Xie Li-Juan, Ying Yi-Bin, Ying Tie-Jin, Tian Hai-Qing, Niu Xiao-Ying, Fu Xia-Ping
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2008 May;28(5):1062-6.
The feasibility of Vis/NIR spectroscopy technique for rapid and non-invasive detection of transgenic tomato leaves from conventional ones was investigated by means of spectral diffuse reflectance mode. A total of 68 samples (38 transgenic ones and 30 non-transgenic ones) were used for classification. The calibration and validation results were analyzed via discriminant analysis (DA) and partial least squares (PLS) discriminant method using TQ 6.2. 1 quantitative software. Models based on the different spectral pre-processing methods (multiplicative signal correction (MSC), first and second derivative) were compared. It was found that the classification accuracy using DA was higher than that using PLS and the best results were gained by using spectra after MSC with InGaAs detector and the classification accuracy was 89.7% (accuracy of 86.8% for transgenic samples and 93.3% for non-transgenic ones). The results show that Vis-NIR diffuse reflectance spectroscopy technique is a feasible and fast method for non-invasive detection of transgenic and non-transgenic tomato leaves.
采用光谱漫反射模式,研究了可见/近红外光谱技术快速、无损检测转基因番茄叶片与常规番茄叶片的可行性。共使用68个样本(38个转基因样本和30个非转基因样本)进行分类。利用TQ 6.2. 1定量软件,通过判别分析(DA)和偏最小二乘(PLS)判别法对校准和验证结果进行分析。比较了基于不同光谱预处理方法(多元散射校正(MSC)、一阶和二阶导数)的模型。结果发现,使用DA的分类准确率高于使用PLS的分类准确率,采用InGaAs探测器并经MSC处理后的光谱获得了最佳结果,分类准确率为89.7%(转基因样本的准确率为86.8%,非转基因样本的准确率为93.3%)。结果表明,可见-近红外漫反射光谱技术是一种用于转基因和非转基因番茄叶片无损检测的可行且快速的方法。