We thank the staff at the Research Center of Modernization of Chinese Medicines, Central South University for providing airPLS and PLS-LDA Matlab codes. This study was supported by the Scientific and Technological Innovation Projects of Hunan Academy of Agricultural Sciences (2010), the Natural Science Foundation of China (Project No.: 20875065).
机构署名：
本校为第一且通讯机构
院系归属：
理学院
摘要：
Raman spectroscopy was used to detect adulterants such as high fructose corn syrup (HFCS) and maltose syrup (MS) in honey. HFCS and MS were each mixed with authentic honey samples in the following ratios: 1:10 (10%), 1:5 (20%) and 1:2.5 (40%, w/w). Adaptive iteratively reweighted penalized least squares (airPLS) was chosen to remove background of spectral data. Partial least squares-linear discriminant analysis (PLS-LDA) was used to develop a binary classification model. Classification of honey authenticity using PLS-LDA showed a total accuracy...
