Identification of desirable mutants in quantitative traits of lentil at early (M ) generation
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Dahbia Tabti, Meriem Laouar, Karthika Rajendran, Shiv Kumar Agrawal, Aissa Abdelguerfi. (2/3/2018). Identification of desirable mutants in quantitative traits of lentil at early (M ) generation. Journal of Environmental Biology, 39 (2), pp. 137-142.
Aim: Narrow genetic base and limited genetic diversity are the major research constraints that affect the efficacy of class breeding methods in lentil. In order to circumvent these conditions, mutation breeding techniques were successfully employed in many studies. The present study was conducted to find the LD50 dose of gamma rays in lentil cultivar, Idlib-3 and also to develop and characterize M2 population for economically important quantitative traits. C Methodology: Initially, seeds of lentil variety Idlib-3 were treated with eight doses (45, 60, 75, 90, 100, 200, 300 and 400 Gy) of gamma rays. Germination percentage was recorded to determine LD50 by probit analysis. After determining LD50, M1 and M2 generations were raised. At M2 generation, mutant families were characterized for a set of ten different economically important traits. Results: The LD50 of gamma rays was calculated as 104.34 Gy based on the germination percentage. In M2 generation many induced mutations such aschlorophyllmutation (2. 7 6 %), stuntedgrowth (1.14%) and dwarf mutants (0.35%) wererecorded. Dunnett's test revealed a total of 13 superior families over parent for various quantitative traits. The results of Best Online Linear Unbiased Predictors (BLUPs) confirmed the recurrence and superiority of same seven families, identified in Dunnett's test for high seed yield. Interpretation: Early selection in M2 generation was found useful to identify new desirable mutant traits in lentil. The superior families identified for early maturity, high yield and more total number of pods per plants could be either utilized as direct mutants or in the future crossing program.
- Agricultural Research Knowledge 
Agrawal, Shiv Kumarhttps://orcid.org/0000-0001-8407-3562