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首页> 外文期刊>Journal of the American Oil Chemists' Society >Classification of Turkish Extra Virgin Olive Oils by a SAW Detector Electronic Nose
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Classification of Turkish Extra Virgin Olive Oils by a SAW Detector Electronic Nose

机译:声表面波检测器电子鼻对土耳其特级初榨橄榄油的分类

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摘要

An electronic nose (e-nose), in combination with chemometrics, has been used to classify the cultivar, harvest year, and geographical origin of economically important Turkish extra virgin olive oils. The aroma fingerprints of the eight different olive oil samples [Memecik (M), Erkence (E), Gemlik (G), Ayvalık (A), Domat (D), Nizip (N), Gemlik–Edremit (GE), Ayvalık–Edremit (AE)] were obtained using an e-nose consisting a surface acoustic wave detector. Data were analyzed by principal component analysis (PCA) and discriminant function analysis (DFA). Classification of cultivars using PCA revealed that A class model was correctly discriminated from N in two harvest years. The DFA classified 100 and 97% of the samples correctly according to the cultivar in the 1st and 2nd harvest years, respectively. Successful separation among the harvest years and geographical origins were obtained. Sensory analyses were performed for determining the differences in the geographical origin of the olive oils and the preferences of the panelists. The panelists could not detect the differences among olive oils from two different regions. The cultivar, harvest year, and geographical origin of extra virgin olive oils could be discriminated successfully by the e-nose.
机译:电子鼻(电子鼻)结合化学计量学已被用于对经济上重要的土耳其特级初榨橄榄油的品种,收成年和地理来源进行分类。八种不同橄榄油样品的香气指纹[Memecik(M),Erkence(E),Gemlik(G),Ayvalık(A),Domat(D),Nizip(N),Gemlik–Edremit(GE),Ayvalık–使用构成表面声波检测器的电子鼻获得Edremit(AE)]。数据通过主成分分析(PCA)和判别函数分析(DFA)进行分析。使用PCA对品种进行分类显示,在两个收获年中,已将A类模型与N正确区分开。在第一个收获年和第二个收获年,DFA分别根据品种正确分类了100%和97%的样品。在收获年和地理来源之间成功分离。进行了感官分析,以确定橄榄油的地理来源和专门小组成员的偏好差异。小组成员无法检测到来自两个不同地区的橄榄油之间的差异。电子鼻可以成功地区分特级初榨橄榄油的品种,收获年限和地理来源。

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