2021
DOI: 10.1016/j.foodcont.2020.107659
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On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry

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Cited by 22 publications
(12 citation statements)
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“…As many chemical methods for the characterisation of non-volatile compounds as markers are time-consuming and require a lot of chemicals, the analysis of volatile compounds is particularly promising [31]. Recent studies also show developments to assess lipid oxidation by volatile compounds online during frying [32].…”
Section: Introductionmentioning
confidence: 99%
“…As many chemical methods for the characterisation of non-volatile compounds as markers are time-consuming and require a lot of chemicals, the analysis of volatile compounds is particularly promising [31]. Recent studies also show developments to assess lipid oxidation by volatile compounds online during frying [32].…”
Section: Introductionmentioning
confidence: 99%
“…In [37], an optimized deep CNN for dendrobium classification based on electronic nose was proposed. In [38], on-line assessment of oil quality during deep frying was addressed by using an electronic nose and proton transfer reaction mass spectrometry. In [39], a novel method for rapid quantitative evaluating formaldehyde in squid based on electronic nose was devised.…”
Section: The Related Applicationsmentioning
confidence: 99%
“…Recently, studies have been carried out using electronic noses to predict the quality of the oil to be processed from the measurements obtained in freshly harvested olives [ 20 ] and to evaluate the odours produced in anomalous fermentations of Spanish-style green olives [ 15 ]. The variation of the volatile organic compounds generated in food after thermal treatments has also been studied to monitor the evaluation of the quality of the oil used for frying [ 21 ], to identify the olfactory profile of rapeseed oil as a function of heating time [ 22 ], or in the sensory evaluation of Californian-style black olive sterilization treatments [ 23 ].…”
Section: Introductionmentioning
confidence: 99%