Chrome Extension
WeChat Mini Program
Use on ChatGLM

Quality Evaluation of Flavoured Extra-Virgin Olive Oils According to Their Chemical Composition

Food Analytical Methods(2023)

University of Messina | University of Urbino

Cited 4|Views11
Abstract
Within extra-virgin olive oil (EVOO) global market, there is a niche market of olive oils flavoured with aromatic and medicinal plants. The use of aromatic and medicinal plants to flavour extra-virgin olive oils enriches the oil both from a sensorial and nutritional point of view, affecting its chemical composition. It is, therefore, necessary to develop analytical techniques useful to investigate in deeply the quali-quantitative profile of molecules contained in both the volatile and non-volatile fractions of extra-virgin olive oil. In the current study, several flavoured EVOOs (with truffle, basil, cardamom, bergamot, lemon, mandarin, sage, porcini mushroom, garlic, and rose) were purchased from local stores and analysed by both HPLC and GC methods to verify the correspondence with the profile of the added aroma. Furthermore, considering the preciousness and cost of some specific flavouring ingredients, in some cases, multidimensional gas chromatographic approach coupled to IRMS or performed by a chiral separation (Es-MDGC) was led to investigate their authenticity. From the results obtained, these complementary approaches allowed confirming the genuineness for most of the flavoured EVOOs. For few flavourings, some differences were detected with respect to literature references, thus requiring additional analytical devices to further authenticate their genuineness.
More
Translated text
Key words
Flavoured extra-virgin olive oils,Volatile compounds,Bioactive compounds,LC-MS,IRMS,SPME-GC/MS
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本研究通过HPLC和GC方法分析了多种风味橄榄油,旨在根据其化学成分评估其质量,并探索多维气相色谱技术辅助下的真伪鉴别方法。

方法】:采用高效液相色谱(HPLC)和气相色谱(GC)技术分析风味橄榄油中的挥发性与非挥发性成分。

实验】:收集了包括松露、罗勒、肉豆蔻、佛手柑、柠檬、橙、鼠尾草、松露菌、大蒜和玫瑰等风味橄榄油样本,并利用HPLC和GC技术验证其与添加香料的化学 profile 的对应关系;对于某些珍贵香料,采用多维气相色谱结合同位素比值质谱(IRMS)或手性分离(Es-MDGC)进行真伪鉴别。结果显示,这些互补方法确认了大多数风味EVOO的真实性,对少数样本发现了与文献参考的差异,需要额外分析设备进行进一步验证。