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利用离子淌度总谱对阿拉比卡咖啡和罗布斯塔咖啡进行特征分析。

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum.

机构信息

Department of Analytical Chemistry, Faculty of Sciences, Agrifood Campus of International Excellence (ceiA3), IVAGRO, University of Cadiz, 11510 Puerto Real, Spain.

Department of Complex Systems, National Centre for Nuclear Research, 05-400 Otwock-Swierk, Poland.

出版信息

Sensors (Basel). 2020 May 31;20(11):3123. doi: 10.3390/s20113123.

Abstract

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches.

摘要

香气是咖啡样本的主要特征之一。市场上通常会找到不同的阿拉比卡和罗布斯塔咖啡混合物,以向消费者提供特定的香气或风味特征。然而,产品标签并不总是标识混合样品或其比例。由于阿拉比卡的价格比罗布斯塔高得多,因此这种信息缺失不仅是一个经济问题,而且对消费者来说可能是一种欺诈行为,此外,这些混合物可能会引起某些个体的过敏反应。在本文中,比较了两种样品前处理技术,然后分析了罗布斯塔、阿拉比卡以及这两种咖啡混合样品中的总挥发性有机化合物(VOCs)。对分析得到的信号进行比较后发现,顶空(HS)分析得到的 VOCs 浓度明显高于使用吸附剂(活性碳纤维带(ACS + HS))进行预浓缩步骤得到的浓度。在本研究的第二部分,评估了使用顶空气相色谱-离子迁移谱(HS-GC-IMS)对阿拉比卡、罗布斯塔和混合咖啡样品(n = 30)进行区分的可能性。使用从 HS 分析得到的离子迁移总和谱(IMSS)与模式识别技术(即线性判别分析(LDA))相结合,作为电子鼻。由于未使用色谱信息,因此未进行单个化合物的鉴定。该新方法可以正确区分所有样品(100%)。还为每种类型的咖啡开发了一个快速简便识别的特征指纹。此外,所开发的方法是环保的,因此是传统方法的良好替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a93/7309026/328d3104e19b/sensors-20-03123-g001.jpg

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