| 马柱文，张振臣，袁清华，屈玉娇，李集勤，李淑玲，陈俊标.烟叶钾含量种质间差异分析及其田间鉴定指标筛选[J].广东农业科学,2019,46(2):16-22 |
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烟叶钾含量种质间差异分析及其田间鉴定指标筛选 |
| Analysis of Differences in Potassium Content among Tobacco Germplasm and Screening of Field Identification Indicators |
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| DOI：10.16768/j.issn.1004-874X.2019.02.003 |
| 中文关键词: 钾含量 种质 形态特征 田间鉴定 |
| 英文关键词: potassium content germplasm morphological characteristic field identification |
| 基金项目:广东省烟草专卖局科技计划项目（粤烟科［2012］28 号）；广东省自然科学基金（2016A030313781）；广东省农业厅科技项目（粤农计［2018］36 号） |
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| 中文摘要: |
| 【目的】探讨烟叶钾含量田间鉴定指标筛选，分析烟草种质间烟叶钾含量差异，筛选其田间鉴定
指标，建立可靠的数学评价模型。【方法】以 31 份烟草种质为试材，采用田间试验，调查株高（x1）、茎围（x2）、
节距（x3）、叶数（x4）、最大叶长（x5）、最大叶宽（x6）、主侧脉夹角（x7）、茎叶夹角（x8）、花冠长度（x9）、
花冠直径（x10）、花萼长度（x11）11 个形态特征指标，运用聚类分析、主成分分析、因子分析和多元逐步回
归分析方法对烟叶钾含量进行综合评价。【结果】通过聚类分析将 31 份烟草种质聚类分成高钾种质、中钾种
质、低钾种质 3 种类型。通过主成分分析将 11 个形态特征指标转换成 5 个彼此独立的综合指标，代表了全部
数据 84.624% 的信息量。通过多元逐步回归分析建立烟叶钾含量的数学评价模型 y=-1.699+0.041x5+0.831x10
（R2=0.9602），估计精度在 89.66% 以上。【结论】叶长及花冠直径对烟叶钾含量信息有极显著的反映能力，
可作为烟叶钾含量的田间鉴定指标。 |
| 英文摘要: |
| 【Objective】In this paper, the screening of field identification indicators of potassium content in
tobacco leaves was explored and the difference of potassium content among tobacco germplasms was analyzed in order to
select suitable identification indicators and establish a mathematical evaluation model.【Method】31 tobacco germplasms
were treated in field experiments. 11 morphological characteristic indicators, such as plant height（x1）, stem girth（x2）,
intermodal distance（x3）, leaf number（x4）, maximum leaf length（x5）, maximum leaf width（x6）, angle of lateral
vto midrib（x7）, angle between stem and leaf（x8）, corolla length（x9）, corolla diameter（x10）and calyx length
（x11）were investigated and hierarchical cluster analysis, principal component analysis, factor analysis and multiple
stepwise regression analysis were used to comprehensively evaluate the potassium content in tobacco leaves. 【Result】
Results revealed that 31 tobacco germplasm were clustered into high potassium germplasm, medium potassium germplasm and low potassium germplasm by cluster analysis. 11 single indexes were transformed into 5 independent comprehensive
indicators through principal component analysis, which represented 84.624% of the whole data of the traits related to tobacco
potassium content. And a mathematical evaluation model of potassium content in tobacco leaves was established by multiple
stepwise regression analysis, i.e.y=-1.699+0.041 x5+0.831 x10（R2=0.9602）,with an accuracy of 89.66%.【Conclusion】
Leaf length（x5）and corolla diameter（x10）reflected the potassium content of tobacco leaves significantly and could be
used as field identification indicators for the potassium content of tobacco leaves. |
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