title: Exploring supervised neighborhood preserving embedding (SNPE) as a nonlinear feature extraction method for vibrational spectroscopic discrimination of agricultural samples according to geographical origins.
abstract: Supervised neighborhood preserving embedding (SNPE), a nonlinear dimensionality reduction method, was employed to represent near-infrared (NIR) and Raman spectral features of agricultural samples (Angelica gigas, sesame, and red pepper), and the newly constructed variables were used to discriminate their geographical origins. This study was done to evaluate the potential of SNPE for recognizing minute spectral differences between classes by preserving local relationships, in comparison with widely adopted linear feature representation methods such as principal component analysis (PCA) and partial least squares (PLS). For this purpose, diffuse reflectance NIR spectral datasets of Angelica gigas, sesame, and red pepper, and a Raman spectral dataset of the same red pepper were prepared. The spectra were represented into new variables in reduced dimensions by PCA, PLS, neighborhood preserving embedding (NPE), and SNPE, and the represented variables were used to determine the geographical origins of samples by using the k-nearest neighbor (k-NN) and support vector machine (SVM). The combination of SNPE and SVM differentiated the geographical origins with improved accuracy. Overall results demonstrate that SNPE is a valuable alternative feature representation method, especially when complex and highly overlapping vibrational spectra are used for analysis.
authors.affiliation: Department of Chemistry and Research Institute for Convergence of Basic Sciences, College of Natural Sciences, Hanyang University, Seoul 133-791, Republic of Korea.
authors.forename: Sanguk
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Chemistry and Research Institute for Convergence of Basic Sciences, College of Natural Sciences, Hanyang University, Seoul 133-791, Republic of Korea.
authors.forename: Jinyoung
authors.initials: J
authors.lastname: Hwang
authors.affiliation: Department of Industrial & Management Engineering, Pohang University of Science and Technology, San 31 Hyojadong, Pohang 790-784, Republic of Korea. Electronic address: hyelee@postech.ac.kr.
authors.forename: Hyeseon
authors.initials: H
authors.lastname: Lee
authors.affiliation: Department of Chemistry and Research Institute for Convergence of Basic Sciences, College of Natural Sciences, Hanyang University, Seoul 133-791, Republic of Korea. Electronic address: hoeil@hanyang.ac.kr.
authors.forename: Hoeil
authors.initials: H
authors.lastname: Chung
mesh_terms: D000383:Agriculture; D029969:Angelica; D002212:Capsicum; D005843:Geography; D031685:Sesamum; D019265:Spectroscopy, Near-Infrared; D013059:Spectrum Analysis, Raman; D060388:Support Vector Machine
keywords: Discrimination of geographical origins; Locally linear embedding; Nonlinear feature extraction methods; Supervised neighborhood preserving embedding; Vibrational spectroscopy