Quantification of chlorophyll content and classification of nontransgenic and transgenic tomato leaves using visible/near-infrared diffuse reflectance spectroscopy.
Quantification of chlorophyll content and classification of nontransgenic and transgenic tomato leaves using visible/near-infrared diffuse reflectance spectroscopy.
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DOI：
10.1021/jf063664m
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发表时间：
2007-05
影响因子：
6.1
通讯作者：
Lijuan Xie;Y. Ying;T. Ying
中科院分区：
文献类型：
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作者：
Lijuan Xie;Y. Ying;T. Ying
利用可见/近红外光谱技术结合多元分析对番茄叶片叶绿素含量进行定量分析，并对不同基因番茄叶片进行分类。在这项研究中，转基因番茄叶片反义LeETR1（n = 106）和他们的父母非转基因（n = 102）在可见光/近红外漫反射模式进行了测量。叶绿素含量的量化实现了偏最小二乘回归的交叉验证预测误差等于2.87。采用偏最小二乘判别分析对叶片进行分类。结果表明，转基因番茄叶片与非转基因番茄叶片的光谱特征存在差异，优化光谱预处理后可获得较好的分类效果。利用光谱数据在全波数和部分波数范围内的导数，分类精度可达100%。这些结果表明，可见/近红外光谱与化学计量学技术可以用来量化叶绿素含量和区分不同基因的番茄叶片，这提供了避免耗时，昂贵和费力的化学和感官分析的好处。
Visible/near-infrared (vis/NIR) spectroscopy combined with multivariate analysis was used to quantify chlorophyll content in tomato leaves and classify tomato leaves with different genes. In this study, transgenic tomato leaves with antisense LeETR1 (n = 106) and their parent nontransgenic ones (n = 102) were measured in vis/NIR diffuse reflectance mode. Quantification of chlorophyll content was achieved by partial least-squares regression with a cross-validation prediction error equal to 2.87. Partial least-squares discriminant analysis was performed to classify leaves. The results show that differences between transgenic and nontransgenic tomato leaves do exist, and excellent classification can be obtained after optimizing spectral pretreatment. The classification accuracy can reach to 100% using the derivative of spectral data in the full and partial wavenumber range. These results demonstrate that vis/NIR spectroscopy together with chemometrics techniques could be used to quantify chlorophyll content and differentiate tomato leaves with different genes, which offers the benefit of avoiding time-consuming, costly, and laborious chemical and sensory analysis.