A Dynamic Model of Heavy Ion $^{7}$Li Irradiation Mutagenesis Based on Maize Inbred Line Nutrition Difference

doi:10.1088/0256-307X/35/4/048701

Chin. Phys. Lett.

2018, Vol. 35

Issue (4): 048701 DOI: 10.1088/0256-307X/35/4/048701

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY

A Dynamic Model of Heavy Ion $^{7}$Li Irradiation Mutagenesis Based on Maize Inbred Line Nutrition Difference

Jin-Shan Hu^1,2**, Jin-Peng Geng¹, Duo-Fang Li¹, Li Sui³, Yong Zhan^1**

¹College of Electrical Engineering, Hebei University of Technology, Tianjin 300401
²College of Chemical Engineering, North China University of Science and Technology, Tangshan 063210
³China Institute of Atomic Energy, Beijing 102413

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Jin-Shan Hu, Jin-Peng Geng, Duo-Fang Li et al 2018 Chin. Phys. Lett. 35 048701

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Abstract To reveal the saddle-type dose effect relationship, we propose a radiation mutagenesis model based on maize nutrition difference resulting from heavy ion $^{7}$Li radiation. Through irradiation mutagenesis, apparent trait selection, amino acids and fatty acids content determination, and modeling, dynamic evolution from microscopic damage and repair initiation to the final macroscopic biological effects are considered simultaneously. The results show that the steady state nature is independent of evolution time and only relates to different radiation doses. Heavy ion $^{7}$Li radiation could effectively cause maize phenotypic variation and could improve nutritional quality. This model not only gives a good fit to the experimental results on most types of amino acids and fatty acids, but also offers an adequate explanation of the experimental phenomenon underlying the saddle-type bimodal dose effect. By combining experimental results with theoretical analyses, we suggest that the synergy of the stimulus effect and momentum transfer is the main cause of the saddle-type dose effect bimodal curve. This provides an effective strategy for conducting maize germplasm innovation.

Received: 20 November 2017 Published: 13 March 2018

PACS:	87.16.A-	(Theory, modeling, and simulations)
	87.18.Vf	(Systems biology)
	87.23.Kg	(Dynamics of evolution)

Fund: Supported by the National Natural Science Foundation of China under Grant No 11735006, the Hebei Natural Science Foundation of China under Grant No B2014209314, and the Hebei Science and Technology Research Project of Higher Education under Grant No ZD2017023.

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https://cpl.iphy.ac.cn/10.1088/0256-307X/35/4/048701 OR https://cpl.iphy.ac.cn/Y2018/V35/I4/048701

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	Jin-Shan Hu
	Jin-Peng Geng
	Duo-Fang Li
	Li Sui
	Yong Zhan

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