4.7 Article

Rapid Identification of Adulteration in Extra Virgin Olive Oil via Dynamic Headspace Sampling and High-Pressure Photoionization Time-of-Flight Mass Spectrometry

期刊

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
卷 70, 期 22, 页码 6775-6784

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jafc.2c01361

关键词

extra virgin olive oil adulteration; HPPI-TOFMS; rapid identification; volatile organic compounds

资金

  1. Natural Science Foundation of China [32001776, 22027804]
  2. Natural Science Foundation of Zhejiang Province [LQ20C200001]
  3. Research Development Fund of Zhejiang AF University [2019FR018]
  4. Dalian High-Level Talents Innovation Support Project [2019RQ101]
  5. Open Fund from the Key Laboratory of Separation and Analytical Chemistry, CAS

向作者/读者索取更多资源

High-pressure photoionization time-of-flight mass spectrometry combined with dynamic headspace sampling was developed for rapid identification of adulteration in extra virgin olive oil. The VOC fingerprints of different edible oils were obtained in just 1.5 min, allowing satisfactory classification. Unique VOCs were identified in specific oils, and the adulteration proportions as low as 3% could be successfully identified. The method showed good agreement between actual and predicted adulteration proportions.
High-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) combined with dynamic headspace sampling was developed for rapid identification of adulteration in extra virgin olive oil (EVOO). The volatile organic compound (VOC) fingerprints of EVOO, refined rapeseed oil (r-RO), peanut oil (PO), corn oil (CO), fragrant rapeseed oil (f-RO), and sunflower oil (SO) were obtained in just 1.5 min, which enabled satisfactory classification of different edible oils. 1,4-Bis(methylene)cyclohexane and dimethyl disulfide were unique VOCs in r-RO and f-RO, respectively, while 2,5-dimethylpyrazine and 2-methylpyrazine were distinctive VOCs in PO. Percentages as low as 3% r-RO, 1% PO, and 1% f-RO in r-RO-EVOO, PO- EVOO, and f-RO-EVOO mixtures, respectively, were successfully identified based on the characteristic VOCs. Linear regression equations of these VOCs were established and utilized for predicting the adulteration proportions. The good agreements between the actual adulteration proportions and the predicted ones demonstrated that HPPI-TOFMS was reliable for the quantification of EVOO adulteration.

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