Literature DB >> 16551599

[Genetic and correlation analysis for agronomic traits in flue-cured tobacco (Nicotiana tabacum L.)].

Bing-Guang Xiao1, Jun Zhu, Xiu-Ping Lu, Yong-Fu Bai, Yong-Ping Li.   

Abstract

By using a genetic model including additive and dominance effects and their interaction with environments, 7 agronomic traits were analyzed for a diallel design in 4 environmental conditions with 14 flue-cured tobacco varieties (or breeding lines) and their 41 F1 crosses. It was revealed that additive effects were the major genetic component for plant height, internode length, and width of leaves. Number of leaves and length of leaves were mainly controlled by dominance x environment interaction effects. Additive x environment interaction effects and dominance x environment interaction effects played a major role for girth of stem. Yield performance was mainly controlled by additive effects and dominance x environment interaction effects. The varieties adapted to local environments tended to have highly positive additive effects. Dominance effects and the dominance x environment interaction effects could perform differently in positive or negative direction for many crosses. The breeding program for hybrids should consider the adaptation of hybrids to specific ecological environments. The analysis of correlation among agronomic traits indicated that most of phenotypic, genotypic, additive and dominance correlation coefficients were positive. Additive correlations were predominance in genetic correlations for most pairs of traits. Yield can be improved by indirect selection on plant height.

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Year:  2006        PMID: 16551599

Source DB:  PubMed          Journal:  Yi Chuan        ISSN: 0253-9772


  1 in total

1.  Identification of QTLs Associated With Agronomic Traits in Tobacco via a Biparental Population and an Eight-Way MAGIC Population.

Authors:  Yutong Liu; Guangdi Yuan; Huan Si; Ying Sun; Zipeng Jiang; Dan Liu; Caihong Jiang; Xuhao Pan; Jun Yang; Zhaopeng Luo; Jianfeng Zhang; Min Ren; Yi Pan; Kefan Sun; He Meng; Liuying Wen; Zhiliang Xiao; Quanfu Feng; Aiguo Yang; Lirui Cheng
Journal:  Front Plant Sci       Date:  2022-06-06       Impact factor: 6.627

  1 in total

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