Genetic parameters and selection strategies for soybean progenies aiming at precocity and grain productivity
收藏DataCite Commons2022-10-18 更新2024-07-29 收录
下载链接:
https://scielo.figshare.com/articles/dataset/Genetic_parameters_and_selection_strategies_for_soybean_progenies_aiming_at_precocity_and_grain_productivity/21353291/1
下载链接
链接失效反馈官方服务:
资源简介:
ABSTRACT Genetic parameters and correlations are useful tools in breeding programs, helping to make decisions about the most efficient method of selecting soybean progenies. The objective was to determine genetic parameters and correlations between characters in 52 soybean genotypes, from 4 populations and to select the superior progenies for early cycle and grain productivity. The experiment was carried out in a randomized block design consisting of 52 RCF3:4 progenies and three controls (UFUS7010, TMG801, BRSGO7560). Agronomic and yield traits were evaluated. For the number of days to flowering and maturity, plant height at maturity and number of nodes at maturity, a high heritability estimate and favorable conditions for selection were observed. The existence of correlations between the characters was verified with the predominance of genetic causes, which allows the success in the indirect selection. By the Mulamba and Mock method, the highest selection gain was obtained, however, for the genotype-ideotype distance index method, greater gains were obtained for production components, therefore, 15 early cycle and productive superior RCF3:4 progenies were selected with a cycle between 79.0 and 105.0 days and production of 302.5 to 463.0 g plot-¹.
摘要 遗传参数与性状相关性是作物育种项目中的核心实用工具,可为大豆后代选育的最优高效方案提供决策支撑。本研究以源自4个群体的52份大豆基因型为材料,旨在解析其性状间的遗传参数与相关性,并筛选出早熟且籽粒产量优异的优良后代。试验采用随机区组设计,共设置52份RCF3:4后代材料与3个对照品种(UFUS7010、TMG801、BRSGO7560),并对农艺性状与产量相关性状进行了评估。针对开花天数、成熟天数、成熟株高及成熟节数等性状,本研究观测到较高的遗传力估计值,为后续选育提供了有利条件。研究证实各性状间存在显著相关性,且相关性主要由遗传因素主导,这为间接选育的成功实施奠定了基础。采用Mulamba与Mock选择法可获得最高的综合选择增益;而采用基因型-理想型距离指数法则在产量组分性状上获得了更为突出的增益。最终本研究筛选出15份早熟且高产的优良RCF3:4后代,其生育周期介于79.0~105.0天,小区产量为302.5~463.0 g。
提供机构:
SciELO journals
创建时间:
2022-10-18



