title: Qualitative and quantitative detection of honey adulterated with high-fructose corn syrup and maltose syrup by using near-infrared spectroscopy.
abstract: Near-infrared spectroscopy (NIR) was used for qualitative and quantitative detection of honey adulterated with high-fructose corn syrup (HFCS) or maltose syrup (MS). Competitive adaptive reweighted sampling (CARS) was employed to select key variables. Partial least squares linear discriminant analysis (PLS-LDA) was adopted to classify the adulterated honey samples. The CARS-PLS-LDA models showed an accuracy of 86.3% (honey vs. adulterated honey with HFCS) and 96.1% (honey vs. adulterated honey with MS), respectively. PLS regression (PLSR) was used to predict the extent of adulteration in the honeys. The results showed that NIR combined with PLSR could not be used to quantify adulteration with HFCS, but could be used to quantify adulteration with MS: coefficient (Rp2) and root mean square of prediction (RMSEP) were 0.901 and 4.041 for MS-adulterated samples from different floral origins, and 0.981 and 1.786 for MS-adulterated samples from the same floral origin (Brassica spp.), respectively.
authors.affiliation: College of Science, Central South University of Forestry and Technology, Changsha 410004, China.
authors.forename: Shuifang
authors.initials: S
authors.lastname: Li
authors.affiliation: Longping Branch Graduate School, Central South University, Changsha 410125, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Hunan Agricultural Product Processing Institute, Hunan Academy of Agricultural Sciences, Changsha 410125, China. Electronic address: Sy6302@126.com.
authors.forename: Yang
authors.initials: Y
authors.lastname: Shan
authors.affiliation: Hunan Agricultural Product Processing Institute, Hunan Academy of Agricultural Sciences, Changsha 410125, China.
authors.forename: Donglin
authors.initials: D
authors.lastname: Su
authors.affiliation: College of Science, Central South University of Forestry and Technology, Changsha 410004, China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Ma
authors.affiliation: College of Science, Central South University of Forestry and Technology, Changsha 410004, China.
authors.forename: Ruizhi
authors.initials: R
authors.lastname: Wen
authors.affiliation: College of Science, Central South University of Forestry and Technology, Changsha 410004, China.
authors.forename: Jiaojuan
authors.initials: J
authors.lastname: Li
mesh_terms: D016002:Discriminant Analysis; D005506:Food Contamination / Q000032:analysis*; D066248:High Fructose Corn Syrup / Q000032:analysis* / Q000737:chemistry; D006722:Honey / Q000032:analysis*; D016018:Least-Squares Analysis; D016014:Linear Models; D008320:Maltose / Q000032:analysis* / Q000737:chemistry; D019265:Spectroscopy, Near-Infrared / Q000379:methods*
chemical_list: D066248:High Fructose Corn Syrup; D008320:Maltose
keywords: Competitive adaptive reweighted sampling (CARS); Honey adulteration; Near-infrared spectroscopy; Partial least squares linear discriminant analysis (PLS-LDA); Partial least squares regression (PLSR)