Atr-ftir光谱结合化学计量学快速分类特级初榨橄榄油和食用油从不同品种可在土耳其市场

F. Arslan
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引用次数: 4

摘要

采用衰减全反射-傅里叶变换红外光谱(ATR-FTIR)和化学计量技术相结合的方法对土耳其市场上的不同商标食用油进行了分类。对特级初榨橄榄油(VOO)、榛子油(HNO)、棉籽油(CSO)、葵花籽油(SFO)和大豆油(SBO)等144种食用油样品进行了光谱分析。采用多变量数据分析的ATR-FTIR方法对其他食用油中多余油脂进行鉴别的可行性进行了评价。采用主成分分析(PCA)、层次聚类分析(HCA)、线性判别分析(LDA)和类类比软独立建模(SIMCA)对食用油进行分类。在4000 ~ 650 cm-1波长范围内采集的光谱和从全光谱中选择的28个不同波长范围的光谱进行了评价,以获得最优的分类模型。多变量分析结果对食用油的分类具有良好的判别性,分类误差小。使用5个预测因子构建的LDA模型,对不同商标的食用油样品进行了100%的正确分类。此外,在有监督的SIMCA模型中,判别分析没有出现误分类,准确率达到95%。因此,ATR-FTIR光谱结合多变量数据分析,可以很好地说明不同品牌的商业食用油根据其质量和纯度的相对位置。
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ATR–FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS FOR RAPID CLASSIFICATION OF EXTRA VIRGIN OLIVE OILS AND EDIBLE OILS FROM DIFFERENT CULTIVARS AVAILABLE ON THE TURKISH MARKETS
A combination of attenuated total reflectance–Fourier transform infrared (ATR–FTIR) spectroscopy and chemometric techniques was used to classify different trademarks of edible oils available on the Turkish markets. A total of 144 spectra of edible oil samples, including extra virgin olive oil (VOO), hazelnut oil (HNO), cottonseed oil (CSO), sunflower oil (SFO) and soybean oil (SBO), was recorded. The feasibility of ATR–FTIR with multivariate data analysis for discrimination of extra VOOs from other edible oils was also evaluated. Classification of edible oils was performed using principal components analysis (PCA), hierarchical cluster analysis (HCA), linear discriminant analysis (LDA) and soft independent modeling of class analogies (SIMCA). The spectra collected from wavelength region of 4000–650 cm-1 and 28 different wavelength ranges selected from full spectra were evaluated for optimal classification models. All multivariate analysis provided excellent discriminations between the edible oil classes with low classification error. LDA models constructed with five predictors, and a total of 100% of edible oil samples from different trademarks were correctly classified. Furthermore, no misclassification was reported for the discriminant analysis in supervised SIMCA models with an accuracy of 95%. Consequently, ATR–FTIR spectroscopy combined with multivariate data analyses provides excellent illustrations of the relative positions of the different brands of commercial edible oils according to their quality and purity.
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