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冬瓜苗期耐低温性鉴定及相关分析 被引量:2

Identification and Analysis of Low Temperature Tolerance in Wax Gourd at Seedling Stage
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摘要 为研究冬瓜在苗期的耐低温特性,对15个冬瓜品种幼苗进行低温胁迫处理,测定幼苗的株高、茎粗、叶面积、鲜物质量和干物质量5个形态指标。通过相关性分析、主成分分析、隶属函数值分析、聚类分析、回归分析等分析方法对冬瓜苗期进行耐低温胁迫鉴定和指标筛选。结果表明:相对株高与相对茎粗、相对叶面积、相对鲜物质量之间呈显著性差异;通过主成分分析筛选到两个主成分,累计贡献率为77.622%;通过综合评价值的大小发现,15份冬瓜材料耐寒能力有明显的区别;通过聚类分析筛选出1个耐低温品种和3个不耐低温品种;通过线性回归分析建立冬瓜幼苗期耐低温方程,方程分析发现冬瓜苗期的5个形态指标都对低温胁迫敏感,可以作为鉴定指标。 In order to research the characteristics of wax gourd resistant to low temperature,taking 15 wax gourd varieties treated with low temperature at seedling stage as the materials to assess their low temperature tolerance and select the indicators by correlation analysis,principal component analysis,membership function analysis,cluster analysis and regression analysis.A total of 5 indicators including seedling height,stem diameter,leaf area,fresh matter and dry matter were measured after low temperature stress at seedling stage.The results showed that the relative height had significant difference with relative stem diameter,relative leaf area and relative fresh weight.The two principal components were screened out by principal component analysis,and the cumulative contribution rate was 77.622%.The cold resistance of the 15 wax gourd materials was distinctly different,by comparing the comprehensive evaluation values.One resistant variety and 3 intolerant varieties were selected out through cluster analysis.A tolerance equation of wax gourd seedlings was established by stepwise regression analysis.Five morphological indexes of wax gourd seedling were sensitive to low temperature and could be used as identification index.
作者 姚金晓 杨飞 王呈阳 王国华 吴菊 YAO Jin-xiao, YANG Fei, WANG Cheng-yang, WANG Guo-hua, WU Ju(Zhoushan Academy of Agricultural and Forestry Sciences,Zhoushan 31600, Chin)
出处 《黑龙江农业科学》 2018年第5期13-17,共5页 Heilongjiang Agricultural Sciences
基金 舟山市公益类科技资助项目(2015C31021)
关键词 冬瓜 低温胁迫 形态指标 主成分分析 隶属函数值 聚类分析 wax gourd low temperature tolerance morphological index principal component analysis membership function value cluster analysis
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