QQ客服 官方微博 反馈留言

	Feasibility study of quantifying and discriminating soybean oil adulteration in camellia oils by attenuated total reflectance MIR and fiber optic diffuse reflectance NIR
	Li Wang ; Frank S.C. Lee ; Xiaoru Wang ; Wang XR(王小如) ; Ying He
	2005-06
关键词	MIR NIR camellia oil adulteration classification quantification
英文摘要	Camellia oil is often the target for adulteration or mislabeling in China because of it is a high priced product with high nutritional and medical values. In this study, the use of attenuated total reflectance infrared spectroscopy (MIR-ATR) and fiber optic diffuse reflectance near infrared spectroscopy (FODR-NIR) as rapid and cost-efficient classification and quantification techniques for the authentication of camellia oils have been preliminarily investigated. MIR spectra in the range of 4000-650 cm(-1) and NIR spectra in the range of 10,000-4000 cm(-1) were recorded for pure camellia oils and camellia oil samples adulterated with varying concentrations of soybean oil (5-25% adulterations in the weight of camellia oil). Identifications is successfully made base on the slightly difference in raw spectra in the MIR ranges of 1132-885 cm(-1) and NIR ranges of 6200-5400 cm(-1) between the pure camellia oil and those adulterated with soybean oil with soft independent modeling of class analogy (SIMCA) pattern recognition technique. Such differences reflect the compositional difference between the two oils with oleic acid being the main ingredient in camellia oil and linoleic acid in the soybean oil. Furthermore, a partial least squares (PLS) model was established to predict the concentration of the adulterant. Models constructed using first derivative by combination of standard normal variate (SNV),. variance scaling (VS), mean centering (MC) and Norris derivative (ND) smoothing pretreatments yielded the best prediction results With MIR techniques. The R value for PLS model is 0.994. The root mean standard error of the calibration set (RMSEC) is 0.645, the root mean standard error of prediction set (RMSEP) and the root mean standard error of cross validation (RMSECV) are 0.667 and 0.85, respectively. While with NIR techniques, NIR data without derivative gave the best quantification results. The R value for NIR PLS model is 0.992. The RMSEC, RMSEP and RMSECV are 0.70, 1.78 and 1.79, respectively. Overall, either of the spectral method is easy to perform and expedient, avoiding problems associated with sample handling and pretreatment than the conventional technique. (c) 2005 Elsevier Ltd. All rights reserved.
语种	英语
出版者	ELSEVIER SCI LTD
内容类型	期刊论文
源URL	[http://dx.doi.org/doi:10.1016/j.foodchem.2005.04.015]
专题	化学化工－已发表论文
推荐引用方式 GB/T 7714	Li Wang,Frank S.C. Lee,Xiaoru Wang,et al. Feasibility study of quantifying and discriminating soybean oil adulteration in camellia oils by attenuated total reflectance MIR and fiber optic diffuse reflectance NIR[J],2005.
APA	Li Wang,Frank S.C. Lee,Xiaoru Wang,王小如,&Ying He.(2005).Feasibility study of quantifying and discriminating soybean oil adulteration in camellia oils by attenuated total reflectance MIR and fiber optic diffuse reflectance NIR..
MLA	Li Wang,et al."Feasibility study of quantifying and discriminating soybean oil adulteration in camellia oils by attenuated total reflectance MIR and fiber optic diffuse reflectance NIR".(2005).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。