Development of Hyperspectral Imaging System to Detect Gene Recombinant Callus

本研究的目的是开发一种检测基因重组植物细胞的高光谱成像系统。由于耐药基因有可能对生态系统产生负面影响，本研究计划使用表达硝酸还原酶（NR）的基因作为标记基因。如果将NR基因引入转基因细胞，重组后的基因降低硝酸盐浓度的潜力要高于野生型。因此，建立了一种检测基因重组愈伤组织中硝酸盐浓度的无损检测方法。所建立的愈伤组织近红外光谱硝酸盐浓度估算数学模型的精度为，测量值与估计值的相关系数为0。7363. 虽然我们尝试用粒子枪法将NR基因导入菠菜细胞，但由于重组条件不合适，无法产生基因重组愈伤组织。然后对高硝酸盐含量(大于961。0 mg/L)，来自低浓度的愈伤组织(小于961。0 mg/L)近红外光谱分析。数学模型预测硝酸盐浓度的准确率达到85%，达到87%。4%来自PLS-DA

The purpose of this research is to develop a hyperspectral imaging system to detect gene recombinant plant cells. Since drug tolerance genes have the potential to negatively affect ecosystems, this research plans to use genes that express the nitrate reductase(NR) as marker genes. If the NR genes are introduced into a cell with a transgene, the recombined genes would show higher potential to reduce nitrate concentration than that of a wild type. Therefore, non-destructive methods for measurements of nitrate concentration in callus were developed to detect the gene recombinant calluses. As for accuracy of developed mathematical model to estimate the nitrate concentration of callus from the near-infrared spectrum, correlation coefficient between measured and estimated nitrate concentration became 0. 7363. Though we tried to introduce the NR gene to spinach cells by using the particle gun method, gene recombinant calluses could not be produced because of inappropriate conditions for the recombination. Then possibilities to discriminate calluses containing high nitrate concentration(more than 961. 0 mg/L) from low concentration calluses(less than 961. 0 mg/L) by processing the near-infrared spectra were examined. Accuracy rate became 85% that was obtained from the mathematical model to predict the nitrate concentration and 87. 4% that was derived from PLS-DA