title: [Prediction analysis of soluble solids content and moisture in honey by near infrared spectroscopy].
abstract: A new method for the analysis of soluble solids content (SSC) in honey by near infrared spectroscopy (NIR) was developed, and moisture was also analyzed. The partial least square regression models of SSC and moisture were built for different pretreatments of the raw spectra in different spectral range. Good predictions were always obtained for all models. The best models of SSC and moisture were obtained by using Norris (3,2) smoothing + first derivative + multiplicative signal correction in total spectral range. The coefficient of determination (R(CV)2) and root mean square error of cross validation (RMSECV), the coefficient of determination (R(p)2) and root mean square error of validation sets (RMSEP) were 0.9986, 0.190, 0.9985 and 0.127 respectively for SSC, while for moisture they were 0.9984, 0.187, 0.9986 and 0.125 respectively. NIR could be used to analyze SSC and moisture in honey. The result of this article was better than that of related documents for moisture.
authors.affiliation: Central South University of Forestry & Technology, Changsha 410004, China. csfulishuifang@126.com
authors.forename: Shui-fang
authors.initials: SF
authors.lastname: Li
authors.forename: Xin
authors.initials: X
authors.lastname: Zhang
authors.forename: Yang
authors.initials: Y
authors.lastname: Shan
authors.forename: Zhong-hai
authors.initials: ZH
authors.lastname: Li
mesh_terms: D006722:Honey / Q000032:analysis*; D016018:Least-Squares Analysis; D019265:Spectroscopy, Near-Infrared