Method for identifying transgenic cottons based on terahertz spectra and WLDA

Terahertz spectroscopy and weighted linear discriminant analysis (WLDA) are applied to identify different transgenic cottons in this paper. Principal component analysis (PCA) is applied to extract relevant features from original spectrum information and eliminate the anomalous samples. Instead of original spectral information, the feature spectrum is selected to fed into the model of WLDA, where an improved linear discrimination method to identify those samples. The results demonstrate that the WLDA method can effectively identify the distinct transgenic cottons, and terahertz spectroscopy can provide a nondestructive, rapid and reliable method to distinguish different transgenic cottons.