H. Itoh, S. Tomoda, Tomoko Hatta, N. Shiraishi, Y. Uno
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引用次数: 2
摘要
本研究的目的是建立一种可以检测基因重组愈伤组织的高光谱成像系统。耐药基因通常被用作标记基因,尽管它们可能对环境产生负面影响。因此,我们的目标是使用编码硝酸还原酶(NR)的基因作为标记基因。将NR基因导入细胞后,重组后的基因与野生型基因相比,硝酸盐还原量更大,从而可以利用硝酸盐浓度来区分基因重组愈伤组织与非基因重组愈伤组织。本研究建立了一种无损检测菠菜(Spinacia oleracea L. ' Orai ')愈伤组织中硝酸盐浓度的方法,以实现基因重组愈伤组织的快速检测。349个愈伤组织的吸收光谱(浓度范围:126.0 mg L - 1 ~ 2697 mg L - 1;标准偏差:646.3 mg L -1),波长范围:400 nm-1000 nm;分辨率:9nm)。采用RQ-Flex法测定愈伤组织中硝酸盐浓度。利用主成分回归(PCR)和偏最小二乘法(PLS)建立了从吸收光谱中估计出愈伤组织中硝酸盐浓度的数学模型,结果表明,硝酸盐浓度的实测值与估计值之间的相关系数为0.7363。模型的校准标准误差(SEC)和预测标准误差(SEP)分别为430.3 mg L - 1和438.7 mg L - 1。
Development of a Hyperspectral Imaging System to Detect Nitrate Concentration of Spinach Callus
The purpose of this study was to develop a hyperspectral imaging system that can detect gene recombinant calluses. Drug tolerance genes are commonly used as marker genes, although they may negatively affect the environment. Hence, we aimed to use the genes that code for nitrate reductase (NR) as marker genes. Once the NR genes are introduced into a cell, the recombined genes would show greater nitrate reduction compared with the wild-type genes, making it possible to use the nitrate concentration for discriminating gene recombinant calluses from non-recombinant ones. In the present study, a non-destruc-tive method of measuring the nitrate concentration in spinach ( Spinacia oleracea L. ‘Orai’) calluses was developed to allow for the rapid detection of the gene recombinant calluses. Absorption spectra of 349 calluses (concentration range: 126.0 mg L - 1 -2697 mg L - 1 ; standard deviation: 646.3 mg L - 1 ) were measured by a hyperspectral camera (wavelength range: 400 nm-1000 nm; resolution: 9 nm). The nitrate concentration of the calluses was measured by the RQ-Flex method. Mathematical models to estimate the nitrate concentration in the calluses from the absorption spectra were developed using the principal component regression (PCR) and partial least squares (PLS) methods, and the correlation coefficient between the measured and estimated nitrate concentration was found to be 0.7363. The standard errors of calibration ( SEC ) and prediction ( SEP ) of the model were 430.3 mg L - 1 and 438.7 mg L - 1 , respectively.