Generation Mean Analysis for Yield and Yield Component Traits in Inter-specific Cross of Rice (Oryza sativa L.)

Abstract

Background: Information on gene action governing yield and yield component traits need to be studied for adoption of effective breeding procedure to wards development and isolation of high yielding promising lines from the cross with resistant to bacterial leaf blight, blast and tolerance to low soil phosphorous. The present investigation was taken up in this context to estimate the gene effects for yield and yield components of the cross, YH3 x AKDRMS 21-54, using five parameter model of generation mean analysis. Methods: The experimental material, P1, P2, F1, F2 and F3 generations, for the investigation was generated from Kharif 2019 onwards and evaluated at Agricultural College, Bapatla during Rabi 2021-22. Gene effects for grain yield and yield attributing traits were studied. Result: Mean effects of all traits studied were significant indicating the presence of sufficient variation for the traits. Significance of scaling tests revealed additive-dominant model as inadequate, indicating the presence of epistasis. Digenic non-allelic interaction model with five parameters, namely, m, d, h, i and l revealed that the epistatic interaction model was adequate to explain the gene action for the traits studied in the present investigation. Dominance x dominance gene interaction was pre-dominant for grain yield per plant and majority of yield component traits studied coupled with duplicate epistasis, indicating the importance of population improvement approaches, such as bi-parental mating and recurrent selection, followed by isolation of purelines in later generations of the cross for effective improvement of yield and majority of the yield component traits.

Combining Ability Studies of Promising Restorer Lines for Yield and Yield Components in Rice (Oryza sativa L.)

“…Rice (Oryza sativa L.) is a staple food crop that plays a crucial role in global food security, feeding nearly half of the world's population (Kumar et al, 2023). India has been the largest producer after China.…”