Delta-12 oleate desaturase gene （FAD2-1） which converts oleic acid into linoleic acid, is the key enzyme determining the fatty acid composition of cottonseed oil. By employing RT-PCR method, full length cDNA of cott...Delta-12 oleate desaturase gene （FAD2-1） which converts oleic acid into linoleic acid, is the key enzyme determining the fatty acid composition of cottonseed oil. By employing RT-PCR method, full length cDNA of cotton delta-12 oleate desat- urase gene GhFAD2-1 containing an open reading frame of 1 158 bp was cloned for constructing RNAi vector. A 515 bp long specific fragment of this gene was se- lected for constructing ihpRNA vector under the control of a seed-specific promoter NAPIN, named pFGC1008-NAPIN-FAD2-1; meanwhile miRNA gene-silencing vector pCAMBIA1302-amiRNA-FAD2-1 targeting GhFAD2-1 was also constructed.展开更多
为寻找最佳光谱检测部位,创新一种高油酸油菜种质资源筛选方法,以44个高油酸含量的甘蓝型油菜为材料,按照从主茎、一次分枝到二次分枝的顺序,采集籽粒反射光谱及油酸含量数据,分析不同部位的原始及一阶微分光谱与对应籽粒油酸含量的相...为寻找最佳光谱检测部位,创新一种高油酸油菜种质资源筛选方法,以44个高油酸含量的甘蓝型油菜为材料,按照从主茎、一次分枝到二次分枝的顺序,采集籽粒反射光谱及油酸含量数据,分析不同部位的原始及一阶微分光谱与对应籽粒油酸含量的相关关系,建立了基于全波长、特征波长的逐步多元线性回归(stepwise multiple linear regression,SMLR)、偏最小二乘回归(partial least squares regression,PLSR)、主成分回归(principal component re‐gression,PCR)估测模型和基于光谱指数的一元线性回归模型,用决定系数(R^(2))、均方根误差(root mean square error,RMSE)、相对预测偏差(relative prediction deviation,RPD)评价模型精度。研究发现,全波长模型中,以主茎原始光谱反射率建立的PLSR模型估测效果最好,校正集R^(2)c、RMSEc分别为0.83、1.63%,验证集R^(2)v、RMSEv、RPD分别为0.71、1.92%、2.00;特征波长模型中,基于一次分枝一阶微分光谱建立的PLSR模型估测效果最优,R^(2)c、R^(2)v为0.85、0.87,RMSEc、RMSEv为1.08%、1.13%,RPD为2.57;在光谱指数模型中,RPD均小于1.50,模型预测效果较差。因此基于一阶微分特征波长的PLSR模型可有效估测一次分枝籽粒油酸含量,为高油酸甘蓝型油菜油酸含量光谱检测取样提供参考。展开更多
文摘Delta-12 oleate desaturase gene （FAD2-1） which converts oleic acid into linoleic acid, is the key enzyme determining the fatty acid composition of cottonseed oil. By employing RT-PCR method, full length cDNA of cotton delta-12 oleate desat- urase gene GhFAD2-1 containing an open reading frame of 1 158 bp was cloned for constructing RNAi vector. A 515 bp long specific fragment of this gene was se- lected for constructing ihpRNA vector under the control of a seed-specific promoter NAPIN, named pFGC1008-NAPIN-FAD2-1; meanwhile miRNA gene-silencing vector pCAMBIA1302-amiRNA-FAD2-1 targeting GhFAD2-1 was also constructed.
文摘为寻找最佳光谱检测部位,创新一种高油酸油菜种质资源筛选方法,以44个高油酸含量的甘蓝型油菜为材料,按照从主茎、一次分枝到二次分枝的顺序,采集籽粒反射光谱及油酸含量数据,分析不同部位的原始及一阶微分光谱与对应籽粒油酸含量的相关关系,建立了基于全波长、特征波长的逐步多元线性回归(stepwise multiple linear regression,SMLR)、偏最小二乘回归(partial least squares regression,PLSR)、主成分回归(principal component re‐gression,PCR)估测模型和基于光谱指数的一元线性回归模型,用决定系数(R^(2))、均方根误差(root mean square error,RMSE)、相对预测偏差(relative prediction deviation,RPD)评价模型精度。研究发现,全波长模型中,以主茎原始光谱反射率建立的PLSR模型估测效果最好,校正集R^(2)c、RMSEc分别为0.83、1.63%,验证集R^(2)v、RMSEv、RPD分别为0.71、1.92%、2.00;特征波长模型中,基于一次分枝一阶微分光谱建立的PLSR模型估测效果最优,R^(2)c、R^(2)v为0.85、0.87,RMSEc、RMSEv为1.08%、1.13%,RPD为2.57;在光谱指数模型中,RPD均小于1.50,模型预测效果较差。因此基于一阶微分特征波长的PLSR模型可有效估测一次分枝籽粒油酸含量,为高油酸甘蓝型油菜油酸含量光谱检测取样提供参考。
