Modelling germination curves of magneto-primed sorghum (Sorghum bicolor) seeds using Logistic and Gompertz models
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Authors
SAMIR KHAIRI LAZIM
College of Agricultural, University of Basrah, Basrah 61001, Iraq
Keywords:
Cumulative germination percentage, Curve-fitting, Germination rate, Magnetic field, Primed seed, Seed priming durationsAbstract
The traditional analysis of germination percentages tends to be quite limited, providing minimal information. Thus, a regression model based on the time to germination can be the most effective approach to describing germination behaviour. In this study, the effects of magneto-priming on sorghum [Sorghum bicolor (L.) Moench] seed germination were analysed and compared using Logistic and Gompertz models (LM and GM), respectively. Sorghum seeds were primed with a static magnetic field for four distinct durations (0, 1, 3, and 5 h). Germination data, gathered over a 10 days period for all magneto-priming exposures, then LM and GM growth curves were utilised to model seed germination. The experiment relied on two key metrics: the coefficient of determination (R2) and the mean square error (MSE) to determine the best fitting growth curve. After the appropriate growth curve was selected, both statistical values and graphical plots were used to compare the model outputs and their parameter estimates. The results showed that the GM fit better than the LM model in describing the germination process of sorghum in the magneto priming test, as it yielded the lowest MSE and highest R2 values. These findings suggest that the GM model can represent the best shape of sorghum germination curves under magneto-primed conditions.
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Abdel Latef, A A Hamed, Dawood M F, Hassanpour H, Rezayian M and Younes N A. 2020. Impact of the static magnetic field on growth, pigments, osmolytes, nitric oxide, hydrogen sulfide, phenylalanine ammonia-lyase activity, antioxidant defense system, and yield in lettuce. Biology 9(7): 172. https://doi.org/10.3390/biology9070172 DOI: https://doi.org/10.3390/biology9070172
Bahler C, Hill R R and Byers R A. 1989. Comparison of Logistic and Weibull functions: The effect of temperature on cumulative germination of alfalfa. Crop Science 29: 142–46. https://doi.org/10.2135/cropsci1989.0011183X002900010032x DOI: https://doi.org/10.2135/cropsci1989.0011183X002900010032x
Bhardwaj J, Anand A and Nagarajan S. 2012. Biochemical and biophysical changes associated with magneto-priming in germinating cucumber seeds. Plant Physiology and Biochemistry 57: 67–73. https://doi.org/10.1016/j.plaphy.2012.05.008 DOI: https://doi.org/10.1016/j.plaphy.2012.05.008
Bormashenko E, Shapira Y, Grynyov R, Whyman G, Bormashenko Y and Drori E. 2015. Interaction of cold radiofrequency plasma with seeds of beans (Phaseolus vulgaris). Journal of Experimental Botany 66: 4013–21. https://doi.org/10.1093/ jxb/erv206 DOI: https://doi.org/10.1093/jxb/erv206
Bukhari S A, Farah N, Mustafa G, Mahmood S and Naqvi S A R. 2019. Magneto-priming improved nutraceutical potential and antimicrobial activity of Momordica charantia L. without affecting nutritive value. Applied Biochemistry and Biotechnology 188(3): 878–92. https://link.springer.com/ article/10.1007/s12010-019-02955-w DOI: https://doi.org/10.1007/s12010-019-02955-w
El-Kassaby Y A, Moss I, Kolotelo D and Stoehr M. 2008. Seed germination: mathematical representation and parameters extraction. Forest Science 54: 220–27. https://doi.org/10.1093/ forestscience/54.2.220 DOI: https://doi.org/10.1093/forestscience/54.2.220
Gregorczyk A. 1991. The logistic function-its application to the description and prognosis of plant growth. Acta Societatis Botanicorum Poloniae 60(1–2): 67–76. https://doi.org/10.5586/ asbp.1991.004 DOI: https://doi.org/10.5586/asbp.1991.004
Hara Y. 1999. Calculation of population parameters using Richards function and application of indices of growth and seed vigor to rice plants. Plant Production Science 2(2): 129–35. https:// doi.org/10.1626/pps.2.129 DOI: https://doi.org/10.1626/pps.2.129
He Y, Zhou L, Zhang R, Shen F, Yang X, Zhou W and He J. 2025. Effects of static magnetic field and elemental enrichment on enhancing seed germination, growth and nutritional quality of mung bean. LWT 232: 118451. https://doi.org/10.1016/j. lwt.2025.118451 DOI: https://doi.org/10.1016/j.lwt.2025.118451
Himoud M S, Lazim S K and Al-Bahadliy A H. 2022. Effect of tillage depths and static magnetic seed treatment on growth parameters and yield of maize (Zea mays L.). Indian Journal of Ecology 49: 18–23. http://indianecologicalsociety.com/ society/conferences/
Hsu H, Nelson C J and Chow W S. 1984. A mathematical model to utilise the logistic function in germination and seedling growth. Journal of Experimental Botany 35(11): 1629–40. https://doi.org/10.1093/jxb/35.11.1629 DOI: https://doi.org/10.1093/jxb/35.11.1629
Joshi-Paneri J, Sharma S, Guruprasad K N and Kataria S. 2023. Enhancing the yield potential of soybean after magneto- priming: Detailed study on its relation to underlying physiological processes. Seeds 2: 60–84. https://doi.org/10.3390/seeds2010006 DOI: https://doi.org/10.3390/seeds2010006
Kataria S, Baghel L and Guruprasad K N. 2015. Acceleration of germination and early growth characteristics of soybean and maize after pre-treated of seeds with static magnetic field. International Journal of Tropical Agriculture 33: 985–92. https://www.cabidigitallibrary.org/doi/full/10.5555/20153336370
Lazim S K and Ramadhan M N. 2023. Effects of physical and chemical seed priming techniques on seed germination and seedling growth of maize (Zea mays L.). Annals of Biology 39(2): 404–10. https://agribiop.com/category/annals-of-biology/page/2/
Lazim S K and Ramadhan M N. 2020. Study effect of a static magnetic field and microwave irradiation on wheat seed germination using different curves fitting model. Journal of Green Engineering 10(1): 3188–205.
Ling Li, Jiafeng J, Jiangang L, Minchong S, Xin H, Hanliang S and Yuanhua D. 2014. Effects of cold plasma treatment on seed germination and seedling growth of soybean. Scientific Reports 4: 5859. https://doi.org/10.1038/srep05859 DOI: https://doi.org/10.1038/srep05859
Mahajan T S and Pandey O P. 2011. Reformulation of Malthus- Verhulst equation for black gram seeds pretreated with magnetic field. International Agrophysic 25: 355-59.
Martinez E, Florez M and Carbonell M V. 2017. Stimulatory effect of the magnetic treatment on the germination of cereal seeds. International Journal of Environment, Agriculture and Biotechnology 2(1): 375–81. https://dx.doi.org/10.22161/ijeab/2.1.47 DOI: https://doi.org/10.22161/ijeab/2.1.47
Moungang N T, Tchitnga R, Kouam E B and Fomethe A. 2020. Logistic curve modeling of the germination of beans seeds (Phaseolus Vulgaris) previously exposed to multi-periodic and chaotic electromagnetic fields. Open Access Journal of Environmental and Soil Sciences 5: 676–87. https://doi.org/10.32474/OAJESS.2020.05.000218 DOI: https://doi.org/10.32474/OAJESS.2020.05.000218
Muszyński S, Gagoś M and Pietruszewski S. 2009. Short-term pre-germination exposure to ELF magnetic field does not influence seedling growth in durum wheat (Triticum durum). Polish Journal of Environmental Studies 18(6): 1065–72.
Muszyñski S and Gladyszewska B. 2008. Representation of He-Ne laser irradiation effect on radish seeds with selected germination indices. International Agrophysics 22(1): 151–57.
Ozdinç N and Yalcın F S. 2025. Stimulating growth parameters by magnetic field in irradiated with gamma radiation soybean varieties. Radiation Effects and Defects in Solids 181(7–8): 1132–49. https://doi.org/10.1080/10420150.2025.2581577 DOI: https://doi.org/10.1080/10420150.2025.2581577
Rathod G R and Anand A. 2015. Effect of seed magneto-priming on growth, yield and Na/K ratio in wheat (Triticum aestivum L.) under salt stress. Indian Society for Plant Physiology 21: 15–22. https://doi.org/10.1007/s40502-015-0189-9 DOI: https://doi.org/10.1007/s40502-015-0189-9
Rymuza K and Radzka E. 2021. Effect of pH levels on soybean seed germination dynamics. Acta Scientiarum Polonorum. Agricultura 20(2): 81–88. https://doi.org/10.37660/aspagr.2021.20.2.4
Shafii B, Price W J, Swensen J B and Murray G A. 1991. Nonlinear estimation of growth curve models for germination data analysis. (In) Proceedings of the 3rd Annual Conference Proceedings, Annual Conference of Applied Statistics in Agriculture, Kansas State University, Manhattan, New York, USA. pp. 19–42. https://doi.org/10.4148/2475-7772.1415 DOI: https://doi.org/10.4148/2475-7772.1415
Shine M B, Kataria S and Guruprasad K N. 2017. Enhancement of maize seeds germination by magneto-priming in perspective with reactive oxygen species. Journal of Agricultural and Crop Research 5: 66–76.
Sousa I F, Neto J E K, Muniz J A, Guimaraes R M, Savian T V and Muniz F R. 2014. Fitting nonlinear autoregressive models to describe coffee seed germination. Ciencia Rural, Santa Maria 44: 2016–2021. https://doi.org/10.1590/0103-8478cr20131341 DOI: https://doi.org/10.1590/0103-8478cr20131341
Souza P F, Santana R C and Fernandes J S C. 2013a. Germination behaviour evaluated using the identity test for nonlinear models. Australian Journal of Basic and Applied Sciences 7(10): 31–36. https://www.researchgate.net/publication/304251047
Tipton J L. 1984. Evaluation of three growth curve models for germination data analysis. Journal of the American Society for Horticultural Science 109(4): 451–54. DOI: https://doi.org/10.21273/JASHS.109.4.451
Torres M and Frutos G. 1989. Analysis of germination curves of aged fennel seeds by mathematical models. Environmental and Experimental Botany 29(3): 409–15. https://doi. org/10.1016/0098-8472(89)90016-6 DOI: https://doi.org/10.1016/0098-8472(89)90016-6
Yin X, Goudriaan J A N, Lantinga E A, Vos J A N and Spiertz H J. 2003. A flexible sigmoid function of determinate growth. Annals of Botany 91(3): 361–71. https://doi.org/10.1093/aob/mcg029 DOI: https://doi.org/10.1093/aob/mcg029
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