Spectral simplification of PCA inter-class distance evaluation: a case of artificial breeding and wild Cordyceps sinensis identification

In recent years, with the increasing market demand for Cordyceps sinensis, the identification of artificial breeding varieties and wild varieties has become particularly important. The traditional identification method of Cordyceps sinensis is time-consuming and inefficient. Based on the advantages of hyperspectral detection technology, a simplified spectral method based on PCA inter-class distance evaluation was proposed. By performing PCA dimensionality reduction on the hyperspectral data of Cordyceps sinensis samples under different spectra, extracting principal components, calculating inter-class distance, and selecting the most recognizable spectra, the identification process was simplified. The preliminary results showed that the inter-class distance between artificial breeding and wild Cordyceps sinensis was the largest when SWIR-1 (1000-1800nm) spectrum was used only. When the Mahalanobis distance is used as an evaluation index, when only SWIR-1 spectrum is used, the Mahalanobis distance value reaches 5.21, which is larger than that of other spectra only. By simplifying the spectrum, the identification of artificial breeding and wild Cordyceps sinensis using only SWIR- 1 spectrum can be effective, and the hardware cost of the spectrometer can be reduced.