Heterosis, Inbreeding Depression and Genotypic Divergence for Some Physiological Parameters in Sesame (Sesamun indicum L.)

Abstract

Heterosis, inbreeding depression, and its relationship with genetic divergence in sesame (Sesamum indicum L.) was studied by growing seven genotypes of sesame, their 21 F₁s and 21 F₂s in summer 2003 in a randomized block design with three replications. CST2002 × MT34 exhibited highest positive heterosis for oil yield plant⁻¹ over mid-parent (43.6%) and better parent (28.4%). Other hybrids showing high, positive and significant heterosis for oil yield plant⁻¹, over both mid- and better parent were MT34× B67, TKG22 × ‘Rama’, MT34 × ‘Rama’ and CST2002 × TKG22. Compared to parents, in general, hybrids had faster crop growth rate (CGR) and leaf area index (LAI) at reproductive and later developmental stages. In general, heterosis for oil yield in sesame might be the result of combined heterotic effects of different physiological traits. The majority of the crosses exhibited positive inbreeding depression in the F₂ generation. Many crosses exhibited positive and significant inbreeding depression for all the flowering traits. In case of oil yield, majority of the crosses expressing significant heterosis also exhibited positive and significant inbreeding depression. However, cross CST2002 × TKG22, which showed positive and significant heterosis over both the parents for oil yield plant⁻¹, also exhibited non-significant inbreeding depression in F₂. Additive genetic effect for oil yield might be important in this cross, which would help to isolate superior pure lines in advanced generations of segregations. Divergence analysis revealed that genotypic diversity among the parents was not related to geographic diversity. Majority of the heterotic hybrids for oil yield were the result of inter-cluster crossing. Genetic divergence can be used as a predictive tool to determine heterotic combinations in sesame.

Keywords:

• sesame (sesamum indicum L.)
• physiological characters
• heterosis
• inbreeding depression

Acknowledgments

Thanks are due to Felipe de Mendiburu ([email protected]) for his support and valuable suggestions to standardize data and for analysis of hierarchical clustering via ‘agricolae’ package.