Classification of Fritillaria using a portable near-infrared spectrometer and fuzzy generalized singular value decomposition

Abstract

Fritillaria is a popular Chinese medicinal crop known for its medicinal value. However, the chemical composition and medicinal value of Fritillaria can vary significantly depending on the variety and origin. Therefore, there is a need for a more efficient and accurate method to identify Fritillaria of different varieties and origins. This study employed a portable near-infrared (NIR) spectrometer to collect NIR spectral data on six kinds of Fritillaria and classify them by using different feature extraction methods. In order to circumvent the limitations of Linear Discriminant Analysis (LDA) in small-sample size problem and improve the classification accuracy, Fuzzy Generalized Singular Value Decomposition (FGSVD) was proposed for feature extraction from NIR spectra. The original NIR data were first pre-processed by the Savitzky-Golay (SG) filtering, and then their dimensionality was reduced by Principal Component Analysis (PCA). After that, Generalized Singular Value Decomposition (GSVD) and FGSVD were performed for feature extraction, respectively. In the end, the spectral data were classified into six categories using the k-Nearest Neighbour (KNN) classifier and Extreme Learning Machines (ELM). The results of the study showed that FGSVD had the highest classification accuracy when using the KNN classifier and was able to achieve 100 % classification accuracy. At the same time, GSVD and LDA were able to achieve 97.5 % and 92.5 % classification accuracy respectively. The classification accuracy obtained by FGSVD was also higher than GSVD and LDA when ELM was used. The highest classification accuracies obtained by FGSVD, GSVD and LDA were 96.9 %, 94.2 % and 92.3 % respectively. Thus, the KNN classifier outperformed ELM in classification. Consequently, the portable near-infrared spectrometer coupled with PCA+FGSVD is a novel strategy for rapid and non-destructive classification of Fritillaria.