摘要
为探索商洛地区小麦主要农艺性状与产量的相互关系,以15个小麦新品种(系)为材料,对其穗粒数、667 m^(2)穗数、千粒重、生育期等7个主要农艺性状和产量进行了相关和通径分析。结果表明穗粒数与产量的相关系数最大,生育期与产量呈显著负相关;偏相关分析显示对产量影响最大的因素是穗粒数,其次是667 m^(2)穗数,而生育期对产量的负向效应最大;在通径分析中,主要农艺性状对产量的直接作用大小为穗粒数>667 m^(2)穗数>株高>基本苗>千粒重>穗长>生育期。相关分析和通径分析一致表明,穗粒数是影响小麦高产育种的主要因素,其次为667 m^(2)穗数,生育期对产量的副作用最大。因此在新品种的选育时,选择熟期偏早,穗粒数和667 m^(2)穗数多的品种(系),更容易获得高产。该研究为商洛地区小麦育种和高产栽培提供了新的理论参考。
In order to explore the relationship between the main agronomic characters and wheat yield in Shangluo area,its correlation and path analysis of the 7 main agronomic characters and yields of 15 new wheat varieties(lines)were carried out,which included grain number per ear,ear number per 667 m^(2),thousand-grain weight,and growth period,etc.The results showed that the correlation coefficient between grain number per ear and yield was the highest,and the growth period and yield had significantly negative correlation;The partial correlation analysis showed that grain number per ear was the most influential factor on yield,followed by ear number per 667 m^(2),while growth period had a largest negative effect on yield.In the path analysis,the direct effect of main agronomic characters on yield was as follows:grain number per ear>ear number per 667 m^(2)>plant height>basic seedling>thousand-grain weight>ear length>growth period.The correlation analysis and path analysis consistently showed that grain number per ear was the main factor affecting high-yield breeding of wheat,followed by ear number per 667 m^(2),the growth period had the the greatest negative effect on yield.Therefore,it is easier to obtain high yield by selecting varieties(lines)with earlier maturity and more grain numbers per ear,ear numbers per 667 m^(2).This study provides a new theoretical reference for wheat breeding and high yield cultivation in Shangluo area.
作者
敬樊
李勇刚
JING Fan;LI Yonggang(Shangluo Research Institute of Agricultural Science,Shangluo,Shannxi 726000,China)
出处
《陕西农业科学》
2021年第5期9-13,共5页
Shaanxi Journal of Agricultural Sciences
关键词
小麦
产量
农艺性状
相关分析
通径分析
Wheat
Yield
Agronomic characters
Correlation analysis
Path analysis