Ophraella communa) in current climate conditions and climate change. Master's thesis of Ferdowsi University of Mashhad. [In Persian with English Summary]
29. Saberali, S. F. and Shirmohamadi-Aliakbarkhani, Z. 2020. Quantifying seed germination response of melon (Cucumis melo L.) to temperature and water potential: Thermal time, hydrotime and hydrothermal time models. South African Journal of Botany, 130: 1-10. [DOI:10.1016/j.sajb.2019.12.024]
30. Shah, S., Ullah, S., Ali, S., Khan, A., Ali, M., and Hassan, S. 2021. Using mathematical models to evaluate germination rate and seedlings length of chickpea seed (Cicer arietinum L.) to osmotic stress at cardinal temperatures. PLoS One, 16(12): e0260990 [DOI:10.1371/journal.pone.0260990] [PMID] []
31. Soltani, A., Robertson, M, J., Torabi, B., Yousefi-Daz, M. and Sarparast, R. 2006. Modeling seedling emergence in chickpea as influenced by temperature and sowing depth. Agricultural and Forest Meteorology, 138: 156-167. [DOI:10.1016/j.agrformet.2006.04.004]
32. Sucur, J., Konstantinivic, B., Crnkovic, M., Vojislava, A., Bursic, V., Samardiz, N., Malencic, D., Prvulovic, D., Popov, M. and Vukovic, G. 2022. Chemical composition of Ambrosia trifida L. and its allelopathic influence on crops. Plant, 10(10): 2222. [DOI:10.3390/plants10102222] [PMID] []
33. Toukasi, S., Kazerouni-Monfared, A., Yaghoubi, B., Oveysi, M., Sasan-Far, R., Rahimiyan-Mashhadi, H. and Hainz, M. 2017. First report of Ambrosia psilostachya from Iran: An invasive plant species establishing in coastal area of Guilan province (N Iran). Rostaniha, 18(2): 226-222. [In Persian with English Summary]
34. Valickova, V., Hamouzova, K. and Kolrova, M. 2017. Germination responses to water potential in Bromus sterilis L. under different temperatures and light regimes. Plant Soil and Environment, 63(8): 368- 374 [DOI:10.17221/406/2017-PSE]
35. Vidotto, F., Tesio, F. and Ferrero, A. 2013. Allelopathic effects of Ambrosia artemisiifolia L. in the invasive process. Crop Protect, 54: 161-167. [DOI:10.1016/j.cropro.2013.08.009]
36. Zhang, H., Tian, Y. and Zhou, D. 2015. A modified thermal time model quantifying germination response to temperature for C3 and C4 species in temperate grassland. Agriculture, 5: 412-426. [DOI:10.3390/agriculture5030412]
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