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Botanical origin discrimination of Greek honeys: Physicochemical parameters vs Raman spectroscopy
Journal of the Science of Food and Agriculture ( IF 4.1 ) Pub Date : 2020-12-07 , DOI: 10.1002/jsfa.10961
Marinos Xagoraris 1 , Elisavet Lazarou 1 , Eleftheria H Kaparakou 1 , Eleftherios Alissandrakis 2 , Petros A Tarantilis 1 , Christos S Pappas 1
Affiliation  

BACKGROUND The authenticity of honey is of high importance since it affects its commercial value. The discrimination of the origin of honey is of prime importance to reinforce the consumer trust. In this study four chemometric models were developed based on the physicochemical parameters according to European and Greek legislation and one using Raman spectroscopy to discriminate Greek honey samples from three commercial monofloral botanical sources. RESULTS The results of physicochemical (glucose, fructose, electrical activity) parameters chemometric models showed that the percentage of correct recognition was fluctuated from 92.2 to 93.8% with cross-validation 90.6-92.2%, and the placement of test set was 79.0-84.3% successful. The addition of maltose content in the previous discrimination models did not improve significantly the discrimination. The corresponding percentages of Raman chemometric model were found 95.3, 90.6, and 84.3%. CONCLUSION The five developed chemometric models presented similar and very satisfactorily results. Given that the recording of Raman spectra is simple, fast, a minimal amount of sample is needed for the analysis, no solvent (environmentally friendly) is used, and no specialized personnel are required we conclude that the chemometric model based on the Raman spectroscopy is an efficient tool to discriminate the botanical origin fir pine and thyme honey varieties. This article is protected by copyright. All rights reserved.

中文翻译:

希腊蜂蜜的植物来源鉴别:理化参数与拉曼光谱

背景技术蜂蜜的真实性非常重要,因为它会影响其商业价值。蜂蜜原产地的辨别对于增强消费者的信任至关重要。在这项研究中,根据欧洲和希腊立法,基于物理化学参数开发了四种化学计量模型,一种使用拉曼光谱来区分来自三种商业单花植物来源的希腊蜂蜜样品。结果理化(葡萄糖、果糖、电活动)参数化学计量模型结果显示,正确识别率在92.2%~93.8%之间波动,交叉验证在90.6~92.2%之间,测试集放置在79.0~84.3%之间成功的。在之前的判别模型中添加麦芽糖含量并没有显着提高判别能力。拉曼化学计量模型的相应百分比分别为 95.3、90.6 和 84.3%。结论 五个开发的化学计量模型呈现相似且非常令人满意的结果。鉴于拉曼光谱的记录简单、快速、分析所需的样品量最少、不使用溶剂(环保),并且不需要专业人员,我们得出结论,基于拉曼光谱的化学计量模型是区分植物来源的冷杉和百里香蜂蜜品种的有效工具。本文受版权保护。版权所有。鉴于拉曼光谱的记录简单、快速、分析所需的样品量最少、不使用溶剂(环保),并且不需要专业人员,我们得出结论,基于拉曼光谱的化学计量模型是区分植物来源的冷杉和百里香蜂蜜品种的有效工具。本文受版权保护。版权所有。鉴于拉曼光谱的记录简单、快速、分析所需的样品量最少、不使用溶剂(环保),并且不需要专业人员,我们得出结论,基于拉曼光谱的化学计量模型是区分植物来源的冷杉和百里香蜂蜜品种的有效工具。本文受版权保护。版权所有。
更新日期:2020-12-07
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