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二次回归正交设计在楸树离体生根培养中的应用
引用本文:于永明,王军辉,张宋智,马建伟,李平英.二次回归正交设计在楸树离体生根培养中的应用[J].南京林业大学学报(自然科学版),2011,0(4):47-50.
作者姓名:于永明  王军辉  张宋智  马建伟  李平英
作者单位:1. 甘肃省小陇山林业科学研究所,甘肃天水,741022
2. 中国林业科学研究院,国家林业局林木培育重点实验室,北京100091
基金项目:“十一五”国家科技支撑计划,农业科技成果转化项目,国家林业局林木培育实验室基金项目
摘    要:应用二次回归正交设计与SPSS软件,建立楸树组培生根培养生根率、根长、发根数、发芽数、芽长、叶数、地上部鲜质量回归方程,通过对各方程进行模拟,得出与生长素NAA配比使用时楸树组培生根培养IBA用量的最佳范围为0200~0344 mg/L。试验发现,一定浓度的NAA主要促使根系的发生与生长,促进瓶苗叶数的增多,对芽长的生长与发芽数无显著作用,促进根系生根率最佳范围为0023~0073 mg/L。IBA用量在0200~0344 mg/L、NAA在0023~0073 mg/L范围内,楸树组培苗生根率可达95 %以上,可靠性为95 %。

关 键 词:楸树  生根率  二次回归正交设计  方差分析

Application of quadratic regressive factorial experiment to in vitro rooting culture of Catalpa bungei
YU Yongming,WANG Junhui,ZHANG Songzhi,MA Jianwei,LI Pingying.Application of quadratic regressive factorial experiment to in vitro rooting culture of Catalpa bungei[J].Journal of Nanjing Forestry University(Natural Sciences ),2011,0(4):47-50.
Authors:YU Yongming  WANG Junhui  ZHANG Songzhi  MA Jianwei  LI Pingying
Institution:1(1.Xiaolongshan Research Institute of Forestry,Tianshui 741022,China;2.Chinese Academy of Forestry,Key Laboratory of Tree Breeding and Cultivation,State Forestry Administration,Beijing 100091,China)
Abstract:Quadratic regressive factorial experiment and SPSS software was used to analyse and optimize concentrations of IBA and NAA added in rooting medium for the rooting rate,root length,root number,sprouting number,bud length,leaf number and shoot fresh weight of Catalpa bungei,we obtained a serial of regression equations.Using such equations to search for the best dosage of IBA and NAA to induce root in vitro culture of C.bungei.The results showed that,a certain concentration of NAA could promote the root differentiation and growth,and increase leaves,but there is no significant role to the growth of buds and sprouting number.The best dosage range of IBA is in 0.200—0.344 mg/L,and dosage range of NAA is in 0.023—0.073 mg/L,the rooting rate was achieved at 95 %,the probability of the event was 95 %.
Keywords:Catalpa bungei  rooting rate  quadratic regressive factorial experiment  variance analysis
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