不同钾处理下小麦重组自交系群体主要农艺性状的表型变异及其相关分析

Phenotypic variation and correlation analysis of major agronomic traits ofwheat recombinant inbred lines population under different potassium levels

    摘要
  • 摘要: 以“山农 483×川 35050”组合衍生的小麦重组自交系(recombinant inbred lines, RIL)群体的 131 个株系及其亲本为试验材料, 于 2008 年和 2009 年采用盆栽土培法, 对低、中、高钾处理条件下0、0.1 g(K2O)·kg?1、0.3 g((K2O)·kg?1小麦 RIL 群体的株高、单株穗数、穗长、小穗数、穗粒数、千粒重、粒长、粒宽和单株籽粒产量共 9 个农艺性状进行了鉴定和统计分析。结果表明, 在 2008—2009 年 3 个钾处理中, 9 个农艺性状在 RIL群体中的表型变异均呈近似正态分布, 其遗传力分别为 80.6%(株高)、 44.7%(单株穗数)、 69.9%(穗长)、 71.4%(小穗数)、76.0%(穗粒数)、74.8%(千粒重)、64.9%(粒长)、40.0%(粒宽)和 33.2%(单株籽粒产量)。株高、小穗数、穗粒数和粒长 4 个性状的表型变异以基因型控制为主, 千粒重和粒宽以基因型×年份互作效应为主, 穗长以基因型和基因型×年份互作效应为主, 单株穗数以基因型×钾水平互作效应为主, 单株籽粒产量的表型变异则主要受基因型×年份×钾水平互作效应控制。在不同钾处理条件下, RIL 群体的平均单株籽粒产量与单株穗数、穗长和穗粒数呈极显著或显著正相关, 但与千粒重的关系不稳定。千粒重与穗粒数、单株穗数无关或显著负相关(r 为?0.07~?0.28); 穗粒数与单株穗数的关系不稳定(r 为?0.03~0.27)。千粒重、穗粒数和单株穗数在遗传过程中的相关系数较低, 彼此具有较强的相对独立性, 不存在绝对的顾此失彼现象。单株籽粒产量与小穗数、穗粒数、千粒重、粒长和粒宽间的相关系数受年份间环境差异的影响较大。

     

    Abstract: Potassium (K) is one of the most important nutrient elements for wheat growth. In China, K mineral is in acute short supply and generally deficient. Hence K is an important limiting factor for agricultural production in China. Deepening our under-standing of genetic correlation among agronomic traits under different K treatments was critical for genetic improvements in wheat under soil K deficiency. Main agronomic traits of plant height (PH), spikes number per plant (SN), spike length (PL), spikelets num-ber per spike (SPI), grains number per spike (GNS), 1000-grain weight (TGW), kernel length (KL), kernel width (KW) and grain weight per plant (GW) of 131 “Shannong 483 × Chuan 35050” recombined inbred lines (RIL) were investigated in a pot trial with three K treatments (0 g·kg?1, 0.1 g·kg?1 and 0.3 g·kg?1 of K2O) in 2008—2009. The traits were analyzed for variance and correlation.Results showed that the frequencies of PH, SN, PL, SPI, GNS, TGW, KL, KW and GW in RIL population were approximate in nor-mal distribution in the 2-year 3-K treatments. Broad-sense heredities (Hb2) of the nine agronomic traits were 80.6%, 44.7%, 69.9%, 71.4%, 76.0%, 74.8%, 64.9%, 40.0% and 33.2%, respectively. Phenotypic variations among PH, SPI, GNS and KL were mainly attributed by genotypes traits. TGW and KW were mainly influenced by interactive effects of genotype and year. PL was mainly driven by genotypes and interactive effects of genotype and year. SN was influenced by interactive effects of genotype and K dose. Then GW was controlled by interactive effects of genotype, year and K dose. Significant positive correlations existed among GW and SN, PL and GNS under different K treatments. However, the correlation between GW and TGW was not stable across the treat-ments. TGW was not related or negatively related with SN and GNS (r=?0.07~?0.28). Also the correlation between SN and GNS was unstable (r=?0.03~0.27). This suggested that TGW, SN and GNS were weakly correlated and independent of genetic processes. No firm trade-off existed among important traits during crop breeding. The correlations among GW and SPI, GSN, TGW, KL and KW were significantly influenced by time.

     

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