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Qualitative and quantitative detection of honey adulterated with high-fructose corn syrup and maltose syrup by using near-infrared spectroscopy

Author:
Li, Shuifang, Zhang, Xin, Shan, Yang, Su, Donglin, Ma, Qiang, Wen, Ruizhi, Li, Jiaojuan
Source:
Food chemistry 2017 v.218 pp. 231-236
ISSN:
0308-8146
Subject:
Brassica, adulterated products, discriminant analysis, high fructose corn syrup, honey, least squares, maltose, models, near-infrared spectroscopy, prediction
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.
Agid:
5496293