Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2025, Vol. 41 ›› Issue (6): 1-9.doi: 10.11924/j.issn.1000-6850.casb2023-0899

Special Issue: 生物技术 水稻

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Analysis of Genetic Effects on Stem Lodging Resistance in Hybrids of Indica and Japonica Rice

LING Bo(), LI Xiangyi, LIANG Yingying, WANG Hongchao, CHEN Xiaoling, XIE Zhanwen, ZHANG Yuting, CHENG Zuxin, LIN Lihui()   

  1. Key Laboratory of Crop Genetic Breeding and Comprehensive Utilization, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou 350002
  • Received:2023-12-29 Revised:2024-04-15 Online:2025-02-25 Published:2025-02-24

Abstract:

The lodging resistance of rice is a complex character, and the analysis of its genetic effect is valuable for improving the lodging resistance of rice. The genetic patterns and parameters of 16 lodging resistance traits in indica and japonica crossbred progeny were analyzed by using additive and dominant genetic model of plant quantitative traits. The variation of additive variance in the ratio of main effect of 9 traits ranged from 49.9% to 72.1%. The dominant variance in the ratio of dominant effect of 7 traits ranged from 48.2% to 87.1%. The additive and dominant variances of 9 traits accounted for significant or extremely significant phenotypic variances, which were controlled by both additive and dominant effects of genes. The 8 characters, such as basal folding resistance and sheath leaf thickness, were negatively correlated with lodging index, which was conducive to improving basal folding resistance and toppling resistance of rice. Indica japonica intermediate type parents have strong lodging resistance heterosis and high breeding value. Effective use of the genetic characteristics of each character has important guiding significance for breeding lodging resistant indica and japonica hybrid generation.

Key words: rice, lodging resistance, stem physical characteristics, stem anatomical structure characters, genetic effect, additive and dominant genetic model, hybrid generation