OPTIMIZATION OF EMS AND DES TREATMENTS FOR INDUCTION OF MUTATIONS IN QUANTITATIVE TRAITS OF MAIZE

LASKAR, RAFIUL AMIN and SHEIKH, NILOFER and HAJONG, SUBARNA and KHAN, TAJ UDDIN (2020) OPTIMIZATION OF EMS AND DES TREATMENTS FOR INDUCTION OF MUTATIONS IN QUANTITATIVE TRAITS OF MAIZE. PLANT CELL BIOTECHNOLOGY AND MOLECULAR BIOLOGY, 21 (43-44). pp. 134-143.

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Abstract

In chemical mutagenesis experiment, LC50 value indicates genotypic sensitivity of a species which facilitates fixing optimal concentrations of mutagens for obtaining higher rate of mutations with nominal population damage. The present study was undertaken in two separate steps where initially the lethal concentration (LC50) value of EMS and DES was calculated and finally the mutations induced through the identified concentrations were quantitatively analysed for yield traits of an indigenous maize germplasm of Mizoram. The probit curve analysis based on the germination percentage of treated maize seeds revealed that LC50 values of EMS and DES to be 117.49 mM and 138.04 mM, respectively. The observations on quantitative traits showed that the LC50 treatments successfully induced significant desirable genetic variations, including maximum improvement of average grain (93.41 g) and stover (198.16 g) yield in 100 mM EMS treatment. The results confirmed relatively higher efficacy of EMS in induction of useful micro-mutations compared to DES at their respective optimum concentrations in the maize germplasm under present study. In conclusion, the study confirmed and recommends the application of EMS and DES concentrations up to the optimum 100 mM and 150 mM, respectively for generating broad spectrum of mutations in quantitative yield traits that could be useful in future mutation breeding programmes of indigenous maize germplasms of Mizoram.

Item Type: Article
Subjects: Science Repository > Biological Science
Depositing User: Managing Editor
Date Deposited: 02 Dec 2023 06:11
Last Modified: 02 Dec 2023 06:11
URI: http://research.manuscritpub.com/id/eprint/3680

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