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内部验证可见近红外光谱非靶向方法,以支持橄榄油原始测试组合。

In-house validation of a visible and near infrared spectroscopy non-targeted method to support panel test of virgin olive oils.

机构信息

Faculty of Agriculture and Forestry Engineering (ETSIAM), University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain.

Faculty of Agriculture and Forestry Engineering (ETSIAM), University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain.

出版信息

Food Res Int. 2024 Sep;192:114799. doi: 10.1016/j.foodres.2024.114799. Epub 2024 Jul 20.

Abstract

In this study, an in-house validation of Visible and Near Infrared Spectroscopy was performed to distinguish between extra virgin olive oil (EVOO) and virgin olive oil (VOO). A total of 161 samples of olive oil of three different categories (EVOO, VOO and lampante (LOO)) were analysed by transflectance using a monochromator instrument. One-class models were initially developed using Partial Least Squares (PLS) Density Modelling to characterize EVOO and VOO category. Once the LOO samples were discriminated, linear and non-linear discriminant models were built to classify EVOO and VOO. Different data pre-treatments and variable selection algorithms were evaluated to establish the best models in terms of Correct Classification Rate (CCR). The best model, obtained after variable selection using PLS Discriminant Analysis, yielded CCR values of 82.35 % for EVOO and 66.67 % for VOO in external validation. These results confirmed that VIS + NIRS technology may be used to provide rapid, non-destructive preliminary screening of olive oil samples for categorization; suspect samples may then be analysed by official analytical methods.

摘要

本研究采用可见近红外光谱(Visible and Near Infrared Spectroscopy)对内进行验证,以区分特级初榨橄榄油(Extra Virgin Olive Oil,EVOO)和初榨橄榄油(Virgin Olive Oil,VOO)。使用分光光度计对 161 个来自三个不同类别的橄榄油样本(特级初榨橄榄油、初榨橄榄油和精炼橄榄油(Lampante,LOO))进行了反射分析。最初使用偏最小二乘(Partial Least Squares,PLS)密度建模方法开发了单类模型,以表征特级初榨橄榄油和初榨橄榄油类别。一旦区分出精炼橄榄油样本,就建立了线性和非线性判别模型来对特级初榨橄榄油和初榨橄榄油进行分类。评估了不同的数据预处理和变量选择算法,以根据正确分类率(Correct Classification Rate,CCR)确定最佳模型。使用 PLS 判别分析进行变量选择后获得的最佳模型,在外部验证中对特级初榨橄榄油的 CCR 值为 82.35%,对初榨橄榄油的 CCR 值为 66.67%。这些结果证实,VIS+NIRS 技术可用于对橄榄油样本进行快速、无损的初步分类筛选;可疑样本可随后通过官方分析方法进行分析。

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